Diagnostic and interventional radiology最新文献

Bouveret syndrome is a rare form of gallstone ileus in which a gallstone causes gastric outlet obstruction via a cholecystoenteric fistula. We present the case of an elderly patient who underwent emergency surgery due to clinical signs of gastric outlet obstruction. Intraoperatively, a large gallstone was identified and removed from the duodenum. A subtotal cholecystectomy was performed, during which the identification of the course of the cystic duct was limited due to considerable inflammatory changes. In the early postoperative period, bile-stained output from the surgical drain raised suspicion of a leak from the cystic duct stump. Given the patient's clinical status and the complexity of the local anatomy with severely inflamed and fibrotic tissues in the hepatoduodenal ligament, the decision was made to proceed with percutaneous treatment. A percutaneous transhepatic biliary drainage was established, and contrast extravasation from the cystic duct remnant was confirmed via fluoroscopic cholangiography. Through the same access, a microvascular plug was successfully deployed into the cystic duct, achieving immediate cessation of bile leakage. The patient's clinical condition improved markedly, and no further intervention was required. This case demonstrates the successful off-label use of polytetrafluoroethylene-covered vascular occlusion devices in managing biliary complications.

Purpose: Pneumothorax is the most common complication following computed tomography (CT)-guided percutaneous transthoracic needle biopsy. In severe cases, it may require chest tube placement, which is associated with increased morbidity. The aim of this study was to evaluate the prognostic value of the pleural tail sign (PTS) as an imaging marker for predicting pneumothorax incidence and severity after lung biopsy.

Methods: A total of 477 patients (mean age 65 ± 11.7 years, 37.2% women) undergoing CT-guided lung biopsies between 2012 and 2021 were retrospectively analyzed in this study. The presence and morphological subtype of PTS-classified as thin PTS or triangular PTS-were assessed on pre-interventional CT imaging. Associations between PTS and pneumothorax outcomes were evaluated using univariate and multivariate binary logistic regression analyses.

Results: No statistically significant association was found between the overall presence of PTS and the incidence of pneumothorax (P = 0.052). However, patients with a triangular PTS showed a significantly increased risk of severe pneumothorax requiring chest tube placement (odds ratio: 2.092, 95% confidence interval: 1.097-3.990, P = 0.025), whereas a thin PTS did not show a statistically significant effect (P = 0.456).

Conclusion: Although PTS does not reliably predict overall pneumothorax risk after CT‑guided lung biopsy, its triangular subtype may serve as a prognostic imaging marker for identifying patients at increased risk of severe pneumothorax requiring chest tube placement.

Clinical significance: The identification of a triangular PTS on pre-interventional CT imaging may help to stratify patients at higher risk of severe pneumothorax following CT-guided lung biopsy. This could enable more informed procedural planning, potentially leading to improved patient outcomes.

Purpose: We aimed to evaluate the predictive ability of baseline multiphase computed tomographic angiography (mCTA) findings and the time from symptom onset to imaging in predicting functional outcomes in patients with middle cerebral artery (MCA) M1 occlusion treated with mechanical thrombectomy (MT).

Methods: A total of 70 patients were evaluated retrospectively. The time between the onset of symptoms and imaging, thrombus density, estimated thrombus length, the Alberta Stroke Program Early CT Score (ASPECTS) on non-contrast CT, collateral circulation (CC), actual thrombus length, and clot burden score were assessed on mCTA images. Patients with a 90-day modified Rankin scale score of 0-2 were categorized as having good outcomes, whereas the others were categorized as having poor outcomes. The mCTA findings of patients with good and poor outcomes were compared, and binary logistic regression analysis was performed to identify independent predictors that could affect clinical outcomes.

Results: The estimated thrombus length, the ASPECTS, thrombus density, clot burden score, and CC grade were not significantly different between patients with good and poor outcomes. The actual thrombus length was shorter in patients with good outcomes than in those with poor outcomes (15.9 mm versus 21.5 mm, P = 0.001). Binary logistic regression analysis revealed that actual thrombus length [P = 0.005, odds ratio (OR): 0.754, 95% confidence interval (CI): 0.61-0.92] and thrombus density (P = 0.022, OR: 1.167, 95% CI: 1.02-1.33) were independent variables for a good outcome. The optimal cut-off value for actual thrombus length was 18.7 mm (area under the curve, 0.74; 95% CI: 0.62-0.86; P = 0.001) to predict good outcomes.

Conclusion: Higher thrombus density and actual thrombus length shorter than 18.7 mm were associated with good clinical outcomes. However, no significant correlation was found between clinical outcomes and the ASPECTS, CC degree, or clot burden scores.

Clinical significance: Thrombus length and density are associated with the clinical outcome of patients with MCA M1 occlusion treated with MT who have distal collateral filling sufficient to depict thrombus margins in mCTA.

The incidence of congenital heart disease (CHD) is approximately 6-7 per 1,000 newborns. With advanced diagnostic, medical, and surgical methods, survival of CHD is increasing, as is the number of people living with CHD. Echocardiography is a useful modality in non-invasive imaging, whereas magnetic resonance imaging (MRI), cardiac MR (CMR), cardiac computed tomography (CT), and CT angiography (CTA) are increasingly gaining ground in congenital cardiac imaging with developing technology. Considering the limited postoperative use of echocardiography, these techniques have assumed vital roles with the increasing population of CHD in children and adults. CMR and cardiac CT can complement the information obtained with echocardiography and invasive cardiac catheterization and can sometimes provide more detail. In postoperative imaging of CHD, CMR allows an evaluation of anatomy, especially with spin echo MRI techniques, whereas cine MRI, created in gradient echo sequences, allows functional data to be obtained. Phase contrast CMR data provides information on flow direction and flow rate, allowing accurate measurement of regurgitation and shunt volume. In addition, in post-gadolinium imaging, data such as on MR angiography, myocardial perfusion, and fibrosis can be obtained with CMR. Cardiac CT and CTA provide great advantages, especially in newborns, by almost completely reducing movement and respiratory artifacts through capabilities such as high spatial and temporal resolution, fast acquisition, and short acquisition time. Three-dimensional reformatted images with contrast-enhanced CMR or cardiac CT/CTA provide excellent visualization of vascular structures in complex CHDs. Coronary imaging can be viewed more easily with CT imaging. This article reviews the literature to provide an overview of the diagnostic value, relative advantages, and overall evaluation of CMR and cardiac CT examinations in the diagnosis and postoperative follow-up of CHD.

Purpose: To assess the performance and feasibility of generative deep learning in enhancing the image quality of T2-weighted (T2W) prostate magnetic resonance imaging (MRI).

Methods: Axial T2W images from the prostate imaging: cancer artificial intelligence dataset (n = 1,476, biologically males; n = 1,500 scans) were used, partitioned into training (n = 1300), validation (n = 100), and testing (n = 100) sets. A Pix2Pix model was trained on original and synthetically degraded images, generated using operations such as motion, Gaussian noise, blur, ghosting, spikes, and bias field inhomogeneities to enhance image quality. The efficacy of the model was evaluated by seven radiologists using the prostate imaging quality criteria to assess original, degraded, and improved images. The evaluation also included tests to determine whether the images were original or synthetically improved. Additionally, the model's performance was tested on the in-house external testing dataset of 33 patients. The statistical significance was assessed using the Wilcoxon signedrank test.

Results: Results showed that synthetically improved images [median score (interquartile range) 4.71 (1)] were of higher quality than degraded images [3.36 (3), P = 0.0001], with no significant difference from original images [5 (1.14), P > 0.05]. Observers equally identified original and synthetically improved images as original (52% and 53%), proving the model's ability to retain realistic attributes. External testing on a dataset of 33 patients confirmed a significant improvement (P = 0.001) in image quality, from a median score of 4 (2.286)-4.71 (1.715).

Conclusion: The Pix2Pix model, trained on synthetically degraded data, effectively improved prostate MRI image quality while maintaining realism and demonstrating both applicability to real data and generalizability across various datasets.

Clinical significance: This study critically assesses the efficacy of the Pix2Pix generative-adversarial network in enhancing T2W prostate MRI quality, demonstrating its potential to produce high-quality, realistic images indistinguishable from originals, thereby potentially advancing radiology practice by improving diagnostic accuracy and image reliability.

Purpose: This study aimed to evaluate the validity of two artificial intelligence (AI)-based bone age assessment programs, BoneXpert and VUNO Med-Bone Age (VUNO), compared with manual assessments using the Greulich-Pyle method in Turkish children.

Methods: This study included a cohort of 292 pediatric cases, ranging in age from 1 to 15 years with an equal gender and number distribution in each age group. Two radiologists, who were unaware of the bone age determined by AI, independently evaluated the bone age. The statistical study involved using the intraclass correlation coefficient (ICC) to measure the level of agreement between the manual and AI-based assessments.

Results: The ICC coefficients for the agreement between the manual measurements of two radiologists indicate almost perfect agreement. When all cases, regardless of gender and age group, were analyzed, an almost perfect positive agreement was observed between the manual and software measurements. When bone age calculations were analyzed separately for boys and girls, no statistically significant differences were found between the two AI-based methods in any subgroup. For boys regardless of age, the ICCs were 0.995 for VUNO and 0.994 for BoneXpert (z = 1.597, P = 0.110), while for girls, the ICCs were 0.994 and 0.995, respectively (z = -1.303, P = 0.193). The overall agreement with manual measurements was high for both VUNO and BoneXpert. In both boys and girls, the agreement remained consistent across different age groups. These findings indicate that both AI-based bone age assessment tools have a high degree of agreement with manual measurements across all age and gender groups, with no significant superiority of one method over the other.

Conclusion: Both BoneXpert and VUNO demonstrated high validity in assessing bone age, with no statistically significant differences between the two methods across gender or pubertal status groups. Notably, this study represents the first evaluation of both BoneXpert and VUNO for bone age assessment in Turkish children, highlighting their potential as reliable and clinically relevant tools for this population.

Clinical significance: Investigating the most suitable AI program for the Turkish population could be clinically significant.

Cardiothoracic surgery, including coronary artery bypass grafting, valve replacement, and transplantation, has considerably advanced, improving patient survival and outcomes. However, non-pulmonary postoperative complications remain a major concern, contributing to morbidity and mortality. These complications encompass cardiovascular events, vascular injuries, infections, and device-related issues that can severely impact recovery. Early diagnosis and timely intervention are crucial to mitigating risks and improving patient outcomes. Advanced imaging modalities such as computed tomography, magnetic resonance imaging, and echocardiography play a pivotal role in identifying and characterizing complications before clinical deterioration occurs. This review highlights the spectrum of acute non-pulmonary complications following cardiothoracic surgery, emphasizing the diagnostic value of imaging in guiding clinical decision-making. By improving the awareness of imaging findings associated with postoperative complications, radiologists and clinicians can facilitate early detection, enabling prompt surgical or medical interventions. A multidisciplinary approach that integrates imaging surveillance with clinical assessment is essential for optimizing patient care and reducing long-term morbidity.