British Journal of Radiology最新文献

Objectives: To evaluate the clinical utility of Node-Reporting and Data System (Node-RADS) 1.0 in assessing axillary lymph node (ALN) on breast MRI.

Methods: This retrospective study included women with clinical T1-T2 stage breast cancer who underwent surgery between April 2014 and March 2023. MRI-ALN status was first evaluated using routine clinical diagnostic criteria. Node-RADS scores were subsequently assigned based on preoperative MRI after a two-week interval. The optimal cut-off was determined using the Youden index. Diagnostic performance was compared for assessing ALN metastasis (ALNM) and pathological ALN (pALN) burden. In the secondary analysis, differences in imaging features were further evaluated in patients with Node-RADS < 3.

Results: The optimal cut-off for diagnosing ALNM was Node-RADS >1. Compared with MRI-ALN status, Node-RADS score demonstrated lower sensitivity (56% vs. 71%, p < 0.01), but comparable specificity (92% vs. 85%, p = 0.16). For assessing pALN burden, Node-RADS > 2 was the optimal cut-off with lower sensitivity (55% vs. 77%, p < 0.01) but higher specificity (82% vs. 62%, p < 0.01). In the secondary analysis, patients with ALNM showed significant differences in cortical morphology and the suspicious breast-side lymph node sign.

Conclusions: Node-RADS 1.0 showed lower sensitivity than conventional MRI diagnosis in assessing ALNM but demonstrated good specificity in evaluating ALNM and pALN burden.

Advances in knowledge: Node-RADS 1.0 showed lower sensitivity than conventional MRI diagnosis in assessing ALNM. The potential value of cortical morphology and the suspicious breast-side lymph node sign in improving the sensitivity of Node-RADS 1.0 warrant further investigation.

Congenital bronchopulmonary malinosculations encompass a spectrum of disorders characterized by anomalous connections among the three components in the lung-airways, parenchyma, and vessels. This review describes these anomalies using a simplified systematic approach to facilitate understanding and diagnosis. The classification framework, based on the presence or absence of arterial, venous, and bronchial anomalies, organizes malinosculations into seven groups. Cross sectional imaging techniques such as CT angiography plays a critical role in delineating anatomical abnormalities, enabling precise identification of malformed components. This systematic approach aids in identifying and managing these complex congenital anomalies, improving diagnostic accuracy and treatment planning.

Objectives: Previous findings reported increased toxicity of FLASH radiotherapy (FLASH) delivered under supplemental oxygen but failed to quantify the change in magnitude of the FLASH sparing effect. This study investigated the impact of oxygen breathing on normal tissue complication probability (NTCP) following FLASH and conventional radiotherapy (CONV) using murine models of acute gastrointestinal and skin toxicity.

Methods: Tumor-free C57BL/6 and BALB/c mice received whole-abdominal or skin irradiation, respectively, using either CONV or FLASH. Dose escalation was performed under air- and oxygen-breathing in both models to determine NTCP curves. The FLASH dose modifying factor (DMF) was derived as the dose ratio at 50% NTCP. Changes in tissue oxygenation, going from air- to oxygen-breathing, were measured in vivo using oxygen sensing by phosphorescence quenching.

Results: Abdominal irradiation under air breathing showed a significant FLASH sparing effect, with a mean DMF of 1.14. This effect was abolished under oxygen breathing, with a mean DMF reduced to 1.00. In contrast, skin irradiation under air breathing demonstrated a strong FLASH sparing effect, with a mean DMF of 1.42, which was largely preserved under oxygen breathing (mean DMF = 1.40). Oxygen breathing markedly increased tissue oxygenation in both the intestine and skin.

Conclusions: Maintaining of the FLASH sparing effect under increased oxygenation is tissue dependent. Our findings indicate potential difference in CONV and FLASH oxygen enhancement ratio (OER) curves.

Advances in knowledge: By conducting dose escalation experiments in animal models we provided first quantification of change in magnitude of FLASH sparing effect under increased tissue oxygenation.

Malignant pleural mesothelioma (PM) is the most common primary tumour of the pleura. Accurate staging is essential for treatment selection and prognostication. The 9th edition of the TNM classification introduces validated, imaging-based updates to tumour (T), node (N), and metastasis (M) staging. This article explores the scientific rationale and clinical utility of TNM 9, with a focus on imaging techniques, automated tumour volume assessment, and future developments in imaging and artificial intelligence.

Objectives: The purpose of this study was to compare the actual bladder capacity of children undergoing voiding cystourethrogram (VCUG) with existing formula-derived estimates and to describe any adverse effects of bladder overdistention during VCUG.

Methods: This retrospective study involved review of 884 consecutive VCUG performed over 3 years. Cases with underlying conditions that could artificially increase bladder capacity, such as neurogenic bladders or vesicoureteral reflux, were excluded.

Results: Included were 440 normal VCUG procedures. Bladder volumes exceeded the expected bladder capacity set by the American Academy of Pediatrics (AAP) and American College of Radiology in 284 VCUG (65%). Of 261 VCUG performed on children <2 years of age, 164 (63%) VCUG exceeded the expected capacity. In the 2-14-year-old age group, 113 (68%) of the 165 VCUG performed exceeded the expected bladder capacity. Among the 14 VCUG performed on children >14 years of age, seven (50%) exceeded the bladder capacity. No adverse effects were found after the VCUG in the 32 VCUG (7.3%) requiring a contrast volume of more than two times the AAP estimates and in the 22 VCUG studies (5%) requiring a contrast volume of more than three times the AAP estimates.

Conclusion: This study suggests that current guidelines often underestimate bladder capacity, and exceeding the expected bladder capacity appears to be reasonably safe without the occurrence of complications.

Advances in knowledge: Current AAP guidelines often underestimate the capacity of the urinary bladder. Exceeding the expected bladder capacity appears to be reasonably safe.

The evidence base supporting the use of thoracic ultrasound to assess the lung parenchyma has expanded and consolidated itself significantly within the last decade. Thoracic ultrasound for lung parenchyma assessment is now finding its way into statements and clinical practice guidelines for several conditions in various settings. Since assessment of patients with possible chest disease is a very common clinical scenario, knowledge of the various types of chest imaging is essential for any physician. The most common indication for thoracic ultrasound for lung parenchymal assessment is for screening and diagnostic purposes. Several new studies have however demonstrated a possible large potential for using thoracic lung ultrasound to monitor lung diseases. The recent COVID-19 pandemic has increased the scope of lung parenchymal ultrasound, from diagnosis to monitoring of the disease. Deep learning of contrast enhances thoracic ultrasound to aid diagnosis is a new developing area. Despite increasing use of thoracic ultrasound in respiratory medicine, a consensus on assessment of competencies, and education is lacking. The aim of this review is to provide the reader with a focus overview of the current use and diagnostic limitation of thoracic ultrasound for assessment of the lung parenchyma, and future development.

Objectives: To establish a 3D V-Net-based segmentation model for adrenal glands on abdominal CT images and validate its performance in multicenter datasets, including chest CT images.

Methods: CT images of adrenal glands were retrospectively collected for the training of the adrenal segmentation model. Abdominal CT scans with normal and abnormal adrenal glands (N = 5660) were recruited as the model development cohort and were split into training, internal validation, and internal test sets for the development of the segmentation model. Two groups of health screening subjects were included for model validation: one from the same institution (N = 6126, validation cohort 1) and one from an outside institution (N = 931, validation cohort 2). Their chest CT images were used for model validation. The Dice similarity coefficient (DSC) was used to evaluate the efficacy of the model.

Results: The DSC of the test set for left and right adrenal segmentation were 0.920 (0.890-0.930) and 0.910 (0.890-0.930), respectively. In the validation cohorts, the DSC values were 0.816 (0.744-0.866) for the left adrenal gland and 0.819 (0.743-0.865) for the right adrenal gland in validation cohort 1, and 0.752 (0.666-0.820) for the left adrenal gland and 0.747 (0.673-0.812) for the right adrenal gland in validation cohort 2.

Conclusions: The 3D V-Net-based adrenal segmentation model achieves considerable segmentation efficacy and demonstrates generalizability from abdominal CT to chest CT, making it suitable for use in CT images with various scanning protocols.

Advances in knowledge: The study developed a deep learning model using 3D V-Net for the segmentation of adrenal glands on CT images, achieving good performance of normal and abnormal glands in validation cohorts with different scanning protocols and from multiple institutions, demonstrating its potential as a "flagging" system aiding diagnosis.

Objectives: This study evaluates the effectiveness of virtual reality enhanced simulation in training medical students for procedural proficiency. It emphasises gender disparities in skill acquisition and confidence-building. Additionally, a cross-training component assesses skill transferability between different virtual interventional radiology procedures.

Methods: 20 medical students were randomised into 2 groups (n = 10 each), training on an advanced virtual reality simulator for interventional radiology. After 5 sessions on their primary case, participants switched cases for a sixth cross-training session. Performance was assessed through virtual fluoroscopy time. Pre- and post-training questions evaluated skill development, confidence levels, and career perceptions.

Results: Virtual fluoroscopy times decreased significantly over 5 sessions, with a mean reduction of 66% (23.85 to 8.06 minutes, p = 0.0023), indicating improved procedural efficiency. Cross-training demonstrated effective skill transfer, with virtual fluoroscopy times approximately 50% shorter compared to the initial training of the alternate group (p = 0.029, n = 10; p = 0.035, n = 8). Female participants (n = 11) reported lower confidence levels in in self-assessed manual dexterity (p = 0.019) but showed comparable or superior performance improvements to males (n = 9) by the end of training.

Conclusion: Simulation effectively enhances procedural expertise and skill adaptability in a virtual environment. Gender-specific findings highlight the need for tailored training strategies to address confidence gaps and support diversity in Interventional Radiology.

Advances in knowledge: Cross-training enhances skill transferability across different interventional radiology procedures. Despite gender-specific differences in perceptions of manual dexterity, performance between genders remains comparable.

Enhancing procedural proficiency in interventional radiology: A Prospective Observational Study on Cross-Training and Exploratory Gender Perspectives in Simulator-Based Education.

Purpose: This study evaluated the diagnostic accuracy of three ultrasound-based parameters-median nerve cross-sectional area (CSA), elasticity (E value), and blood flow pixel ratio (BFPR)-in grading carpal tunnel syndrome (CTS) severity. These parameters were assessed using high-frequency ultrasound, shear wave elastography (SWE), and superb microvascular imaging (SMI), with nerve conduction studies (NCS) as the reference standard.

Methods: A prospective study conducted between April 2024 and January 2025 included 128 patients with suspected CTS and 25 healthy controls, totaling 223 median nerves. CTS severity was categorized as mild, moderate, or severe based on NCS results.

Results: CSA increased from 10.05 mm2 in controls to 17.35 mm2 in severe CTS, E value rose from 42.35 kPa to 128.39 kPa, and BFPR increased from 3.99% to 19.76%. BFPR had the highest sensitivity for detecting mild CTS (cutoff 5.9%). Significant correlations (r > 0.78, p < 0.0001) were found among CSA, E value, and BFPR. ROC analysis showed excellent diagnostic accuracy with AUC values of 0.90-0.97 for distinguishing controls from CTS patients and 0.93-0.95 for differentiating mild from moderate-to-severe CTS.

Conclusion: Multiparametric ultrasound, particularly BFPR via SMI, provides a reliable, non-invasive alternative to NCS for early CTS detection and severity grading, with potential for standardizing diagnostic guidelines.

Advancement in knowledge: This study improves ultrasound-based CTS diagnosis by integrating CSA, E value, and BFPR, offering an effective method for early detection and severity grading. BFPR, especially via SMI, demonstrates high sensitivity for mild CTS and could standardize diagnostic approaches.

Objectives: This study evaluated 3 LLM chatbots (GPT-3.5-turbo, GPT-4-turbo, and GPT-4o) on their effectiveness in supporting patient education by answering common patient questions for CT, MRI, and DSA informed consent, assessing their accuracy and clarity.

Methods: Two radiologists formulated 90 questions categorized as general, clinical, or technical. Each LLM answered every question 5×. Radiologists then rated the responses for medical accuracy and clarity, while medical physicists assessed technical accuracy using a Likert scale. Semantic similarity was analyzed with SBERT and cosine similarity.

Results: Ratings improved with newer model versions. Linear mixed-effects models revealed that GPT-4 models were rated significantly higher than GPT-3.5 (P < .001) by both physicians and physicists. However, physicians' ratings for GPT-4 models showed a significant performance decrease for complex modalities like DSA and MRI (P < .01), a pattern not observed in physicists' ratings. SBERT analysis revealed high internal consistency across all models. SBERT analysis revealed high internal consistency across all models.

Conclusion: Variability in ratings revealed that while models effectively handled general and technical questions, they struggled with contextually complex medical inquiries requiring personalized responses and nuanced understanding. Statistical analysis confirms that while newer models are superior, their performance is modality-dependent and perceived differently by clinical and technical experts.

Advances in knowledge: This study evaluates the potential of LLMs to enhance informed consent in radiology, highlighting strengths in general and technical questions while noting limitations with complex clinical inquiries, with performance varying significantly by model type and imaging modality.