British Journal of Radiology最新文献

{"title":"Quality assurance in lung cancer screening.","authors":"Adnan G Taib, Iain T H Au-Yong, Arjun Nair, Anand Devaraj, Yan Chen, David R Baldwin","doi":"10.1093/bjr/tqae229","DOIUrl":"https://doi.org/10.1093/bjr/tqae229","url":null,"abstract":"<p><p>The effectiveness of screening programmes is critically dependent on the accuracy of the screening test. Where this relies on clinical expertise, there is an imperative to assure that the level of expertise meets expected standards. In cancer screening involving images, the focus is on the reader. Auditing of results is fraught with difficulty because of the time taken to accumulate enough data with confirmed outcomes to identify underperformance before any harm is done. Late recognition can lead to the need for reanalysis and recall of screening participants with loss of confidence in the programme. External Quality Assurance (EQA) is a method that enables clinical expertise to be tested rapidly by using test datasets with confirmed clinical outcome. In the UK, the breast cancer screening programme has had EQA in place for over 30 years. This article describes the development of the first EQA process in lung cancer screening, using the experience gained from running the breast cancer EQA, and the proposed future developments.</p>","PeriodicalId":9306,"journal":{"name":"British Journal of Radiology","volume":" ","pages":""},"PeriodicalIF":1.8,"publicationDate":"2024-11-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142675228","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"The optimal energy level of virtual monochromatic imaging in Dual-energy CT arthrography of the wrist.","authors":"Bo Mi Chung, Guen Young Lee, Sujin Kim","doi":"10.1093/bjr/tqae238","DOIUrl":"https://doi.org/10.1093/bjr/tqae238","url":null,"abstract":"<p><strong>Objectives: </strong>To suggest an optimal energy level of virtual monochromatic images (VMIs) in dual-energy CT arthrography of the wrist.</p><p><strong>Methods: </strong>This retrospective study included 53 patients with wrist CT arthrography. Conventional polychromatic images and VMIs at four energy levels (40 to 70 keV at 10 keV intervals) were obtained. Image noise, signal-to-noise ratio (SNR), and contrast-to-noise ratio (CNR) were measured, and qualitative analysis of image quality and diagnostic confidence was performed. For each patient, an energy level with the best image quality was chosen by consensus. Comparisons of quantitative and qualitative parameters between VMI sets were performed.</p><p><strong>Results: </strong>The image noise of bone and muscle were increased with decreasing energy level (p < 0.001). The noise of contrast was highest on 60 keV VMI. SNR and CNR (between contrast and muscle) were increased with decreasing energy level and were markedly increased between 60 and 50 keV (p < 0.001). The 60 keV VMI demonstrated the highest image quality and diagnostic confidence, chosen as the best diagnostic image (n = 31/53). Given that the attenuation of the contrast material was low on the conventional image, the optimal energy level of the best VMI tended to be low.</p><p><strong>Conclusion: </strong>Wrist dual-energy CT arthrography with VMIs at 60 keV or less could improve image quality and diagnostic performance by increasing SNR and CNR in cases with low contrast attenuation.</p><p><strong>Advances in knowledge: </strong>Wrist dual-energy CT arthrography with VMIs at variable keV could be utilised to enhance SNR and CNR, thereby achieving diagnostic images of high quality.</p>","PeriodicalId":9306,"journal":{"name":"British Journal of Radiology","volume":" ","pages":""},"PeriodicalIF":1.8,"publicationDate":"2024-11-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142615164","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"DynaCT biliary reconstruction via a 3D C-arm cholangiography system: clinical application in hepatolithiasis.","authors":"Ya-Wen Cao, Dong-Qiao Chen, Jie-Long Lin, Zhao-Wei Ding, Pei-Heng Li, Rong-Qi Li, Yong-Qing Ye","doi":"10.1093/bjr/tqae237","DOIUrl":"https://doi.org/10.1093/bjr/tqae237","url":null,"abstract":"<p><strong>Objective: </strong>Dyna computed tomography (DynaCT) is an innovative clinical imaging tool used to obtain three-dimensional (3D) images of biliary structures via the Artis Zee DSA system (SIEMENS Company, Germany). DynaCT is a type of 3D cone beam computed tomography (CBCT) reconstruction produced from a two-dimensional (2D) cholangiography system by rotating the C-arm without moving the patient. The aim of this study was to evaluate the technical approach and application value of DynaCT to diagnosis hepatolithiasis and biliary stenosis.</p><p><strong>Methods: </strong>This was a retrospective single-centre series of 37 hepatolithiasis patients with tubes receiving one-step percutaneous transhepatic cholangioscopic lithotripsy (one-step PTCSL) between October 2021 and October 2022: twenty-one patients were guided by CT (CT group) and sixteen by DynaCT biliary reconstruction (DynaCT group). We compared DynaCT biliary reconstruction technology with computed tomography (CT) in the application of bile ducts.</p><p><strong>Results: </strong>DynaCT biliary reconstruction was successfully performed in 37 patients. Biliary stenosis, including anatomy, morphology, and size, was visualized via DynaCT. Compared with the CT group, the DynaCT group was characterized by significantly more target biliary branches with stones (92 vs. 48, P < 0.05), a higher percentage of secondary stenosis (75.76% vs. 24.24%, p < 0.05), a greater percentage of biliary infection (37.5% vs. 9.5%, P = 0.041), a shorter overall stone clearance time (26.38 ± 13.49 vs. 52.67 ± 30.10, P = 0.001), and a lower rate of reoperation for residual stones (25.00% vs. 66.67%, P = 0.012). DynaCT had a lower contrast agent (25.61 ± 5.13 vs. 42.69 ± 11.15, p < 0.05). However, DynaCT increased radiation exposure (38.12 ± 10.59 vs. 25.79 ± 4.76, p < 0.05). There were no significant differences between the two groups regarding the clearance ratio of the calculus or several postoperative complications.</p><p><strong>Conclusion: </strong>DynaCT for biliary reconstruction has the potential to be a powerful evaluation tool for one-step PTCSL surgery and could lead to new possibilities for hepatobiliary surgery.</p><p><strong>Advances in knowledge: </strong>DynaCT was used for the first time in patients with hepatolithiasis and biliary stenosis. Compared with CT, DynaCT for biliary reconstruction results in higher-quality 3D biliary, blood vessel and liver images. On the basis of the DynaCT biliary model, one-step PTCSL has the potential to improve the stone clearance ratio and shorten the stone clearance time and reoperation ratio.</p>","PeriodicalId":9306,"journal":{"name":"British Journal of Radiology","volume":" ","pages":""},"PeriodicalIF":1.8,"publicationDate":"2024-11-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142614797","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A Review of Applications of Photon-Counting Computed Tomography in Head and Neck Imaging.","authors":"Siddhant Dogra, Nitesh Shekhrajka, Gul Moonis","doi":"10.1093/bjr/tqae226","DOIUrl":"https://doi.org/10.1093/bjr/tqae226","url":null,"abstract":"<p><p>Photon-counting CT (PCCT), approved for clinical practice for over two years now, both improves on features of conventional energy-integrating detector (EID) CT and introduces new capabilities such as multienergy acquisition. PCCT is already transforming all domains of radiology, including head and neck imaging, and will become increasingly utilized in the approaching years. In this review, we first concisely explain the key physical principles distinguishing PCCT from EID-CT. We then discuss how the underlying physics leads to the novel features associated with PCCT, focusing on improved artifact reduction, spatial resolution, contrast-to-noise ratio, as well as multienergy acquisition and reduced contrast and radiation doses. Next, we review head and neck PCCT applications and comparison to EID-CT in dental imaging, sinus imaging, temporal bone, tumor imaging, and vascular imaging. Within the temporal bone applications, we explore normal anatomy, pathologic anatomy, and the appearance of protheses and implants. Representative imaging is provided to highlight differences between PCCT and EID-CT. Finally, we highlight areas of ongoing research in PCCT.</p>","PeriodicalId":9306,"journal":{"name":"British Journal of Radiology","volume":" ","pages":""},"PeriodicalIF":1.8,"publicationDate":"2024-11-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142614399","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Ultrasound S-detect system can improve diagnostic performance of less experienced radiologists in differentiating breast masses. A retrospective dual-center study.","authors":"Li-Wen Du, Hong-Li Liu, Meng-Jun Cai, Jia-Zhen Pan, Hai-Ling Zha, Chen-Lei Nie, Min-Jia Lin, Cui-Ying Li, Min Zong, Bo Zhang","doi":"10.1093/bjr/tqae233","DOIUrl":"https://doi.org/10.1093/bjr/tqae233","url":null,"abstract":"<p><strong>Objective: </strong>To compare the performance of radiologists when assisted by an S-detect system with that of radiologists or an S-detect system alone in diagnosing breast masses on US images in a dual-center setting.</p><p><strong>Methods: </strong>US images were retrospectively identified 296 breast masses (150 benign, 146 malignant) by investigators at two medical centers. Six radiologists from the two centers independently analyzed the US images and classified each mass into categories 2 to 5. The radiologists then re-reviewed the images with the assistance of the S-detect system. The diagnostic value of radiologists alone, S-detect system alone, and S-detect alone, and radiologists + S-detect were analyzed and compared.</p><p><strong>Results: </strong>Radiologists had significantly decreased the average false negative rate (FNR) for diagnosing breast masses using S-detect system (- 10.7%) (P < 0.001) and increased the area under the receiver operating characteristic curve (AUC) from 0.743 to 0.788 (P < 0.001). Seventy-seven out of 888 US images from six radiologists in this study were changed positively (from false negative to true positive or from false positive to true negative) with the S-detect, while 39 out of 888 US images were altered negatively.</p><p><strong>Conclusion: </strong>Radiologists had better performance for the diagnosis of malignant breast masses on US images with an S-detect system than without.</p><p><strong>Advances in knowledge: </strong>The study used a dual-center design and compared the performance of the radiologists alone, the S-detect alone, and the radiologists combined with the S-detect. The study reported an improvement in sensitivity and AUC particularly for low to intermediate-level radiologists, involved cases and radiologists from two different centers, and compared the diagnostic value of using S-detect system for masses of different sizes.</p>","PeriodicalId":9306,"journal":{"name":"British Journal of Radiology","volume":" ","pages":""},"PeriodicalIF":1.8,"publicationDate":"2024-11-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142615170","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Assessing the Performance of ChatGPT and Bard/Gemini Against Radiologists for PI-RADS Classification Based on Prostate Multiparametric MRI Text Reports.","authors":"Kang-Lung Lee, Dimitri A Kessler, Iztok Caglic, Yi-Hsin Kuo, Nadeem Shaida, Tristan Barrett","doi":"10.1093/bjr/tqae236","DOIUrl":"https://doi.org/10.1093/bjr/tqae236","url":null,"abstract":"<p><strong>Objectives: </strong>Large language models (LLMs) have shown potential for clinical applications. This study assesses their ability to assign PI-RADS categories based on clinical text reports.</p><p><strong>Methods: </strong>One hundred consecutive biopsy-naïve patients' multiparametric prostate MRI reports were independently classified by two uroradiologists, GPT-3.5, GPT-4, Bard, and Gemini. Original report classifications were considered definitive.</p><p><strong>Results: </strong>Out of 100 MRIs, 52 were originally reported as PI-RADS 1-2, 9 PI-RADS 3, 19 PI-RADS 4, and 20 PI-RADS 5. Radiologists demonstrated 95% and 90% accuracy, while GPT-3.5 and Bard both achieved 67%. Accuracy of the updated versions of LLMs increased to 83% (GTP-4) and 79% (Gemini), respectively. In low suspicion studies (PI-RADS 1-2), Bard and Gemini (F1: 0.94, 0.98, respectively) outperformed GPT-3.5 and GTP-4 (F1:0.77, 0.94, respectively), whereas for high probability MRIs (PI-RADS 4-5), GPT-3.5 and GTP-4 (F1: 0.95, 0.98, respectively) outperformed Bard and Gemini (F1: 0.71, 0.87, respectively). Bard assigned a non-existent PI-RADS 6 \"hallucination\" for two patients. Inter-reader agreements (Κ) between the original reports and the senior radiologist, junior radiologist, GPT-3.5, GTP-4, BARD, and Gemini were 0.93, 0.84, 0.65, 0.86, 0.57, and 0.81, respectively.</p><p><strong>Conclusions: </strong>Radiologists demonstrated high accuracy in PI-RADS classification based on text reports, while GPT-3.5 and Bard exhibited poor performance. GTP-4 and Gemini demonstrated improved performance compared to their predecessors.</p><p><strong>Advances in knowledge: </strong>This study highlights the limitations of LLMs in accurately classifying PI-RADS categories from clinical text reports. While the performance of LLMs has improved with newer versions, caution is warranted before integrating such technologies into clinical practice.</p>","PeriodicalId":9306,"journal":{"name":"British Journal of Radiology","volume":" ","pages":""},"PeriodicalIF":1.8,"publicationDate":"2024-11-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142614792","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Recurrence-Free Survival Prediction for Anal Squamous Cell Carcinoma After Chemoradiotherapy using Planning CT-based Radiomics Model.","authors":"Shanshan Tang, Kai Wang, David Hein, Gloria Lin, Nina N Sanford, Jing Wang","doi":"10.1093/bjr/tqae235","DOIUrl":"https://doi.org/10.1093/bjr/tqae235","url":null,"abstract":"<p><strong>Objectives: </strong>Approximately 30% of non-metastatic anal squamous cell carcinoma (ASCC) patients will experience recurrence after chemoradiotherapy (CRT), and currently available clinical variables are poor predictors of treatment response. We aimed to develop a model leveraging information extracted from radiation pretreatment planning CT to predict recurrence-free survival (RFS) in ASCC patients after CRT.</p><p><strong>Methods: </strong>Radiomics features were extracted from planning CT images of 96 ASCC patients. Following pre-feature selection, the optimal feature set was selected via step-forward feature selection with a multivariate Cox proportional hazard model. The RFS prediction was generated from a radiomics-clinical combined model based on an optimal feature set with five repeats of nested five-fold cross validation. The risk stratification ability of the proposed model was evaluated with Kaplan-Meier analysis.</p><p><strong>Results: </strong>Shape- and texture-based radiomics features significantly predicted RFS. Compared to a clinical-only model, radiomics-clinical combined model achieves better performance in the testing cohort with higher C-index (0.80 vs 0.73) and AUC (0.84 vs 0.78 for 1-year RFS, 0.84 vs 0.79 for 2-year RFS, and 0.85 vs 0.81 for 3-year RFS), leading to distinctive high- and low-risk of recurrence groups (p < 0.001).</p><p><strong>Conclusions: </strong>A treatment planning CT based radiomics and clinical combined model had improved prognostic performance in predicting RFS for ASCC patients treated with CRT as compared to a model using clinical features only.</p><p><strong>Advances in knowledge: </strong>The use of radiomics from planning CT is promising in assisting in personalized management in ASCC. The study outcomes support the role of planning CT-based radiomics as potential imaging biomarker.</p>","PeriodicalId":9306,"journal":{"name":"British Journal of Radiology","volume":" ","pages":""},"PeriodicalIF":1.8,"publicationDate":"2024-11-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142614818","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A framework for developing Generic Implant Safety Procedures (GISPs) for scanning patients with medical implants and devices in MRI.","authors":"Jonathan P Ashmore, Sarah J Prescott, John McLean, Daniel J Wilson, Geoff Charles-Edwards, Peter Wright, David Grainger, Gareth J Barker, Alexandra J Lipton, Rachel Watt, Deepa Gopalan, Mark R Radon","doi":"10.1093/bjr/tqae232","DOIUrl":"https://doi.org/10.1093/bjr/tqae232","url":null,"abstract":"<p><p>UK guidelines for MR safety recommend that MRI departments refer to the implant manufacturer for advice regarding the MRI safety of scanning patients with an implantable medical device prior to scanning [1]. This process of assuring safety can be time consuming, leading to delays and potential cancellations of a patient's MRI. Furthermore, at times the implant cannot be identified, or the implant manufacturers cannot provide up to date MRI safety information. The purpose of generic implant safety procedures (GISPs) is to define a process for managing patients with certain types of implants where the risk from scanning is low. This process incorporates scope for an evidence-based risk-benefit decision to scan some groups of patients under locally-approved conditions, without seeking to identify the exact make and model of the implant and subsequent assurance of MR safety from the implant manufacturer. This publication provides best practice recommendations from a multi-professional working group for the development of these procedures. It is supported by The Institute of Physics and Engineering in Medicine, The Society of Radiographers, The Royal College of Radiologists, The British institute of Radiology, The British Association of MR Radiographers, The International Society of Magnetic Resonance in Medicine British and Irish Chapter and the NHS Scotland MRI Physics Group.</p>","PeriodicalId":9306,"journal":{"name":"British Journal of Radiology","volume":" ","pages":""},"PeriodicalIF":1.8,"publicationDate":"2024-11-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142614263","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A generalized health index: automated thoracic CT-derived biomarkers predict life expectancy.","authors":"Cameron Beeche, Tong Yu, Jing Wang, David Wilson, Pengyu Chen, Emrah Duman, Jiantao Pu","doi":"10.1093/bjr/tqae234","DOIUrl":"https://doi.org/10.1093/bjr/tqae234","url":null,"abstract":"<p><strong>Objective: </strong>To identify image biomarkers associated with overall life expectancy from low-dose computed tomography and integrate them as an index for assessing an individual's health.</p><p><strong>Methods: </strong>Two categories of CT image features, body composition tissues and cardiopulmonary vasculature characteristics, were quantified from LDCT scans in the Pittsburgh Lung Screening Study cohort(n = 3,635). Cox proportional-hazards models identified significant image features which were integrated with subject demographics to predict the subject's overall hazard. Subjects were stratified using composite model predictions and feature-specific risk stratification thresholds. The model's performance was validated extensively, including 5-fold cross-validation on PLuSS baseline, PLuSS follow-up examinations, and the National Lung Screening Trial (NLST).</p><p><strong>Results: </strong>The composite model had significantly improved prognostic ability compared to the baseline model (p < 0.01) with AUCs of 0.774 (95% CI: 0.757-0.792) on PLuSS, 0.723 (95% CI: 0.703-0.744) on PLuSS follow-up, and 0.681 (95% CI: 0.651-0.710) on the NLST cohort. The identified high-risk stratum were several times more likely to die, with mortality rates of 79.34% on PLuSS, 76.47% on PLuSS follow-up, and 46.74% on NLST. Two cardiopulmonary structures (intrapulmonary artery vein ratio, intrapulmonary vein density) and two body composition tissues (SM density, bone density) identified high-risk patients.</p><p><strong>Conclusions: </strong>Body composition and pulmonary vasculatures are predictive of an individual's health risk; their integrations with subject demographics facilitate the assessment of an individual's overall health status or susceptibility to disease.</p><p><strong>Advances in knowledge: </strong>CT-computed body composition and vasculature biomarkers provide improved prognostic value. The integration of CT biomarkers and patient demographic information improves subject risk stratification.</p>","PeriodicalId":9306,"journal":{"name":"British Journal of Radiology","volume":" ","pages":""},"PeriodicalIF":1.8,"publicationDate":"2024-11-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142614279","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Refining MRI Protocols for Endometriosis: A Comparative Study of Abbreviated and Full MRI Sequences.","authors":"Arvin Arian, Nafise Karimi, Nasrin Ahmadinejad, Sina Azadnajafabad, Sina Delazar","doi":"10.1093/bjr/tqae230","DOIUrl":"https://doi.org/10.1093/bjr/tqae230","url":null,"abstract":"<p><strong>Objectives: </strong>Endometriosis is a significant cause of chronic abdominal pain and infertility in females, often overlooked due to its resemblance to other abdominopelvic pathologies. This study aims to compare the diagnostic performance and agreement rate between an abbreviated MRI protocol (aMRI) and a full MRI protocol (fMRI) for detecting pelvic endometriosis.</p><p><strong>Methods: </strong>We retrospectively analyzed 446 consecutive MRI exams, including both full (fMRI) and abbreviated (aMRI) protocols, performed for suspected pelvic endometriosis. An expert radiologist assessed the presence of endometriosis at 14 distinct anatomical sites. Each MRI protocol was interpreted in random order, with a minimum two-week interval between sessions to minimize recall bias. Agreement between the protocols was evaluated using kappa statistics.</p><p><strong>Results: </strong>The average age of the patients was 34.13 years. The highest incidences of endometriosis were found in the ovaries (88.8%) and the rectouterine pouch (65%). The MRI protocols demonstrated perfect agreement (kappa coefficient = 1) for the ovaries, bladder, uterus, and cesarean section scar. High agreement was also observed in the rectum and uterine ligaments (kappa coefficients of 0.98 and 0.97). Detection of malignant transformation in existing ovarian endometriomas showed substantial concordance with a kappa coefficient of 0.66.</p><p><strong>Conclusions: </strong>An abbreviated non-contrast MRI protocol exhibits diagnostic accuracy comparable to that of a comprehensive protocol in detecting pelvic endometriosis, with similar confidence and reproducibility.</p><p><strong>Advances in knowledge: </strong>This study demonstrates that an abbreviated MRI protocol is as effective as a full protocol in diagnosing pelvic endometriosis, potentially allowing for quicker, cost-effective imaging without compromising diagnostic accuracy.</p>","PeriodicalId":9306,"journal":{"name":"British Journal of Radiology","volume":" ","pages":""},"PeriodicalIF":1.8,"publicationDate":"2024-11-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142614991","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}