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The umbilical cord blood (UCB) donated in public UCB banks is a source of hematopoietic stem cells (HSC) alternative to bone marrow for allogeneic HSC transplantation (HSCT). However, the high rejection rate of the donated units due to the strict acceptance criteria and the wide application of the haploidentical HSCT have resulted in significant limitation of the use of UCB and difficulties in the economic sustainability of the public UCB banks. There is an ongoing effort within the UCB community to optimize the use of UCB in the field of HSCT and a parallel interest in exploring the use of UCB for applications beyond HSCT i.e., in the fields of cell therapy, regenerative medicine and specialized transfusion medicine. In this report, we describe the mode of operation of the three public UCB banks in Greece as an example of an orchestrated effort to develop a viable UCB banking system by (a) prioritizing the enrichment of the national inventory by high-quality UCB units from populations with rare human leukocyte antigens (HLA), and (b) deploying novel sustainable applications of UCB beyond HSCT, through national and international collaborations. The Greek paradigm of the public UCB network may become an example for countries, particularly with high HLA heterogeneity, with public UCB banks facing sustainability difficulties and adds value to the international efforts aiming to sustainably expand the public UCB banking system. [ABSTRACT FROM AUTHOR]

Ultrasound-guided hydrodistention has been established as an effective minimally invasive treatment option for glenohumeral joint adhesive capsulitis (AC). Nonetheless, the long-term outcomes of the procedure have not yet been established. A total of 202 patients with AC were prospectively recruited and followed up for a total of 2 years. Pain and functionality were assessed with the use of the visual analogue scale (VAS) and the disabilities of the arm, shoulder, and hand (DASH) score, respectively, at the beginning and the end of the follow-up period. The relapse of AC over the 2-year period and the effect of diabetes were also evaluated in the treatment cohort. The Mann–Whitney U test was used to compare mean scores at the two time points, and Cox survival analysis and χ2 test were used to assess the effect of diabetes on AC relapse. VAS and DASH scores were significantly lower at 2 years compared with the beginning of the follow-up period (p < 0.001). Diabetes was diagnosed in 38/202 patients (18.8%) and was found to be significantly associated with recurrence of the disease (p < 0.001). In conclusion, in this observational study, we have demonstrated that ultrasound-guided hydrodistention is linked to excellent long-term outcomes for the treatment of AC, which are significantly worse in patients with diabetes. [ABSTRACT FROM AUTHOR]

Detecting active inflammatory sacroiliitis at an early stage is vital for prescribing medications that can modulate disease progression and significantly delay or prevent debilitating forms of axial spondyloarthropathy. Conventional radiography and computed tomography offer limited sensitivity in detecting acute inflammatory findings as these methods primarily identify chronic structural lesions. Conversely, Magnetic Resonance Imaging (MRI) is the preferred technique for detecting bone marrow edema, although it is a complex process requiring extensive expertise. Additionally, ascertaining the origin of lesions can be challenging, even for experienced medical professionals. Machine learning (ML) has showcased its proficiency in various fields by uncovering patterns that are not easily perceived from multi-dimensional datasets derived from medical imaging. The aim of this study is to develop a radiomic signature to aid clinicians in diagnosing active sacroiliitis. A total of 354 sacroiliac joints were segmented from axial fluid-sensitive MRI images, and their radiomic features were extracted. After selecting the most informative features, a number of ML algorithms were utilized to identify the optimal method for detecting active sacroiliitis, leading to the selection of an Extreme Gradient Boosting (XGBoost) model that accomplished an Area Under the Receiver-Operating Characteristic curve (AUC-ROC) of 0.71, thus further showcasing the potential of radiomics in the field. [ABSTRACT FROM AUTHOR]

Simple Summary: This study focuses on the integration of 99mTc Sestamibi SPECT/CT and radiomics analysis to characterize benign renal oncocytic neoplasia. Our research includes renal tumors with histopathological analysis (conducted by independent pathologists) serving as the ground truth. Radiomics data were extracted from contrast-enhanced CT images to build machine-learning models. The combined SPECT/radiomics model achieved higher accuracy (95%) than the radiomics-only model (75%) and visual evaluation of 99mTc Sestamibi SPECT/CT alone (90.8%). This approach promises the improvement of diagnostic accuracy in renal tumor characterization and the reduction in unnecessary surgery for benign tumors. The increasing evidence of oncocytic renal tumors positive in 99mTc Sestamibi Single Photon Emission Tomography/Computed Tomography (SPECT/CT) examination calls for the development of diagnostic tools to differentiate these tumors from more aggressive forms. This study combined radiomics analysis with the uptake of 99mTc Sestamibi on SPECT/CT to differentiate benign renal oncocytic neoplasms from renal cell carcinoma. A total of 57 renal tumors were prospectively collected. Histopathological analysis and radiomics data extraction were performed. XGBoost classifiers were trained using the radiomics features alone and combined with the results from the visual evaluation of 99mTc Sestamibi SPECT/CT examination. The combined SPECT/radiomics model achieved higher accuracy (95%) with an area under the curve (AUC) of 98.3% (95% CI 93.7–100%) than the radiomics-only model (71.67%) with an AUC of 75% (95% CI 49.7–100%) and visual evaluation of 99mTc Sestamibi SPECT/CT alone (90.8%) with an AUC of 90.8% (95%CI 82.5–99.1%). The positive predictive values of SPECT/radiomics, radiomics-only, and 99mTc Sestamibi SPECT/CT-only models were 100%, 85.71%, and 85%, respectively, whereas the negative predictive values were 85.71%, 55.56%, and 94.6%, respectively. Feature importance analysis revealed that 99mTc Sestamibi uptake was the most influential attribute in the combined model. This study highlights the potential of combining radiomics analysis with 99mTc Sestamibi SPECT/CT to improve the preoperative characterization of benign renal oncocytic neoplasms. The proposed SPECT/radiomics classifier outperformed the visual evaluation of 99mTc Sestamibii SPECT/CT and the radiomics-only model, demonstrating that the integration of 99mTc Sestamibi SPECT/CT and radiomics data provides improved diagnostic performance, with minimal false positive and false negative results. [ABSTRACT FROM AUTHOR]

Multiple myeloma (MM) is one of the most common hematological malignancies affecting the bone marrow. Radiomics analysis has been employed in the literature in an attempt to evaluate the bone marrow of MM patients. This manuscript aimed to systematically review radiomics research on MM while employing a radiomics quality score (RQS) to accurately assess research quality in the field. A systematic search was performed on Web of Science, PubMed, and Scopus. The selected manuscripts were evaluated (data extraction and RQS scoring) by three independent readers (R1, R2, and R3) with experience in radiomics analysis. A total of 23 studies with 2682 patients were included, and the median RQS was 10 for R1 (IQR 5.5–12) and R3 (IQR 8.3–12) and 11 (IQR 7.5–12.5) for R2. RQS was not significantly correlated with any of the assessed bibliometric data (impact factor, quartile, year of publication, and imaging modality) (p > 0.05). Our results demonstrated the low quality of published radiomics research in MM, similarly to other fields of radiomics research, highlighting the need to tighten publication standards. [ABSTRACT FROM AUTHOR]

Differential diagnosis between avascular necrosis (AVN) and transient osteoporosis of the hip (TOH) can be complicated even for experienced MSK radiologists. Our study attempted to use MR images in order to develop a deep learning methodology with the use of transfer learning and a convolutional neural network (CNN) ensemble, for the accurate differentiation between the two diseases. An augmented dataset of 210 hips with TOH and 210 hips with AVN was used to finetune three ImageNet-trained CNNs (VGG-16, InceptionResNetV2, and InceptionV3). An ensemble decision was reached in a hard-voting manner by selecting the outcome voted by at least two of the CNNs. Inception-ResNet-V2 achieved the highest AUC (97.62%) similar to the model ensemble, followed by InceptionV3 (AUC of 96.82%) and VGG-16 (AUC 96.03%). Precision for the diagnosis of AVN and recall for the detection of TOH were higher in the model ensemble compared to Inception-ResNet-V2. Ensemble performance was significantly higher than that of an MSK radiologist and a fellow (P < 0.001). Deep learning was highly successful in distinguishing TOH from AVN, with a potential to aid treatment decisions and lead to the avoidance of unnecessary surgery. [ABSTRACT FROM AUTHOR]

The rapid evolution of regenerative medicine and its associated scientific fields, such as tissue engineering, has provided great promise for multiple applications where replacement and regeneration of damaged or lost tissue is required. In order to evaluate and optimise the tissue engineering techniques, visualisation of the material of interest is crucial. This includes monitoring of the cellular behaviour, extracellular matrix composition, scaffold structure, and other crucial elements of biomaterials. Non-invasive visualisation of artificial tissues is important at all stages of development and clinical translation. A variety of preclinical and clinical imaging methods--including confocal multiphoton microscopy, optical coherence tomography, magnetic resonance imaging (MRI), and computed tomography (CT)--have been used for the evaluation of artificial tissues. This review attempts to present the imaging methods available to assess the composition and quality of 3D microenvironments, as well as their integration with human tissues once implanted in the human body. The review provides tissue-specific application examples to demonstrate the applicability of such methods on cardiovascular, musculoskeletal, and neural tissue engineering. [ABSTRACT FROM AUTHOR]

The purpose of this study was to compare the measurement of several anatomical features of the medial patellofemoral ligament (MPFL) between magnetic resonance imaging (MRI) and by direct fashion during dissection. We hypothesized that the measurements between these two techniques would agree. MRI of 30 fresh-frozen cadaveric knees was followed by dissection. MPFL patella and femoral attachment were evaluated; their shape, length, and width were measured; and measurements were compared. MRI was deemed unreliable for the determination of several of the aforementioned anatomical features. Important findings include: (a) observations on MPFL attachment at medial patella side and attachment to quadriceps were identical between dissection and MRI; (b) average width at patella insertion was significantly different between the two methods (p = 0.002); and (c) an attachment to the quadriceps tendon was present in 20/30 specimens and d. detailed measurements of a thin, non-linear, and three-dimensional structure, such as the MPFL, cannot be performed on MRI, due to technical difficulties. This anatomical radiological study highlights the shape, anatomical measurements (length and width), and attachment of the MPFL using a relatively large cadaveric sample and suggests that MRI is not reliable for detailed imaging of its three-dimensional anatomy. [ABSTRACT FROM AUTHOR]

This research focuses on the anatomical insertion of the synovial capsule around the knee. The attachments of the capsule were measured in 50 knee MR imaging studies with large intraarticular effusion. Corresponding measurements were performed in 20 fresh frozen cadaveric specimens, for validation. Femoral and tibial capsular reflections were defined as the distances between the attachment sites of the capsule and the femoral or tibial joint line and they were recorded in three coronal planes (anterior/middle/posterior). On MR imaging, the lateral/medial femoral capsular reflection mean values were 6.5/4.57 cm, 2.74/1.74 cm and 1.52/1.99 cm in the anterior, middle and posterior plane, respectively. MR imaging-based measurements did not differ significantly compared to corresponding cadaveric measurements. The mean values of the lateral/medial tibial capsular reflection on MR imaging were 0.09/0.11 cm, 0.34/0.26 cm and 0.62/0.34 cm in the anterior, middle and posterior plane, respectively. On cadaveric dissection, the maximum mean value was 1.45 cm, measured on the lateral side of the anterior plane. Apart from the lateral aspect of the posterior plane, MR imaging measurements were significantly lower, compared to the corresponding cadaveric measurements. The greatest femoral and tibial capsular reflections were found on the anterior and lateral side of the anterior plane. MR imaging appears to underestimate the distal extent of the knee capsule. Anatomical details of the knee capsule should be considered for safe insertion of external fixator pins. [ABSTRACT FROM AUTHOR]

Differentiation between transient osteoporosis (TOH) and avascular necrosis (AVN) of the hip is a longstanding challenge in musculoskeletal radiology. The purpose of this study was to utilize MRI-based radiomics and machine learning (ML) for accurate differentiation between the two entities. A total of 109 hips with TOH and 104 hips with AVN were retrospectively included. Femoral heads and necks with segmented radiomics features were extracted. Three ML classifiers (XGboost, CatBoost and SVM) using 38 relevant radiomics features were trained on 70% and validated on 30% of the dataset. ML performance was compared to two musculoskeletal radiologists, a general radiologist and two radiology residents. XGboost achieved the best performance with an area under the curve (AUC) of 93.7% (95% CI from 87.7 to 99.8%) among ML models. MSK radiologists achieved an AUC of 90.6% (95% CI from 86.7% to 94.5%) and 88.3% (95% CI from 84% to 92.7%), respectively, similar to residents. The general radiologist achieved an AUC of 84.5% (95% CI from 80% to 89%), significantly lower than of XGboost (p = 0.017). In conclusion, radiomics-based ML achieved a performance similar to MSK radiologists and significantly higher compared to general radiologists in differentiating between TOH and AVN. [ABSTRACT FROM AUTHOR]

Ultrasound-guided hydrodistention has been established as an effective minimally invasive treatment option for glenohumeral joint adhesive capsulitis (AC). Nonetheless, the long-term outcomes of the procedure have not yet been established. A total of 202 patients with AC were prospectively recruited and followed up for a total of 2 years. Pain and functionality were assessed with the use of the visual analogue scale (VAS) and the disabilities of the arm, shoulder, and hand (DASH) score, respectively, at the beginning and the end of the follow-up period. The relapse of AC over the 2-year period and the effect of diabetes were also evaluated in the treatment cohort. The Mann-Whitney U test was used to compare mean scores at the two time points, and Cox survival analysis and χ 2 test were used to assess the effect of diabetes on AC relapse. VAS and DASH scores were significantly lower at 2 years compared with the beginning of the follow-up period ( p < 0.001). Diabetes was diagnosed in 38/202 patients (18.8%) and was found to be significantly associated with recurrence of the disease ( p < 0.001). In conclusion, in this observational study, we have demonstrated that ultrasound-guided hydrodistention is linked to excellent long-term outcomes for the treatment of AC, which are significantly worse in patients with diabetes.