Search Results (49)

Background: Ectopic pregnancy occurs in about 1–2% of all pregnancies, with 95% implanting in the fallopian tubes. Hepatic implantation is one of the rarest and most dangerous forms of abdominal ectopic pregnancy. Its diagnosis is often delayed because of nonspecific symptoms, and it is also often difficult for routine ultrasound imaging to visualize ectopic pregnancy sites that are not in the pelvis. Since this type of pregnancy carries a risk of severe hemorrhage, early identification is crucial. Case: A 30-year-old woman, gravida 3 para 2, presented with a serum β-hCG of 66,408 mIU/mL, but no intrauterine pregnancy was detected on ultrasound imaging. At an outside facility, a laparoscopy was performed, which also failed to show a pelvic ectopic pregnancy. The patient then received her first dose of methotrexate and was subsequently transferred to a tertiary care center for further evaluation. MRI and liver ultrasound showed a 2.3 cm subcapsular lesion in segment 5 of the liver that was suspicious for a hepatic ectopic pregnancy. However, these imaging studies could not exclude a gestational trophoblastic disease or hepatic neoplasm. A dilation and curettage revealed no trophoblastic tissue. The patient next received two additional doses of methotrexate on hospital days 4 and 7 due to an inadequate decline in interval β-hCG; β-hCG levels declined gradually but steadily over several months until they became undetectable and indicated a successful medical treatment of her hepatic ectopic pregnancy. Conclusions: This case highlights the complex diagnostic and treatment challenges presented by a hepatic ectopic pregnancy. Multimodal imaging, serial monitoring of β-hCG levels, and the engagement of a multidisciplinary team were essential factors in achieving a safe, nonsurgical, and successful resolution of this condition. When a pregnancy of unknown location is suspected, extended imaging studies are critical tools for patient evaluation after initial imaging studies and laparoscopy are inconclusive. Full article

Background and Objectives: Tubal reanastomosis is an alternative option for women seeking fertility after sterilization. Thus, anastomosis healing quality and peri-tubal adhesions play a crucial role. TISSEEL^® fibrin sealant may enhance tissue repair and reduce foreign-body reaction. We evaluated the effect of TISSEEL^®, used alone or with sutures, on anastomotic healing and adhesion formation in a rat uterine horn model. Materials and Methods: Thirty female Wistar rats were randomized to Suture, TISSEEL^®, or Suture + TISSEEL^® groups (n = 10 each). After bilateral uterine horn transection, reanastomosis was performed with sutures alone, fibrin sealant alone, or combined sutures and sealant. On postoperative day 14, reanastomosis segments were collected for blinded histologic assessment and evaluation of modified Ehrlich–Hunt score parameters (inflammation, fibrosis, neovascularization and collagen production). Intra-abdominal adhesions were also macroscopically assessed. Results: Two animals died perioperatively and 56 uterine horns were included in the final analysis (Suture n = 18, TISSEEL^® n = 18, Suture + TISSEEL^® n = 20). The distribution of inflammation and fibrosis severity grades, as assessed by the modified Ehrlich–Hunt scoring system, did not differ significantly between the study groups (p = 0.208 and p = 0.652, respectively). In contrast, high-grade neovascularization (grades 3–4) was more common in TISSEEL^® groups (77.8% TISSEEL^®, 80.0% Suture + TISSEEL^®, 33.3% Suture, p = 0.004), while increased collagen deposition was also more common in the TISSEEL^® groups (p = 0.011), after binary analysis. Severe adhesions were more common in the Suture group (66.7% vs. 11.1% in the TISSEEL^® group and 30.0% in the Suture + TISSEEL^® group, p = 0.037). Conclusions: TISSEEL^®, alone or as an adjunct to sutures, improves neovascularization and collagen production and is associated with milder adhesions without increased inflammation or fibrosis. The use of fibrin sealant TISSEEL^® may be a useful tool in tubal reconstructive surgery. Full article

Background: Accurate quantification of visceral (VAT) and subcutaneous adipose tissue (SAT) is critical for understanding the cardiometabolic consequences of obstructive sleep apnea (OSA) and other chronic diseases. This study validates a customization framework using pre-trained networks for the development of automated VAT/SAT segmentation models using hybrid positron emission tomography (PET)/magnetic resonance imaging (MRI) data from OSA patients. While the widespread adoption of deep learning models continues to accelerate the automation of repetitive tasks, establishing a customization framework is essential for developing models tailored to specific research questions. Methods: A UNet-ResNet50 model, pre-trained on RadImageNet, was iteratively trained on 59, 157, and 328 annotated scans within a closed-loop system on the Discovery Viewer platform. Model performance was evaluated against manual expert annotations in 10 independent test cases (with 80–100 MR slices per scan) using Dice similarity coefficients, segmentation time, intraclass correlation coefficients (ICC) for volumetric and metabolic agreement (VAT/SAT volume and standardized uptake values [SUVmean]), and Bland–Altman analysis to evaluate the bias. Results: The proposed deep learning pipeline substantially improved segmentation efficiency. Average annotation time per scan was 121.8 min (manual segmentation), 31.8 min (AI-assisted segmentation), and only 1.2 min (fully automated AI segmentation). Segmentation performance, assessed on 10 independent scans, demonstrated high Dice similarity coefficients for masks (0.98 for VAT and SAT), though lower for contours/boundary delineation (0.43 and 0.54). Agreement between AI-derived and manual volumetric and metabolic VAT/SAT measures was excellent, with all ICCs exceeding 0.98 for the best model and with minimal bias. Conclusions: This scalable and accurate pipeline enables efficient abdominal fat quantification using hybrid PET/MRI for simultaneous volumetric and metabolic fat analysis. Our framework streamlines research workflows and supports clinical studies in obesity, OSA, and cardiometabolic diseases through multi-modal imaging integration and AI-based segmentation. This facilitates the quantification of depot-specific adipose metrics that may strongly influence clinical outcomes. Full article

Accurate segmentation of the pancreas in Computed Tomography (CT) scans is a challenging task, which may be crucial for the diagnosis and treatment planning of pancreatic cancer. The irregular shape of the pancreas, its low contrast relative to surrounding tissues, and its close proximity to other complex anatomical structures make it difficult to accurately delineate its contours. Furthermore, a significant class imbalance between foreground (pancreas) and background voxels in an abdominal CT series represents an additional challenge for deep-learning-based approaches. In this study, we developed a deep learning model for automated pancreas segmentation based on a 3D U-Net architecture enhanced with an attention mechanism to improve the model capability to focus on relevant anatomical features of the pancreas. The model was trained and evaluated on two widely used benchmark datasets for volumetric segmentation, the NIH Healthy Pancreas-dataset and the Medical Segmentation Decathlon (MSD) pancreas dataset. The proposed attention-guided 3D U-Net achieved a Dice score of 80.8 ± 2.1%, ASSD of 2.1 ± 0.3 mm, and HD₉₅ of 8.1 ± 1.6 mm on the NIH dataset, and the values of 78.1 ± 1.1%, 3.3 ± 0.3 mm, and 12.3 ± 1.5 mm for the same metrics on the MSD dataset, demonstrating the value of attention mechanisms in improving segmentation performance in complex and low-contrast anatomical regions. Full article

Objective: Obesity increases the risk of endometrial cancer (EC). In this study, we aimed to investigate the prognostic effect of sarcopenia, sarcopenic obesity and sarcopenic visceral obesity, calculated with the help of cross-sectional imaging methods of muscle and visceral adipose tissue from body composition parameters, in EC. Methods: Patients diagnosed with EC were identified between January 2014 and June 2024. The combination of radiological markers and patient outcomes can predict prognosis. The skeletal muscle index (SMI) and visceral fat index (VFI) were calculated from computed tomography (CT) and/or abdominal magnetic resonance (MR) scans taken at the time of diagnosis at the Lumbal 3 (L3) vertebra level. The findings of these analyses demonstrate the strongest correlation with the ratio of muscle and visceral fat tissue throughout the body. The loss of muscle and fat is an unfavourable indicator in patients with EC. The present study analysed the prognostic values of sarcopenia, sarcopenic obesity, sarcopenic visceral obesity, and the visceral fat index in EC. The total skeletal muscle area was calculated in square centimetres. Body surface area (m²) was calculated using the Mosteller formula: ((height (cm) × weight (kg))/3600)^1/2. To normalize body composition components, the skeletal muscle index was calculated as cm²/m². Results: The study comprised a total of 236 EC patients. The prevalence of sarcopenia, sarcopenic obesity, and sarcopenic visceral obesity were found to be 48.31%, 33.47%, and 22.88%, respectively. The presence of sarcopenia, high VFI levels, sarcopenic obesity, and sarcopenic visceral obesity did not demonstrate statistical significance in the survival analysis. However, stage increase (p = 0.001), primary tumour localization in the lower uterine segment (p = 0.001), serous carcinoma (p = 0.001), increased grade in endometrioid carcinoma (p = 0.023), and lymphovascular invasion (p = 0.001) were significantly associated with increased mortality risk. The presence of sarcopenia was found to be significant in patients with obesity (p = 0.008) and those aged ≥ 65 years (p = 0.001). Conclusions: In EC survival, established prognostic factors such as serous histopathology, LVI positivity, and the extent of surgical staging are prioritised. The presence of these well-established markers means the potential effect of BMI-based observations, such as the ‘obesity paradox’, and even body composition measurements, such as sarcopenic obesity, are now statistically insignificant. Our findings suggest that aggressive tumour biology (serous type, LVI) and surgery, rather than metabolic variables such as sarcopenia, sarcopenic obesity and sarcopenic visceral obesity, are the direct reason for the survival difference. This is due to the tumour’s aggressive nature and clinical characteristics (e.g., age at diagnosis, operability, stage, primary tumour localization in the lower uterine segment, serous carcinoma, grade, and LVI positivity) rather than metabolic variables. Full article

Accurate spleen segmentation in abdominal CT scans remains a critical challenge in medical image analysis due to variable morphology, low tissue contrast, and proximity to similar anatomical structures. This paper presents an enhanced U-Net architecture that addresses these challenges through multi-slice contextual integration and interpretable deep learning. Our approach incorporates three-channel inputs from adjacent CT slices, implements a hybrid loss function combining Dice and binary cross-entropy terms, and integrates Grad-CAM visualization for enhanced model interpretability. Comprehensive evaluation on the Medical Decathlon dataset demonstrates superior performance, with a Dice similarity coefficient of 0.923 ± 0.04, outperforming standard 2D approaches by 3.2%. The model exhibits robust performance across varying slice thicknesses, contrast phases, and pathological conditions. Grad-CAM analysis reveals focused attention on spleen–tissue interfaces and internal vascular structures, providing clinical insight into model decision-making. The system demonstrates practical applicability for automated splenic volumetry, trauma assessment, and surgical planning, with processing times suitable for clinical workflow integration. Full article

Recent advances in cardiovascular imaging have revolutionized the assessment and management of abdominal aortic aneurysm (AAA) through the integration of sophisticated haemodynamic biomarkers. This comprehensive review evaluates the clinical utility and mechanistic significance of multiple biomarkers in AAA pathogenesis, progression, and treatment outcomes. Advanced cardiac imaging modalities, including four-dimensional magnetic resonance imaging (4D MRI), computational fluid dynamics (CFD), and specialized echocardiography, enable precise quantification of critical haemodynamic parameters. Wall shear stress (WSS) emerges as a fundamental biomarker, with values below 0.4 Pa indicating pathological conditions and increased risk for aneurysm progression. Time-averaged wall shear stress (TAWSS), typically maintaining values above 1.5 Pa in healthy arterial segments, provides crucial information about sustained haemodynamic forces affecting the vessel wall. The oscillatory shear index (OSI), ranging from 0 (unidirectional flow) to 0.5 (purely oscillatory flow), quantifies directional changes in WSS during cardiac cycles. In AAA, elevated OSI values between 0.3 and 0.4 correlate with disturbed flow patterns and accelerated disease progression. The relative residence time (RRT), combining TAWSS and OSI, identifies regions prone to thrombosis, with values exceeding 2–3 Pa⁻¹ indicating increased risk. The endothelial cell activation potential (ECAP), calculated as OSI/TAWSS, serves as an integrated metric for endothelial dysfunction risk, with values above 0.2–0.3 Pa⁻¹ suggesting increased inflammatory activity. Additional biomarkers include the volumetric perivascular characterization index (VPCI), which assesses vessel wall inflammation through perivascular tissue analysis, and pulse wave velocity (PWV), measuring arterial stiffness. Central aortic systolic pressure and the aortic augmentation index provide essential information about cardiovascular load and arterial compliance. Novel parameters such as particle residence time, flow stagnation, and recirculation zones offer detailed insights into local haemodynamics and potential complications. Implementation challenges include the need for specialized equipment, standardized protocols, and expertise in data interpretation. However, the potential for improved patient outcomes through more precise risk stratification and personalized treatment planning justifies continued development and validation of these advanced assessment tools. Full article

Background/Objectives: Chronic kidney disease (CKD) is a prevalent condition with many cases remaining undiagnosed, although early detection is essential. Adipose tissue distribution—particularly perirenal fat thickness (PrFT)—has recently been linked to renal pathophysiology. This study assessed the association between CT-derived parameters of fat distribution and kidney morphology with CKD. Materials and Methods: This retrospective study included 237 patients (117 subjects, 120 controls) who underwent abdominal CT and had serum creatinine data. The dataset was randomly split (70% training, 30% test) to develop and evaluate a logistic regression model. CKD was defined as estimated Glomerular Filtration Rate (eGFR) < 60 mL/min/1.73 m². PrFT was measured as the distance from the posterior renal capsule to the posterior abdominal wall; renal hilum fat was segmented using a −195 to −45 HU range. Additional parameters (measured using automated segmentation tools) included kidney volume (KV), visceral/subcutaneous fat areas, skeletal muscle area and attenuation, and liver attenuation. Bilateral measurements were averaged. Results: KV (OR = 0.249, 95% CI: 0.146–0.422, p < 0.001) and PrFT (2nd tercile: OR = 7.720, 95% CI: 2.860–20.839; 3rd tercile: OR = 16.892, 95% CI: 5.727–49.822; both p < 0.001) were identified as independent predictors of CKD. These variables were used to construct a simplified model, which demonstrated moderate clinical applicability (AUC = 0.894) when evaluated on the test subset. Conclusions: KV and PrFT emerged as independent predictors of CKD, forming the basis of a simplified model with potential for opportunistic clinical application. This approach may facilitate earlier detection of CKD in patients undergoing CT imaging for unrelated clinical reasons. These imaging parameters are not intended to replace serum creatinine or eGFR but may serve as complementary predictors in specific clinical contexts. Full article

Objective: To evaluate the impact of body composition parameters, including specifically sarcopenic obesity (SO), on postoperative and oncological outcomes in patients undergoing radical cystectomy (RC) for bladder cancer, thereby addressing a paucity of data in this setting. Methods: A retrospective observational study was conducted in patients who underwent RC. Preoperative CT scans were analyzed using semi-automatic segmentation software to assess body composition parameters, with measurements of adipose and muscle tissue obtained at the level of the L3 vertebra. Results: A total of 249 patients were included, of whom 127 (52.5%) met the criteria for sarcopenia, 53 (21.3%) for obesity, and 14 (5.6%) for SO. Multivariate analysis identified previous abdominal surgery (OR 2.56, 95% CI 1.24–5.23, p = 0.011), total serum protein level (OR 0.57, 95% CI 0.36–0.88, p = 0.013), and SO (OR 7.01, 95% CI 1.06–37.05, p = 0.045) as independent predictors of 90-day postoperative complications. Patients with SO experienced significantly higher rates of abdominal wall complications (p = 0.03). However, in multivariate analyses, SO was not associated with overall survival (despite a p value of 0.04 at univariate analysis), cancer-specific survival, or progression-free survival. Conclusions: Preoperative CT-based assessment of body composition is a valuable tool in the surgical evaluation of patients undergoing RC. SO appears to be an independent predictor of short-term postoperative complications and should be considered when planning prehabilitation strategies. Full article

This study introduces a deep learning-based strategy to automatically detect the L3 slice and segment abdominal tissues from computed tomography (CT) images. Accurate measurement of muscle and fat composition at the L3 level is critical as it can serve as a prognostic biomarker for cancer diagnosis and treatment. However, current manual approaches are time-consuming and prone to class imbalance, since L3 slices constitute only a small fraction of the entire CT dataset. In this study, we propose an optimization-incorporated strategy that integrates augmentation ratio and class weight adjustment as correction design variables within deep learning models. In this retrospective study, the CT dataset was privately collected from 150 prostate cancer and bladder cancer patients at the Department of Urology of Gangneung Asan Hospital. A ResNet50 classifier was used to detect the L3 slice, while standard Unet, Swin-Unet, and SegFormer models were employed to segment abdominal tissues. Bayesian optimization determines optimal augmentation ratios and class weights, mitigating the imbalanced distribution of L3 slices and abdominal tissues. Evaluation of CT data from 150 prostate and bladder cancer patients showed that the optimized models reduced the slice detection error to approximately 0.68 ± 1.26 slices and achieved a Dice coefficient of up to 0.987 ± 0.001 for abdominal tissue segmentation-improvements over the models that did not consider correction design variables. This study confirms that balancing class distribution and properly tuning model parameters enhances performance. The proposed approach may provide reliable and automated biomarkers for early cancer diagnosis and personalized treatment planning. Full article

Knowledge of realistic loads is crucial in the engineering design process of medical devices and for assessing their interaction with the spinal system. Depending on the type of modeling, current numerical spine models generally either neglect the active musculature or oversimplify the passive structural function of the spine. However, the internal loading conditions of the spine are complex and greatly influenced by muscle forces. It is often unclear whether the assumptions made provide realistic results. To improve the prediction of realistic loading conditions in both conservative and surgical treatments, we modified a previously validated forward dynamic musculoskeletal model of the intact lumbosacral spine with a muscle-driven approach in three scenarios. These exploratory treatment scenarios included an extensible lumbar orthosis and spinal instrumentations. The latter comprised bisegmental internal spinal fixation, as well as monosegmental lumbar fusion using an expandable interbody cage with supplementary posterior fixation. The biomechanical model responses, including internal loads on spinal instrumentation, influences on adjacent segments, and effects on abdominal soft tissue, correlated closely with available in vivo data. The muscle forces contributing to spinal movement and stabilization were also reliably predicted. This new type of modeling enables the biomechanical study of the interactions between active and passive spinal structures and technical systems. It is, therefore, preferable in the design of medical devices and for more realistically assessing treatment outcomes. Full article

Background: Crohn’s disease (CD) is a complex systemic entity, characterized by the progressive and relapsing inflammatory involvement of any part of the gastrointestinal tract. Its clinical pattern may be categorized as penetrating, stricturing or non-penetrating non-stricturing. Methods: In this paper, we performed a database search (Pubmed, MEDLINE, Mendeley) using combinations of the queries “crohn”, “stricture” and “elastography” up to 19 June 2024 to summarize current knowledge regarding the diagnostic utility of ultrasound (US) and magnetic resonance (MR) elastography techniques in the evaluation of stricturing CD by means of an assessment of the transmural intestinal fibrosis. We decided to include papers published since 1 January 2017 for further evaluation (n = 24). Results: Despite growing collective and original data regarding numerous applications of mostly ultrasound elastography (quantification of fibrosis, distinguishing inflammatory from predominantly fibrotic strictures, assessment of treatment response, predicting disease progression) constantly emerging, to date, we are still lacking a uniformization in both cut-off values and principles of measurements, i.e., reference tissue in strain elastography (mesenteric fat, abdominal muscles, unaffected bowel segment), units, not to mention subtle differences in technical background of SWE techniques utilized by different vendors. All these factors imply that ultrasound elastography techniques are hardly translatable throughout different medical centers and practitioners, largely depending on the local experience. Conclusions: Nonetheless, the existing medical evidence is promising, especially in terms of possible longitudinal comparative studies (follow-up) of patients in the course of the disease, which seems to be of particular interest in children (lack of radiation, less invasive contrast media) and terminal ileal disease (easily accessible). Full article

Background: Ehlers–Danlos syndrome (EDS), Marfan syndrome (MFS), and Loeys–Dietz syndrome (LDS) are connective tissue disorders frequently associated with vascular aneurysm formation, dissections, and subsequent major complications. Regular imaging surveillance is recommended for these conditions. However, no guidelines currently exist regarding imaging modality or surveillance intervals. Methods: This retrospective single-center observational study analyzed clinical and imaging data of patients attending an outpatient clinic for vascular connective tissue disorders between August 2008 and January 2024. Imaging (1424 data points in total) and clinical data were extracted from electronic health records. Analysis primarily included a comparison of vessel diameter progression across imaging modalities, with an additional review of the clinical history of vascular events. Results: In total, 19 patients with vascular connective tissue disorders (vCTDs) underwent consultations at our outpatient clinic. Nine (47.4%) patients experienced vascular events, while two (10.5%) passed away during the study period. Multimodal imaging surveillance revealed a tendency towards arterial diameter increase. Consistent ultrasound monitoring provided more reliable diameter progression data for the same arterial segment than a combination of imaging modalities. Temporal analysis indicated a tendency for the continuous growth of the abdominal aorta, the common and internal carotid artery, and the common femoral and popliteal artery. Conclusion: The study highlights the importance of standardized, modality-specific imaging protocols in monitoring patients with vCTDs. The variability in disease progression among these patients further complicates surveillance strategies, contemplating the need for individualized approaches. Further research and prospective multicenter studies are required to refine and improve monitoring protocols. Full article

Background: Body composition assessment using computed tomography (CT) scans may be hampered by software costs. To facilitate its implementation in resource-limited settings, two open-source segmentation programs (Horos and CoreSlicer) were transversally validated in colorectal cancer patients. Methods: Contrast-enhanced abdominal CT scans were analyzed following the Alberta protocol. The Cross-Sectional Area (CSA) and intensities of skeletal muscle tissue (MT), subcutaneous adipose tissue (SAT), visceral adipose tissue (VAT), and intramuscular adipose tissue (IMAT) were measured. The Skeletal Muscle Index (SMI) was calculated. Cutoff points were applied to the SMI, MT intensity, and VAT CSA to define muscle atrophy, myosteatosis, and abdominal obesity. The inter-software agreement was evaluated using different statistical tools. Results: A total of 68 participants were measured. The MT CSA and SMI displayed no differences. The MT CSA agreement was excellent, and both programs provided equal muscle atrophy prevalences. CoreSlicer underestimated the MT intensity, with a non-significant myosteatosis prevalence increase (+5.88% and +8.82%) using two different operative definitions. CoreSlicer overestimated the CSA and intensity in both VAT and SAT, with a non-significant increase (+2.94%) in the abdominal obesity prevalence. Conclusions: Both software programs were feasible tools in the study group. The MT CSA showed great inter-software agreement and no muscle atrophy misdiagnosis. Segmentation differences in the MT intensity and VAT CSA caused limited diagnostic misclassification in the study sample. Full article

Background and Objectives: Spontaneous colonic perforations (SCPs) in teenagers and young adults are extremely rare. Common underlying conditions, such as colonic tumors and diverticulitis, are absent at that age. The vascular type of Ehlers–Danlos Syndrome (vEDS) is one cause of SCP. Methods: A 23-year-old male presented with an acute abdomen. The abdominal CT showed pneumoperitoneum with a large amount of fluid in the pelvis and abdomen, indicating hollow viscus rupture. At the level of the sigmoid colon, a defect in the intestinal wall and gas bubbles were seen. Results: Exploratory laparotomy confirmed sigmoid colon perforation without underlying pathology. Loop sigmoid colostomy was performed. Revisional surgery was undertaken due to clinical deterioration and intra-abdominal free fluid with small-bowel distension and air-liquid levels on abdominal CT 6 days later. Ileal subserosal hematomas were found, and many had ruptured, leaving a “zebra” pattern with lines of residual hematomas on the borders of subserosal hematomas. Genetic analysis confirmed vEDS. Conclusions: SCP in young adults or teenagers, in the absence of colonic disease, with clinical manifestations of connective tissue disorders should trigger genetic investigations for vEDS. SCP with a known vEDS could be treated with total colectomy to prevent further SCPs in the remaining colon. If segmental resections are performed, further SCP should be immediately excluded with any significant abdominal pain. Full article