Frontiers in radiology最新文献

Interrupted aortic arch (IAA) is a rare congenital cardiovascular anomaly characterized by the absence of continuity between the ascending and descending aorta, often accompanied by congenital heart defects such as ventricular septal defects and patent ductus arteriosus. Accurate preoperative imaging is essential for surgical planning and patient management. This study aimed to compare the diagnostic accuracy of echocardiography and computed tomography angiography (CTA) in evaluating thoracic findings in patients with IAA. A retrospective analysis was conducted on 58 patients (median age: 18 days) diagnosed with IAA between September 2020 and January 2023 at the Heart Center, University Medical Center, Astana, Kazakhstan. Conventional echocardiography and multislice CTA were performed using standardized protocols. Sensitivity, specificity, and other diagnostic performance metrics were calculated. Statistical comparisons were made using McNemar's and Wilcoxon signed-rank tests, with p < 0.05 considered significant. Echocardiography correctly identified 91.4% of IAA cases, while CTA achieved 100% sensitivity and specificity. McNemar's test revealed a significant difference in diagnostic performance favoring CTA (p < 0.05). Measurements of the ascending aorta diameter showed no statistically significant difference between the two modalities (p = 0.09). IAA was predominantly type A (48.3%) and type B (46.6%), with hypoplastic ascending aorta identified in 34.5% of patients. Echocardiography remains a practical initial imaging modality for IAA, offering portability and cost-effectiveness. However, CTA demonstrated superior diagnostic accuracy and anatomical resolution, making it the preferred tool for detailed preoperative evaluation and surgical planning. Future studies with larger cohorts and additional modalities could further refine diagnostic strategies for IAA.

Background: Accurate targeting and lesion placement are critical in treating movement disorders with magnetic resonance-guided focused ultrasound (MRgFUS). Indirect atlas-based targeting often lacks precision. Direct anatomical targeting with 3T MRI offers a promising alternative. This report aims to refine MRgFUS thalamotomy by integrating advanced imaging and lesion conformality strategies.

Material and methods: Preoperative and postoperative white matter null (WMn) MR-imaging was employed for direct Vim detection. Essential anatomical landmarks are identified. Dual-lesion conformality was used to adapt to the spatial distribution of the Vim.

Results: Lesions of the Vim were identifiable using the postoperative WMn MRI sequence. The direct visualization of the Vim usually avoids extension into the internal capsule and the sensory thalamic nucleus. Sagittal imaging confirmed the dual-lesion conformational strategy which conforms to the antero-superior orientation of the Vim.

Conclusions: Direct Vim targeting for MRgFUS is feasible for individual cases with the use of WMnMPRAGE MRI sequences. The use of lesion conformality adapts well to the anatomical and spatial distribution of Vim. Further studies will be needed to confirm the safety profile of this approach and correlate with clinical outcomes.

Adrenal vein sampling (AVS) is the gold standard for subtyping primary aldosteronism (PA). However, through conventional AVS, unilateral PA may be misdiagnosed as bilateral PA. Compared with conventional AVS, segmental AVS with additional sampling in adrenal tributaries can detect aldosterone-producing adenomas (APAs) with higher sensitivity. Herein, we describe two cases wherein high aldosterone levels were not detected through initial segmental AVS but were identified in anomalous drainage veins during the second AVS session. In Case 1, computed tomography (CT) during left adrenal arteriovenography revealed a fine renal capsular vein connecting an adrenal nodule to the third lumbar vein. Sampling in this vein during the second AVS revealed high aldosterone levels. The surgical specimen showed the presence of an 11 mm APA. Furthermore, Case 2 presented with bilateral small adrenal nodules; bilateral renal capsular vein sampling was performed during the second AVS session. The samples from the renal capsular vein connected to the renal vein revealed considerably high aldosterone levels. Left adrenalectomy revealed the presence of a 6 mm aldosterone-producing nodule. These cases highlight the importance of anomalous drainage vein sampling, the limitation of conventional and segmental AVS in diagnosing PA, and the utility of CT during adrenal arteriovenography for estimating the drainage route.

Bladder cancer is a malignant tumour with a high morbidity and mortality rate in the world. Moreover, it is the most prevalent as well as commonly diagnosed in older individuals, with a median age of 73 years, and it has been reported that the most frequently seen histological type of bladder cancer was urothelial carcinoma. We present a unique case of a 44-year-old female with enteric-type adenocarcinoma, a rare and aggressive bladder cancer. Her symptoms included frequent micturition (Urination) and hematuria (blood in urine), at which point she was diagnosed with High-grade urothelial carcinoma. The malignancy worsened despite cycles of treatment requiring extensive surgery. After further tests, it was found that she had urothelial carcinoma with features of intestinal tissue (tissue of the intestine) and that the disease had infiltrated into nearby blood vessels and nerves. Radiation therapy was recommended to decrease the risk of local recurrence after surgery. The challenges in treating such a patient and the positive aspects this approach can give are highlighted in a case report.

Introduction: Chylous ascites, defined as the pathological accumulation of lymphatic fluid in the peritoneal cavity, presents significant challenges due to the lack of standardized treatment protocols. This study evaluates the dual diagnostic and therapeutic role of Lipiodol® lymphangiography in managing post-operative chylous ascites, with a focus on its potential to inform modern interventional strategies.

Materials and methods: A retrospective review was conducted of four patients treated for post-operative chylous ascites at our institution between 2017 and 2023. These patients, who developed refractory chylous ascites following oncological surgeries involving radical lymphadenectomy, underwent Lipiodol® lymphangiography. Diagnostic findings, therapeutic outcomes, and procedural details were analyzed.

Results: Lipiodol® lymphangiography demonstrated a dual function, providing precise anatomical localization of lymphatic leaks while facilitating therapeutic embolization due to its viscosity. All four patients achieved resolution of chylous ascites following lymphangiography alone, with a 100% success rate after the first attempt. No complications were reported within 30 days post-procedure, underscoring the safety of this minimally invasive technique.

Conclusions: Lipiodol® lymphangiography represents an effective diagnostic and therapeutic modality for post-operative chylous ascites, offering a minimally invasive alternative to traditional surgical interventions. By elucidating the pathway for both diagnosis and treatment, this study highlights its potential role in establishing standardized protocols for managing this complex condition.

Idiopathic Intracranial hypertension (IIH), also referred to as pseudotumor cerebri, is a term used to describe increased intracranial pressure in the absence of a known identifiable secondary cause. Despite advancements of neuroimaging techniques, imaging of the pathological underpinnings in the diagnosis of IIH has been limited. Although the causation of IIH has been ascribed to increased Cerebrospinal Fluid production and disordered drainage through the dural sinuses, new evidence shows that the glymphatic system which is an alternate pathway of drainage is likely to play a pivotal role. In this review, we address the pathophysiological underpinnings in the causation of IIH and discusses characteristic anatomical imaging findings on conventional MRI and explore the role of advanced imaging techniques.

Virtual autopsy, an advanced forensic technique, utilizes cutting-edge imaging technologies such as computed tomography (CT) and magnetic resonance imaging (MRI) to investigate the cause and manner of death without the need for physical dissection. By creating detailed, three-dimensional data of the entire body or specific areas of interest, these post-mortem imaging modalities provide a comprehensive, non-invasive approach to examining decedents. This article explores the historical development of virtual autopsy, its current applications in forensic medicine, and its promising future. It highlights the crucial roles of CT and MRI in forensic death investigations, while also addressing the challenges and limitations associated with these imaging techniques in post-mortem examinations.

Objective: This study aimed to determine the diagnostic precision of a deep learning algorithm for the classificaiton of non-contrast brain CT reports.

Methods: A total of 1,861 non-contrast brain CT reports were randomly selected, anonymized, and annotated for urgency level by two radiologists, with review by a senior radiologist. The data, encrypted and stored in Excel format, were securely maintained on a university cloud system. Using Python 3.8.16, the reports were classified into four urgency categories: emergency, not emergency but needs timely attention, clinically non-significant and normal. The dataset was split, with 800 reports used for training and 200 for validation. The DistilBERT model, featuring six transformer layers and 66 million trainable parameters, was employed for text classification. Training utilized the Adam optimizer with a learning rate of 2e-5, a batch size of 32, and a dropout rate of 0.1 to prevent overfitting. The model achieved a mean F1 score of 0.85 through 5-fold cross-validation, demonstrating strong performance in categorizing radiology reports.

Results: Of the 1,861 scans, 861 cases were identified as fit for study through the senior radiologist and self-hosted Label Studio interpretations. It was observed that the algorithm achieved a sensitivity of 91% and a specificity of 90% in the measurements made on the test data. The F1 score was measured as 0.89 for the best fold. The algorithm most successfully distinguished emergency results with positive predictive values that were unexpectedly lower than in previously reported studies. Beam hardening artifacts and excessive noise, compromising the quality of CT scan images, were significantly associated with decreased model performance.

Conclusion: The proposed deep learning algorithm demonstrated high diagnostic accuracy, sensitivity, and specificity in classifying non-contrast brain CT reports. These results indicate the feasibility of automated identification of critical cases, which may support workflow efficiency and timely patient management in radiology practice.