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Background: Urethral obstruction is a common and life-threatening condition in male small ruminants. Case presentation: This case report describes a 3-year old 103 kg Zwartbles breeding ram, presented with the complaint of straining, suspected to have an urethral obstruction. The work-up included clinical examination, laboratory analyses, ultrasound imaging, (contrast) radiography and urine examination. At presentation, blood analysis revealed a respiratory alkalosis, hyperkalaemia and mild azotaemia. On transabdominal ultrasound an enlarged bladder (diameter 11 cm) and free fluid surrounding the right kidney were observed. Treatment of the animal included tube cystostomy, intravenous perfusion, antimicrobial treatment, ammonium chloride and NSAIDs. No indications for urolithiasis were found on ultrasound, radiography, or urine examination. As no improvement was seen despite 16 days of therapy, a contrast radiograph of the urinary tract, as well as reproductive exam were conducted. Positive anterograde urethrogram showed a contrast filled cavitary lesion at the caudal aspect of the pelvic urethra. The reproductive ultrasonography revealed the same large urethral distention or abscess compressing the pelvic urethra, as well as severe testicular degeneration in both testis. The results of the contrast radiograph and the reproductive exam lead to the decision to euthanize the animal, as the animal would not be capable of breeding. Computed tomography was performed post-mortem, which showed close relation between the cavitary lesion and the left bulbourethral gland. Pathology revealed a lymphoplasmacytic to suppurative infection at the level of the urogenital tract, chronic interstitial nephritis and a perirenal to cortical abscess of the right kidney as well as a periurethral abscess. As for the reproductive system, multifocal interstitial inflammatory infiltrates were seen on the entire system. Marked fibrosis and atrophy was seen at the level of the testes and both epididymides. Conclusions: A periurethral abscess should be included in the differential diagnosis for an urethral obstruction in small ruminants. The extensive medical imaging, together with the ante-mortem and post-mortem findings, makes this a good reference case for diagnosticians confronted with urethral problems in a ram. [ABSTRACT FROM AUTHOR]

Objectives: The integration of machine learning and radiomics in medical imaging has significantly advanced diagnostic and prognostic capabilities in healthcare. This study focuses on developing and validating an artificial intelligence (AI) model using U-Net architectures for the accurate detection and segmentation of spinal metastases from computed tomography (CT) images, addressing both osteolytic and osteoblastic lesions. Methods: Our methodology employs multiple variations of the U-Net architecture and utilizes two distinct datasets: one consisting of 115 polytrauma patients for vertebra segmentation and another comprising 38 patients with documented spinal metastases for lesion detection. Results: The model demonstrated strong performance in vertebra segmentation, achieving Dice Similarity Coefficient (DSC) values between 0.87 and 0.96. For metastasis segmentation, the model achieved a DSC of 0.71 and an F-beta score of 0.68 for lytic lesions but struggled with sclerotic lesions, obtaining a DSC of 0.61 and an F-beta score of 0.57, reflecting challenges in detecting dense, subtle bone alterations. Despite these limitations, the model successfully identified isolated metastatic lesions beyond the spine, such as in the sternum, indicating potential for broader skeletal metastasis detection. Conclusions: The study concludes that AI-based models can augment radiologists' capabilities by providing reliable second-opinion tools, though further refinements and diverse training data are needed for optimal performance, particularly for sclerotic lesion segmentation. The annotated CT dataset produced and shared in this research serves as a valuable resource for future advancements. [ABSTRACT FROM AUTHOR]

Objective: To assess the diagnostic performance of post-contrast CT for predicting moderate hepatic steatosis in an older adult cohort undergoing a uniform CT protocol, utilizing hepatic and splenic attenuation values. Materials and methods: A total of 1676 adults (mean age, 68.4 ± 10.2 years; 1045M/631F) underwent a CT urothelial protocol that included unenhanced, portal venous, and 10-min delayed phases through the liver and spleen. Automated hepatosplenic segmentation for attenuation values (in HU) was performed using a validated deep-learning tool. Unenhanced liver attenuation < 40.0 HU, corresponding to > 15% MRI-based proton density fat, served as the reference standard for moderate steatosis. Results: The prevalence of moderate or severe steatosis was 12.9% (216/1676). The diagnostic performance of portal venous liver HU in predicting moderate hepatic steatosis (AUROC = 0.943) was significantly better than the liver–spleen HU difference (AUROC = 0.814) (p < 0.001). Portal venous phase liver thresholds of 80 and 90 HU had a sensitivity/specificity for moderate steatosis of 85.6%/89.6%, and 94.9%/74.7%, respectively, whereas a liver–spleen difference of −40 HU and −10 HU had a sensitivity/specificity of 43.5%/90.0% and 92.1%/52.5%, respectively. Furthermore, livers with moderate–severe steatosis demonstrated significantly less post-contrast enhancement (mean, 35.7 HU vs 47.3 HU; p < 0.001). Conclusion: Moderate steatosis can be reliably diagnosed on standard portal venous phase CT using liver attenuation values alone. Consideration of splenic attenuation appears to add little value. Moderate steatosis not only has intrinsically lower pre-contrast liver attenuation values (< 40 HU), but also enhances less, typically resulting in post-contrast liver attenuation values of 80 HU or less. Clinical relevance statement: Moderate steatosis can be reliably diagnosed on post-contrast CT using liver attenuation values alone. Livers with at least moderate steatosis enhance less than those with mild or no steatosis, which combines with the lower intrinsic attenuation to improve detection. Key Points: The liver–spleen attenuation difference is frequently utilized in routine practice but appears to have performance limitations. The liver–spleen attenuation difference is less effective than liver attenuation for moderate steatosis. Moderate and severe steatosis can be identified on standard portal venous phase CT using liver attenuation alone. [ABSTRACT FROM AUTHOR]

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Purpose: The study aims to show how the "Puncture Cube" (PC) (Medical Templates, Egg, Switzerland) compares to the freehand method (FHM) for CT-guided punctures. Methods: The PC is a patient-mounted disassemblable cube consisting of an upper and lower template with multiple holes each to predefine puncture trajectory. A total of 80 punctures (FHM in-plane, FHM off-plane, PC in-plane, PC off-plane) was performed by 4 radiologists on a target 9.1 cm below surface level of a neoprene covered elliptical cylinder gelatin phantom. The PC was never disassembled. Evaluated parameters were procedure time, number of CT-scans, euclidean distance (ED) and normal distance (ND). Respective parameters of FHM and PC were compared using the Wilcoxon signed-rank test and Levene test with significance levels of 5%. Results: PC achieved smaller ED and ND values after initial needle insertion without corrections for both in-plane and off-plane punctures (P > 0.05). Variance of initial NDs was off-plane significantly larger for FHM. Final ED after needle path corrections was smaller for FHM both in- and off-plane (P < 0.05). Final off-plane ND was significantly lower for FHM with no significant difference in final in-plane ND. FHM off-plane punctures were significantly faster. There was no significant difference in CT-scans between both methods. Conclusion: Utilizing the PC may improve initial needle positioning and safety especially off-plane. However, better final needle positioning after correction with the greater freedom of movement method may suggest need for disassembly of the cube [ABSTRACT FROM AUTHOR]

By utilizing computed tomography (CT) technology, we can gain a comprehensive understanding of the specific details within the material. When combined with computational mechanics, this approach allows us to predict the structural response through numerical simulation, thereby avoiding the high experimental costs. In this study, the tensile cracking behavior of carbon–silicon carbide (C/SiC) composites is numerically simulated using the bond-based peridynamics model (BB-PD), which is based on geometric models derived from segmented images of three-dimensional (3D) CT data. To obtain results efficiently and accurately, we adopted a deep learning-based image recognition model to identify the kinds of material and then the pixel type that corresponds to the material point, which can be modeled by BB-PD for failure simulation. The numerical simulations of the composites indicate that the proposed image-based peridynamics (IB-PD) model can accurately reconstruct the actual composite microstructure. It can effectively simulate various fracture phenomena such as interfacial debonding, crack propagation affected by defects, and damage to the matrix. [ABSTRACT FROM AUTHOR]

Hepatocellular carcinoma (HCC) is one of the common and fatal malignant tumors worldwide, and the burden of HCC is particularly severe in China. Physiologically, the blood supply to healthy liver is mainly from the portal vein, supplemented by the hepatic artery. While in the development of HCC, the main source of blood supply to HCC is changed from the portal vein to the hepatic artery. The characteristics of HCC vascularization are important for imaging, surgery, interventional therapy, targeted therapy, etc. Even in the future, with the development of radiation therapy technology, such as proton and heavy ion therapy and artificial intelligence technology, the dynamic changes in HCC blood perfusion can be used as a new biomarker of tumor activity to provide accurate information on the intensity modulation of radiotherapy, so that accurate measurements of HCC blood perfusion is of great significance in guiding the diagnosis and treatment of HCC. The technologies for measurement of HCC blood perfusion have developed from invasive techniques, such as inert gas scavenging, electromagnetic flowmeter, and radionuclide-labeled erythrocyte elution in the middle of the last century to the present non-invasive techniques of CT. With the development of CT imaging technology in the last 30 years, the CT-based imaging technology can assess the status of organ and tissue perfusion relatively easily and accurately. In this paper, the various CT measurement techniques of blood perfusion in HCC were categorized into three types: semi-quantitative technique, relative quantitative technique, and absolute quantitative technique. Their basic principle, scanning methods, and clinical applications were discussed to provide a reference for the diagnosis and treatment of HCC. [ABSTRACT FROM AUTHOR]

Background: Lung cancer is the most common type of cancer. Detection of lung cancer at an early stage can reduce mortality rates. Pulmonary nodules may represent early cancer and can be identified through computed tomography (CT) scans. Malignant risk can be estimated based on attributes like size, shape, location, and density. Purpose: Deep learning algorithms have achieved remarkable advancements in this domain compared to traditional machine learning methods. Nevertheless, many existing anchor‐based deep learning algorithms exhibit sensitivity to predefined anchor‐box configurations, necessitating manual adjustments to obtain optimal outcomes. Conversely, current anchor‐free deep learning‐based nodule detection methods normally adopt fixed‐size nodule models like cubes or spheres. Methods: To address these technical challenges, we propose a multiscale 3D anchor‐free deep learning network (M3N) for pulmonary nodule detection, leveraging adjustable nodule modeling (ANM). Within this framework, ANM empowers the representation of target objects in an anisotropic manner, with a novel point selection strategy (PSS) devised to accelerate the learning process of anisotropic representation. We further incorporate a composite loss function that combines the conventional L2 loss and cosine similarity loss, facilitating M3N to learn nodules' intensity distribution in three dimensions. Results: Experiment results show that the M3N achieves 90.6% competitive performance metrics (CPM) with seven predefined false positives per scan on the LUNA 16 dataset. This performance appears to exceed that of other state‐of‐the‐art deep learning‐based networks reported in their respective publications. Individual test results also demonstrate that M3N excels in providing more accurate, adaptive bounding boxes surrounding the contours of target nodules. Conclusions: The newly developed nodule detection system reduces reliance on prior knowledge, such as the general size of objects in the dataset, thus it should enhance overall robustness and versatility. Distinct from traditional nodule modeling techniques, the ANM approach aligns more closely with the morphological characteristics of nodules. Time consumption and detection results demonstrate promising efficiency and accuracy which should be validated in clinical settings. [ABSTRACT FROM AUTHOR]

Background: Pericardial cysts, though rare and benign, can present with various clinical symptoms depending on their size and location in the body. The detection of these cysts typically relies on imaging studies for a conclusive diagnosis, with surgical removal being the definitive treatment. Case presentation: This case report details the clinical journey of a 32-year-old Iranian woman with a family history of breast and lung cancer, who experienced left-sided chest pain. Utilizing a combination of clinical history review, mammography, echocardiography, and computed tomography, a precise diagnosis of a 10 cm × 3.5 cm pericardial cyst was achieved. The patient underwent median sternotomy for complete cyst excision. Conclusions: While pericardial cysts are often asymptomatic and benign, they can lead to life-threatening complications. Hence, regular follow-up is advised, and in certain instances, minimally invasive interventions or surgery may be necessary. [ABSTRACT FROM AUTHOR]

Purpose: This scoping review aimed to assess the current research on artificial intelligence (AI)--enhanced opportunistic screening approaches for stratifying osteoporosis and osteopenia risk by evaluating vertebral trabecular bone structure in CT scans. Methods: PubMed, Scopus, and Web of Science databases were systematically searched for studies published between 2018 and December 2023. Inclusion criteria encompassed articles focusing on AI techniques for classifying osteoporosis/osteopenia or determining bone mineral density using CT scans of vertebral bodies. Data extraction included study characteristics, methodologies, and key findings. Results: Fourteen studies met the inclusion criteria. Three main approaches were identified: fully automated deep learning solutions, hybrid approaches combining deep learning and conventional machine learning, and non-automated solutions using manual segmentation followed by AI analysis. Studies demonstrated high accuracy in bone mineral density prediction (86-96%) and classification of normal versus osteoporotic subjects (AUC 0.927-0.984). However, significant heterogeneity was observed in methodologies, workflows, and ground truth selection. Conclusions: The review highlights AI's promising potential in enhancing opportunistic screening for osteoporosis using CT scans. While the field is still in its early stages, with most solutions at the proof-of-concept phase, the evidence supports increased efforts to incorporate AI into radiologic workflows. Addressing knowledge gaps, such as standardizing benchmarks and increasing external validation, will be crucial for advancing the clinical application of these AI-enhanced screening methods. Integration of such technologies could lead to improved early detection of osteoporotic conditions at a low economic cost. [ABSTRACT FROM AUTHOR]

Deep learning (DL) requires a large amount of training data to improve performance and prevent overfitting. To overcome these difficulties, we need to increase the size of the training dataset. This can be done by augmentation on a small dataset. The augmentation approaches must enhance the model's performance during the learning period. There are several types of transformations that can be applied to medical images. These transformations can be applied to the entire dataset or to a subset of the data, depending on the desired outcome. In this study, we categorize data augmentation methods into four groups: Absent augmentation, where no modifications are made; basic augmentation, which includes brightness and contrast adjustments; intermediate augmentation, encompassing a wider array of transformations like rotation, flipping, and shifting in addition to brightness and contrast adjustments; and advanced augmentation, where all transformation layers are employed. We plan to conduct a comprehensive analysis to determine which group performs best when applied to brain CT images. This evaluation aims to identify the augmentation group that produces the most favorable results in terms of improving model accuracy, minimizing diagnostic errors, and ensuring the robustness of the model in the context of brain CT image analysis. [ABSTRACT FROM AUTHOR]

Background: The study aimed to observe the internal structure of coconuts from two locations (coastal and non-coastal) using computed tomography (CT). Methods: Seventy-six mature coconuts were collected from Wenchang and Ding'an cities in Hainan Province. These coconuts were scanned four times using CT, with a two-week interval between each scan. CT data were post-processed to reconstruct two-dimensional slices and three-dimensional models. The density and morphological parameters of coconut structures were measured, and the differences in these characteristics between the two groups and the changes over time were analyzed. Results: Time and location had interactive effects on CT values of embryos, solid endosperms and mesocarps, morphological information such as major axis of coconut, thickness of mesocarp, volume of coconut water and height of bud (p < 0.05). Conclusions: Planting location and observation time can affect the density and morphology of some coconut structures. [ABSTRACT FROM AUTHOR]

The cancer invasion of the large intestine, a destructive process that begins within the mucous membrane, causes cancer cells to gradually erode specific layers of the intestinal wall. The normal tissues of the intestine are progressively replaced by a tumour mass, leading to the impairment of the large intestine's proper morphology and function. At the ultrastructural level, the disintegration of the extracellular matrix (ECM) by cancer cells triggers the activation of inflammatory cells (macrophages) and connective tissue cells (myofibroblasts) in this area. This accumulation and the functional interactions between these cells form the tumour microenvironment (TM). The constant modulation of cancer cells and cancer-associated fibroblasts (CAFs) creates a specific milieu akin to non-healing wounds, which induces colon cancer cell proliferation and promotes their survival. This review focuses on the processes occurring at the "front of cancer invasion", with a particular focus on the role of the desmoplastic reaction in neoplasm development. It then correlates the findings from the microscopic observation of the cancer's ultrastructure with the potential of modern radiological imaging, such as computer tomography (CT) and magnetic resonance imaging (MRI), which visualizes the tumour, its boundaries, and the tissue reactions in the large intestine. [ABSTRACT FROM AUTHOR]

Establishing a positive identification of human remains found in a forensic setting is often accomplished through DNA, fingerprints, or odontology. However, when these primary identifiers cannot be applied, practitioners can rely on combining points of concordance derived from other identification modalities such as antemortem trauma, pathology, or unique skeletal morphologies to build up a case for identification. In order to conduct these comparisons, forensic anthropologists must be well trained and experienced in human skeletal variation and antemortem trauma to properly evaluate a particular skeletal trait and understand its value with respect to personal identification. In addition to macroscopic analysis of skeletal features and standard radiographic images, recent forensic anthropological efforts of establishing personal identity from the skeleton have employed high-quality clinical imaging technologies. This article presents three forensic anthropological cases in which positive identification was established on the basis of multiple antemortem to postmortem comparison modalities that included skeletal variation, antemortem fracture morphologies, trabecular patterns, dental traits, and implanted surgical devices. These cases use a variety of imaging techniques, such as cranial radiographic images, dental radiographs, computed tomography, photography, and 3D surface scans of the skeletal remains, to achieve personal identification. Key points The identification of the remains becomes a top priority in forensic investigations. Dental treatment, implanted surgical devices, anatomical variation, and healed skeletal trauma can provide useful features for the antemortem vs. postmortem records comparison. This article discusses three cases in which multiple forms of antemortem and postmortem imaging were used to compare skeletal areas of interest. All cases were carried out by the Mercyhurst University Forensic Anthropology Team. [ABSTRACT FROM AUTHOR]

Abstract Background Urethral obstruction is a common and life-threatening condition in male small ruminants. Case presentation This case report describes a 3-year old 103 kg Zwartbles breeding ram, presented with the complaint of straining, suspected to have an urethral obstruction. The work-up included clinical examination, laboratory analyses, ultrasound imaging, (contrast) radiography and urine examination. At presentation, blood analysis revealed a respiratory alkalosis, hyperkalaemia and mild azotaemia. On transabdominal ultrasound an enlarged bladder (diameter 11 cm) and free fluid surrounding the right kidney were observed. Treatment of the animal included tube cystostomy, intravenous perfusion, antimicrobial treatment, ammonium chloride and NSAIDs. No indications for urolithiasis were found on ultrasound, radiography, or urine examination. As no improvement was seen despite 16 days of therapy, a contrast radiograph of the urinary tract, as well as reproductive exam were conducted. Positive anterograde urethrogram showed a contrast filled cavitary lesion at the caudal aspect of the pelvic urethra. The reproductive ultrasonography revealed the same large urethral distention or abscess compressing the pelvic urethra, as well as severe testicular degeneration in both testis. The results of the contrast radiograph and the reproductive exam lead to the decision to euthanize the animal, as the animal would not be capable of breeding. Computed tomography was performed post-mortem, which showed close relation between the cavitary lesion and the left bulbourethral gland. Pathology revealed a lymphoplasmacytic to suppurative infection at the level of the urogenital tract, chronic interstitial nephritis and a perirenal to cortical abscess of the right kidney as well as a periurethral abscess. As for the reproductive system, multifocal interstitial inflammatory infiltrates were seen on the entire system. Marked fibrosis and atrophy was seen at the level of the testes and both epididymides. Conclusions A periurethral abscess should be included in the differential diagnosis for an urethral obstruction in small ruminants. The extensive medical imaging, together with the ante-mortem and post-mortem findings, makes this a good reference case for diagnosticians confronted with urethral problems in a ram.

Objective: This study aimed to investigate the chest computed tomography (CT) findings of SARS-CoV-2 Omicron variants in elderly patients with underlying diseases. Methods: We retrospectively analyzed data from 140 elderly patients with underlying diseases who were infected with SARS-CoV-2 Omicron variants. The patients were divided into a moderate group and a severe/critical group based on their clinical classifications. Clinical data, laboratory results, and chest CT data (including lesion distribution, morphology, image signs, and lung lobe score) were collected and analyzed for all patients. Results: Hypertension and hyperlipidemia were the most prevalent underlying diseases among elderly patients with the Omicron variant of SARS-CoV-2. Ground-glass density opacity was the main chest CT manifestation, typically presenting as a mixed distribution across multiple lung lobes. Common clinical symptoms include fever, cough, and sputum production. The proportion of patients with fever was significantly higher in the severe/critical group compared to the moderate group. Additionally, the lymphocyte count was higher in the moderate group compared to the severe/critical group, while the procalcitonin level was significantly higher in the severe/critical group. Pleural thickening was also more prevalent in the severe/critical group. The right inferior lobe score was the highest in both groups (2 (1,3) and 3 (2,4) for moderate and severe/critical groups, respectively), with the total score and individual lobe scores being significantly higher in the severe/critical group. Conclusions: Chest CT scans play a crucial role in classifying disease severity and evaluating disease progression in elderly patients with underlying diseases infected with the Omicron variant of the novel coronavirus. These findings can also guide clinical treatment decisions.

Abstract Background Pericardial cysts, though rare and benign, can present with various clinical symptoms depending on their size and location in the body. The detection of these cysts typically relies on imaging studies for a conclusive diagnosis, with surgical removal being the definitive treatment. Case presentation This case report details the clinical journey of a 32-year-old Iranian woman with a family history of breast and lung cancer, who experienced left-sided chest pain. Utilizing a combination of clinical history review, mammography, echocardiography, and computed tomography, a precise diagnosis of a 10 cm × 3.5 cm pericardial cyst was achieved. The patient underwent median sternotomy for complete cyst excision. Conclusions While pericardial cysts are often asymptomatic and benign, they can lead to life-threatening complications. Hence, regular follow-up is advised, and in certain instances, minimally invasive interventions or surgery may be necessary.

Background. The neck, its bone-cartilaginous and muscle apparatus, etc. high activity is well known. Cervical spine degenerative-dystrophic processes are considered to be an urgent problem. The purpose of the study was to determine the clinical and morphometric changes of the cervical spine in humans and animals with neck pain based on a clinical and neurological examination, determination of the vertebral body density, their configuration, and ratio for timely correction and prognosis of this patho­logy. Materials and methods. Pain intensity was studied in humans and animals using the adapted visual-analogue scale. The inde­xes of computer tomography with measurement of vertebral body density, and morphometric indexes with an emphasis on C5-C7 le­vel were also studied. All studies were conducted following existing bioethical standards. Results. The pathology of spine configuration was registered in 84.6 % of the examined patients in the form of angular kyphosis or straightened lordosis, more often in women. It was observed in 34.7 % of cases in dogs and cats. The normal configuration is more common: in cats — 78.6 % and in dogs of small breeds — 78.5 %, in large breed dogs — only 26.3 %, and deformations were more frequent than in cats and small dogs (2.7 times more). The cervical vertebrae bodies density in all groups decreased toward the caudal direction with a difference of 18.1 % in humans. In cats — 2.7 %, in dogs of small breeds, it was higher (7.5 %), and in large breed dogs, it reached 14.3 %. The maximum deviations of the studied indicators were found in humans and maximally coincided with those in dogs of large breeds. Conclusions. Thus, animals, especially dogs of large breeds, can serve as a model for studying etiopathogenetic factors, the course, prognosis of degeneration of the bone-cartilage apparatus.

Objective: The aim of this study was to determine optimal radiological parameters for assessment of the round window approach in cochlear implantation surgery. Materials and methods: Patients undergoing cochlear implantation at the Department of Otolaryngology in Szczecin, between 2015 and 2022 inclusive, were eligible for the study. Radiological assessments were performed according to eight parameters (seven proposed in the literature) and visibility clinical assessments were made intra-operatively on a scale of 1 to 5 (1 - not visible, 5 - fully visible). Visibility assessments of the round window niche (RWN) and round window membrane (RWM) allowed the difference (RWN minus RWM) to be used as a clinical assessment of the size of the overhang over the round window. Results: Computed tomography images of 57 ears from 52 patients were analyzed in terms of round window access. The study group included 26 females and 26 males, ranging in age from 1 year to 80 years, with a median age of 41 years. In clinical assessment, round window visibility was rated as 5, after removal of the bone overhang, in 69% of patients. Cochlear access through the round window was achieved in 39 (68%) cases, extended access through the round window in 13 (23%) cases and cochleostomy was performed in 5 (9%) cases. Statistically significant ordinal correlations with round-window access were found using one parameter from the literature (Chen_Angle) and from our proposal (RWM_prediction). From parameters describing the bone overhang of the round window, positive correlations (using Kendall rank tests) were found using parameters from the literature (Sarafraz_OH and Mehanna_OH). Conclusions: Radiological measurements describing access to the round window which determine the angle based on the anatomy of the posterior wall of the auditory canal and the position of the facial nerve were found to be of the highest value. Clinical relevance statement: In the future, the use of algorithms for computed tomography evaluation and robot-assisted surgery will require parameters for assessing round window access, for surgery planning and choice of electrode. The parameters proposed by various authors are summarized, allowing researchers to assess their usefulness in further clinical practice. [ABSTRACT FROM AUTHOR]

Abstract Background Chitinase-3 like-protein-1 (CHI3L1) is a member of the mammalian chitinase-like proteins and elevated serum CHI3L1 level has been proved to be associated with poor prognosis in hepatocellular carcinoma (HCC). This study aimed to investigate the relationship between serum CHI3L1 levels and body composition parameters in patients with HCC after liver transplantation (LT). Methods This retrospective study enrolled 200 patients after LT for HCC. Blood samples were collected and serum concentrations of CHI3L1 were measured by enzyme-linked immunosorbent assay. Computer tomography (CT) were used to estimate skeletal muscle and adipose tissue mass. Spearman’s rank correlation test was performed to assess associations between serum CHI3L1 levels and these body composition parameters. A Cox proportional-hazards regression model was performed to identify independent prognostic factors. Overall survival (OS) and recurrence-free survival (RFS) curves were constructed using the Kaplan-Meier method and compared by the log-rank test. Results Total 71 patients (35.5%) were diagnosed with myosteatosis according to skeletal muscle radiation attenuation (SMRA). The 5-year OS rates were 66.9% in non-myosteatosis group, significantly higher than 49.5% in myosteatosis group (p = 0.025), while the RFS of myosteatosis group (5-year RFS: 52.6%) or non-myosteatosis group (5-year RFS: 42.0%) shown no significant difference (p = 0.068). The serum CHI3L1 level were significantly negative correlated with SMRA (r = -0.3, p

Background. The effect of spinal deformity surgical correction in children with severe neuromuscular scoliosis (NMS) on lung function remains unexplored.Objective. The aim of the study is to — to survey the dynamics of volume and structure of lungs pneumatization in children after surgical correction of severe neuromuscular deformities of the spine complicated by respiratory disorders.Methods. CT scans of lungs from 5 children with right-sided NMS, grade IV (Cobb angle < 50°) and functional respiratory disorders (lung capacity < 30% of normal value according to spirometry data and/or clinical signs of respiratory failure) were retrospectively studied. Right and left lungs volumes, their ratio (asymmetry index), indicators of distribution of tissue density of each lung (as a percentage of total volume) before (not earlier than 2 months) and after (not later than 3 months) surgical correction of scoliosis were determined via the data processing from CT scans of the thoracic spine.Results. All children had both lung volumes below reference values (healthy peers) before surgery. The right lung volume increased by 11% (6.4–40.6%), the left lung — by 41% (22.5–90%) with the asymmetry index approaching the reference values for the corresponding age after correction of spinal deformity (the value of scoliotic deformity decreased (median) from 94 to 68°). The volume of normal ventilation zones increased from 30 to 50% on the right side, and from 41 to 55% on the left side, primarily due to decrease in the volume of hypoventilation zones, but not atelectasis and emphysema.Conclusion. Surgical correction of spinal deformity in children with NMS, grade IV, complicated with respiratory failure led to normalization of lungs volume and tissue density characteristics already in the early postoperative period.

Abstract Background The diagnosis of solitary pulmonary nodules has always been a difficult and important point in clinical research, especially granulomatous nodules (GNs) with lobulation and spiculation signs, which are easily misdiagnosed as malignant tumors. Therefore, in this study, we utilised a CT deep learning (DL) model to distinguish GNs with lobulation and spiculation signs from solid lung adenocarcinomas (LADCs), to improve the diagnostic accuracy of preoperative diagnosis. Methods 420 patients with pathologically confirmed GNs and LADCs from three medical institutions were retrospectively enrolled. The regions of interest in non-enhanced CT (NECT) and venous contrast-enhanced CT (VECT) were identified and labeled, and self-supervised labels were constructed. Cases from institution 1 were randomly divided into a training set (TS) and an internal validation set (IVS), and cases from institutions 2 and 3 were treated as an external validation set (EVS). Training and validation were performed using self-supervised transfer learning, and the results were compared with the radiologists’ diagnoses. Results The DL model achieved good performance in distinguishing GNs and LADCs, with area under curve (AUC) values of 0.917, 0.876, and 0.896 in the IVS and 0.889, 0.879, and 0.881 in the EVS for NECT, VECT, and non-enhanced with venous contrast-enhanced CT (NEVECT) images, respectively. The AUCs of radiologists 1, 2, 3, and 4 were, respectively, 0.739, 0.783, 0.883, and 0.901 in the (IVS) and 0.760, 0.760, 0.841, and 0.844 in the EVS. Conclusions A CT DL model showed great value for preoperative differentiation of GNs with lobulation and spiculation signs from solid LADCs, and its predictive performance was higher than that of radiologists.

Background: Chitinase-3 like-protein-1 (CHI3L1) is a member of the mammalian chitinase-like proteins and elevated serum CHI3L1 level has been proved to be associated with poor prognosis in hepatocellular carcinoma (HCC). This study aimed to investigate the relationship between serum CHI3L1 levels and body composition parameters in patients with HCC after liver transplantation (LT). Methods: This retrospective study enrolled 200 patients after LT for HCC. Blood samples were collected and serum concentrations of CHI3L1 were measured by enzyme-linked immunosorbent assay. Computer tomography (CT) were used to estimate skeletal muscle and adipose tissue mass. Spearman's rank correlation test was performed to assess associations between serum CHI3L1 levels and these body composition parameters. A Cox proportional-hazards regression model was performed to identify independent prognostic factors. Overall survival (OS) and recurrence-free survival (RFS) curves were constructed using the Kaplan-Meier method and compared by the log-rank test. Results: Total 71 patients (35.5%) were diagnosed with myosteatosis according to skeletal muscle radiation attenuation (SMRA). The 5-year OS rates were 66.9% in non-myosteatosis group, significantly higher than 49.5% in myosteatosis group (p = 0.025), while the RFS of myosteatosis group (5-year RFS: 52.6%) or non-myosteatosis group (5-year RFS: 42.0%) shown no significant difference (p = 0.068). The serum CHI3L1 level were significantly negative correlated with SMRA (r = -0.3, p < 0.001). Interestingly, in patients with myosteatosis, Kaplan-Meier analysis revealed that elevated serum CHI3L1 levels were associated with worse OS (p < 0.001) and RFS (p = 0.047). However, in patients without myosteatosis, Kaplan-Meier analysis found elevated serum CHI3L1 levels were not associated with OS (p = 0.070) or RFS (p = 0.104). Conclusions: Elevated CHI3L1 was negatively correlated with SMRA, and predicted poorer prognosis in Chinese population after LT for HCC, especially in those patients with concomitant myosteatosis. Monitoring serum CHI3L1 can predict prognosis and effectively guide individual nutrition intervention. [ABSTRACT FROM AUTHOR]

Lung cancer is currently the leading cause of cancer-related death. To lower the mortality from lung cancer, early detection is crucial. A precise and effective method of diagnosis by medical professionals is necessary for early detection of lung-related cancers in order to maximize the success rate of treatment. It is particularly difficult to catch it in the early stages of dissemination because there are no symptoms in the early stages. Using specific image processing ideas on computed tomography (CT), we can identify the tumor state in the early phases of spread and diagnose this at an early level. The early detection is crucial for curing and restraining the spread of uncontrolled malignant cells. The best outcomes for accurately identifying malignant tumors in their early stages come from combining the effects of morphological filtering and a contour-based picture segmentation technique. The segmented lung CT scan pictures that were malignant were separated from the rest of the testing dataset by a support vector machine (SVM) classifier in the subsequent analysis phase. Various image quality and performance metrics, such as accuracy, sensitivity, precision and specificity are used to validate the proposed technique. [ABSTRACT FROM AUTHOR]

Machine learning (ML) is commonly used to develop survival-predictive radiomic models in non-small cell lung cancer (NSCLC) patients, which helps assist treatment decision making. Radiomic features derived from computer tomography (CT) lung images aim to capture quantitative tumor characteristics. However, these features are determined by humans, which poses a risk of including irrelevant or redundant variables, thus reducing the model's generalization. To address this issue, we propose using genetic programming (GP) to automatically construct new features with higher discriminant power than the original radiomic features. To achieve this goal, we introduce a fitness function that measures the classification performance ratio of output to input. The constructed features are then input for various classifiers to predict the two-year survival of NSCLC patients from two public CT datasets. Our approach is compared against two popular feature selection methods in radiomics to choose relevant radiomic features, and two GP-based feature construction methods whose fitness functions are based on measuring the constructed features' quality. The experimental results show that survival prediction models trained on GP-based constructed features outperform feature selection methods. Also, maximizing the classification performance gain output-to-input ratio produces features with higher discriminative power than only maximizing the classification accuracy from constructed features. Furthermore, a survival analysis demonstrated statistically significant differences between survival and non-survival groups in the Kaplan–Meier curves. Therefore, the proposed approach can be used as a complementary method for oncologists in determining the clinical management of NSCLC patients. [ABSTRACT FROM AUTHOR]

Background: Streak artifacts induced by irregular arm positioning have been an issue in diagnosing the abdomen. Purpose: To illustrate the risk of misdiagnosis in abdominal computed tomography (CT) of patients with irregular arm positioning through a case-by-case evaluation and to test if it can be solved by the artificial intelligence iterative reconstruction (AIIR) algorithm. Material and Methods: By reviewing 5220 cases of chest and thoracoabdominal CT, 64 patients with irregular arm positioning were enrolled, whose image data were reconstructed using AIIR in addition to routine hybrid iterative reconstruction (HIR). Lesion detection for livers, spleens, kidneys, gallbladders, and pancreas on AIIR images, performed by two radiologists, was compared with those on HIR images. Discrepancies arising from AIIR images included both cases with additional abnormalities and those with corrections made on previous detections. For cases with discrepancies, artifact scores for organs where discrepancies were found, and contrast-to-noise ratios (CNRs) of cysts with discrepancies were compared between two image sets. Results: Additional abnormalities were detected for 15 cases: additional liver cirrhosis (n=2); additional gallbladder stone (n=1); additional cholecystitis (n=1), additional spleen nodule (n=1); additional kidney cysts (n=8); additional liver cysts (3); and additional spleen cyst (n=1). A spleen contusion was corrected for one case. All involved artifact scores were improved on AIIR images. CNRs of involved liver, kidney, and spleen cysts were improved by up to 539.7%, 538.5%, and 245.5%, respectively. Conclusion: Irregular arm positioning may induce a variety of misdiagnoses in abdominal CT, which is almost totally avoidable by the AIIR algorithm. [ABSTRACT FROM AUTHOR]

Background: Combined PET/CT using 18F could be very effective with minimal hazards as well as false findings compared to the use one of these components alone in assessment of lymphoma. The purpose of this study was to review the usefulness of FDG PET/CT in diagnosis and staging of lymphoma, assessment of response to therapy, follow up and assessment of remissions and relapses among patients who had extranodal lymphoma. Methods: This cross-sectional study involved 36 patients who had pathologically confirmed lymphoma who underwent PET/CT study. A PET/CT in-line system was used to collect all of the data (General Electric PET CT Discovery). Prior to conducting a diagnostic enhanced whole-body CT scan, we conducted a low-dose enhanced CT scan, then a whole-body PET study. Results: The study compared the efficacy of contrast-enhanced CT and PET/CT in detecting lymphoma manifestations in 36 patients. PET/CT showed high sensitivity (100%) in detecting lymph node involvement and other extranodal manifestations, with varying specificity. Treatment response was evaluated using International Harmonization Project (IHP) and visual assessment based on the Déauville Criteria, showing a high level of agreement between the two methods. Conclusion: One promising oncologic imaging modality that could play a significant role in lymphoma care is a PET/CT combination that using 18F-FDG. In the early interim and after treatment ended, response assessments based on the Deauville criteria seemed to agree with IHP classifications to a reasonable degree. [ABSTRACT FROM AUTHOR]

Background: The purpose of this systematic review (SR) is to gather evidence on the use of machine learning (ML) models in the diagnosis of intraosseous lesions in gnathic bones and to analyze the reliability, impact, and usefulness of such models. This SR was performed in accordance with the PRISMA 2022 guidelines and was registered in the PROSPERO database (CRD42022379298). Methods: The acronym PICOS was used to structure the inquiry‐focused review question "Is Artificial Intelligence reliable for the diagnosis of intraosseous lesions in gnathic bones?" The literature search was conducted in various electronic databases, including PubMed, Embase, Scopus, Cochrane Library, Web of Science, Lilacs, IEEE Xplore, and Gray Literature (Google Scholar and ProQuest). Risk of bias assessment was performed using PROBAST, and the results were synthesized by considering the task and sampling strategy of the dataset. Results: Twenty‐six studies were included (21 146 radiographic images). Ameloblastomas, odontogenic keratocysts, dentigerous cysts, and periapical cysts were the most frequently investigated lesions. According to TRIPOD, most studies were classified as type 2 (randomly divided). The F1 score was presented in only 13 studies, which provided the metrics for 20 trials, with a mean of 0.71 (±0.25). Conclusion: There is no conclusive evidence to support the usefulness of ML‐based models in the detection, segmentation, and classification of intraosseous lesions in gnathic bones for routine clinical application. The lack of detail about data sampling, the lack of a comprehensive set of metrics for training and validation, and the absence of external testing limit experiments and hinder proper evaluation of model performance. [ABSTRACT FROM AUTHOR]

Medical Imaging Phantoms (MIPs) calibrate imaging devices, train medical professionals, and can help procedural planning. Traditional MIPs are costly and limited in customization. Additive manufacturing allows for customizable, patient-specific phantoms. This study examines the CT attenuation characteristics of contrast-injectable, chambered 3D-printed phantoms to optimize tissue-mimicking capabilities. A MIP was constructed from a CT of a complex pelvic tumor near the iliac bifurcation. A 3D reconstruction of these structures composed of three chambers (aorta, inferior vena cava, tumor) with ports for contrast injection was 3D printed. Desired attenuations were 200 HU (arterial I), 150 HU (venous I), 40 HU (tumor I), 150 HU (arterial II), 90 HU (venous II), and 400 HU (tumor II). Solutions of Optiray 350 and water were injected, and the phantom was scanned on CT. Attenuations were measured using ROIs. Mean attenuation for the six phases was as follows: 37.49 HU for tumor I, 200.50 HU for venous I, 227.92 HU for arterial I, 326.20 HU for tumor II, 91.32 HU for venous II, and 132.08 HU for arterial II. Although the percent differences between observed and goal attenuation were high, the observed relative HU differences between phases were similar to goal HU differences. The observed attenuations reflected the relative concentrations of contrast solutions used, exhibiting a strong positive correlation with contrast concentration. The contrast-injectable tumor phantom exhibited a useful physiologic range of attenuation values, enabling the modification of tissue-mimicking 3D-printed phantoms even after the manufacturing process. [ABSTRACT FROM AUTHOR]

The commonly used automatic segmentation algorithms often have over-segmentation and error-segmentation problems when segmenting conglutinated bone fragments in computed tomography (CT) images. And the end face details of the fragments are lost in this process. At present, bone fragments are often manually segmented by doctors. This increases the workload of doctors and takes low efficiency and poor accuracy in bone segmentation. We propose an automatic bone fragment segmentation algorithm based on morphology to segment the conglutinated and separated bone fragments and reconstruct them in 2D and 3D spaces. The pixel classification and clustering method based on morphology are proposed in in the algorithm to identify the pixels in the fracture images. And a concave points detection method is proposed to segment the conglutination area of the fractured bone. This algorithm and two other commonly used algorithms are used in the experiment to segment the three typical fracture images. The segmentation results are quantitatively analyzed to demonstrate the advantages of the morphology algorithm. The morphology algorithm performs well in the metrics of Accuracy (.93 ±.07), Sensitivity (.92 ±.08), Dice coefficient (.92 ±.08) and Mean intersection over union (MIoU) (.92 ±.07). The segmentation results of this algorithm are closest to the manual segmentation results of doctors compared to the other two algorithms. We have demonstrated that the algorithm proposed in this paper has good segmentation accuracy for separated and conglutinated bone fragments. This algorithm significantly improves the segmentation accuracy and efficiency of bone fragments under complex fracture conditions. [ABSTRACT FROM AUTHOR]

Background: The diagnosis of solitary pulmonary nodules has always been a difficult and important point in clinical research, especially granulomatous nodules (GNs) with lobulation and spiculation signs, which are easily misdiagnosed as malignant tumors. Therefore, in this study, we utilised a CT deep learning (DL) model to distinguish GNs with lobulation and spiculation signs from solid lung adenocarcinomas (LADCs), to improve the diagnostic accuracy of preoperative diagnosis. Methods: 420 patients with pathologically confirmed GNs and LADCs from three medical institutions were retrospectively enrolled. The regions of interest in non-enhanced CT (NECT) and venous contrast-enhanced CT (VECT) were identified and labeled, and self-supervised labels were constructed. Cases from institution 1 were randomly divided into a training set (TS) and an internal validation set (IVS), and cases from institutions 2 and 3 were treated as an external validation set (EVS). Training and validation were performed using self-supervised transfer learning, and the results were compared with the radiologists' diagnoses. Results: The DL model achieved good performance in distinguishing GNs and LADCs, with area under curve (AUC) values of 0.917, 0.876, and 0.896 in the IVS and 0.889, 0.879, and 0.881 in the EVS for NECT, VECT, and non-enhanced with venous contrast-enhanced CT (NEVECT) images, respectively. The AUCs of radiologists 1, 2, 3, and 4 were, respectively, 0.739, 0.783, 0.883, and 0.901 in the (IVS) and 0.760, 0.760, 0.841, and 0.844 in the EVS. Conclusions: A CT DL model showed great value for preoperative differentiation of GNs with lobulation and spiculation signs from solid LADCs, and its predictive performance was higher than that of radiologists. [ABSTRACT FROM AUTHOR]

Objective: To identify the most sensitive imaging examination method to evaluate the prognosis of esophageal squamous cell carcinoma (ESCC). Materials and methods: Thirty patients with esophageal squamous cell carcinoma (ESCC) participated in the study and underwent chemoradiotherapy (CRT). They were divided into two groups based on their survival status: the survival group and non-survival group. The diagnostic tests were utilized to determine the most effective imaging examination method for assessing the prognosis. Results: 1. There were no significant differences in tumor length shown on esophagography or computed tomography (CT) or the maximal esophageal wall thickness shown on CT at the specified time points between the two groups. 2. The tumor length on diffusion-weighted imaging (DWI) in the survival group was significantly lower than in the non-survival group at the end of the sixth week of treatment (P=0.001). The area under the ROC curve was 0.840 (P=0.002), and the diagnostic efficiency was moderately accurate. 3. The apparent diffusion coefficient (ADC) values of the survival group were significantly higher than those in the non-survival group at the end of the fourth week and sixth week of treatment (both P<0.001). Areas under the curve were 0.866 and 0.970, with P values of 0.001 and <0.001 and good diagnostic accuracy. Cox regression analyses indicated the ADC at the end of the sixth week of treatment was an independent risk factor. Conclusions: Compared with esophagography and CT, DW-MRI has certain advantages in predicting the prognosis of ESCC. [ABSTRACT FROM AUTHOR]

Background. The neck, its bone-cartilaginous and muscle apparatus, etc. high activity is well known. Cervical spine degenerative-dystrophic processes are considered to be an urgent problem. The purpose of the study was to determine the clinical and morphometric changes of the cervical spine in humans and animals with neck pain based on a clinical and neurological examination, determination of the vertebral body density, their configuration, and ratio for timely correction and prognosis of this pathology. Materials and methods. Pain intensity was studied in humans and animals using the adapted visual-analogue scale. The indexes of computer tomography with measurement of vertebral body density, and morphometric indexes with an emphasis on C5-C7 level were also studied. All studies were conducted following existing bioethical standards. Results. The pathology of spine configuration was registered in 84.6 % of the examined patients in the form of angular kyphosis or straightened lordosis, more often in women. It was observed in 34.7 % of cases in dogs and cats. The normal configuration is more common: in cats — 78.6 % and in dogs of small breeds — 78.5 %, in large breed dogs — only 26.3 %, and deformations were more frequent than in cats and small dogs (2.7 times more). The cervical vertebrae bodies density in all groups decreased toward the caudal direction with a difference of 18.1 % in humans. In cats — 2.7 %, in dogs of small breeds, it was higher (7.5 %), and in large breed dogs, it reached 14.3 %. The maximum deviations of the studied indicators were found in humans and maximally coincided with those in dogs of large breeds. Conclusions. Thus, animals, especially dogs of large breeds, can serve as a model for studying etiopathogenetic factors, the course, prognosis of degeneration of the bone-cartilage apparatus. [ABSTRACT FROM AUTHOR]

To compare and evaluate the performance of artificial intelligence (AI) against physicians in classifying benign and malignant pulmonary nodules from computerized tomography (CT) images. A total of 506 CT images with pulmonary nodules were retrospectively collected. The AI was trained using in-house software. For comparing the diagnostic performance of artificial intelligence and different groups of physicians in pulmonary nodules, statistical methods of receiver operating characteristic (ROC) curve and area under the curve (AUC) were analyzed. The nodules in CT images were analyzed in a case-by-case manner. The diagnostic accuracy of AI surpassed that of all groups of physicians, exhibiting an AUC of 0.88 alongside a sensitivity of 0.80, specificity of 0.84, and accuracy of 0.83. The area under the curve (AUC) of seven groups of physicians varies between 0.63 and 0.84. The sensitivity of the physicians within these groups varies between 0.4 and 0.76. The specificity of different groups ranges from 0.8 to 0.85. Furthermore, the accuracy of the seven groups ranges from 0.7 to 0.82. The professional insights for enhancing deep learning models were obtained through an examination conducted on a per-case basis. AI demonstrated great potential in the benign–malignant classification of pulmonary nodules with higher accuracy. More accurate information will be provided by AI when making clinical decisions. [ABSTRACT FROM AUTHOR]

Key Clinical Message: Omental infarction is a rare cause of acute abdominal pain, often benign and self‐limiting. The significance of infarction lies in the fact that it can mimic other abdominal pathologies including appendicitis, cholecystitis, pancreatitis, or reflux disease. Diagnostic laparoscopy provides the definitive diagnosis of omental infarction, but it is invasive and limited due to resources. Computed tomography of the abdomen and pelvis has been considered the gold standard to diagnosing omental infarction when a non‐invasive diagnostic approach is required. Additionally, ultrasound can also be used alternatively for children. Currently, there is no consensus in the diagnosis and management of patients with imaging‐proven omental infarction. Spontaneous infarcted omentum must be considered by surgeons and radiologists as a rare cause of acute abdominal pain as patients can experience good outcomes with either conservative or operative approach. However, conservative management must only be considered in stable patients where alternative pathology is unlikely. [ABSTRACT FROM AUTHOR]

Brain abscesses in ruminants often arise from primary infection foci, leading to an unfavorable prognosis for affected animals. This highlights the need for comprehensive studies on brain abscesses across different ruminant species. We retrospectively investigated medical records of epidemiological, clinical, neuroimaging, anatomopathological, and bacteriological findings in six ruminants (three goats, two cows, and one sheep) diagnosed with brain abscesses. All animals studied were female. Apathy (50%), compulsive walking (33%), decreased facial sensitivity (33%), head pressing (33%), seizures (33%), semicomatous mental status (33%), strabismus (33%), unilateral blindness (33%), and circling (33%) represented the most common neurologic signs. Leukocytosis and neutrophilia were the main findings in the hematological evaluation. Cerebrospinal fluid (CSF) analysis revealed predominant hyperproteinorrachia and pleocytosis. In three cases, computed tomography or magnetic resonance imaging were used, enabling the identification of typical abscess lesions, which were subsequently confirmed during postmortem examination. Microbiological culture of the abscess samples and/or CSF revealed bacterial coinfections in most cases. Advanced imaging examinations, combined with CSF analysis, can aid in diagnosis, although confirmation typically relies on postmortem evaluation and isolation of the causative agent. This study contributes to clinicopathological aspects, neuroimages, and bacteriological diagnosis of brain abscesses in domestic ruminants. [ABSTRACT FROM AUTHOR]

Objective: This study investigates the importance of bone density, surface area, and diameter of anatomical structures of the superior semicircular canal (SSC), lateral semicircular canal (LSC), posterior semicircular canal (PSC), utricle, and saccule in patients diagnosed with superior semicircular canal dehiscence (SSCD). Materials and methods: The bone density, surface area, and diameter of SSC, LSC, PSC, utricle, and saccule were measured and compared between the SSCD group and control group. Fifteen ears in the SSCD group and 60 ears in the control group were evaluated. Additionally, within the SSCD group, the dehiscent and healthy sides were evaluated independently. Results: SSC's bone density was significantly lower in the SSCD group compared to the control group (p = 0.008). No significant differences were found in surface area and diameter between the groups (p > 0.05). While most of the anatomical structures showed no significant difference in bone density between dehiscent and healthy ears (p > 0.05), SSC bone density was significantly lower in affected ears (p = 0.000) in SSCD group. Conclusion: Based on the data obtained in this study, bone density and anatomical structure may be useful in patients diagnosed with SSCD. [ABSTRACT FROM AUTHOR]

Spread through air space (STAS) is a novel invasive pattern of lung adenocarcinoma (LUAD), and preoperative knowledge of STAS status is helpful in choosing an appropriate surgical approach. This retrospective study collected and analyzed 602 patients diagnosed with LUAD from two medical centers: center 1 was randomly partitioned into training (n = 358) and validation cohorts (n = 154) at a 7:3 ratio; and center 2 was the external test cohort (n = 90). Super resolution was performed on all images to acquire high-resolution images, which were used to train the SE-ResNet50 model, before creating an equivalent parameter ResNet50 model. Disparities were compared between the two models using receiver operating characteristic curves, area under the curve, accuracy, precision, sensitivity, and specificity. In this study, 512 and 90 patients with LUAD were enrolled from centers 1 and 2, respectively. The curve values of the SE-ResNet50 and ResNet50 models were compared for training, validation, and test cohorts, resulting in values of 0.933 vs 0.909, 0.783 vs 0.728, and 0.806 vs 0.695, respectively. In the external test cohort, the accuracy of the SE-ResNet50 model demonstrated a 10% improvement over the ResNet50 model (82.2% vs 72.2%). The SE-ResNet50 model based on computed tomography super-resolution has great potential for predicting STAS status in patients with solid or partially solid LUAD, with superior predictive performance compared to traditional deep learning models. [ABSTRACT FROM AUTHOR]

This paper proposes a technique for medical picture fusion based on the guided image filter . It utilizes guided filtering to smooth images, using texture information as guidance for the filter . Weight maps of the detail images are created through pixel weight computation based on image statistics. Finally, the source images are combined using a weighted average combining approach. The effectiveness of the proposed method is evaluated in terms of multiple quantitative image quality assessment factors and compared with several state-of-the-art image fusion algorithms. Experimental results indicate that the suggested approach for image fusion is effective. [ABSTRACT FROM AUTHOR]

Background The study aimed to observe the internal structure of coconuts from two locations (coastal and non-coastal) using computed tomography (CT). Methods Seventy-six mature coconuts were collected from Wenchang and Ding’an cities in Hainan Province. These coconuts were scanned four times using CT, with a two-week interval between each scan. CT data were post-processed to reconstruct two-dimensional slices and three-dimensional models. The density and morphological parameters of coconut structures were measured, and the differences in these characteristics between the two groups and the changes over time were analyzed. Results Time and location had interactive effects on CT values of embryos, solid endosperms and mesocarps, morphological information such as major axis of coconut, thickness of mesocarp, volume of coconut water and height of bud (p

This brief report aimed to show the utility of photon-counting technology alongside standard cranial imaging protocols for visualizing shunt valves in a patient’s cranial computed tomography scan. Photon-counting CT scans with cranial protocols were retrospectively surveyed and four types of shunt valves were encountered: proGAV 2.0®, M.blue®, Codman Certas®, and proSA®. These scans were compared with those obtained from non-photon-counting scanners at different time points for the same patients. The analysis of these findings demonstrated the usefulness of photon-counting technology for the clear and precise visualization of shunt valves without any additional radiation or special reconstruction patterns. The enhanced utility of photon-counting is highlighted by providing superior spatial resolution compared to other CT detectors. This technology facilitates a more accurate characterization of shunt valves and may support the detection of subtle abnormalities and a precise assessment of shunt valves.

Abstract Objectives To compare the changes in condylar position after mandibular reconstruction with free fibular flap(FFF) and the differences between computer-assisted techniques and traditional methods on CT images. Methods Thirty-four patients who underwent mandibular reconstruction with free fibular flap were selected according to the inclusion and exclusion criteria. In the 3D group, virtual surgical planning (VSP) with osteotomy cutting plate and placement guiding plate were used, while the traditional group underwent freehand reconstruction. The CT data of 68 temporomandibular joints (TMJs) were recorded before and immediately after surgery. The condylar position was evaluated by measuring the anterior space (AS), posterior space (PS) and superior space (SS), and the ln (PS/AS) was calculated according to the method proposed by Pullinger and Hollender. Results In the patients included in the 3D group, the condyle on the ipsilateral side moved slightly backward; however, in the patients in the traditional group, the ipsilateral side moved considerably anteroinferior. No obvious changes on the contralateral side were noted. In the 3D group, 33% of ipsilateral condyles were in the posterior position postoperatively when compared with the preoperative position (13%). In the traditional group, the number of ipsilateral condyles in the anterior position increased from 4 to 10, accounting for 53% postoperatively. Contrary to the traditional group, the 3D group presented less condylar displacement on the ipsilateral side postoperatively. Conclusions This study showed a decreased percentage of change in condylar position postoperatively when VSP was used. Virtual surgical planning improved the accuracy of FFF mandibular reconstruction and made the condylar position more stable.

Colonic lipomas are relatively rare benign tumors which are composed of mature fat cells and occur most frequently in the large intestine. The occurrence of colonic lipomas in the transverse colon is relatively uncommon. Generally, colonic lipomas are asymptomatic, and many individuals might not experience any noticeable symptoms. Therefore, they are usually discovered incidentally during colonoscopy or as a result of diagnostic imaging prescribed for other reasons. The size and location of the lipoma could influence the clinical presentation. If symptoms occur, they include abdominal pain, changes in bowel habits, or gastrointestinal bleeding. The prognosis for colonic lipomas is generally excellent but it requires an individualized approach based on the specific characteristics of the tumor, the patient’s symptoms, and other clinical considerations. We report a case of a colonic intussusception caused by a colonic lipoma in an adult who underwent surgery, with an uneventful recovery.

Radiant porous burners with a high power density, emitting intense radiation were investigated. Different geometrical structures were applied as porous inlay in a state-of-the-art, two-layer porous burner with a rectangular shape. Structures were made of SiSiC and manufactured by the replica method using foaming and hybrid additive manufacturing. Subject to the study were foam structures as well as lattice structures with random strut distribution based on the Voronoi tessellation and with regular distribution based on the Kelvin and Hendecahedron cell geometry. The structures were designed with the intention of enhancing the irradiation by optimising the specific surface area distribution along the flow direction. The additive manufacturing method enables this through a local increase in pore density and the implementation of additional surfaces. Image processing was used to demonstrate the effectiveness of this approach and to characterise the structures in specific surface areas. Volume averaged values and distribution along the thickness were analysed. The radiation efficiency was derived from measurements of the radiation intensity on discrete points in parallel to the radiating surface using a radiometer. The burner was operated with methane as fuel at a specific burner power in the range of 600kWm−2 to 1000kWm−2 and an equivalence ratio of ϕ=0.7. Measured radiation efficiency was compared to a limiting radiation efficiency obtained from theoretical calculations. Highest radiation efficiency was obtained for a foam structure with a specific surface area of 622m−1. Structures based on the geometry of a hendecahedron and a kelvin cell achieved comparable efficiencies. The lowest values were observed for a randomly distributed lattice structure with nominal pore density of 10 PPI. A relation between volume averaged specific surface area values and measured radiation efficiency is derived and proven. Additionally, efficiency could be improved by targeted surface area increase applying closed windows or a gradient in pore size respectively.

This study provides an objective comparison of cranial computed tomography (CT) imaging quality and radiation dose between photon counting detectors (PCCTs) and energy-integrated detectors (EIDs). We retrospectively analyzed 158 CT scans from 76 patients, employing both detector types on the same individuals to ensure a consistent comparison. Our analysis focused on the Computed Tomography Dose Index and the Dose-Length Product together with the contrast-to-noise ratio and the signal-to-noise ratio for brain gray and white matter. We utilized standardized imaging protocols and consistent patient positioning to minimize variables. PCCT showed a potential for higher image quality and lower radiation doses, as highlighted by this study, thus achieving diagnostic clarity with reduced radiation exposure, underlining its significance in patient care, particularly for patients requiring multiple scans. The results demonstrated that while both systems were effective, PCCT offered enhanced imaging and patient safety in neuroradiological evaluations. [ABSTRACT FROM AUTHOR]

This brief report aimed to show the utility of photon-counting technology alongside standard cranial imaging protocols for visualizing shunt valves in a patient's cranial computed tomography scan. Photon-counting CT scans with cranial protocols were retrospectively surveyed and four types of shunt valves were encountered: proGAV 2.0®, M.blue®, Codman Certas®, and proSA®. These scans were compared with those obtained from non-photon-counting scanners at different time points for the same patients. The analysis of these findings demonstrated the usefulness of photon-counting technology for the clear and precise visualization of shunt valves without any additional radiation or special reconstruction patterns. The enhanced utility of photon-counting is highlighted by providing superior spatial resolution compared to other CT detectors. This technology facilitates a more accurate characterization of shunt valves and may support the detection of subtle abnormalities and a precise assessment of shunt valves. [ABSTRACT FROM AUTHOR]