British Journal of Radiology最新文献

Objective: To evaluate the sensitivity, specificity, and overall diagnostic performance of X-ray imaging in detecting retained surgical foreign bodies (RSFBs) during and after elective surgical procedures.

Material and methods: Over six years, a total of 145 cases of surgical missed item events (SMIEs) were reported; in 69 (47.58%) cases, a diagnostic image was indicated. Statistical results and significant cases are presented.

Results: The mean age was 56.81 years, and 70.76% were females. General surgery accounted for the highest number of adverse events, with 28 cases (43.07%), while needles were the most frequently lost items, which is also reported in 28 cases (43.7%). The prevalence of the X-ray imaging to locate a foreign body was 46.5%, sensitivity 30%, specificity 100%, and accuracy 99.98%. Due to its low sensitivity, a negative X-ray cannot rule out the presence of an RSFB. A total of 14 (21.54%) complications were registered, and no deaths occurred.

Conclusion: X-rays are highly specific, when an item is detected, and it is truly present, but their low sensitivity means that a negative image cannot rule out a retained foreign body. Negative findings should not be considered definitive, particularly in high-risk cases.

Advances in knowledge: The study shows that while X-rays offer high specificity (100%) and accuracy (99.98%), their sensitivity remains low at 30%. X-rays are effective at confirming the presence of foreign bodies, but less reliable in ruling out their absence. The key takeaway here is the need for supplemental imaging modalities in cases where high suspicion of RSFBs is raised by a negative X-ray.

Clinicaltrials.gov: NCT04293536.

Objectives: This observational study aimed to define a standardized sonographic approach for evaluating the elementary lesions of the tendon-bone junction (TBJ) in insertional Achilles tendinopathy (IAT).

Methods: Using high-frequency transducers, we matched the histological microarchitecture and the anatomical features of the TBJ of the Achilles tendon in patients with a clinical diagnosis of IAT. Colour/power Doppler assessments have been performed as well.

Results: Fifty-eight patients, with a mean age of 54 years (54.50 ± 11.72) and a gender distribution of 32 males (55.17%) and 26 females (44.83%), were enrolled in this observational study. Five elementary lesions of IAT were sonographically defined: bone spur, calcified longitudinal fissuration, intra-tendinous bony formation, tendon-bone disjunction, and fibrocartilage hyperemia. Moreover, specific sonographic signs have been identified to differentiate bony spurs in the growing phase and end-stage.

Conclusions: Using high-frequency B-mode and high-sensitive Doppler imaging, detailed sonographic assessment of the TBJ can be performed in IAT patients. The aforementioned 5 elementary lesions can be considered as a standardized approach for prompt examination of this complex/anatomical region.

Advances in knowledge: Recent advances in ultrasound equipment allow for accurate assessment of the TBJ of the AT. The present observational study defined 5 elementary sonographic lesions of the IAT as bone spur, calcified longitudinal fissuration, intra-tendinous bony formation, tendon-bone disjunction, and fibrocartilage hyperemia. Pertinent ultrasound-guided procedures targeting the TBJ are also discussed.

Evaluating normal and pathological bone marrow (BM) remains a challenging task for radiologists. Magnetic resonance imaging (MRI) has demonstrated to be the most effective modality for BM assessment, offering superior accuracy over conventional X-ray and computed tomography (CT). However, the traditional morphological MRI approach, relying on T1-weighted and other sequences, may not be sufficient in fully characterizing BM pathology or providing predictive and monitoring capabilities in an era of quantitative and personalized medicine. This review categorizes BM imaging modalities into 3 conceptual stages: past-future, present-future, and future-future. The "past-future" includes well-established but underutilized MRI sequences in the field of BM assessment, such as DIXON, DWI, and PWI. The "present-future" encompasses recent advances such as AI integration for image acquisition and emerging CT modalities like dual energy CT (DECT). Finally, the "future-future" anticipates transformative technologies including photon-counting CT (PCCT), ultra-high field MRI (5T and 7T), MRI fingerprinting, radiomics, and advanced AI applications. Each stage highlights the evolving toolkit available to radiologists for accurate BM characterization, early detection, and effective monitoring. Embracing these innovations will empower radiologists to provide more precise, patient-specific care, shaping the future of BM imaging.

Objectives: To evaluate US radiologists' attitudes towards artificial intelligence (AI) in radiology, identify demographic factors influencing these perceptions, and analyse the potential challenges and opportunities AI integration presents in radiological practice.

Methods: A cross-sectional survey of 322 board-certified radiologists was conducted using Amazon Mechanical Turk (MTurk) and Qualtrics. The survey collected demographic data (age, gender, experience, and subspecialty) and assessed attitudes towards AI integration in radiology. Pearson's chi-square tests were used to evaluate correlations between demographic variables and perceptions of AI's impact, confidence in its role, and anticipated adoption timelines.

Results: The majority of radiologists (82.9%) indicated that AI would significantly impact radiology. Younger radiologists (<40 years) displayed higher optimism and greater familiarity with AI tools compared to their older counterparts. Statistical analysis revealed significant correlations between age and optimism (χ2 = 47.551, P < .001) and between gender and confidence in AI's role (χ2 = 21.982, P < .001). Subspecialty differences emerged, with 87.5% of emergency radiologists anticipating AI adoption within 3-5 years, whereas 26.3% of paediatric radiologists predicted adoption within 6-10 years. Notably, younger radiologists showed increased susceptibility to errors when evaluating misleading AI-generated outputs, underscoring the necessity for structured training programs.

Conclusions: The integration of AI in radiology holds transformative potential but poses challenges, including overreliance, varying familiarity levels, and subspecialty-specific disparities. Structured education and robust regulatory frameworks are critical to optimize AI's adoption and minimize associated risks.

Advances in knowledge: This study highlights significant demographic variations in radiologists' attitudes towards AI and underscores the importance of targeted training and interventions to support effective AI integration. These findings add to the existing research by emphasizing the necessity for structured AI training tailored to demographic and subspecialty needs.

Objectives: Characterization of thrombus is important for guiding treatment in chronic thromboembolic pulmonary hypertension (CTEPH). This study presents a novel scoring system for visual assessment of CTEPH on CT pulmonary angiography (CTPA), incorporating both disease location and extent to determine the impact on survival outcomes.

Methods: Patients with CTEPH were identified retrospectively from the Assessing the Spectrum of Pulmonary Hypertension Identified at a Referral Centre registry. The scoring system emphasizes disease based on their predominant location as central, segmental, and distal disease. Survival analysis was conducted using Cox-regression and Kaplan-Meier survival curves.

Results: A total of 208 patients with CTEPH were included (mean age 66 ± 13.6 years, 52.4% female). Mosaic perfusion and infarction were commonly seen in patients with distal disease (92% and 88%). Patients with central and distal disease had more severe pulmonary hemodynamics and lower gas transfer (TLCO) than patients with segmental disease. Central and distal disease showed similar survival, whereas survival was worse in central compared to segmental disease for all patients (P < .001), including those undergoing (P < .04) and not undergoing endarterectomy (P < .001). Central disease was an independent predictor of mortality in those not undergoing endarterectomy (hazard ratio 1.9, P < .01).

Conclusions: Our scoring system showed excellent interobserver agreement. Thromboembolic disease location was shown to be a predictor of mortality, with central disease independently associated with shorter survival in patients not undergoing pulmonary endarterectomy.

Advances in knowledge: This is a novel scoring system for characterizing CTEPH on CTPA, considering disease location and extent. It provides disease location as a predictor of survival, introducing a new framework for patient stratification and clinical decision-making.

Objectives: This study aimed to develop and validate a machine learning-based computed tomography (CT) radiomics method to preoperatively predict the presence of central lymph node metastasis (CLNM) in patients with papillary thyroid microcarcinoma (PTMC).

Methods: A total of 921 patients with histopathologically proven PTMC from 3 medical centres were included in this retrospective study and divided into training, internal validation, external test 1, and external test 2 sets. Radiomics features of thyroid tumours were extracted from CT images and selected for dimensional reduction. Five machine learning classifiers were applied, and the best classifier was selected to calculate radiomics scores (rad-scores). Then, the rad-scores and clinical factors were combined to construct a nomogram model.

Results: In the 4 sets, 35.18% (324/921) patients were CLNM+. The XGBoost classifier showed the best performance, with the highest average area under the curve (AUC) of 0.756 in the validation set. The nomogram model incorporating XGBoost-based rad-scores with age and sex showed better performance than the clinical model in the training [AUC: 0.847 (0.809-0.879) vs. 0.706 (0.660-0.748)], internal validation [AUC: 0.773 (0.682-0.847) vs. 0.671 (0.575-0.758)], external test 1 [AUC: 0.807 (0.757-0.852) vs. 0.639 (0.580-0.695)], and external test 2 [AUC: 0.746 (0.645-0.830) vs. 0.608 (0.502-0.707)] sets. Furthermore, the nomogram showed better clinical benefit than the clinical and radiomics models.

Conclusions: The nomogram model based on the XGBoost classifier exhibited favourable performance. This model provides a potential approach for the non-invasive diagnosis of CLNM in patients with PTMC.

Advances in knowledge: This study developed a potential surrogate of preoperative accurate evaluation of CLNM status, which is non-invasive and easy-to-use.

Objectives: By expressing radiation detriment in terms of disability-weighted life years (DALY) it is possible to quantify the balance between medical benefit and radiation detriment for medical exposures. This method is applied to a representative transgender population.

Methods: The lifetime DALY detriment with age at acute radiation exposure to a unit 1 Sv is calculated for a range of transgender combinations of organs and ages at transition, and the results are fitted to a simple model. When scaled by effective dose, the rates of change of the fits are equivalent to disability weights as used in the calculation of DALY.

Results: The radiation disability weights vary slightly with organ combinations and age at transition for transgender populations, but are generally less that the radiation disability weights established for males and females.

Conclusions: The radiation detriment to the transgender population from medical exposures is generally slightly less than that for male and female populations.

Advances in knowledge: In general, the ratios of benefit to detriment for transgender patients undergoing radiological procedures are large, and not significantly different from those for male and female patients.

Skeletal dysplasias constitute a heterogeneous assemblage of over 770 genetically determined disorders. The 2023 revision of the classification of Genetic Skeletal Disorders represents a seminal advancement, integrating radiologic phenotypes with molecular and biochemical information to accommodate the expanding complexity of skeletal pathology. Radiologists remain indispensable in elucidating these conditions, as imaging phenotypes continue to underpin the delineation of these disorders. This review discusses the intricate radiologic manifestations of skeletal dysplasias within the framework of the current classification, advocating for the adoption of a structured radiological reporting.