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Objectives: To develop an ensemble multi-task deep learning (DL) framework for automatic and simultaneous detection, segmentation, and classification of primary bone tumors (PBTs) and bone infections based on multi-parametric MRI from multi-center. Methods: This retrospective study divided 749 patients with PBTs or bone infections from two hospitals into a training set (N = 557), an internal validation set (N = 139), and an external validation set (N = 53). The ensemble framework was constructed using T1-weighted image (T1WI), T2-weighted image (T2WI), and clinical characteristics for binary (PBTs/bone infections) and three-category (benign/intermediate/malignant PBTs) classification. The detection and segmentation performances were evaluated using Intersection over Union (IoU) and Dice score. The classification performance was evaluated using the receiver operating characteristic (ROC) curve and compared with radiologist interpretations. Result: On the external validation set, the single T1WI-based and T2WI-based multi-task models obtained IoUs of 0.71 ± 0.25/0.65 ± 0.30 for detection and Dice scores of 0.75 ± 0.26/0.70 ± 0.33 for segmentation. The framework achieved AUCs of 0.959 (95%CI, 0.955–1.000)/0.900 (95%CI, 0.773–0.100) and accuracies of 90.6% (95%CI, 79.7–95.9%)/78.3% (95%CI, 58.1–90.3%) for the binary/three-category classification. Meanwhile, for the three-category classification, the performance of the framework was superior to that of three junior radiologists (accuracy: 65.2%, 69.6%, and 69.6%, respectively) and comparable to that of two senior radiologists (accuracy: 78.3% and 78.3%). Conclusion: The MRI-based ensemble multi-task framework shows promising performance in automatically and simultaneously detecting, segmenting, and classifying PBTs and bone infections, which was preferable to junior radiologists. Clinical relevance statement: Compared with junior radiologists, the ensemble multi-task deep learning framework effectively improves differential diagnosis for patients with primary bone tumors or bone infections. This finding may help physicians make treatment decisions and enable timely treatment of patients. Key Points: • The ensemble framework fusing multi-parametric MRI and clinical characteristics effectively improves the classification ability of single-modality models. • The ensemble multi-task deep learning framework performed well in detecting, segmenting, and classifying primary bone tumors and bone infections. • The ensemble framework achieves an optimal classification performance superior to junior radiologists' interpretations, assisting the clinical differential diagnosis of primary bone tumors and bone infections. [ABSTRACT FROM AUTHOR]

Aneurysmal bone cyst (ABC) is a rare and usually painful condition, representing about 1% of all bone tumors. A geographical lytic, expansile, and septated radiological pattern, with fluid–fluid levels on MRI, is classically displayed. ABC can be a primary bone lesion (70% of patients) or can arise in an underlying condition and is subsequently named "ABC-like changes" (30%). ABC-like changes are more frequently encountered in skeletal segments affected by chondroblastoma, fibrous dysplasia, giant cell tumor, osteoblastoma, non-ossifying fibroma, and osteosarcoma. In this article, we describe the first case of ABC-like changes developed in association with an ultra-rare sclerosing bone disease: melorheostosis. Melorheostosis is characterized by recognizable patterns on radiological studies with a pathological increased bone density and a cortical thickening within the periosteal or endosteal space, usually with a "dripping candle wax" appearance. More rarely, other different radiological patterns can be observed, such as "osteopatia striata-like," "osteoma-like," "myositis ossificans-like," and mixed patterns. Pain and limb hypotrophy are the most common clinical manifestations. We report the case of a Caucasian male with a clinic-radiological diagnosis of melorheostosis (with epiphyseal osteopoikilosis) since the age of twelve. At the age of nineteen, he suffered from increased pain in the proximal right thigh, and the radiological control revealed an expansive septated lesion at the right proximal femoral bone. The diagnosis of ABC-like changes developed in melorheostosis was obtained after CT-guided bone biopsy and confirmed by open-incisional biopsy. [ABSTRACT FROM AUTHOR]

The article focuses on the implications of primary bone sarcoma (PBS) for anesthetists, emphasizing the importance of preparation for surgery and perioperative management. Topics include preoperative planning coordinated by multidisciplinary teams, histological diagnosis and its impact on treatment strategies, and the specific effects of neoadjuvant treatments such as chemotherapy, radiotherapy, and immunotherapy on patients undergoing surgery.

Purpose: To conduct a systematic review and meta-analysis of publications to evaluate the analgesic efficacy and safety of percutaneous thermal ablation (PTA) plus percutaneous cementoplasty (PCP) (PTA + PCP) for painful bone metastases. Methods: We searched PubMed, Cochrane Library and Embase for articles published up to October 2022. Outcomes were a 10-point pain scale, morphine equivalents daily dose (MEDD) and complications. A subgroup confined to spinal bone metastases was analyzed. Results: Twenty-one articles were selected for the analysis. The 21 selected articles involved a total of 661 cases. The pooled pain scales at pre-PTA + PCP, 1 day, 1 week and 1-, 3-, and 6 months post-PTA + PCP were 7.60 (95% confidence interval [CI], 7.26–7.95, I2 = 89%), 3.30 (95% CI, 2.25–4.82, I2 = 98%), 2.58 (95% CI, 1.99–3.35, I2 = 94%), 2.02 (95% CI, 1.50–2.71, I2 = 93%), 1.78 (95% CI, 1.26–2.53, I2 = 95%), and 1.62 (95% CI, 1.14–2.31, I2 = 88%), and in the subgroup, 7.97 (95% CI, 7.45–8.52, I2 = 86%), 3.01 (95% CI, 1.43–6.33, I2 = 98%), 2.95 (95% CI, 1.93–4.51, I2 = 95%), 2.34 (95% CI, 1.82–3.01, I2 = 68%), 2.18 (95% CI, 1.57–3.03, I2 = 78%), and 2.01 (95% CI, 1.16–3.48, I2 = 86%). Mean MEDD decreased up to 3 months post-PTA + PCP in 4 articles. The overall pooled major complication rate was 4% (95% CI, 2–6%, I2 = 2%). Conclusions: The updated systematic review and meta-analysis indicates that PTA + PCP for painful bone metastases is safe, and can lead to rapid and sustained pain reduction. [ABSTRACT FROM AUTHOR]

Aims: The discovery of somatic genetic alterations established many histiocytic disorders as haematologic neoplasms. We aimed to investigate the demographic characteristics and additional haematologic cancers of patients diagnosed with histiocytic disorders in The Netherlands. Methods and results: We retrieved data on histiocytosis patients from the Dutch Nationwide Pathology Databank (Palga). During 1993 to 2022, more than 4000 patients with a pathologist‐assigned diagnosis of a histiocytic disorder were registered in Palga. Xanthogranulomas were the most common subtype, challenging the prevailing assumption that Langerhans cell histiocytosis (LCH) is the most common histiocytic disorder. LCH and juvenile xanthogranuloma (JXG) had a peak incidence in the first years of life; males were overrepresented among all histiocytosis subgroups. 118 patients had a histiocytic disorder and an additional haematologic malignancy, including 107 (91%) adults at the time of histiocytosis diagnosis. In 16/118 patients, both entities had been analysed for the same genetic alteration(s). In 11 of these 16 patients, identical genetic alterations had been detected in both haematologic neoplasms. This included two patients with PAX5 p.P80R mutated B cell acute lymphoblastic leukaemia and secondary histiocytic sarcoma, further supporting that PAX5 alterations may predispose (precursor) B cells to differentiate into the myeloid lineage. All 4/11 patients with myeloid neoplasms as their additional haematologic malignancy had shared N/KRAS mutations. Conclusions: This population‐based study highlights the frequency of xanthogranulomas. Furthermore, our data add to the growing evidence supporting clonal relationships between histiocytic/dendritic cell neoplasms and additional myeloid or lymphoid malignancies. Particularly adult histiocytosis patients should be carefully evaluated for the development of these associated haematologic cancers. [ABSTRACT FROM AUTHOR]

Objectives: To develop a deep learning (DL) model for differentiating between osteolytic osteosarcoma (OS) and giant cell tumor (GCT) on radiographs. Methods: Patients with osteolytic OS and GCT proven by postoperative pathology were retrospectively recruited from four centers (center A, training and internal testing; centers B, C, and D, external testing). Sixteen radiologists with different experiences in musculoskeletal imaging diagnosis were divided into three groups and participated with or without the DL model's assistance. DL model was generated using EfficientNet-B6 architecture, and the clinical model was trained using clinical variables. The performance of various models was compared using McNemar's test. Results: Three hundred thirty-three patients were included (mean age, 27 years ± 12 [SD]; 186 men). Compared to the clinical model, the DL model achieved a higher area under the curve (AUC) in both the internal (0.97 vs. 0.77, p = 0.008) and external test set (0.97 vs. 0.64, p < 0.001). In the total test set (including the internal and external test sets), the DL model achieved higher accuracy than the junior expert committee (93.1% vs. 72.4%; p < 0.001) and was comparable to the intermediate and senior expert committee (93.1% vs. 88.8%, p = 0.25; 87.1%, p = 0.35). With DL model assistance, the accuracy of the junior expert committee was improved from 72.4% to 91.4% (p = 0.051). Conclusion: The DL model accurately distinguished osteolytic OS and GCT with better performance than the junior radiologists, whose own diagnostic performances were significantly improved with the aid of the model, indicating the potential for the differential diagnosis of the two bone tumors on radiographs. Critical relevance statement: The deep learning model can accurately distinguish osteolytic osteosarcoma and giant cell tumor on radiographs, which may help radiologists improve the diagnostic accuracy of two types of tumors. Key points: • The DL model shows robust performance in distinguishing osteolytic osteosarcoma and giant cell tumor. • The diagnosis performance of the DL model is better than junior radiologists'. • The DL model shows potential for differentiating osteolytic osteosarcoma and giant cell tumor. [ABSTRACT FROM AUTHOR]

Introduction: the glomus tumor is a benign neoplasm originated in the smooth muscle cells of the vascular glomus. Approximately 80% of lesions are located on the upper extremity and, of these, the majority are in the subungual area. The diagnosis must include imaging tests, among which ultrasound stands out, being a good alternative due to its low cost and accessibility. Objective: we present a case of late diagnosis of surgically managed glomus tumor, as well as a review of the existing literature for diagnosis, treatment, and prognosis of this uncommon pathology. Clinical case: the case of a 52-year-old female patient who reported chronic, burning pain, radiating to the distal phalanx of the thumb with no history of trauma, of 2 years of evolution and which limited her daily life activities, is presented. The exploration with interphalangeal Doppler ultrasound is complemented, being an excellent alternative due to its easy accessibility. A glomus tumor was diagnosed in the interphalangeal thumb. An «H» approach was performed on the interphalangeal fold with subungual dissection with resection of the tumor piece and follow-up by an outpatient clinic where a surgical wound with adequate healing was found. Physical examination with capacity for the mobilization of the distal interphalangeal joint (IFJ) and visual analogue scale (VAS) 1 point. The updated pathological evaluation of the existence of a glomus tumor. Conclusions: ultrasound is an excellent aid in the diagnosis, as well as in the surgical planning for the treatment of the glomus tumor; for being accessible, low cost and highly effective. The anatomopathological study is the gold standard. [ABSTRACT FROM AUTHOR]

Reconstruction of distal tibial defects pose a difficult challenge because the bone is subcutaneous and close to the tendons and neurovascular bundles. Distally based pedicled fibula with retrograde flow can be used for the reconstruction of distal tibial defects. This is based on the communicating branch of the peroneal artery to the posterior tibial artery. We present three cases of distal tibia primary tumours which were resected and reconstructed using recycled autograft plus distally based pedicled fibula and ankle arthrodesis. This pedicled retrograde fibula flap is a novel technique for the reconstruction of distal tibial defects after oncological resections. It provides a vascularized graft without the need for microvascular surgery and without violating the normal limb. Meticulous dissection of and preservation of the communicating branches between the peroneal artery and the posterior tibial artery with confirmation of retrograde flow before dividing the proximal peroneal pedicle is sine quo non for the success of this graft. This flap overcomes the drawback of the limited arc of rotation and limited reach of proximal pedicle-based flap for distal tibial reconstruction. Long-term functional outcomes, limb shortening associated with this flap, and its effect on functional outcomes remain to be ascertained. [ABSTRACT FROM AUTHOR]

Objectives: The diagnosis of osteoid osteomas (OO) about the hip can be challenging as presenting symptoms can mimic other, more common, periarticular pathologies. Our aims were to identify the most common misdiagnoses and treatments, mean delay in diagnosis, characteristic imaging features and provide tips for avoiding diagnostic imaging pitfalls for patients with OO of the hip. Methods: We identified 33 patients (34 tumors) with OO about the hip who were referred for radiofrequency ablation between 1998 and 2020. Imaging studies reviewed included radiographs (n = 29), CT (n = 34), and MRI (n = 26). Results: The most common initial diagnoses were femoral neck stress fracture (n = 8), femoroacetabular impingement (FAI) (n = 7), and malignant tumor or infection (n = 4). The mean time from symptom onset to diagnosis of OO was 15 months (range, 0.4–84). The mean time from initial incorrect diagnosis to OO diagnosis was 9 months (range, 0–46). Conclusions: The diagnosis of OO of the hip is challenging, with up to 70% of cases initially misdiagnosed as a femoral neck stress fracture, FAI, bone tumor, or other joint pathology in our series. Consideration of OO in the differential diagnosis of hip pain in adolescent patients and awareness of the characteristic imaging findings are critical for making an accurate diagnosis. Key Points: • The diagnosis of osteoid osteoma of the hip can be challenging, as demonstrated by long delays in time to initial diagnosis and high rates of misdiagnoses which can lead to inappropriate interventions. • Familiarity with the spectrum of imaging features of OO, especially on MRI, is imperative given the increase in the utilization of this modality for the evaluation of young patients with hip pain and FAI. • Consideration of OO in the differential diagnosis of hip pain in adolescent patients and awareness of the characteristic imaging findings, including bone marrow edema and the utility of CT, are critical for making a timely and accurate diagnosis. [ABSTRACT FROM AUTHOR]

Tumors of hematopoietic origin are rare tumors that can be confused with benign and malignant tumors of the bone with their clinical and morphological features. Plasma cell myeloma, solitary plasmacytoma, Non-Hodgkin Lymphoma, acute lymphoblastic leukemia/lymphoma, and Langerhans cell histiocytosis are hematological neoplasms that mainly involve the bone. Plasma cell myeloma is the most common primary malignant bone neoplasm, and diffuse large B-cell lymphoma (DLBCL) is the most common type of non-Hodgkin lymphoma arising in bone. In this case report, we will retrospectively investigate the diagnosis and treatment management and postoperative clinical outcomes of patients diagnosed with tumors of hematopoietic origin, evaluated by the Bone and Soft Tissue Tumor Council between 2005 and 2021, and emphasize the importance of the approach to these tumors. [ABSTRACT FROM AUTHOR]

Objective: To develop and validate a deep learning (DL) model based on CT for differentiating bone islands and osteoblastic bone metastases. Materials and methods: The patients with sclerosing bone lesions (SBLs) were retrospectively included in three hospitals. The images from site 1 were randomly assigned to the training (70%) and intrinsic verification (10%) datasets for developing the two-dimensional (2D) DL model (single-slice input) and "2.5-dimensional" (2.5D) DL model (three-slice input) and to the internal validation dataset (20%) for evaluating the performance of both models. The diagnostic performance was evaluated using the internal validation set from site 1 and additional external validation datasets from site 2 and site 3. And statistically analyze the performance of 2D and 2.5D DL models. Results: In total, 1918 SBLs in 728 patients in site 1, 122 SBLs in 71 patients in site 2, and 71 SBLs in 47 patients in site 3 were used to develop and test the 2D and 2.5D DL models. The best performance was obtained using the 2.5D DL model, which achieved an AUC of 0.996 (95% confidence interval [CI], 0.995–0.996), 0.958 (95% CI, 0.958–0.960), and 0.952 (95% CI, 0.951–0.953) and accuracies of 0.950, 0.902, and 0.863 for the internal validation set, the external validation set from site 2 and site 3, respectively. Conclusion: A DL model based on a three-slice CT image input (2.5D DL model) can improve the prediction of osteoblastic bone metastases, which can facilitate clinical decision-making. Key Points: • This study investigated the value of deep learning models in identifying bone islands and osteoblastic bone metastases. • Three-slice CT image input (2.5D DL model) outweighed the 2D model in the classification of sclerosing bone lesions. • The 2.5D deep learning model showed excellent performance using the internal (AUC, 0.996) and two external (AUC, 0.958; AUC, 0.952) validation sets. [ABSTRACT FROM AUTHOR]

Objectives: Automatic bone lesions detection and classifications present a critical challenge and are essential to support radiologists in making an accurate diagnosis of bone lesions. In this paper, we aimed to develop a novel deep learning model called You Only Look Once (YOLO) to handle detecting and classifying bone lesions on full-field radiographs with limited manual intervention. Methods: In this retrospective study, we used 1085 bone tumor radiographs and 345 normal bone radiographs from two centers between January 2009 and December 2020 to train and test our YOLO deep learning (DL) model. The trained model detected bone lesions and then classified these radiographs into normal, benign, intermediate, or malignant types. The intersection over union (IoU) was used to assess the model's performance in the detection task. Confusion matrices and Cohen's kappa scores were used for evaluating classification performance. Two radiologists compared diagnostic performance with the trained model using the external validation set. Results: In the detection task, the model achieved accuracies of 86.36% and 85.37% in the internal and external validation sets, respectively. In the DL model, radiologist 1 and radiologist 2 achieved Cohen's kappa scores of 0.8187, 0.7927, and 0.9077 for four-way classification in the external validation set, respectively. The YOLO DL model illustrated a significantly higher accuracy for intermediate bone tumor classification than radiologist 1 (95.73% vs 88.08%, p = 0.004). Conclusions: The developed YOLO DL model could be used to assist radiologists at all stages of bone lesion detection and classification in full-field bone radiographs. Key Points: • YOLO DL model can automatically detect bone neoplasms from full-field radiographs in one shot and then simultaneously classify radiographs into normal, benign, intermediate, or malignant. • The dataset used in this retrospective study includes normal bone radiographs. • YOLO can detect even some challenging cases with small volumes. [ABSTRACT FROM AUTHOR]

While nowadays, CT-guided bone biopsy represents the gold standard tool for histopathological and microbiological diagnosis of skeletal lesions, the role of US-guided bone biopsy has not yet been fully explored. US-guided biopsy offers several advantages, such as the absence of ionizing radiation, fast acquisition time, as well as good intra-lesional echo, and structural and vascular characterization. Despite that, a consensus in regard to its applications in bone neoplasms has not been established. Indeed CT-guided technique (or fluoroscopic ones) still represents the standard choice in clinical practice. This review article aims to review the literature data about US-guided bone biopsy, underlying clinical-radiological indications, advantages of the procedure and future perspectives. Bone lesions taking the best advantages of the US-guided biopsy are osteolytic, determining the erosion of the overlying bone cortex and/or with an extraosseous soft-tissue component. Indeed, osteolytic lesions with extra-skeletal soft-tissue involvement represent a clear indication for US-guided biopsy. Moreover, even lytic bone lesions with cortical thinning and/or cortical disruption, especially located in the extremities or pelvis, can be safely sampled with US guidance with very good diagnostic yield. US-guided bone biopsy is proven to be fast, effective and safe. Additionally, it offers real-time needle evaluation, an advantage when compared to CT-guided bone biopsy. In the current clinical settings, it seems relevant to select the exact eligibility criteria for this imaging guidance since the effectiveness can vary depending on the type of lesion and body site involved. [ABSTRACT FROM AUTHOR]

Objectives: To ascertain the role of CT and conventional radiographs for the initial characterization of focal bone lesions. Methods: Images from 184 patients with confirmed bone tumors included in an ethics committee-approved study were retrospectively evaluated. The reference for benign-malignant distribution was based on histological analysis and long-term follow-up. Radiographs and CT features were analyzed by 2 independent musculoskeletal radiologists blinded to the final diagnosis. Lesion margins, periosteal reaction, cortical lysis, endosteal scalloping, presence of pathologic fracture, and lesion mineralization were evaluated. Results: The benign-malignant distribution in the study population was 68.5–31.5% (126 benign and 58 malignant). In the lesions that could be seen in both radiographs and CT, the performance of these methods for the benign-malignant differentiation was similar (accuracy varying from 72.8% to 76.5%). The interobserver agreement for the overall evaluation of lesion aggressiveness was considerably increased on CT compared to radiographs (Kappa of.63 vs.22). With conventional radiographs, 18 (9.7%) and 20 (10.8%) of the lesions evaluated were not seen respectively by readers 1 and 2. Among these unseen lesions, 50%–61.1% were located in the axial skeleton. Compared to radiographs, the number of lesions with cortical lysis and endosteal scalloping was 26–34% higher with CT. Conclusion: Although radiographs remain the primary imaging tool for lesions in the peripheral skeleton, CT should be performed for axial lesions. CT imaging can assess the extent of perilesional bone lysis more precisely than radiographs with a better evaluation of lesion fracture risk. [ABSTRACT FROM AUTHOR]

Metastatic disease is a main cause of mortality in prostate cancer and remains to be incurable despite emerging new treatment agents. Development of novel treatment agents are confined within the boundaries of our knowledge of bone metastatic prostate cancer. Exploration into the underlying mechanism of metastatic tumorigenesis and treatment resistance will further expose novel targets for novel treatment agents. Up to date, many of these researches have been conducted with animal models which have served as classical tools that play a pivotal role in understanding the fundamental nature of cancer. The ability to reproduce the natural course of prostate cancer would be of profound value. However, currently available models do not reproduce the entire process of tumorigenesis to bone metastasis and are limited to reproducing small portions of the entire process. Therefore, knowledge of available models and understanding the strengths and weaknesses for each model is key to achieve research objectives. In this article, we take an overview of cell line injection animal models and patient derived xenograft models that have been applied to the research of human prostate cancer bone metastasis. [ABSTRACT FROM AUTHOR]

Simple Summary: Musculoskeletal tumors often require surgical treatment, which can result in substantial peri-operative blood loss. Preoperative transarterial embolization (TAE) is used to reduce peri-operative blood loss during the surgery of musculoskeletal tumors but there is no consensus about the actual place of TAE in the musculoskeletal tumor therapeutic algorithm, and there is no firm recommendation about its best technical approach. The purpose of this study was to report our experience in preoperative TAE of musculoskeletal tumors regarding the effectiveness of preoperative TAE in terms of blood loss and functional outcomes. For 31 patients, we found that TAE led to complete (58%) or near-complete (42%) tumor devascularization, allowing bloodless surgery in 71% of patients and moderate transfusion needs for the remaining 29%. A total of 27% of patients had complete improvement of the initial symptoms at the end of the follow-up, 15 (50%) with partially satisfying improvement, 4 (13%) with partially unsatisfying improvement and 3 (10%) with no improvement. The purpose of this study was to report the effectiveness of preoperative transcatheter arterial embolization (TAE) of musculoskeletal tumors in terms of blood loss and functional outcomes. Patients who underwent preoperative TAE of hypervascular musculoskeletal tumors between January 2018 and December 2021 were retrospectively included. The patients' characteristics, TAE procedure details, degree of post-TAE devascularization, surgical outcomes in terms of red blood cell transfusion and functional results were collected. The degree of devascularization was compared between patients who had peri-operative transfusion and those who did not. Thirty-one patients were included. The 31 TAE procedures led to complete (58%) or near-complete (42%) tumor devascularization. Twenty-two patients (71%) had no blood transfusion during surgery. Nine patients (29%) had a blood transfusion, with a median number of red blood cell packs of three (q1, 2; q3, 4; range: 1–4). Eight patients (27%) had complete improvement of the initial musculoskeletal symptoms at the end of the follow-up, 15 (50%) had partially satisfying improvement, 4 (13%) had partially unsatisfying improvement and 3 (10%) had no improvement. Our study suggests that preoperative TAE of hypervascular musculoskeletal tumors allowed for bloodless surgery in 71% of patients and minimal transfusion needs for the remaining 29%. [ABSTRACT FROM AUTHOR]

Fibrous dysplasia is an uncommon genetic disorder in which bone is replaced by immature bone and fibrous tissue, manifesting as slowgrowing lesions. Sporadic post-zygotic activating mutations in GNAS gene result in dysregulated GαS-protein signaling and elevation of cyclic adenosine monophosphate in affected tissues. This condition has a broad clinical spectrum, ranging from insignificant solitary lesions to severe disease. The craniofacial area is the most common site of fibrous dysplasia, and nine out of 10 patients with fibrous dysplasia affecting the craniofacial bones present before the age of 5. Surgery is the mainstay of treatment, but the technique varies according to the location and severity of the lesion and associated symptoms. The timing and indications of surgery should be carefully chosen with multidisciplinary consultations and a patient-specific approach. [ABSTRACT FROM AUTHOR]

Background: Despite significant improvements in oncological treatment, the management of soft tissue defects following malignant tumor resection remains challenging. We investigated whether autologous menisci and cruciate ligament, which are traditionally discarded, can be recycled as a supplemental flap in repairing soft tissue defects following malignant bone tumor resection and endoprosthetic reconstruction around the knee. Methods: Four knee specimens were dissected to provide a basis for the design of the menisci–cruciate ligament composite. Then, 40 patients with bone malignancies around the knee were enrolled and underwent reconstruction with free or vascularized composite following malignant tumor resection. The clinical, radiographic, and functional outcomes of this technique were evaluated in >1‐year follow‐up in each patient and compared with 87 patients who suffered from bone malignancies around the knee and were treated by limb salvage but without composite at our center over the same period. During the follow‐up, a composite from one patient who underwent secondary amputation was retrieved and examined for in vivo remodeling. Results: Fourteen patients were treated with vascularized composite transfer (10 distal femurs and 4 proximal tibias) and 26 patients with free composite transfer (19 distal femurs and 7 proximal tibias). The composite can be used to cover the area of soft tissue defect from 22 to 48.38 cm2 (34.67 ± 6.48 cm2). With contrast‐enhanced ultrasound, peripheral rim healing and dotted blood flow signal at the side of anastomosis were detected on a patient 16 months after free composite transfer. Gross macroscopic remodeling and histopathologic analysis of a retrieved composite also indicated good healing with surrounding tissues and living cells in the composite. The complications and oncologic outcomes were comparable between study and control cohorts, but better Musculoskeletal Tumor Society (MSTS) score for patients reconstructed with composite (26.68 vs. 25.66, p = 0.004). Of note, MSTS score was higher for patients reconstructed with composite at distal femur subdivision compared with the same subdivision in the control cohort (26.97 vs. 25.90, p = 0.009). No statically significant difference was noted in complications, oncologic, and functional outcomes for patients reconstructed with free or vascularized composite. Conclusion: Autogenous menisci–cruciate ligament composite is an alternative option for soft tissue reconstruction. Either vascularized or free composite can be applied, depending on the size and localization of the defect. [ABSTRACT FROM AUTHOR]

Background: Cancer-induced bone pain (CIBP) is considered to have both nociceptive and neuropathic components. However, the prevalence, risk factors, and impact of the neuropathic components are yet poorly understood. Methods: We estimate the prevalence of neuropathic pain (NP) features in patients with CIBP at a tertiary care pain clinic setting using the Douleur Neuropathique 4 questionnaire and evaluate their associated factors and their impact after 4 weeks of treatment using the Brief Pain Inventory questionnaire and the Edmonton Symptom Assessment System. Results: A total of 133 patients were recruited. The estimated prevalence of NP was 30.8% (95% confidence interval: 23.6%-39.1%). Initially, the patients with NP had significantly higher average pain scores (6.00 vs. 5.05, P = 0.006), higher total interference scores (5.84 vs. 4.89, P = 0.033), and symptom distress scores (35.88 vs. 26.52, P = 0.002). After 4 weeks of treatment, patients in both groups reported significantly decreased pain intensity and improved quality of life. However, the patients with NP still reported significantly higher average pain (4.61 vs. 3.58, P = 0.048), trending toward higher total interference scores (3.52 vs. 2.99, P = 0.426), and symptom distress scores (23.30 vs. 20.77, P = 0.524). From multivariate analysis, the independent risk factors for NP were younger age, pain in the extremities, and higher average pain scores. Conclusions: NP are common in patients with CIBP. These conditions negatively affect pain intensity and the patient's quality of life before and after treatment. [ABSTRACT FROM AUTHOR]

Background: An increasing number of patients are surviving sarcoma after lower limb-salvage surgery (LSS) and are left with functional limitations. This systematic review aimed to determine the therapeutic validity and effectiveness of exercise interventions after lower limb-salvage surgery (LSS) for sarcoma. Methods: A systematic review was conducted using formal narrative synthesis of intervention studies (with and without control group) identified through PubMed, Embase, Cochrane Library, CINAHL, and PEDro databases. Studies were included if participants were treated with LSS for unilateral lower limb sarcoma and followed an exercise intervention using active exercise, physical training, or rehabilitation before and/or after surgery. This review's outcome measures were interventions' therapeutic validity, assessed using the CONTENT scale (0 to 9); methodological quality, identified using the Downs & Black checklist (0 to 28); interventions' effectiveness, assessed based on differences in outcome measures between intervention and control groups; and certainty of evidence, classified according to the GRADE approach. Results: Seven studies involving 214 participants were included. None of the included interventions were therapeutically valid (median 5, range 1–5). All but one study were of at least fair methodological quality (median 18, range 14–21). There was very low-quality evidence that exercise interventions resulted in increased knee range of motion (MD 10–15°) or compliance (MD 30%), and reduced functionality scores (MD -5%) compared to usual care. Conclusions: We found overall low therapeutic validity of interventions, performed in overall low-quality studies. Combined with the very low certainty of evidence, the results prevent drawing valid conclusions on the interventions' effectiveness. Future studies should aim for uniformity among their methodological approaches and outcome measures, using the CONTENT scale as a template to avert insufficient reporting. Trial registration: PROSPERO CRD42021244635. [ABSTRACT FROM AUTHOR]

Objective: Rare disease. Background: BCOR::CCNB3 sarcoma is a rare mesenchymal tumor that was formerly included in the undifferentiated/unclassified sarcoma group and was recently reclassified as one of undifferentiated small round cell sarcomas with a genetically distinct subtype in the WHO 2020 classification. Because of its rarity, still not much is known, especially about its clinical features. Case Report: A 15-year-old boy presented with almost 1-year intermittent thigh pain. On the first visit, a pathologic fracture of the femur and a big mass expanding through the femoral cortex with lobular shape and homogenous appearance were recognized on radiography and magnetic resonance imaging. Plain radiography, which was taken 6 months before at a local clinic, showed an expansion and thickening of the right proximal femoral shaft. Biopsy specimen of the lesion revealed a proliferation of round to spindle tumor cells with diffuse and strong immunohistochemical nuclear positivity for BCOR and CCNB3. Under the diagnosis of BCOR::CCNB3 sarcoma of the femur, a chemotherapy based on a protocol of Ewing sarcoma, followed by a wide resection and total femoral replacement surgery, were conducted. The effect of chemotherapy was favorable, showing no microscopic residual tumor. Although postoperative chemotherapy was not completed because of a minor infection detected on the surgical site, the patient was doing well, without any recurrence, for 3 years. Conclusions: BCOR::CCNB3 sarcoma of the bone is a quite rare tumor with much lower incidence than Ewing sarcoma. Notable clinical characteristics of the current case were a 1-year-long symptomatic period and homogenous appearance on MRI. [ABSTRACT FROM AUTHOR]

We retrospectively reviewed 28 patients (15 women and 13 men) with benign bone tumors or pseudotumors treated with curettage and filling with freeze-dried bovine bone graft Orthogen (Baumer S/A, São Paulo, Brazil). The aim of the study was to evaluate the rate of incorporation of Orthogen into the host bone, as well as to describe the outcomes of bone healing (quality, time, and complications). General characteristics, tumor volume, size, site, complications, percent filled, and healing quality at 6 and 12 months were assessed through radiographs. Mean patient age was 20.5 (range 4.7–75.1) years. The most common lesion type was simple bone cyst (12/28), and the most common sites were the tibia (7/28) and humerus (7/28). There were no postoperative pathologic fractures. Two cases (7.1%) of serous fluid leakage through the wound occurred. Mean cavity volume was 20.1 (range 2.7–101.4) cm3. At 6 and 12 months, 75% and 77.8% of cavities, respectively, showed complete bone healing. At 12 months, 81% of cavities filled >90% with graft showed complete bone healing vs. only 19% of those filled <90%. Filling with bovine bone graft resulted in few complications and excellent healing after curettage of benign bone tumors or pseudotumors. Complete healing occurred in most cases by 12 months. Cavities with a higher percentage of filling had a higher rate of complete radiographic incorporation. [ABSTRACT FROM AUTHOR]

The role of interventional radiology (IR) is expanding. With new techniques being developed and tested, this radiology subspecialty is taking a step forward in different clinical scenarios, especially in oncology. Musculoskeletal tumoral diseases would definitely benefit from a low-invasive approach that could reduce mortality and morbidity in particular. Thermal ablation through IR has already become important in the palliation and consolidation of bone metastases, oligometastatic disease, local recurrences, and treating specific benign tumors, with a more tailored approach, considering the characteristics of every patient. As image-guided ablation techniques lower their invasiveness and increase their efficacy while the collateral effects and complications decrease, they become more relevant and need to be considered in patient care pathways and clinical management, to improve outcomes. We present a literature review of the different percutaneous and non-invasive image-guided thermal ablation methods that are currently available and that could in the future become relevant to manage musculoskeletal oncologic diseases. [ABSTRACT FROM AUTHOR]

Bone marrow edema (BME)-like signal intensity involving the epiphyses of tubular bones represents a frequent magnetic resonance imaging finding associated with a wide spectrum of bone and joint disorders. It is important to distinguish this finding from cellular infiltration of bone marrow and to be aware of the differential diagnosis of underlying causes. With a general focus on the adult musculoskeletal system, this article reviews the pathophysiology, clinical presentation, histopathology, and imaging findings of nontraumatic conditions associated with epiphyseal BME-like signal intensity: transient bone marrow edema syndrome, subchondral insufficiency fracture, avascular necrosis, osteoarthritis, arthritis, and bone neoplasms. [ABSTRACT FROM AUTHOR]

Background: Insufficient evidence exists to support or refute use of NSAIDs for managing cancer pain. Palliative physicians support a placebo-controlled trial of NSAIDs as strong opioid adjuncts for cancer-induced bone pain as the most pragmatic design to benefit clinical practice. Aim: We aimed to determine patient numbers receiving palliative radiotherapy for cancer-induced bone pain, estimate the suitability of NSAID prescription and determine survival, guiding future trial feasibility. Design: A retrospective observational database analysis was undertaken using 5 years of routinely collected regional radiotherapy and healthcare data, filtered to achieve a cohort with cancer-induced bone pain. Demographics and survival were linked to available serology and co-morbidity data. Setting/participants: Data was sourced from the regional Leeds Cancer Centre, a tertiary care setting. Patients who underwent palliative single fraction 8 gray (Gy) radiotherapy treatment for cancer-induced bone pain were included, totalling 2411 over 5 years. Results: A mean of 478 patients received palliative radiotherapy for cancer-induced bone pain annually. Median age (IQR) was 70 (62–77); negatively skewed (−0.69). 65.3% died within 1 year of radiotherapy; 48.0% within 6 months. Age was not associated with survival on univariable analysis (HR 0.999 (95% CI 0.996–1.003)). Serology from 1063 patients (44.2%) were available; eGFR was ⩾60 mL/min/1.73 m2 in 83.0%. From available data (1352 pts; 51.6% of sample), 20.2% had a coded co-morbidity contra-indicating NSAIDs. Combining serology and co-morbidities, 68.5% could be considered for NSAID prescription. Conclusions: Patient numbers at a regional radiotherapy centre support the feasibility of trial recruitment. Available serology and co-morbidity data suggest two-thirds may be suitable for NSAID prescription. [ABSTRACT FROM AUTHOR]

Aim: Mega-prosthetic reconstruction is the most common treatment method for massive osteoarticular defects caused by tumor resection around the knee. The new implant is a highly modular rotational-hinged megaprosthesis system with a distinct pentagonal stem geometry and variable implantation options. The aim of this study is to present the mid-term implant survival characteristics, functional and radiological results and mechanical complication profile of the new megaprosthesis. Methods: One hundred and one mega-prosthetic knee reconstruction procedures in 90 patients (M/F: 51/39) utilizing the new implant system were retrospectively analyzed. In 68 patients, the megaprosthesis was used for primary reconstruction following tumor resection while it was used for revision of other implants in 22. The mean age was 28.5 (7–66) years and the mean follow-up was 59.2 (24–124) months. The most common primary pathology was osteosarcoma with 63–70% patients, the most common anatomical site of involvement was the distal femur with 56–62% patients. Results: Henderson Type 2 failure (aseptic loosening) was seen in only 2–2.2% patients while Type 3 (structural failure) was seen in 29–32.2% Although the 5-year anchorage survival rate was 94.3%, overall mechanical implant survival was 76.1% at 5 years due to a relatively high failure rate in the first-generation hinge mechanism of the implant. The 5-year hinge survival rate demonstrated a significant improvement rate from 61.7% to 87.2% between the first and second generations of the implant (p = 0.027). The mean MSTS score was 24 out of 30 (14–29). The mean cumulative ISOLS radiographic score for index megaprosthesis operations was 19.7 (12–24), which corresponded to excellent outcome. Conclusion: The new megaprosthesis system is a reliable choice for the reconstruction of tumor-related massive osteoarticular defects around the knee. Although long-term follow-up is necessary for a definitive evaluation of the implant's survival characteristics, midterm follow-up yields exceptional anchorage properties related to pentagonal stem geometry with very good functional outcomes. [ABSTRACT FROM AUTHOR]

Aim: Bone tissue is the primary organ of hematopoiesis and osteogenesis in healthy individuals. Bone tissue is one of the most frequently metastasized organs. In addition, for all types of cancer, it is an indication that cancer has reached a level where it can no longer be cured and the patient's life expectancy is reduced. The aim of this study was to retrospectively evaluate the cases operated for bone metastasis. Material and Methods: A total of 67 patients who underwent a biopsy or operation due to bone tumors at Eskişehir Osmangazi University Medical Faculty Hospital between January 2020 and January 2022 were included in this study. Results: Of the metastatic cases, 49 (73.1%) were male and 18 (26.9%) were female. The mean age of the patients was 61.7±19.8 (range, 9-88) years. The most frequently metastasized tumors were lung carcinoma and tumor of unknown primary in males, while lung and breast in females. Tumors most frequently metastasize to the spine region. There were 6 (9.0%) cases, 1 (1.5%) of which was mesenchymal, in which the primary origin couldn't be detected in metastatic tumors. Conclusion: Bone pain is always a symptom that is suspicious for metastasis in a patient followed up with a diagnosis of cancer and requires further investigation. Treatment is more palliative after bone metastasis. There is a need for targeted studies to prevent metastasis. It should be kept in mind that the primary focus may not be detected in all clinical and imaging methods in a group of patients. [ABSTRACT FROM AUTHOR]

Hemangiopericytoma/solitary fibrous tumor (HPC/STF) is a rare tumor arising from Zimmerman's pericytes and it is characterized by an aggressive malignancy, with a high tendency for local and distant recurrence. The authors report the case of a middle-aged woman with HPC/SFT of the right parietal bone, which is an extremely rare primary location of involvement. The patient presented with a painful deformity of insidious growth at the right parietal region. Assessment with cranial computed tomography scan and magnetic resonance imaging revealed an expansive lesion at the right parietal bone, with exocranial extension and 27 mm of maximal diameter. Craniotomy with gross tumor removal, duraplasty, and cranioplasty was performed, and the diagnosis of HPC/SFT, WHO grade III, was established by pathological and immunohistochemical analysis. The patient was then evaluated for adjuvant radiation therapy and received a dose of 60 Gy (2 Gy/fraction) with 3D conformal radiotherapy to the surgical bed. The adjuvant treatment was uneventful and, after 8 months of follow-up, there was no suspected local or distant recurrence. The rarity of this diagnosis, its aggressive behavior, and the lack of published data posed several challenges for the treatment management. [ABSTRACT FROM AUTHOR]

Objectives: To develop and validate machine learning models to distinguish between benign and malignant bone lesions and compare the performance to radiologists. Methods: In 880 patients (age 33.1 ± 19.4 years, 395 women) diagnosed with malignant (n = 213, 24.2%) or benign (n = 667, 75.8%) primary bone tumors, preoperative radiographs were obtained, and the diagnosis was established using histopathology. Data was split 70%/15%/15% for training, validation, and internal testing. Additionally, 96 patients from another institution were obtained for external testing. Machine learning models were developed and validated using radiomic features and demographic information. The performance of each model was evaluated on the test sets for accuracy, area under the curve (AUC) from receiver operating characteristics, sensitivity, and specificity. For comparison, the external test set was evaluated by two radiology residents and two radiologists who specialized in musculoskeletal tumor imaging. Results: The best machine learning model was based on an artificial neural network (ANN) combining both radiomic and demographic information achieving 80% and 75% accuracy at 75% and 90% sensitivity with 0.79 and 0.90 AUC on the internal and external test set, respectively. In comparison, the radiology residents achieved 71% and 65% accuracy at 61% and 35% sensitivity while the radiologists specialized in musculoskeletal tumor imaging achieved an 84% and 83% accuracy at 90% and 81% sensitivity, respectively. Conclusions: An ANN combining radiomic features and demographic information showed the best performance in distinguishing between benign and malignant bone lesions. The model showed lower accuracy compared to specialized radiologists, while accuracy was higher or similar compared to residents. Key Points: • The developed machine learning model could differentiate benign from malignant bone tumors using radiography with an AUC of 0.90 on the external test set. • Machine learning models that used radiomic features or demographic information alone performed worse than those that used both radiomic features and demographic information as input, highlighting the importance of building comprehensive machine learning models. • An artificial neural network that combined both radiomic and demographic information achieved the best performance and its performance was compared to radiology readers on an external test set. [ABSTRACT FROM AUTHOR]

Background: Even though radiologic diagnosis of bone tumors and tumor-like lesions is usually based on radiographs, radiographically faint imaging features sometimes remain challenging due to overlapping anatomical structures. Purpose: To compare tomosynthesis with radiography for the evaluation of bone tumors and tumor-like lesions. Material and Methods: Forty-seven bone tumors and tumor-like lesions were assessed with radiographs and tomosynthesis images. Two radiologists independently analyzed imaging features of lesions, including margin, periosteal reaction, cortical thinning, matrix mineralization, cortical destruction (such as pathologic fracture), and extraosseous soft-tissue extension. Computed tomography (CT) imaging was used as a reference method. Diagnostic performances of radiography and tomosynthesis were analyzed and compared based on sensitivity, specificity, accuracy, positive predictive value, and negative predictive value. Effective radiation dose was compared among the three imaging modalities by phantom studies. Results: Inter-observer variability (kappa value) for imaging features was slight to moderate on radiography (0.167–0.588), whereas it was nearly perfect on tomosynthesis (0.898–1.000) except for extraosseous soft-tissue extension (0.647 vs. 0.647). Tomosynthesis showed significantly higher sensitivity than radiography in evaluating the margin for bone tumors or tumor-like lesions (1.00 vs. 0.85; P = 0.016), and significantly higher accuracy than radiography in evaluating the margin and matrix mineralization for those (1.00 vs. 0.85; P = 0.016 and 0.91 vs.0.77; P = 0.023, respectively). In phantom studies, mean effective radiation doses were highest in order of CT, tomography, and radiography. Conclusion: Tomosynthesis increases sensitivity and accuracy of the margin as well as accuracy of the matrix mineralization of bone tumors and tumor-like lesions compared to radiography. [ABSTRACT FROM AUTHOR]

Purpose: Morphological magnetic resonance (MR) and computed tomography (CT) features are used in combination with histology for diagnosis and treatment selection of primary bone neoplasms. Isolated functional MRI parameters have shown potential in diagnosis. Our goal is to facilitate diagnosis of primary bone neoplasms of the skull base, mobile spine and sacrum, by a comprehensive approach, combining morphological and functional imaging parameters.Pre-treatment MR of 80 patients with histologically proven diagnosis of a primary bone neoplasm of the skull base, mobile spine and sacrum were retrospectively analyzed for morphological and functional MRI parameters. Functional parameters were measured in 4 circular regions of interest per tumor placed on non-adjacent scan slices. Differences in values of functional parameters between different histologies were analyzed with Dunn’s test.Chordomas were the predominant histology (60.0%). Most neoplasms (80.0%) originated in the midline and had geographical (78.2%) bone destruction. Amorphous-type calcification (pre-existing bone) was seen only in chordomas. Homogeneous contrast enhancement pattern was seen only in chondrosarcoma and plasmacytoma. Ktrans and Kep were significantly lower in both chordoma, and chondrosarcoma compared to giant cell tumor of the bone (p = 0.006 – 0.011), and plasmacytoma (p = 0.004 – 0.014). Highest diffusion-weighted MRI apparent diffusion coefficient (ADC) values corresponded to chondrosarcoma and were significantly higher to those of chordoma (p = 0.008).We identified the most discriminating morphological parameters and added functional MR parameters based on histopathological features that are useful in making a confident diagnosis of primary bone neoplasms in the skull base, mobile spine and sacrum.Materials and methods: Morphological magnetic resonance (MR) and computed tomography (CT) features are used in combination with histology for diagnosis and treatment selection of primary bone neoplasms. Isolated functional MRI parameters have shown potential in diagnosis. Our goal is to facilitate diagnosis of primary bone neoplasms of the skull base, mobile spine and sacrum, by a comprehensive approach, combining morphological and functional imaging parameters.Pre-treatment MR of 80 patients with histologically proven diagnosis of a primary bone neoplasm of the skull base, mobile spine and sacrum were retrospectively analyzed for morphological and functional MRI parameters. Functional parameters were measured in 4 circular regions of interest per tumor placed on non-adjacent scan slices. Differences in values of functional parameters between different histologies were analyzed with Dunn’s test.Chordomas were the predominant histology (60.0%). Most neoplasms (80.0%) originated in the midline and had geographical (78.2%) bone destruction. Amorphous-type calcification (pre-existing bone) was seen only in chordomas. Homogeneous contrast enhancement pattern was seen only in chondrosarcoma and plasmacytoma. Ktrans and Kep were significantly lower in both chordoma, and chondrosarcoma compared to giant cell tumor of the bone (p = 0.006 – 0.011), and plasmacytoma (p = 0.004 – 0.014). Highest diffusion-weighted MRI apparent diffusion coefficient (ADC) values corresponded to chondrosarcoma and were significantly higher to those of chordoma (p = 0.008).We identified the most discriminating morphological parameters and added functional MR parameters based on histopathological features that are useful in making a confident diagnosis of primary bone neoplasms in the skull base, mobile spine and sacrum.Results: Morphological magnetic resonance (MR) and computed tomography (CT) features are used in combination with histology for diagnosis and treatment selection of primary bone neoplasms. Isolated functional MRI parameters have shown potential in diagnosis. Our goal is to facilitate diagnosis of primary bone neoplasms of the skull base, mobile spine and sacrum, by a comprehensive approach, combining morphological and functional imaging parameters.Pre-treatment MR of 80 patients with histologically proven diagnosis of a primary bone neoplasm of the skull base, mobile spine and sacrum were retrospectively analyzed for morphological and functional MRI parameters. Functional parameters were measured in 4 circular regions of interest per tumor placed on non-adjacent scan slices. Differences in values of functional parameters between different histologies were analyzed with Dunn’s test.Chordomas were the predominant histology (60.0%). Most neoplasms (80.0%) originated in the midline and had geographical (78.2%) bone destruction. Amorphous-type calcification (pre-existing bone) was seen only in chordomas. Homogeneous contrast enhancement pattern was seen only in chondrosarcoma and plasmacytoma. Ktrans and Kep were significantly lower in both chordoma, and chondrosarcoma compared to giant cell tumor of the bone (p = 0.006 – 0.011), and plasmacytoma (p = 0.004 – 0.014). Highest diffusion-weighted MRI apparent diffusion coefficient (ADC) values corresponded to chondrosarcoma and were significantly higher to those of chordoma (p = 0.008).We identified the most discriminating morphological parameters and added functional MR parameters based on histopathological features that are useful in making a confident diagnosis of primary bone neoplasms in the skull base, mobile spine and sacrum.Conclusion: Morphological magnetic resonance (MR) and computed tomography (CT) features are used in combination with histology for diagnosis and treatment selection of primary bone neoplasms. Isolated functional MRI parameters have shown potential in diagnosis. Our goal is to facilitate diagnosis of primary bone neoplasms of the skull base, mobile spine and sacrum, by a comprehensive approach, combining morphological and functional imaging parameters.Pre-treatment MR of 80 patients with histologically proven diagnosis of a primary bone neoplasm of the skull base, mobile spine and sacrum were retrospectively analyzed for morphological and functional MRI parameters. Functional parameters were measured in 4 circular regions of interest per tumor placed on non-adjacent scan slices. Differences in values of functional parameters between different histologies were analyzed with Dunn’s test.Chordomas were the predominant histology (60.0%). Most neoplasms (80.0%) originated in the midline and had geographical (78.2%) bone destruction. Amorphous-type calcification (pre-existing bone) was seen only in chordomas. Homogeneous contrast enhancement pattern was seen only in chondrosarcoma and plasmacytoma. Ktrans and Kep were significantly lower in both chordoma, and chondrosarcoma compared to giant cell tumor of the bone (p = 0.006 – 0.011), and plasmacytoma (p = 0.004 – 0.014). Highest diffusion-weighted MRI apparent diffusion coefficient (ADC) values corresponded to chondrosarcoma and were significantly higher to those of chordoma (p = 0.008).We identified the most discriminating morphological parameters and added functional MR parameters based on histopathological features that are useful in making a confident diagnosis of primary bone neoplasms in the skull base, mobile spine and sacrum. [ABSTRACT FROM AUTHOR]

Bone cancer pain (BCP) profoundly impacts patient’s quality of life, demanding more effective pain management strategies. The aim of this systematic review was to investigate the role of inflammatory cytokines as potential molecular targets in BCP. A systematic search for animal rodent models of bone cancer pain studies was conducted in PubMed, Scopus, and Web of Science. Methodological quality and risk of bias were assessed using the SYRCLE RoB tool. Twenty-five articles met the inclusion criteria, comprising animal studies investigating molecular targets related to inflammatory cytokines in BCP. A low to moderate risk of bias was reported. Key findings in 23 manuscripts revealed upregulated classic pro-inflammatory cytokines (TNF-α, IL-1β, IL-6, IL-17, IL-18, IL-33) and chemokines in the spinal cord, periaqueductal gray, and dorsal root ganglia. Interventions targeting these cytokines consistently mitigated pain behaviors. Additionally, it was demonstrated that glial cells, due to their involvement in the release of inflammatory cytokines, emerged as significant contributors to BCP. This systematic review underscores the significance of inflammatory cytokines as potential molecular targets for alleviating BCP. It emphasizes the promise of targeted interventions and advocates for further research to translate these findings into effective therapeutic strategies. Ultimately, this approach holds the potential to enhance the patient’s quality of life. [ABSTRACT FROM AUTHOR]

Objectives: To evaluate the performance and reproducibility of MR imaging features in the diagnosis of joint invasion (JI) by malignant bone tumors. Methods: MR images of patients with and without JI (n = 24 each), who underwent surgical resection at our institution, were read by three radiologists. Direct (intrasynovial tumor tissue (ITT), intraarticular destruction of cartilage/bone, invasion of capsular/ligamentous insertions) and indirect (tumor size, signal alterations of epiphyseal/transarticular bone (bone marrow replacement/edema-like), synovial contrast enhancement, joint effusion) signs of JI were assessed. Odds ratios, sensitivity, specificity, PPV, NPV, and reproducibilities (Cohen's and Fleiss' κ) were calculated for each feature. Moreover, the diagnostic performance of combinations of direct features was assessed. Results: Forty-eight patients (28.7 ± 21.4 years, 26 men) were evaluated. All readers reliably assessed the presence of JI (sensitivity = 92–100 %; specificity = 88–100%, respectively). Best predictors for JI were direct visualization of ITT (OR = 186–229, p < 0.001) and destruction of intraarticular bone (69–324, p < 0.001). Direct visualization of ITT was also highly reliable in assessing JI (sensitivity, specificity, PPV, NPV = 92–100 %), with excellent reproducibility (κ = 0.83). Epiphyseal bone marrow replacement and synovial contrast enhancement were the most sensitive indirect signs, but lacked specificity (29–54%). By combining direct signs with high specificity, sensitivity was increased (96 %) and specificity (100 %) was maintained. Conclusion: JI by malignant bone tumors can reliably be assessed on preoperative MR images with high sensitivity, specificity, and reproducibility. Particularly direct visualization of ITT, destruction of intraarticular bone, and a combination of highly specific direct signs were valuable, while indirect signs were less predictive and specific. Key Points: • Direct visualization of intrasynovial tumor was the single most sensitive and specific (92–100%) MR imaging sign of joint invasion. • Indirect signs of joint invasion, such as joint effusion or synovial enhancement, were less sensitive and specific compared to direct signs. • A combination of the most specific direct signs of joint invasion showed best results with perfect specificity and PPV (both 100%) and excellent sensitivity and NPV (both 96 %). [ABSTRACT FROM AUTHOR]

Objective: To report a single center's experience evaluating the efficacy and safety of computed tomography–guided radiofrequency ablation for the treatment of osteoid osteoma in children. Materials and methods: Institutional database research identified 33 symptomatic patients (≤ 18 years of age; male/female ratio: 21/12, mean age 13.09 ± 3.66) with osteoid osteoma who were treated by CT-guided RFA. Technical and clinical success as well as complication rates were recorded. The duration of the procedure, the number of computed tomography scans and the results of the biopsy were assessed. Pain, prior, the following morning and 1 week, 1/6/12 months after the procedure were compared by means of a numeric visual scale (NVS) questionnaire. Results: Mean lesion size was 8.28 ± 4.24 mm. Mean follow-up was 23.33 ± 17.61 months (range 12–62). Mean pain score prior to radiofrequency ablation was 9.06 ± 0.80 NVS units. On week 1 and 1/6/12 months, all patients were pain-free reporting 0 NVS units (p < 0.05). The mean procedure time was 54 min (range 51–59) and a mean of 7 CT scans were performed during the ablation session. RF electrode was successfully placed in the center of the nidus in all cases. In our study, none of our patient experienced recurrence of the pain, nor complications. Conclusion: The present study demonstrates that percutaneous CT-guided radiofrequency ablation constitutes a safe and effective technique for osteoid osteoma treatment in children. [ABSTRACT FROM AUTHOR]

Giant cell tumour of bone (GCTB) is a locally aggressive bone neoplasm with a rare tendency to metastasise, most commonly to the lungs. The management of metastatic GCTB (metGCTB) is controversial due to its unpredictable behaviour. Asymptomatic patients should be monitored radiologically and undergo treatment only when disease progression occurs. Surgery is recommended for resectable metGCTB. Denosumab, a monoclonal antibody which inhibits receptor activator of nuclear factor‐κB ligand, is recommended for unresectable metGCTB with evidence from phase II trials demonstrating its safety and efficacy. Relapse after denosumab withdrawal may occur and prolonged treatment may be associated with serious adverse events, thus further research is warranted to inform a maintenance regimen with reduced dosing and frequency. Combined denosumab and bisphosphonate therapy has the potential to achieve sustained disease control or remission in unresectable metGCTB without requiring long‐term treatment and should be evaluated in prospective trials. Various novel agents have demonstrated in vitro and anecdotal efficacy and warrant further evaluation. [ABSTRACT FROM AUTHOR]

Objectives: To build and validate deep learning and machine learning fusion models to classify benign, malignant, and intermediate bone tumors based on patient clinical characteristics and conventional radiographs of the lesion. Methods: In this retrospective study, data were collected with pathologically confirmed diagnoses of bone tumors between 2012 and 2019. Deep learning and machine learning fusion models were built to classify tumors as benign, malignant, or intermediate using conventional radiographs of the lesion and potentially relevant clinical data. Five radiologists compared diagnostic performance with and without the model. Diagnostic performance was evaluated using the area under the curve (AUC). Results: A total of 643 patients' (median age, 21 years; interquartile range, 12–38 years; 244 women) 982 radiographs were included. In the test set, the binary category classification task, the radiological model of classification for benign/not benign, malignant/nonmalignant, and intermediate/not intermediate had AUCs of 0.846, 0.827, and 0.820, respectively; the fusion models had an AUC of 0.898, 0.894, and 0.865, respectively. In the three-category classification task, the radiological model achieved a macro average AUC of 0.813, and the fusion model had a macro average AUC of 0.872. In the observation test, the mean macro average AUC of all radiologists was 0.819. With the three-category classification fusion model support, the macro AUC improved by 0.026. Conclusion: We built, validated, and tested deep learning and machine learning models that classified bone tumors at a level comparable with that of senior radiologists. Model assistance may somewhat help radiologists' differential diagnoses of bone tumors. Key Points: • The deep learning model can be used to classify benign, malignant, and intermediate bone tumors. • The machine learning model fusing information from radiographs and clinical characteristics can improve the classification capacity for bone tumors. • The diagnostic performance of the fusion model is comparable with that of senior radiologists and is potentially useful as a complement to radiologists in a bone tumor differential diagnosis. [ABSTRACT FROM AUTHOR]

Objectives: To develop an algorithm to link undiagnosed patients to previous patient histories based on radiographs, and simultaneous classification of multiple bone tumours to enable early and specific diagnosis.For this retrospective study, data from 2000 to 2021 were curated from our database by two orthopaedic surgeons, a radiologist and a data scientist. Patients with complete clinical and pre-therapy radiographic data were eligible. To ensure feasibility, the ten most frequent primary tumour entities, confirmed histologically or by tumour board decision, were included. We implemented a ResNet and transformer model to establish baseline results. Our method extracts image features using deep learning and then clusters the k most similar images to the target image using a hash-based nearest-neighbour recommender approach that performs simultaneous classification by majority voting. The results were evaluated with precision-at-k, accuracy, precision and recall. Discrete parameters were described by incidence and percentage ratios. For continuous parameters, based on a normality test, respective statistical measures were calculated.Included were data from 809 patients (1792 radiographs; mean age 33.73 ± 18.65, range 3–89 years; 443 men), with Osteochondroma (28.31%) and Ewing sarcoma (1.11%) as the most and least common entities, respectively. The dataset was split into training (80%) and test subsets (20%). For k = 3, our model achieved the highest mean accuracy, precision and recall (92.86%, 92.86% and 34.08%), significantly outperforming state-of-the-art models (54.10%, 55.57%, 19.85% and 62.80%, 61.33%, 23.05%).Our novel approach surpasses current models in tumour classification and links to past patient data, leveraging expert insights.The proposed algorithm could serve as a vital support tool for clinicians and general practitioners with limited experience in bone tumour classification by identifying similar cases and classifying bone tumour entities.• Addressed accurate bone tumour classification using radiographic features.• Model achieved 92.86%, 92.86% and 34.08% mean accuracy, precision and recall, respectively, significantly surpassing state-of-the-art models.• Enhanced diagnosis by integrating prior expert patient assessments.Materials and methods: To develop an algorithm to link undiagnosed patients to previous patient histories based on radiographs, and simultaneous classification of multiple bone tumours to enable early and specific diagnosis.For this retrospective study, data from 2000 to 2021 were curated from our database by two orthopaedic surgeons, a radiologist and a data scientist. Patients with complete clinical and pre-therapy radiographic data were eligible. To ensure feasibility, the ten most frequent primary tumour entities, confirmed histologically or by tumour board decision, were included. We implemented a ResNet and transformer model to establish baseline results. Our method extracts image features using deep learning and then clusters the k most similar images to the target image using a hash-based nearest-neighbour recommender approach that performs simultaneous classification by majority voting. The results were evaluated with precision-at-k, accuracy, precision and recall. Discrete parameters were described by incidence and percentage ratios. For continuous parameters, based on a normality test, respective statistical measures were calculated.Included were data from 809 patients (1792 radiographs; mean age 33.73 ± 18.65, range 3–89 years; 443 men), with Osteochondroma (28.31%) and Ewing sarcoma (1.11%) as the most and least common entities, respectively. The dataset was split into training (80%) and test subsets (20%). For k = 3, our model achieved the highest mean accuracy, precision and recall (92.86%, 92.86% and 34.08%), significantly outperforming state-of-the-art models (54.10%, 55.57%, 19.85% and 62.80%, 61.33%, 23.05%).Our novel approach surpasses current models in tumour classification and links to past patient data, leveraging expert insights.The proposed algorithm could serve as a vital support tool for clinicians and general practitioners with limited experience in bone tumour classification by identifying similar cases and classifying bone tumour entities.• Addressed accurate bone tumour classification using radiographic features.• Model achieved 92.86%, 92.86% and 34.08% mean accuracy, precision and recall, respectively, significantly surpassing state-of-the-art models.• Enhanced diagnosis by integrating prior expert patient assessments.Results: To develop an algorithm to link undiagnosed patients to previous patient histories based on radiographs, and simultaneous classification of multiple bone tumours to enable early and specific diagnosis.For this retrospective study, data from 2000 to 2021 were curated from our database by two orthopaedic surgeons, a radiologist and a data scientist. Patients with complete clinical and pre-therapy radiographic data were eligible. To ensure feasibility, the ten most frequent primary tumour entities, confirmed histologically or by tumour board decision, were included. We implemented a ResNet and transformer model to establish baseline results. Our method extracts image features using deep learning and then clusters the k most similar images to the target image using a hash-based nearest-neighbour recommender approach that performs simultaneous classification by majority voting. The results were evaluated with precision-at-k, accuracy, precision and recall. Discrete parameters were described by incidence and percentage ratios. For continuous parameters, based on a normality test, respective statistical measures were calculated.Included were data from 809 patients (1792 radiographs; mean age 33.73 ± 18.65, range 3–89 years; 443 men), with Osteochondroma (28.31%) and Ewing sarcoma (1.11%) as the most and least common entities, respectively. The dataset was split into training (80%) and test subsets (20%). For k = 3, our model achieved the highest mean accuracy, precision and recall (92.86%, 92.86% and 34.08%), significantly outperforming state-of-the-art models (54.10%, 55.57%, 19.85% and 62.80%, 61.33%, 23.05%).Our novel approach surpasses current models in tumour classification and links to past patient data, leveraging expert insights.The proposed algorithm could serve as a vital support tool for clinicians and general practitioners with limited experience in bone tumour classification by identifying similar cases and classifying bone tumour entities.• Addressed accurate bone tumour classification using radiographic features.• Model achieved 92.86%, 92.86% and 34.08% mean accuracy, precision and recall, respectively, significantly surpassing state-of-the-art models.• Enhanced diagnosis by integrating prior expert patient assessments.Conclusion: To develop an algorithm to link undiagnosed patients to previous patient histories based on radiographs, and simultaneous classification of multiple bone tumours to enable early and specific diagnosis.For this retrospective study, data from 2000 to 2021 were curated from our database by two orthopaedic surgeons, a radiologist and a data scientist. Patients with complete clinical and pre-therapy radiographic data were eligible. To ensure feasibility, the ten most frequent primary tumour entities, confirmed histologically or by tumour board decision, were included. We implemented a ResNet and transformer model to establish baseline results. Our method extracts image features using deep learning and then clusters the k most similar images to the target image using a hash-based nearest-neighbour recommender approach that performs simultaneous classification by majority voting. The results were evaluated with precision-at-k, accuracy, precision and recall. Discrete parameters were described by incidence and percentage ratios. For continuous parameters, based on a normality test, respective statistical measures were calculated.Included were data from 809 patients (1792 radiographs; mean age 33.73 ± 18.65, range 3–89 years; 443 men), with Osteochondroma (28.31%) and Ewing sarcoma (1.11%) as the most and least common entities, respectively. The dataset was split into training (80%) and test subsets (20%). For k = 3, our model achieved the highest mean accuracy, precision and recall (92.86%, 92.86% and 34.08%), significantly outperforming state-of-the-art models (54.10%, 55.57%, 19.85% and 62.80%, 61.33%, 23.05%).Our novel approach surpasses current models in tumour classification and links to past patient data, leveraging expert insights.The proposed algorithm could serve as a vital support tool for clinicians and general practitioners with limited experience in bone tumour classification by identifying similar cases and classifying bone tumour entities.• Addressed accurate bone tumour classification using radiographic features.• Model achieved 92.86%, 92.86% and 34.08% mean accuracy, precision and recall, respectively, significantly surpassing state-of-the-art models.• Enhanced diagnosis by integrating prior expert patient assessments.Clinical relevance statement: To develop an algorithm to link undiagnosed patients to previous patient histories based on radiographs, and simultaneous classification of multiple bone tumours to enable early and specific diagnosis.For this retrospective study, data from 2000 to 2021 were curated from our database by two orthopaedic surgeons, a radiologist and a data scientist. Patients with complete clinical and pre-therapy radiographic data were eligible. To ensure feasibility, the ten most frequent primary tumour entities, confirmed histologically or by tumour board decision, were included. We implemented a ResNet and transformer model to establish baseline results. Our method extracts image features using deep learning and then clusters the k most similar images to the target image using a hash-based nearest-neighbour recommender approach that performs simultaneous classification by majority voting. The results were evaluated with precision-at-k, accuracy, precision and recall. Discrete parameters were described by incidence and percentage ratios. For continuous parameters, based on a normality test, respective statistical measures were calculated.Included were data from 809 patients (1792 radiographs; mean age 33.73 ± 18.65, range 3–89 years; 443 men), with Osteochondroma (28.31%) and Ewing sarcoma (1.11%) as the most and least common entities, respectively. The dataset was split into training (80%) and test subsets (20%). For k = 3, our model achieved the highest mean accuracy, precision and recall (92.86%, 92.86% and 34.08%), significantly outperforming state-of-the-art models (54.10%, 55.57%, 19.85% and 62.80%, 61.33%, 23.05%).Our novel approach surpasses current models in tumour classification and links to past patient data, leveraging expert insights.The proposed algorithm could serve as a vital support tool for clinicians and general practitioners with limited experience in bone tumour classification by identifying similar cases and classifying bone tumour entities.• Addressed accurate bone tumour classification using radiographic features.• Model achieved 92.86%, 92.86% and 34.08% mean accuracy, precision and recall, respectively, significantly surpassing state-of-the-art models.• Enhanced diagnosis by integrating prior expert patient assessments.Key Points: To develop an algorithm to link undiagnosed patients to previous patient histories based on radiographs, and simultaneous classification of multiple bone tumours to enable early and specific diagnosis.For this retrospective study, data from 2000 to 2021 were curated from our database by two orthopaedic surgeons, a radiologist and a data scientist. Patients with complete clinical and pre-therapy radiographic data were eligible. To ensure feasibility, the ten most frequent primary tumour entities, confirmed histologically or by tumour board decision, were included. We implemented a ResNet and transformer model to establish baseline results. Our method extracts image features using deep learning and then clusters the k most similar images to the target image using a hash-based nearest-neighbour recommender approach that performs simultaneous classification by majority voting. The results were evaluated with precision-at-k, accuracy, precision and recall. Discrete parameters were described by incidence and percentage ratios. For continuous parameters, based on a normality test, respective statistical measures were calculated.Included were data from 809 patients (1792 radiographs; mean age 33.73 ± 18.65, range 3–89 years; 443 men), with Osteochondroma (28.31%) and Ewing sarcoma (1.11%) as the most and least common entities, respectively. The dataset was split into training (80%) and test subsets (20%). For k = 3, our model achieved the highest mean accuracy, precision and recall (92.86%, 92.86% and 34.08%), significantly outperforming state-of-the-art models (54.10%, 55.57%, 19.85% and 62.80%, 61.33%, 23.05%).Our novel approach surpasses current models in tumour classification and links to past patient data, leveraging expert insights.The proposed algorithm could serve as a vital support tool for clinicians and general practitioners with limited experience in bone tumour classification by identifying similar cases and classifying bone tumour entities.• Addressed accurate bone tumour classification using radiographic features.• Model achieved 92.86%, 92.86% and 34.08% mean accuracy, precision and recall, respectively, significantly surpassing state-of-the-art models.• Enhanced diagnosis by integrating prior expert patient assessments.Graphical abstract: To develop an algorithm to link undiagnosed patients to previous patient histories based on radiographs, and simultaneous classification of multiple bone tumours to enable early and specific diagnosis.For this retrospective study, data from 2000 to 2021 were curated from our database by two orthopaedic surgeons, a radiologist and a data scientist. Patients with complete clinical and pre-therapy radiographic data were eligible. To ensure feasibility, the ten most frequent primary tumour entities, confirmed histologically or by tumour board decision, were included. We implemented a ResNet and transformer model to establish baseline results. Our method extracts image features using deep learning and then clusters the k most similar images to the target image using a hash-based nearest-neighbour recommender approach that performs simultaneous classification by majority voting. The results were evaluated with precision-at-k, accuracy, precision and recall. Discrete parameters were described by incidence and percentage ratios. For continuous parameters, based on a normality test, respective statistical measures were calculated.Included were data from 809 patients (1792 radiographs; mean age 33.73 ± 18.65, range 3–89 years; 443 men), with Osteochondroma (28.31%) and Ewing sarcoma (1.11%) as the most and least common entities, respectively. The dataset was split into training (80%) and test subsets (20%). For k = 3, our model achieved the highest mean accuracy, precision and recall (92.86%, 92.86% and 34.08%), significantly outperforming state-of-the-art models (54.10%, 55.57%, 19.85% and 62.80%, 61.33%, 23.05%).Our novel approach surpasses current models in tumour classification and links to past patient data, leveraging expert insights.The proposed algorithm could serve as a vital support tool for clinicians and general practitioners with limited experience in bone tumour classification by identifying similar cases and classifying bone tumour entities.• Addressed accurate bone tumour classification using radiographic features.• Model achieved 92.86%, 92.86% and 34.08% mean accuracy, precision and recall, respectively, significantly surpassing state-of-the-art models.• Enhanced diagnosis by integrating prior expert patient assessments. [ABSTRACT FROM AUTHOR]

Objectives: Amputation due to gangrene and arthroplasty for degenerative joint disease are common orthopedic procedures and are expected to increase as populations age. Histopathologic examination of these specimens can identify unsuspected diseases.Methods: We reviewed gangrenous amputations and large joint arthroplasty specimens for diagnosis of unexpected lymphoma, January 2014 to January 2020. Pathology and medical records were reviewed to determine diagnosis, treatment, and outcome.Results: Five cases (0.08%) of unexpected primary extranodal marginal zone lymphoma (MZL) centered in bone were identified in 1,624 amputations for gangrene and 4,163 arthroplasty specimens. The female-to-male distribution was 3:2. Median age was 71 years (range, 62-87). The 3 cases arising in the setting of gangrene involved the first toe phalanges and metatarsals, and the femoral head was involved in all cases of joint disease (2 cases). The bone showed variable (10%-80%) infiltration by dense populations of small lymphoid cells with MZL immunophenotype. One patient died from sepsis 18.5 months after diagnosis; all others are alive with a median follow-up of 27.45 months.Conclusions: Histopathologic examination of nonneoplastic orthopedic specimens identifies unexpected primary bone extranodal MZL in a small percentage of cases. This neoplasm may be the result of chronic antigenic stimulation in some circumstances. [ABSTRACT FROM AUTHOR]

Objectives: Vertebral invasion is a key prognostic factor and a critical aspect of surgical planning for superior sulcus tumors. This study aims to further evaluate MRI features of vertebral invasion in order to distinguish it from reactive inflammatory changes. Methods: Between 2000 and 2016, a retrospective study was performed at a single institution. All patients with superior sulcus tumors undergoing surgery, including at least two partial vertebrectomies, were included. An expert radiologist evaluated qualitative and quantitative MRI signal intensity characteristics (contrast-to-noise ratio [CNR]) of suspected involved and non-involved vertebrae. A comparison of CNR of invaded and sane vertebrae was performed using non-parametric tests. Imaging data were correlated with pathological findings. Results: A total of 92 surgical samples of vertebrectomy were analyzed. The most specific sequences for invasion were T1 and T2 weighted (92% and 97%, respectively). The most sensitive sequences were contrast enhanced T1 weighted fat suppressed and T2 weighted fat suppressed (100% and 80%). Loss of extrapleural paravertebral fat on the T1-weighted sequence was highly sensitive (100%) but not specific (63%). Using quantitative analysis, the optimum cut-off (p < 0.05) to distinguish invasion from reactive inflammatory changes was CNR > 11 for the T2-weighted fat-sat sequence (sensitivity 100%), CNR > 9 for contrast-enhanced T1-weighted fat-suppressed sequence (sensitivity 100%), and CNR < − 30 for the T1-weighted sequence (specificity 97%). Combining these criteria, 23 partial vertebrectomies could have been avoided in our cohort. Conclusion: Qualitative and quantitative MRI analyses are useful to discriminate vertebral invasion from reactive inflammatory changes. Key Points: • Abnormal signal intensity in a vertebral body adjacent to a superior sulcus tumor may be secondary to direct invasion or reactive inflammatory changes. • Accurate differentiation between invasion and reactive inflammatory changes significantly impacts surgical planning. T1w and T2w are the best sequences to differentiate malignant versus benign bone marrow changes. The use of quantitative analysis improves MRI specificity. • Using contrast media improves the sensitivity for the detection of tumor invasion. [ABSTRACT FROM AUTHOR]

A 65-year-old woman presented with a solid mass on the right temporal area. The mass had grown for over 2 years without any initiating event of trauma or inflammation. Before excision, the patient went through a computed tomography scan, revealing a calcified mass without bony connection. Under general anesthesia, an excisional biopsy was performed. Microscopic examination confirmed a diagnosis of soft tissue osteoma. Soft tissue osteoma is rare, especially in the head and neck region. Osteomas in the temporal region have not been reported yet. Due to its rarity, osteoma might be misdiagnosed as another soft tissue or bone origin tumor. Its treatment of choice is simple excision. In this review, we present an unusual clinical form of soft tissue osteoma. [ABSTRACT FROM AUTHOR]

Objectives: Identify the most pertinent imaging features for solitary bone tumor characterization using a multimodality approach and propose a systematic evaluation system. Methods: Data from a prospective trial, including 230 participants with histologically confirmed bone tumors, typical "do not touch" lesions, and stable chondral lesions, were retrospectively evaluated. Clinical data, CT, and MR imaging features were analyzed by a musculoskeletal radiologist blinded to the diagnosis using a structured report. The benign-malignant distribution of lesions bearing each image feature evaluated was compared to the benign-malignant distribution in the study sample. Benign and malignant indicators were identified. Two additional readers with different expertise levels independently evaluated the study sample. Results: The sample included 140 men and 90 women (mean age 40.7 ± 18.3 years). The global benign-malignant distribution was 67–33%. Seven imaging features reached the criteria for benign indicators with a mean frequency of benignancy of 94%. Six minor malignant indicators were identified with a mean frequency of malignancy of 60.5%. Finally, three major malignant indicators were identified (Lodwick-Madewell grade III, aggressive periosteal reaction, and suspected metastatic disease) with a mean frequency of malignancy of 82.4%. A bone tumor imaging reporting and data system (BTI-RADS) was proposed. The reproducibility of the BTI-RADS was considered fair (kappa = 0.67) with a mean frequency of malignancy in classes I, II, III, and IV of 0%, 2.2%, 20.1%, and 71%, respectively. Conclusion: BTI-RADS is an evidence-based systematic approach to solitary bone tumor characterization with a fair reproducibility, allowing lesion stratification in classes of increasing malignancy frequency. Trial registration: Clinical trial number NCT02895633. Key Points: • The most pertinent CT and MRI criteria allowing bone tumor characterization were defined and presented. • Lodwick-Madewell grade III, aggressive periosteal reaction, and suspected metastatic disease should be considered major malignant indicators associated with a frequency of malignancy over 75%. • The proposed evidence-based multimodality reporting system stratifies solitary bone tumors in classes with increasing frequencies of malignancy. [ABSTRACT FROM AUTHOR]

Objectives: To test the hypothesis that an accelerated, T1-weighted 3D CAIPIRINHA SPACE sequence with isotropic voxel size offers a similar performance to conventional T1-weighted 2D TSE (turbo spin echo) for the evaluation of bone tumor extent and characteristics.Methods: Thirty-four patients who underwent 3-T MRI with 3DT1 (CAIPIRINHA SPACE TSE) and 2DT1 (TSE) were included. Sequence acquisition time was reported. Two radiologists independently evaluated each technique for tumor location, size/length, tumor-to-joint distance, signal intensity, margin/extraosseous extension, and signal-to-noise (SNR) and contrast-to-noise (CNR) ratios.Results: Tumors were located in long (20/36, 55.5%) and pelvic (16/36, 44.4%) bones. 3DT1 sequence required an average acquisition time of 235 s (± 42 s, range 156-372), while two plane 2DT1 sequences combined (coronal and axial) had an average acquisition time of 381 s (± 73 s, range 312-523). There was no difference in the measurements of tumor length and tumor-to-joint distance (p = 0.95) between 3DT1 and 2DT1 images. Tumors were hypointense (17/36, 47.2% vs 17/36, 47.2%), isointense (12/36, 33.3% vs 12/36, 33.3%), or hyperintense (7/36, 19.4% vs 7/36, 19.4%) on 3DT1 vs 2DT1, respectively. Assessment of tumor margins and extraosseous extension was similar, and there was no difference in tumor SNR or CNR (p > 0.05).Conclusions: An accelerated 3D CAIPIRINHA SPACE T1 sequence provides comparable assessments of intramedullary bone tumor extent and similar tumor characteristics to conventional 2DT1 MRI. For the assessment of bone tumors, the isotropic volume acquisition and multiplanar reformation capability of the 3DT1 datasets can obviate the need for 2DT1 acquisitions in multiple planes.Key Points: • 3DT1 offers an equivalent performance to 2DT1 for the assessment of bone tumor characteristics, with faster and higher resolution capability, obviating the need for acquiring 2DT1 in multiple planes. • There was no difference in the measurements of tumor length and tumor-to-joint distance obtained on 3DT1 and 2DT1 images. • There was no difference in signal-to-noise ratio (SNR) or contrast-to-noise ratio (CNR) measures between 3DT1 and 2DT1. [ABSTRACT FROM AUTHOR]

Objective: Rare disease Background: Osteoma is a benign bone tumor that typically arises in facial bones and less frequently in the long bones. It rarely occurs in the appendiceal skeleton. Pathologic findings are similar to those for parosteal osteosarcoma, periostitis ossificans, and osteoid osteoma. Diagnosing osteoma at an unusual site is always problematic. Here, we present a case of costal osteoma that was found incidentally on screening and produced mild symptoms in the patient. Case Report: A 53-year-old man was examined because of a rib mass in the eighth rib on his left side, which had been present for 2 years. A computed tomography scan revealed that the intensely dense mass arose from the external surface of the eighth rib. Microscopic examination showed that the lesion consisted of mature lamellar bone with several Haversian systems, typical of an osteoma. No atypical spindle cells or necrosis were identified. The diagnosis was osteoma. Conclusions: Because the anatomy of the ribs poses a challenge when performing needle biopsy, diagnosing bony lesions solely based on that technique is difficult. The diagnosis of costal osteoma should be made carefully, based on clinical, radiological, and pathological findings. To the best of our knowledge, ours is the first case report about a costal osteoma. It is useful for chest surgeons, pathologists, and radiologists as an example of a rare presentation of this tumor. [ABSTRACT FROM AUTHOR]

Objective To investigate the effect of hsa _ circ _ 0006948 ( circ _ 0006948 ) on the proliferation, migration and invasion of ostcosm-coma cells m1d the tmderlying mechanism. Methods A total of 120 ostcosarcoma tissues and 40 adjacent normal tissue samples were collected from patients admitted to the First People's Hospital of Shangqiu City from 2009 to 2015. Microarray analysis was performed to detect the differential expressions of cirdlNA in Smis-2 cell. The mRNA expressions of circ_0006948, microRNA (miR)-490-3p m1d autophal related protein 7 (ATG7) in osteosarcoma cells, NHOst cells, ostcos tissues and mljacent tissues were detected by real-time q1umtitative reverse transcription polymerase chain reaction ( RT-qPCR) . Cell done formation assay was used to detect cell proliferation ability, Transwell assay was used to detect cell invasion ability, ;md cell scratch assay was used to detect cell migration ability. The interactions between circ_0006948 and miR-490-3p, miR-490-3p and ATG7 were detected by dual luciforase repmier gene assay. The correlation between miR-490-3p and ATG7 was analyzed by TargetScan database, mul the expression levels of Bd-2 and Bax proteins in cells were detected by western blot. Results The mRNA expression levels of circ _ 0006948, miR-490-3p and ATG7 in SAOS-2 cells were significantly different from NH Ost cells ( P < 0. 0 l ) . TI1e mRNA expression levels of circ _ 0006948, miR-490-3p and ATG7 in osteosarcoma tissues were significently different from adjacent tissues ( P

Osteoid osteoma is a painful, benign and common bone tumor that is prevalent in young adults. The typical clinical presentation consists of pain that becomes worse at night and is relieved by nonsteroidal anti-inflammatory drugs. The most common imaging finding is a lytic lesion, known as a nidus, with variable intralesional mineralization, accompanied by bone sclerosis, cortical thickening and surrounding bone marrow edema, as well as marked enhancement with intravenous contrast injection. When the lesion is located in typical locations (intracortical bone and the diaphyses of long bones), both characteristic clinical and radiological features are diagnostic. However, osteoid osteoma is a multifaceted pathology that can have unusual presentations, such as intraarticular osteoid osteoma, epiphyseal location, lesions at the extremities and multicentric nidi, and frequently present atypical clinical and radiological manifestations. In addition, many conditions may mimic osteoid osteoma and vice versa, leading to misdiagnosis. Therefore, it is essential to understand these musculoskeletal diseases and their imaging findings to increase diagnostic accuracy, enable early treatment and prevent poor prognosis. [ABSTRACT FROM AUTHOR]

Objective: To evaluate the role of pre-biopsy MRI for management planning in patients with atypical cartilaginous tumours (ACT) diagnosed on image-guided core needle biopsy (IGCNB). Materials and methods: Retrospective review of patients diagnosed with ACT of the appendicular skeleton based on IGCNB who subsequently underwent surgical curettage or resection. Data collected included age, sex, skeletal location and surgical histology classified as ACT, high-grade chondrosarcoma (HG-CS) and dedifferentiated chondrosarcoma (DD-CS). Pre-biopsy MRI studies were reviewed independently by 2 radiologists blinded to surgical histology results and graded as ACT, HG-CS and DD-CS based on MRI features. Results: The study included 24 males and 28 females (mean age 42.1 years; range 9–76 years). One patient had 2 lesions treated, making a total of 53 lesions. Tumours were located in the femur in 21 cases, humerus in 17, tibia in 9, radius in 4 and ulna and fibula in 1 each. Surgical histology was ACT in 41 cases, HG-CS in 10 and DD-CS in 2, indicating mismatch between IGCNB and surgical histology in 12/53 cases (22.6%). Predicted MRI grade for the 2 readers was ACT in 39 cases each, HG-CS in 13 and 14 cases and DD-CS in 1 and 0 cases. Sensitivity, specificity and accuracy of MRI for predicting HG-CS/DD-CS were 91%, 93% and 92%, respectively. Inter-observer correlation was very good (kappa = 0.94). Discussion: Review of MRI findings in patients with ACT diagnosed on IGCNB is vital for identifying patients with a HG-CS/DD-CS and is recommended when planning surgical management or considering repeat IGCNB. [ABSTRACT FROM AUTHOR]

Myoepithelial carcinoma occurs mainly in salivary glands but rarely can also occur in soft tissues or bone. In this paper, we evaluated the role of surgical margins, radiotherapy, and chemotherapy in myoepithelial carcinoma of soft tissue and bone (MC-SB) treated at our Institute. Medical records of 33 patients presenting with MC-SB between 1998 and 2015 at our institution were retrospectively analysed, and diagnosis and treatment were studied. The median follow-up was 58.5 months. Twenty patients had tumours originating in soft tissues and 13 in bone. Eight patients (24.2%) had metastases at diagnosis, the remaining 25 had localised disease. Thirty-two underwent resection of the primary lesion. In 29 surgical margins were evaluated: wide in 28 with 10/28 who recurred (35.7%) and marginal resection in 1 who also recurred. Six patients received adjuvant radiotherapy. Metastases developed in 15/25 patients (60%) with localised disease at onset. Chemotherapy was administered in patients with metastatic advanced disease. Cisplatin+doxorubicin was administered in six patients as first-line chemotherapy with an objective response in 5/6 patients with a median 4-month duration. Five-year overall survival rate was 62.6% in patients with localised tumours and 12.5% in those metastatic at diagnosis. MC-SB showed a high incidence of local recurrences and metastases. Despite different chemotherapy regimens, the outcome remains poor in patients with metastatic disease. Due to the absence of a standard protocol, we encourage treatment by multidisciplinary teams in referral centres with renowned expertise. • Being rare, reports on soft tissue and bone myoepithelial carcinoma are scarce. • Despite wide margins, local recurrences and metastases frequently occur. • Neoadjuvant or adjuvant radiotherapy should be considered in prospective studies. • Platinum-based agents, doxorubicin, paclitaxel are used in advanced disease. • Multidisciplinary treatment should be encouraged in selected referral centres. [ABSTRACT FROM AUTHOR]

Background: Giant cell tumor of bone (GCTB) is a rare osteoclastogenic stromal tumor. GCTB can rarely undergo malignant transformation. This post hoc analysis evaluated and classified malignancies in patients with GCTB who received denosumab.Methods: This analysis was conducted on patients with pathologically confirmed GCTB and measurable active disease treated with denosumab 120 mg subcutaneously once every 4 weeks, with loading doses on study days 8 and 15, as part of a phase 2, open-label, multicenter study. We identified potential cases of malignancy related to GCTB through an independent multidisciplinary review or medical history, associated imaging or histopathologic reports, and disease course. The findings were summarized and no statistical analysis was performed.Results: Twenty of five hundred twenty-six patients (3.8%) who received at least one dose of denosumab were misdiagnosed with GCTB that was later discovered to be malignancies: five primary malignant GCTB, five secondary malignant GCTB, four sarcomatous transformations, and six patients with other malignancies (giant cell-rich osteosarcoma, undifferentiated pleomorphic sarcoma, spindle cell sarcoma, osteogenic sarcoma, phosphaturic mesenchymal tumor of mixed connective tissue type, and fibrosarcoma/malignant fibrous histiocytoma). Many malignancies were present before denosumab was initiated (8 definitive cases, 7 likely cases), excluding potential involvement of denosumab in these cases. Signs associated with potential misdiagnoses of GCTB included poor mineralization with denosumab treatment, rapid relapse in pain, or a failure of the typical dramatic improvement in pain normally observed with denosumab.Conclusions: Although rare, GCTB can undergo malignant transformation, and rates in this study were consistent with previous reports. Signs of poor mineralization or lack of response to denosumab treatment may warrant close monitoring.Trial Registration: clinicaltrials.gov , ( NCT00680992 ). Registered May 20, 2008. [ABSTRACT FROM AUTHOR]

Background: Bone neoplasms present poor prognosis due to recurrence and metastasis. Although the role microRNAs (miRNAs) in inhibiting growth and metastasis of bone neoplasms has been investigated, the underlying potential molecular mechanisms mediated by miRNA-128 (miR-218) for the invasiveness of bone neoplasms cells are still not completely understood. The purpose of this study was to identify the regulatory mechanisms of miR-218 in bone neoplasms cells. Methods: Western blotting, quantitative reverse transcription-polymerase chain reaction (qRT-PCR), Counting Kit-8 assay, terminal deoxynucleotidyl transferase-mediated dUTP nick end labeling (TUNEL) staining, luciferase activity assay immunofluorescence, and immunohistochemistry were used to analyze the regulatory effects of miR-218 on bone neoplasms cells. Results: Here, the results showed that transfection of miR-128 suppressed bone neoplasms cells proliferation, migration, and invasion. Genetic knockdown of miR-128 in bone neoplasms cells suppressed the activation of the Wnt/β-catenin and epithelial-mesenchymal transition (EMT) signaling pathways. Activation of Wnt or EMT blocked miR-128-inhibited cells proliferation and migration in bone neoplasms cells. Exogenously introduced miR-128 markedly inhibited tumor regeneration in bone neoplasms xenograft models. Conclusions: These results define a tumor-regulated function for miR-128 in bone neoplasms by down-regulation of the Wnt/β-catenin and EMT signal pathways, which provided a potential target for bone neoplasms gene therapy. [ABSTRACT FROM AUTHOR]

We present the case of a 50-year-old patient who reported chronic pain under the nail of the little finger for five years, with no trauma history and which restricted his work activity. The glomus tumor is a benign neoplasm characterized by an acute and circumscribed pain in the subungual region that increases with pressure and cold, which are objective symptoms to suspect this condition. The highest incidence of glomus tumors occurs in adults; however, as it is infrequent, delayed diagnosis is common. The diagnosis must include imaging scans, especially ultrasound, which are an excellent and very accessible alternative in different populations. In our case, the tumor was clearly observed on the ultrasound images, which was crucial to choose the surgical excision as treatment. The anatomopathological evaluation revealed a glomus tumor and the subsequent relief of symptoms were confirmed after the surgery. [ABSTRACT FROM AUTHOR]