Abdominal Radiology最新文献

{"title":"Factors influencing diagnostic yield in ultrasound-guided omental biopsies: insights from a retrospective study.","authors":"Ali Dablan, Osman Nuri Bayrak, İlhan Nahit Mutlu, Hamit Yücel Barut, Elife Akgün, Sidar Bağbudar, Özgür Kılıçkesmez","doi":"10.1007/s00261-025-04797-z","DOIUrl":"https://doi.org/10.1007/s00261-025-04797-z","url":null,"abstract":"<p><strong>Purpose: </strong>To evaluate the safety, diagnostic accuracy, and factors influencing the diagnostic yield of ultrasound (US)-guided omental biopsies.</p><p><strong>Materials and methods: </strong>This retrospective study included 109 patients who underwent US-guided omental biopsies between June 2020 and June 2024. Pre-biopsy diagnostic images (CT, MRI, or [18 F]FDG PET/CT) were reviewed. Diagnostic accuracy, sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), and adverse events were evaluated. Surgical or clinical diagnoses with follow-up served as the diagnostic reference standard. Associations between diagnostic yield and findings on pre-biopsy imaging and biopsy US were explored.</p><p><strong>Results: </strong>The study achieved a technical success rate of 100%. Initial biopsy results showed a sensitivity of 82.6%, specificity of 100%, PPV of 100%, NPV of 60.5%, and diagnostic accuracy of 86.2%. The pre-biopsy imaging modality was not related to diagnostic accuracy. Ascites interposition on the puncture route was significantly higher in patients without diagnostic accuracy (73.3% vs. 30.9%, p = 0.002). Deeper lesions exhibited lower diagnostic accuracy (p = 0.003). No major or minor complications were associated with the biopsies.</p><p><strong>Conclusion: </strong>Percutaneous omental biopsy is an effective and safe method for evaluating omental abnormalities. Depth from the needle entry site and the presence of ascites along the puncture route were identified as factors affecting diagnostic accuracy. The choice of imaging modality did not impact diagnostic outcomes, highlighting the importance of lesion-specific factors in the planning of biopsies.</p>","PeriodicalId":7126,"journal":{"name":"Abdominal Radiology","volume":" ","pages":""},"PeriodicalIF":2.3,"publicationDate":"2025-01-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143035729","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Enhanced accuracy and stability in automated intra-pancreatic fat deposition monitoring of type 2 diabetes mellitus using Dixon MRI and deep learning.","authors":"Zhongxian Pan, Qiuyi Chen, Haiwei Lin, Wensheng Huang, Junfeng Li, Fanqi Meng, Zhangnan Zhong, Wenxi Liu, Zhujing Li, Haodong Qin, Bingsheng Huang, Yueyao Chen","doi":"10.1007/s00261-025-04804-3","DOIUrl":"https://doi.org/10.1007/s00261-025-04804-3","url":null,"abstract":"<p><strong>Purpose: </strong>Intra-pancreatic fat deposition (IPFD) is closely associated with the onset and progression of type 2 diabetes mellitus (T2DM). We aimed to develop an accurate and automated method for assessing IPFD on multi-echo Dixon MRI.</p><p><strong>Materials and methods: </strong>In this retrospective study, 534 patients from two centers who underwent upper abdomen MRI and completed multi-echo and double-echo Dixon MRI were included. A pancreatic segmentation model was trained on double-echo Dixon water images using nnU-Net. Predicted masks were registered to the proton density fat fraction (PDFF) maps of the multi-echo Dixon sequence. Deep semantic segmentation feature-based radiomics (DSFR) and radiomics features were separately extracted on the PDFF maps and modeled using the support vector machine method with 5-fold cross-validation. The first deep learning radiomics (DLR) model was constructed to distinguish T2DM from non-diabetes and pre-diabetes by averaging the output scores of the DSFR and radiomics models. The second DLR model was then developed to distinguish pre-diabetes from non-diabetes. Two radiologist models were constructed based on the mean PDFF of three pancreatic regions of interest.</p><p><strong>Results: </strong>The mean Dice similarity coefficient for pancreas segmentation was 0.958 in the total test cohort. The AUCs of the DLR and two radiologist models in distinguishing T2DM from non-diabetes and pre-diabetes were 0.868, 0.760, and 0.782 in the training cohort, and 0.741, 0.724, and 0.653 in the external test cohort, respectively. For distinguishing pre-diabetes from non-diabetes, the AUCs were 0.881, 0.688, and 0.688 in the training cohort, which included data combined from both centers. Testing was not conducted due to limited pre-diabetic patients. Intraclass correlation coefficients between radiologists' pancreatic PDFF measurements were 0.800 and 0.699 at two centers, suggesting good and moderate reproducibility, respectively.</p><p><strong>Conclusion: </strong>The DLR model demonstrated superior performance over radiologists, providing a more efficient, accurate and stable method for monitoring IPFD and predicting the risk of T2DM and pre-diabetes. This enables IPFD assessment to potentially serve as an early biomarker for T2DM, providing richer clinical information for disease progression and management.</p>","PeriodicalId":7126,"journal":{"name":"Abdominal Radiology","volume":" ","pages":""},"PeriodicalIF":2.3,"publicationDate":"2025-01-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142998363","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Radiomics for prediction of perineural invasion in colorectal cancer: a systematic review and meta-analysis.","authors":"Ning Tang, Shicen Pan, Qirong Zhang, Jian Zhou, Zhiwei Zuo, Rui Jiang, Jinping Sheng","doi":"10.1007/s00261-024-04713-x","DOIUrl":"https://doi.org/10.1007/s00261-024-04713-x","url":null,"abstract":"<p><strong>Background: </strong>Perineural invasion (PNI) in colorectal cancer (CRC) is a significant prognostic factor associated with poor outcomes. Radiomics, which involves extracting quantitative features from medical imaging, has emerged as a potential tool for predicting PNI. This systematic review and meta-analysis aimed to evaluate the diagnostic accuracy of radiomics models in predicting PNI in CRC.</p><p><strong>Methods: </strong>A comprehensive literature search was conducted across PubMed, Embase, and Web of Science for studies published up to July 28, 2024. Inclusion criteria focused on studies using radiomics models to predict PNI in CRC with sufficient data to construct diagnostic accuracy metrics. The quality of the included studies was assessed using QUADAS-2 and METRICS tools. Pooled estimates of sensitivity, specificity, and area under the curve (AUC) were calculated. Subgroup analyses were performed based on imaging modalities, segmentation methods, and other variables.</p><p><strong>Results: </strong>Twelve studies comprising 2853 patients were included in the systematic review, with ten studies contributing to the meta-analysis. The pooled sensitivity and specificity for radiomics models in predicting PNI were 0.74 (95% CI: 0.63-0.82) and 0.85 (95% CI: 0.79-0.90), respectively, in the training cohorts. In the validation cohorts, the sensitivity was 0.65 (95% CI: 0.57-0.72), and specificity was 0.85 (95% CI: 0.81-0.89). The AUC was 0.87 (95% CI: 0.63-0.82) for the training cohorts and 0.84 (95% CI: 0.81-0.87) for the validation cohorts, indicating good diagnostic accuracy. The METRICS scores for the included studies ranged from 65.8 to 85.1%, with an overall average score of 67.25%, reflecting good methodological quality. However, significant heterogeneity was observed across studies, particularly in sensitivity and specificity estimates.</p><p><strong>Conclusion: </strong>Radiomics models show promise as a non-invasive tool for predicting PNI in CRC, with moderate to good diagnostic accuracy. However, the current study's limitations, including reliance on retrospective data, geographic concentration in China, and methodological variability, suggest that further research is needed. Future studies should focus on prospective designs, standardization of methodologies, and the integration of advanced machine-learning techniques to improve the clinical applicability and reliability of radiomics models in CRC management.</p>","PeriodicalId":7126,"journal":{"name":"Abdominal Radiology","volume":" ","pages":""},"PeriodicalIF":2.3,"publicationDate":"2025-01-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142998381","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Differentiation of intrapancreatic accessory spleen from pancreatic neuroendocrine tumor using MRI R2.","authors":"Jun Gu Kang, Jae Hyon Park, Mi-Suk Park, Kyunghwa Han, Hee Seung Lee, Hyun Kyung Yang","doi":"10.1007/s00261-024-04758-y","DOIUrl":"https://doi.org/10.1007/s00261-024-04758-y","url":null,"abstract":"<p><strong>Purpose: </strong>To evaluate the performance of R2* in distinguishing intrapancreatic accessory spleens (IPASs) from pancreatic neuroendocrine tumors (PNETs).</p><p><strong>Methods: </strong>Two radiologists (R1 and R2) retrospectively reviewed the MRIs of 20 IPAS and 20 PNET patients. IPASs were diagnosed with uptake on 99mTc labeled heat-damaged red blood cell scintigraphy or characteristic findings on CT/MRI and ≥ 12 month-long-stability. PNETs were histopathologically diagnosed with resection. Using McNemar test, sensitivities and specificities of the diagnostic criterion based on R2* mass-to-spleen ratio (MSR) were compared with those of the other criteria using contrast-enhanced (CE) MRI and apparent diffusion coefficient (ADC) MSR.</p><p><strong>Results: </strong>The study included 40 patients (median age, 54; interquartile range, 43-65; 24 men, 16 women). IPASs exhibited spleen-isointensity on T2WI, late arterial and portal phases, and diffusion-weighted images more frequently than PNETs (p <.05). ADC MSRs were lower (p <.001) and R2* MSRs were higher (p <.001) in IPASs compared to PNETs. For R1, sensitivity and specificity were 45.0% and 100.0% for criterion 1 (spleen-isointensity on CE-MRI); 45.0% and 85.0% for criterion 2 (ADC MSR ≤ 1.08); 90.0% and 95.0% for criterion 3 (0.9 ≤ R2* MSR ≤ 1.7). For R2, 75.0% and 100.0%; 45.0% and 90.0%; 90.0% and 100.0%. Criterion 3 showed higher sensitivity than criterion 1 for R1 (p =.004), and criterion 2 for R1 and R2 (p =.012). There was no difference in specificity.</p><p><strong>Conclusion: </strong>For differentiating IPAS from PNET, R2* showed higher sensitivity than, and similar specificity to CE-MRI and ADC.</p>","PeriodicalId":7126,"journal":{"name":"Abdominal Radiology","volume":" ","pages":""},"PeriodicalIF":2.3,"publicationDate":"2025-01-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142998361","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Inter-reader reliability of Ovarian-Adnexal Reporting and Data System US: a systematic review and meta-analysis.","authors":"Sang Min Bae, Dong Hwan Kim, Ji Hun Kang","doi":"10.1007/s00261-025-04813-2","DOIUrl":"https://doi.org/10.1007/s00261-025-04813-2","url":null,"abstract":"<p><strong>Purpose: </strong>Ovarian-Adnexal Reporting and Data System (O-RADS) US provides a standardized lexicon for ovarian and adnexal lesions, facilitating risk stratification based on morphological features for malignancy assessment, which is essential for proper management. However, systematic determination of inter-reader reliability in O-RADS US categorization remains unexplored. This study aimed to systematically determine the inter-reader reliability of O-RADS US categorization and identify the factors that affect it.</p><p><strong>Methods: </strong>Original articles reporting the inter-reader reliability of O-RADS US in lesion categorization were identified in the MEDLINE, EMBASE, and Web of Science databases from January 2018 to December 2023. DerSimonian-Laird random-effects models were used to determine the meta-analytic pooled inter-reader reliability of the O-RADS US categorization. Subgroup meta-regression analysis was performed to identify the factors causing study heterogeneity.</p><p><strong>Results: </strong>Fourteen original articles with 5139 ovarian and adnexal lesions were included. The inter-reader reliability of O-RADS US in lesion categorization ranged from 0.71 to 0.99, with a meta-analytic pooled estimate of 0.83 (95% CI, 0.78-0.88), indicating almost perfect reliability. Substantial study heterogeneity was observed in the inter-reader reliability of the O-RADS US categorization (I² = 96.9). In subgroup meta-regression analysis, reader experience was the only factor associated with study heterogeneity. Pooled inter-reader reliability of the O-RADS US categorization was higher in studies with all experienced readers (0.86; 95% CI, 0.81-0.91) compared to those with multiple readers including trainees (0.74; 95% CI, 0.70-0.78; P = 0.009). The inter-reader reliability of US descriptors ranged from 0.39 to 0.97, with ascites and peritoneal nodules showing almost perfect reliability (0.79- 0.97).</p><p><strong>Conclusion: </strong>The O-RADS US risk stratification system demonstrated almost perfect inter-reader reliability in lesion categorization. Our results highlight the importance of targeted training and descriptor simplification to improve inter-reader reliability and clinical adoption.</p>","PeriodicalId":7126,"journal":{"name":"Abdominal Radiology","volume":" ","pages":""},"PeriodicalIF":2.3,"publicationDate":"2025-01-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142998365","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"CT-based machine learning radiomics predicts Ki-67 expression level and its relationship with overall survival in resectable pancreatic ductal adenocarcinoma.","authors":"Jiahao Chen, Zhuangxuan Ma, Yamin Xu, Jieqiong Ge, Hongfei Yao, Chunjing Li, Xiao Hu, Yunlong Pu, Ming Li, Chongyi Jiang","doi":"10.1007/s00261-025-04798-y","DOIUrl":"https://doi.org/10.1007/s00261-025-04798-y","url":null,"abstract":"<p><strong>Background: </strong>The prognostic prediction of pancreatic ductal adenocarcinoma (PDAC) remains challenging. This study aimed to develop a radiomics model to predict Ki-67 expression status in PDAC patients using radiomics features from dual-phase enhanced CT, and integrated clinical characteristics to create a radiomics-clinical nomogram for prognostic prediction.</p><p><strong>Methods: </strong>In this retrospective study, data were collected from 124 PDAC patients treated surgically at a single center, from January 2017 to March 2023. Patients were categorized according to the Ki-67 expression rate. Radiomics features were extracted from arterial and portal venous phase CT images using 3D Slicer v5.0.3. A radiomics model was formulated and validated to predict the Ki-67 expression, and a nomogram combining clinical indicators and the radiomics model was developed to predict 1, 2 and 3 year overall survival (OS).</p><p><strong>Results: </strong>The optimal Ki-67 expression rate cutoff was identified as 50%, with significant OS differences. The developed radiomics model showed good predictive ability with area under the curves of 0.806 and 0.801 in the training and validation groups, respectively. High radiomics score, elevated carbohydrate antigen 19-9 (CA19-9), and receipt of adjuvant chemotherapy were identified as independent prognostic factors for OS. The radiomics-clinical nomogram accurately predicted 1, 2 and 3 year OS in PDAC patients.</p><p><strong>Conclusions: </strong>The radiomics-clinical nomogram provides a non-invasive and efficient method for predicting Ki-67 expression and overall survival in PDAC patients, which could potentially guide clinical decision-making and improve patient outcomes.</p>","PeriodicalId":7126,"journal":{"name":"Abdominal Radiology","volume":" ","pages":""},"PeriodicalIF":2.3,"publicationDate":"2025-01-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142998260","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Multi-parametric MRI combined with radiomics for the diagnosis and grading of endometrial fibrosis.","authors":"Huanhuan Wang, Li Zhu, Hui Zhu, Jie Meng, Huanhuan Liang, Danyan Li, Yali Hu, Zhengyang Zhou","doi":"10.1007/s00261-024-04785-9","DOIUrl":"https://doi.org/10.1007/s00261-024-04785-9","url":null,"abstract":"<p><strong>Purpose: </strong>To evaluate the application of multi-parametric MRI (MP-MRI) combined with radiomics in diagnosing and grading endometrial fibrosis (EF).</p><p><strong>Methods: </strong>A total of 74 patients with severe endometrial fibrosis (SEF), 41 patients with mild to moderate fibrosis (MMEF) confirmed by hysteroscopy, and 40 healthy women of reproductive age were prospectively enrolled. The enrolled data were randomly stratified and divided into a train set (108 cases: 28 healthy women, 29 with MMEF, and 51 with SEF) and a test set (47 cases: 12 healthy women, 12 MMEF and 23 SEF) at a ratio of 7:3. All participants underwent T2 and DWI sequence scans. By freely delineating the volume of interest (VOI) of the endometrium in three subgroups, radiomic features were extracted and selected. Two feature selection methods and four machine learning (ML) classifiers were combined in pairs to establish five prediction models [model₁ (T2 + ADC + clinical data), model₂ (T2 + ADC), model₃ (T2), model₄ (ADC), and model₅ (clinical data)], resulting in a total of 40 classification models. The predictive performance of all models was evaluated using the area under the curve (AUC), F1-score, and accuracy (ACC).</p><p><strong>Results: </strong>The \"UFS-LR\" model, which combined unsupervised feature selection (UFS) with the logistic regression (LR) classifier, performed the best, with an average AUC of 0.92 on the test set. Among the five models constructed via UFS-LR, model₁ exhibited the best performance, with average AUC, F1-score, and ACC values of 0.92, 0.80, and 0.81, respectively. T2-related features were the most significant in distinguishing fibrosis levels, with T2_wavelet-LLL_gldm_DependenceVariance being the most important characteristic among them.</p><p><strong>Conclusion: </strong>MP-MRI radiomics analysis using ML has excellent performance in grading EF. This approach is non-invasive and has the potential to reduce the reliance on hysteroscopy.</p>","PeriodicalId":7126,"journal":{"name":"Abdominal Radiology","volume":" ","pages":""},"PeriodicalIF":2.3,"publicationDate":"2025-01-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142998366","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A nomogram to preoperatively predict the aggressiveness of pancreatic neuroendocrine tumors based on CT features and 3D CT radiomic features.","authors":"Ziyao Wang, Jiajun Qiu, Xiaoding Shen, Fan Yang, Xubao Liu, Xing Wang, Nengwen Ke","doi":"10.1007/s00261-024-04759-x","DOIUrl":"https://doi.org/10.1007/s00261-024-04759-x","url":null,"abstract":"<p><strong>Objectives: </strong>Combining Computed Tomography (CT) intuitive anatomical features with Three-Dimensional (3D) CT multimodal radiomic imaging features to construct a model for assessing the aggressiveness of pancreatic neuroendocrine tumors (pNETs) prior to surgery.</p><p><strong>Methods: </strong>This study involved 242 patients, randomly assigned to training (170) and validation (72) cohorts. Preoperative CT and 3D CT radiomic features were used to develop a model predicting pNETs aggressiveness. The aggressiveness of pNETs was characterized by a combination of factors including G3 grade, nodal involvement (N + status), presence of distant metastases, and/or recurrence of the disease.</p><p><strong>Results: </strong>Three distinct predictive models were constructed to evaluate the aggressiveness of pNETs using CT features, 3D CT radiomic features, and their combination. The combined model demonstrated the greatest predictive accuracy and clinical applicability in both the training and validation sets (AUCs (95% CIs) = 0.93 (0.90-0.97) and 0.89 (0.79-0.98), respectively). Subsequently, a nomogram was developed using the features from the combined model, displaying strong alignment between actual observations and predictions as indicated by the calibration curves. Using a nomogram score of 86.06, patients were classified into high- and low-aggressiveness groups, with the high-aggressiveness group demonstrating poorer overall survival and shorter disease-free survival.</p><p><strong>Conclusion: </strong>This study presents a combined model incorporating CT and 3D CT radiomic features, which accurately predicts the aggressiveness of PNETs preoperatively.</p>","PeriodicalId":7126,"journal":{"name":"Abdominal Radiology","volume":" ","pages":""},"PeriodicalIF":2.3,"publicationDate":"2025-01-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142998344","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Gender differences in self-reported participation in ultrasound-guided procedures: a retrospective analysis.","authors":"Jacqueline M Godbe, Benjamin S Strnad, Zaid Alkaabneh, Lasya P Daggumati, Malak Itani","doi":"10.1007/s00261-025-04805-2","DOIUrl":"https://doi.org/10.1007/s00261-025-04805-2","url":null,"abstract":"<p><strong>Background: </strong>Across multiple procedural specialties, female trainees tend to perform fewer procedures and receive less autonomy than their male counterparts. However, there is currently no data on procedure contribution levels for radiology trainees.</p><p><strong>Objective: </strong>To evaluate whether there was a difference in the degree of reported participation in ultrasound-guided procedures between male and female trainees at our institution.</p><p><strong>Methods: </strong>This retrospective study assessed for differences in the reported level of participation between male and female trainees in ultrasound (US) guided paracentesis and thoracentesis. We performed a radiology information system (RIS) search of US guided procedures performed on adult patients from 7/1/2018 to 2/29/2024. Trainee participation levels in the procedures were determined per available reports and classified into independently performed, assisted, or observed. We evaluated the differential reporting of procedure contributions for male and female trainees based on observed vs. expected frequencies, as well as the effect of the trainees' and supervising physicians' gender and experience level on these contributions.</p><p><strong>Results: </strong>A total of 189 trainees (52 female, 137 male) and 58 supervising physicians (18 female and 40 male) were included. The study evaluated 4156 reports, which showed no difference in the percentage of independently completed procedures (females 80.9% vs. 81.9%, X² (1, N = 4156) = 0.494, p = 0.48) except when supervised by junior physicians less than 2 years out of training (females 81.0% vs. 86.5%, X² (1, N = 1908) = 8.19, p = 0.0042). However, female trainees were more likely than male trainees to report observing procedures (females 9.2% vs. 5.2%, X2 (1, N = 4156) = 21.1, p < 0.00001) rather than actively participating in procedures despite a similar training level; this difference was not observed when supervising physicians were females.</p><p><strong>Conclusion: </strong>Female radiology trainees report a similar percentage of independently performed procedures but a lower rate of active participation than male trainees.</p>","PeriodicalId":7126,"journal":{"name":"Abdominal Radiology","volume":" ","pages":""},"PeriodicalIF":2.3,"publicationDate":"2025-01-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142998364","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Performance of MR fusion biopsy, systematic biopsy and combined biopsy on prostate cancer detection rate in 1229 patients stratified by PI-RADSv2 score on 3T multi-parametric MRI.","authors":"Hannah H Riskin-Jones, Alex G Raman, Rushikesh Kulkarni, Corey W Arnold, Anthony Sisk, Ely Felker, David S Lu, Leonard S Marks, Steven S Raman","doi":"10.1007/s00261-024-04753-3","DOIUrl":"https://doi.org/10.1007/s00261-024-04753-3","url":null,"abstract":"<p><strong>Purpose: </strong>We analyzed the additional value of systematic biopsy (SB) to MR-Ultrasound fusion biopsy (MRgFbx) for detection of clinically significant prostate cancer (csPCa), as increased sampling may cause increased morbidity.</p><p><strong>Materials and methods: </strong>This retrospective study cohort was comprised of 1229 biopsy sessions between July 2016 and May 2020 in men who had a Prostate Imaging-Reporting and Data System (PI-RADSv2) category ≥ 3 lesion on 3 Tesla multiparametric MRI (3TmpMRI) and subsequent combined biopsy (CB; MRgFbx and SB) for suspected prostate cancer (PCa). Cancer detection rates (CDR) were calculated for CB, MRgFbx and SB in the study cohort and sub-cohorts stratified by biopsy history and PI-RADSv2 category. For 927 men with unilateral MR-visible lesions, SB CDR was additionally calculated for contralateral (SBc) and ipsilateral (SBi) subcohorts.</p><p><strong>Results: </strong>On CB, the CDR for csPCa was 54.8% (673/1229). CDR for csPCa was significantly higher for MRgFbx (50.0%, CI 47.1-52.8%) compared to SB (35.3%, CI 32.6-38.1%) for all PI-RADSv2 ≥ 3 categories (p < .05). The MRgFbx CDR for PI-RADSv2 categories 3, 4, and 5 were 81.5%, 88.5%, and 95.6% respectively. For unilateral lesion cases, significantly more csPCa was detected in the SBi compared to the SBc subcohort (30.1% (279/927) vs. 10.4%, (96/927), p < 0.001). The combination of MRgFbx and SBi detected csPCa in 97.0% (480) of the 495 csPCa detected by CB.</p><p><strong>Conclusion: </strong>MRgFbx had a higher CDR for csPCa than SB. While CB detected more csPCa than either method alone, in patients with a PI-RADSv2 category of 5, MRgFbx approximated the performance of CB. In unilateral lesion cases, SBc provided minimal added benefit.</p>","PeriodicalId":7126,"journal":{"name":"Abdominal Radiology","volume":" ","pages":""},"PeriodicalIF":2.3,"publicationDate":"2025-01-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142998368","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}