European Radiology最新文献

{"title":"Influence of plaque characteristics by coronary computed tomography angiography on lesion-specific ischemia: a systematic review and meta-analysis.","authors":"Nadia Iraqi, Bjarne L Nørgaard, Damini Dey, Jawdat Abdulla","doi":"10.1007/s00330-025-11516-1","DOIUrl":"10.1007/s00330-025-11516-1","url":null,"abstract":"<p><strong>Objectives: </strong>To evaluate the association between plaque characteristics and burden by coronary computed tomography angiography (CCTA) and ischemia determined by invasively measured fractional flow reserve (FFR), and whether the addition of plaque characteristics improves ischemia discrimination beyond coronary stenosis alone.</p><p><strong>Methods: </strong>A systematic literature review and meta-analysis of studies from PubMed, EMBASE, and the Cochrane Library databases, published between January 2005 and October 2024 were conducted to assess the relationship between quantitative and qualitative coronary plaque characteristics and invasive FFR. Pooled analyses were performed using weighted mean difference for plaque volumes with 95% confidence intervals and odds ratios for qualitative plaque findings.</p><p><strong>Results: </strong>A total of 29 studies involving 4416 patients (mean age 63 ± 9 years and 71% male) with predominantly stable coronary artery disease were included. Data on 3923 lesions and 3520 vessels were pooled. Total plaque, non-calcified plaque, and percent aggregate plaque volumes, as well as percent plaque burden, were inversely associated with FFR at both per-lesion and per-vessel levels (all, p-values < 0.05). The presence of high-risk plaque characteristics, including low-attenuation plaque, napkin-ring sign, and spotty calcification, were more frequently observed in lesions and vessels with FFR ≤ 0.80 (all, p-values < 0.05). Among plaque volumes, the percent aggregate plaque volume consistently improved ischemia discrimination independently of stenosis.</p><p><strong>Conclusion: </strong>CCTA-derived quantification of plaque volumes and identification of high-risk plaque characteristics are associated with ischemia and significantly enhance discrimination of ischemia-causing lesions independently of coronary stenosis severity.</p><p><strong>Key points: </strong>Question Plaque characteristics have been suggested as the missing link between coronary artery stenosis severity and ischemia. Findings High-risk plaque characteristics and larger coronary plaque volumes are associated with ischemia (FFR ≤ 0.80). Clinical relevance The addition of CCTA-derived plaque assessment improved the discrimination of ischemia compared with stenosis evaluation alone. Combining coronary stenosis and plaque assessment may improve the non-invasive assessment of patients with coronary artery disease and gatekeeping to the catheterization laboratory.</p>","PeriodicalId":12076,"journal":{"name":"European Radiology","volume":" ","pages":"6271-6290"},"PeriodicalIF":4.7,"publicationDate":"2025-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12417243/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143718239","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Diffusion levels for quantitative assessment of the apparent diffusion coefficient value in prostate MRI: a proof-of-concept bicentric study.","authors":"Rossano Girometti, Valeria Peruzzi, Paola Clauser, Nina Pötsch, Maria De Martino, Miriam Isola, Gianluca Giannarini, Alessandro Crestani, Chiara Zuiani, Lorenzo Cereser, Pascal At Baltzer","doi":"10.1007/s00330-025-11547-8","DOIUrl":"10.1007/s00330-025-11547-8","url":null,"abstract":"<p><strong>Objectives: </strong>To investigate the performance of Diffusion levels (DLs) in diagnosing clinically significant prostate cancer (csPCa) when combined with the PI-RADS version 2.1.</p><p><strong>Materials and methods: </strong>This retrospective, bicentric study included 261 men who underwent 3.0-T prostate MRI between March 2020 and April 2023, receiving systematic and target prostate biopsy on PI-RADS ≥ 3 lesions. Two readers measured the Apparent diffusion coefficient (ADC) of PI-RADS 1-5 findings in the peripheral zone. By plotting the cumulative frequency of csPCa versus ADCs and using ROC analysis, we derived four DLs expressing levels of restricted diffusion, i.e., very low DL (VL-DL), low DL (L-DL), intermediate DL (I-DL), and high DL (H-DL). We compared the per-lesion diagnostic performance in assessing csPCa (grading group ≥ 2 cancer) assuming to biopsy PI-RADS ≥ 3 lesions (strategy 1), PI-RADS ≥ 3 lesions adjusted with ADC values (strategy 2-4), and PI-RADS ≥ 3 lesions adjusted with DLs (strategy 5-7). Net benefit was assessed with decision curve analysis.</p><p><strong>Results: </strong>csPCa was found in 79/261 men (30.3%) and 152/528 lesions (28.8%). There was a negative correlation (p < 0.0001) between ADC versus malignancy rate (tau -0.970) and DLs versus csPCa grading group (tau -0.614). csPCa prevalence was highest in VL-DL (72.2%) and L-DL (54.4%). Most DLs-based strategies increased specificity, positive predictive value (PPV), and net benefit compared to ADC-based strategies or PI-RADS alone. The best strategy showed 94.7% sensitivity, 82.9% specificity, 69.2% PPV, and 97.5% negative predictive value.</p><p><strong>Conclusion: </strong>While larger-scale validation is needed, DLs have the potential to improve PI-RADS-based biopsy decisions for detecting csPCa in the peripheral zone.</p><p><strong>Key points: </strong>Question It is still unclear how to incorporate quantitative information from diffusion-weighted imaging (DWI) into prostate MRI. Findings Combining DWI-derived diffusion levels (DLs) with the PI-RADS version 2.1 categorization reduced false positives while preserving high sensitivity for clinically significant prostate cancer. Clinical relevance DLs permit to easily account for ADC values of prostate lesions and, in turn, refine biopsy decisions.</p>","PeriodicalId":12076,"journal":{"name":"European Radiology","volume":" ","pages":"6171-6182"},"PeriodicalIF":4.7,"publicationDate":"2025-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12417251/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143795028","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Improving the diagnostic performance of contrast-enhanced mammography through lesion conspicuity and enhancement quantification.","authors":"Iris Allajbeu, Muzna Nanaa, Roido Manavaki, Vasiliki Papalouka, Ioana Bene, Nicholas Payne, Elisabetta Giannotti, Thiemo van Nijnatten, Fleur Kilburn-Toppin, Nuala Healy, Fiona Gilbert","doi":"10.1007/s00330-025-11501-8","DOIUrl":"10.1007/s00330-025-11501-8","url":null,"abstract":"<p><strong>Objectives: </strong>To analyze qualitative and quantitative enhancement of breast lesions on CEM and their impact on specificity and overall diagnostic performance in predicting malignancy. A secondary objective was to compare lesion enhancement patterns between CEM and contrast-enhanced (CE)-MRI.</p><p><strong>Methods: </strong>The cohort included screening and symptomatic cases from CEM research studies (December 2016-March 2023) with an identifiable lesion. Three breast radiologists independently assessed lesion conspicuity as low, moderate, or high, based on the BI-RADS CEM lexicon. Lesion enhancement was quantified by drawing two regions of interest representing lesion and background parenchyma, to calculate contrast enhancement from the early (CE_early) and late (CE_late) views. Area-under-the-curve (AUC) was used to assess diagnostic performance, with thresholds determined using the maximum Youden index. Cohen's κ was used to measure agreement between CEM and DCE-MRI enhancement patterns. p-values < 0.05 were deemed statistically significant.</p><p><strong>Results: </strong>From 503 CEM studies, 143 BI-RADS 2-5 lesions were analyzed. Lesion conspicuity was significantly associated with lesion histology (p < 0.001), contrast enhancement metrics (CE_early, CE_late), and enhancement patterns on CEM recombined images. CE_early performed better in differentiating malignant from benign lesions or background parenchymal enhancement (BPE), with AUC values of 0.83 and 0.88 and 90% specificity in distinguishing BPE from cancers. There was fair/moderate agreement between lesion enhancement patterns on CEM and DCE-MRI (Cohen's κ = 0.35, p < 0.001), with a higher agreement for lesions exhibiting a wash-out pattern (Cohen's κ = 0.5, p < 0.001).</p><p><strong>Conclusion: </strong>Both conspicuity and quantification of lesion enhancement can improve CEM specificity in predicting malignancy, with CE_early offering the best diagnostic performance.</p><p><strong>Key points: </strong>Question Quantifying lesion enhancement conspicuity on contrast-enhanced mammography (CEM) has demonstrated potential in differentiating malignancy from benign lesions and BPE. Finding Contrast from the early recombined view (CEearly) performed better in discriminating malignant from benign lesions and BPE, with 90% specificity for BPE vs cancers. Clinical relevance Conspicuity and quantification of lesion enhancement on CEM can improve the specificity and overall diagnostic performance of CEM in cancer detection. Implementation of conspicuity thresholds in routine CEM interpretation could potentially reduce unnecessary recalls and benign biopsies.</p>","PeriodicalId":12076,"journal":{"name":"European Radiology","volume":" ","pages":"6385-6397"},"PeriodicalIF":4.7,"publicationDate":"2025-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12417241/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143778990","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Intravoxel incoherent motion-derived histogram analysis for quantitative evaluation of tumor budding and prognostic stratification in rectal cancer.","authors":"Ao Yang, Xin Zhang, Peng Zhou, Xiaoli Chen","doi":"10.1007/s00330-025-11612-2","DOIUrl":"10.1007/s00330-025-11612-2","url":null,"abstract":"<p><strong>Objective: </strong>To determine the value of intravoxel incoherent motion (IVIM) for quantitative tumor budding (TB) evaluation and prognostic stratification in patients with rectal cancer (RC).</p><p><strong>Materials and methods: </strong>This study enrolled 189 RC patients (training set 148, validation set 41) who underwent IVIM and were subsequently treated surgically within 2 weeks between January 2022 and April 2023. Hematoxylin-eosin staining was used for TB scoring. IVIM metrics were calculated on MRI images using biexponential fitting and histogram analysis. Differences in IVIM histogram metrics between the low-intermediate grade budding (Bd 1 + 2) and the high-grade budding (Bd 3) were analyzed. Multivariate logistic regression analysis was used to build the Combined model. The area under the receiver operating characteristic curve (AUC) was used to assess the diagnostic performance of the IVIM histogram metrics and the Combined model. Kaplan-Meier analysis was employed to estimate disease-free and overall survival rates for patients.</p><p><strong>Results: </strong>Multivariate logistic analysis showed that the D_25th percentile, D_75th percentile, D_90th percentile, and D_95th percentile were independent predictors of Bd 3 (all p < 0.05). The Combined model incorporating these four factors had the best diagnostic performance, with the AUC, sensitivity, and specificity of 0.852, 73.02%, and 82.35% in the training set and 0.856, 75.00%, and 86.21% in the validation set. Furthermore, the score of the Combined model was significantly associated with worse 2-year overall survival (hazard ratio 6.804, 95% confidence interval 2.214 to 20.909, p = 0.001).</p><p><strong>Conclusion: </strong>The IVIM histogram metrics could distinguish different TB grades and be used as a preoperative risk stratification tool.</p><p><strong>Key points: </strong>Questions Does intravoxel incoherent motion based on histogram analysis predict tumor budding grades and its prognosis in patients with rectal cancer? Findings The histogram metrics of slow diffusion coefficient are an independent prediction factor of high-grade tumor budding and a risk factor of poor 2-year overall survival. Clinical relevance This combined model, based on slow diffusion coefficient, is a reliable tool for preoperative predicting 2-year overall survival in patients with rectal cancer, contributing to risk stratification and individual treatment.</p>","PeriodicalId":12076,"journal":{"name":"European Radiology","volume":" ","pages":"6482-6494"},"PeriodicalIF":4.7,"publicationDate":"2025-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143974152","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Predicting lymphovascular invasion in stage IA lung adenocarcinoma: a CT-based classification and regression tree model.","authors":"Lihua Chen, Yangfan Su, Yao Huang, Junli Tao, Xuemei Huang, Kai Li, Daihong Liu, Jiuquan Zhang","doi":"10.1007/s00330-025-11593-2","DOIUrl":"10.1007/s00330-025-11593-2","url":null,"abstract":"<p><strong>Background: </strong>Lymphovascular invasion (LVI) is a significant histopathological marker associated with poor prognosis in patients. However, there is a notable lack of reliable, non-invasive preoperative tools to predict LVI accurately.</p><p><strong>Purpose: </strong>To develop and validate a computed tomography (CT)-based classification and regression tree (CART) model for the preoperative prediction of LVI in patients with clinical stage IA lung adenocarcinoma (LUAD).</p><p><strong>Materials and methods: </strong>This multicenter cohort study recruited patients who underwent resection and had a preoperative CT examination. An internal cohort (n = 525) is included to construct the LVI classification and regression tree model (LVI-CART). An external cohort (n = 115) and a public cohort (n = 57) are then used to fully validate the predictive performance of the LVI-CART. Kaplan-Meier survival analysis and univariable Cox regression analyses were conducted to investigate the relationship between predicted LVI status and survival.</p><p><strong>Results: </strong>The LVI-CART model includes two features, diameter and nodule type, and shows acceptable performance in predicting pathological LVI, with area under the curve values of 0.719, 0.756, and 0.835 in the internal validation set, external validation set and test set, respectively. A predicted LVI positive relative to the median value in the outcomes cohort was found to be independently associated with 1-, 3-year RFS and 1-, 3-, 5-year OS (all p-values < 0.05).</p><p><strong>Conclusions: </strong>The LVI-CART model could be used to preoperatively predict LVI and identify patients with poor prognosis in clinical IA LUAD. The model is like to be simple and easily applicable to risk stratification.</p><p><strong>Key points: </strong>Question Lymphovascular invasion is a critical histopathological indicator of poor prognosis, necessitating reliable non-invasive preoperative predictive tools. Findings The classification and regression tree model for predicting lymphovascular invasion (LVI-CART) model demonstrates adequate predictive ability for pathological LVI, portending poor recurrence-free and overall survival. Clinical relevance The LVI-CART model provides clinicians with an easy-to-use method for preoperative identification of patients with clinical stage IA lung adenocarcinoma who are LVI-positive. It also provides a framework for a comprehensive assessment of patient survival risk.</p>","PeriodicalId":12076,"journal":{"name":"European Radiology","volume":" ","pages":"6357-6368"},"PeriodicalIF":4.7,"publicationDate":"2025-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143984936","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Contrast-enhanced mammography: a success story with open issues and fascinating perspectives.","authors":"Francesco Sardanelli","doi":"10.1007/s00330-025-11605-1","DOIUrl":"10.1007/s00330-025-11605-1","url":null,"abstract":"","PeriodicalId":12076,"journal":{"name":"European Radiology","volume":" ","pages":"6382-6384"},"PeriodicalIF":4.7,"publicationDate":"2025-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143985165","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Evaluation of a deep learning segmentation tool to help detect spinal cord lesions from combined T2 and STIR acquisitions in people with multiple sclerosis.","authors":"Baptiste Lodé, Burhan Rashid Hussein, Cédric Meurée, Ricky Walsh, Malo Gaubert, Nicolas Lassalle, Guilhem Courbon, Agathe Martin, Jeanne Le Bars, Françoise Durand-Dubief, Bertrand Bourre, Adil Maarouf, Olivier Outteryck, Clément Mehier, Alexandre Poulin, Camille Cathelineau, Jeremy Hong, Guillaume Criton, Sophie Motillon-Alonso, Augustin Lecler, Frédérique Charbonneau, Loïc Duron, Alexandre Bani-Sadr, Céline Delpierre, Jean-Christophe Ferré, Gilles Edan, François Cotton, Romain Casey, Francesca Galassi, Benoit Combès, Anne Kerbrat","doi":"10.1007/s00330-025-11541-0","DOIUrl":"10.1007/s00330-025-11541-0","url":null,"abstract":"<p><strong>Objective: </strong>To develop a deep learning (DL) model for the detection of spinal cord (SC) multiple sclerosis (MS) lesions from both sagittal T2 and short tau inversion recovery (STIR) sequences and to investigate whether such a model could improve the performance of clinicians in detecting SC lesions.</p><p><strong>Materials and methods: </strong>A DL tool was developed based on SC sagittal T2 and STIR acquisitions from the imaging database of the French MS registry (OFSEP), including retrospective data from 40 different scanners. A multi-reader study based on retrospective data was performed between December 2023 and June 2024 to compare the performance of 20 clinicians in interpreting upper and lower SC acquisitions with and without the use of the tool. A ground truth was established by three experts. Sensitivity, precision, and inter-reader variability were evaluated.</p><p><strong>Results: </strong>We included 50 patients (39 females, median age: 41 years [range: 15-67]) with SC MRI acquired between February 2017 and December 2022. When reading with the tool, the clinicians' mean sensitivity to detect SC lesions improved (from 74.3% [95% CI = 67.8-80.6%] to 79.2% [95% CI: 73.5-85.0%]; p < 0.0001), with no evidence of difference in the mean precision: (69.0% [95% CI: 62.8-75.2%] vs 70.1% [95% CI: 64.3-75.9%]; p = 0.08). Inter-reader variability in lesion detection was slightly improved with the tool (Light's kappa = 0.55 vs 0.60), but without statistical difference (p = 0.056).</p><p><strong>Conclusion: </strong>The use of an automatic tool can help clinicians detect SC lesions in pwMS by increasing their sensitivity.</p><p><strong>Key points: </strong>Question No tool to help detect MS SC lesions is used in clinical practice despite their frequency and prognostic value. Findings This DL-based tool led to improvement in clinicians' sensitivity in detecting SC lesions from both sagittal T2 and STIR sequences, without decreasing precision. Clinical relevance Our study indicated the potential of a DL-based tool to assist clinicians in the challenging task of detecting SC lesions in people with MS on a combination of sequences commonly acquired in clinical practice.</p>","PeriodicalId":12076,"journal":{"name":"European Radiology","volume":" ","pages":"5954-5964"},"PeriodicalIF":4.7,"publicationDate":"2025-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12417267/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143788049","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Super-resolution ultrasound imaging of intranodal lymphatic sinuses for predicting sentinel lymph node metastasis in breast cancer: a preliminary study.","authors":"ShuJun Xia, Qing Hua, YanYan Song, CongCong Yuan, YuHang Zheng, RuoLin Tao, JiaLe Xu, EnHeng Cai, YuLu Zhang, FangGang Wu, Wei Guo, Yuan Tian, YiJie Dong, JianQiao Zhou","doi":"10.1007/s00330-025-11520-5","DOIUrl":"10.1007/s00330-025-11520-5","url":null,"abstract":"<p><strong>Objectives: </strong>Accurate preoperative localization and characterization of sentinel lymph nodes (SLNs) is vital in breast cancer management. The application of super-resolution ultrasound (SRUS) imaging to visualize intranodal lymphatic sinuses for the prediction of SLN metastasis has yet to be investigated. The study aimed to assess the value of SRUS imaging of intranodal lymphatic sinuses in predicting SLN metastasis in breast cancer patients.</p><p><strong>Methods: </strong>A total of 154 SLNs from 143 patients with breast cancer were prospectively included. All patients underwent conventional US of axillary lymph nodes and SRUS imaging of lymph sinus by percutaneous microbubble injection. Qualitative and quantitative analysis were performed for SRUS imaging, with qualitative analysis focusing on identifying perfusion defects and quantitative analysis including parameters such as lymphatic sinus density, sinus diameter, sinus distance, and lymph flow velocity. The areas under the receiver operating characteristic curve (AUC), sensitivity, and specificity were calculated for conventional US, SRUS, and combined conventional US and SRUS.</p><p><strong>Results: </strong>Among the 154 SLNs, 73 were metastatic and 81 were reactive. In predicting metastatic SLNs, the AUC for SRUS (0.824; 95% CI: 0.761-0.888) was significantly higher than that for conventional US (0.661; 95% CI: 0.596-0.726) (p < 0.001). The combination of SRUS and conventional US achieved the highest AUC (0.844; 95% CI: 0.785-0.904), which was significantly higher than conventional US alone (p < 0.001), but not significantly different from SRUS alone (p = 0.2).</p><p><strong>Conclusion: </strong>Imaging lymphatic sinuses by SRUS has the potential to predict metastatic SLNs in patients with breast cancer.</p><p><strong>Key points: </strong>Question Super-resolution ultrasound (SRUS) used for visualizing intranodal lymphatic sinuses for the prediction of sentinel lymph nodes (SLNs) metastasis has yet to be investigated. Findings Microlymphatic circulation of SLNs were imaged by SRUS at ten microns scale. SRUS showed better performance for predicting metastatic SLNs than conventional ultrasound. Clinical relevance SRUS is a reliable tool to image lymphatic sinuses and characterize metastatic SLNs in patients with breast cancer. It helps diagnosis of lymph node status and clinical decision-making of breast cancer.</p>","PeriodicalId":12076,"journal":{"name":"European Radiology","volume":" ","pages":"6079-6088"},"PeriodicalIF":4.7,"publicationDate":"2025-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143788179","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Deep learning and conventional hip MRI for the detection of labral and cartilage abnormalities using arthroscopy as standard of reference.","authors":"Alexander W Marka, Felix Meurer, Vanessa Twardy, Markus Graf, Kilian Weiss, Marcus R Makowski, Dimitrios C Karampinos, Jan Neumann, Klaus Woertler, Ingo J Banke, Sarah C Foreman","doi":"10.1007/s00330-025-11546-9","DOIUrl":"10.1007/s00330-025-11546-9","url":null,"abstract":"<p><strong>Objectives: </strong>To evaluate the performance of high-resolution deep learning-based hip MR imaging (CSAI) compared to standard-resolution compressed sense (CS) sequences using hip arthroscopy as standard of reference.</p><p><strong>Methods: </strong>Thirty-two patients (mean age, 37.5 years (± 11.7), 24 men) with femoroacetabular impingement syndrome underwent 3-T MR imaging prior to hip arthroscopy. Coronal and sagittal intermediate-weighted TSE sequences with fat saturation were obtained using CS (0.6 × 0.8 mm) and high-resolution CSAI (0.3 × 0.4 mm), with 3 mm slice thickness and similar acquisition times (3:55-4:12 min). MR scans were independently assessed by three radiologists and a hip arthroscopy specialist for labral and cartilage abnormalities. Sensitivity, specificity, and accuracy were calculated using arthroscopy as reference standard. Statistical comparisons between CS and CSAI were performed using McNemar's test.</p><p><strong>Results: </strong>Labral abnormality detection showed excellent sensitivity for radiologists (CS and CSAI: 97-100%) and the surgeon (CS: 81%, CSAI: 90%, p = 0.08), with 100% specificity. Overall cartilage lesion sensitivity was significantly higher with CSAI versus CS (42% vs. 37%, p < 0.001). Highest sensitivity was observed in superolateral acetabular cartilage (CS: 81%, CSAI: 88%, p < 0.001), while highest specificity was found for the anteroinferior acetabular cartilage (CS and CSAI: 99%). Sensitivity was lowest for the assessment of the anteroinferior and posterior acetabular zones, and inferior and posterior femoral zones (CS and CSAI < 6%).</p><p><strong>Conclusion: </strong>CS and CSAI MR imaging showed excellent diagnostic performance for labral abnormalities. Despite CSAI's improved cartilage lesion detection, overall diagnostic performance for cartilage assessment remained suboptimal.</p><p><strong>Key points: </strong>Question Accurate preoperative detection of labral and cartilage lesions in femoroacetabular impingement remains challenging, with current MRI protocols showing variable diagnostic performance. Findings High-resolution deep learning-based and standard-resolution compressed sense MRI demonstrate comparable diagnostic performance, with high accuracy for labral defects but limited sensitivity for cartilage lesions. Clinical relevance Current MRI protocols, regardless of resolution optimization, show persistent limitations in cartilage evaluation, indicating the need for further technical advancement to improve diagnostic confidence in presurgical planning.</p>","PeriodicalId":12076,"journal":{"name":"European Radiology","volume":" ","pages":"6065-6078"},"PeriodicalIF":4.7,"publicationDate":"2025-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12417240/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144063029","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Quantitative MRI detects delayed perfusion and impact of bronchial artery dilatation on pulmonary circulation in patients with cystic fibrosis.","authors":"Patricia Leutz-Schmidt, Julian Grolig, Lena Wucherpfennig, Olaf Sommerburg, Monika Eichinger, Sabine Wege, Simon Y Graeber, Jens-Peter Schenk, Abdulsattar Alrajab, Hans-Ulrich Kauczor, Mirjam Stahl, Marcus A Mall, Arnd Koeppe, Britta Nestler, Michael Selzer, Simon M F Triphan, Mark O Wielpütz","doi":"10.1007/s00330-025-11589-y","DOIUrl":"10.1007/s00330-025-11589-y","url":null,"abstract":"<p><strong>Objectives: </strong>MRI detects abnormal lung perfusion in patients with cystic fibrosis (CF). However, little is known about the contribution of bronchial arteries to lung perfusion in CF. We hypothesized that delayed perfusion can be detected by dynamic contrast-enhanced (DCE-)MRI and that bronchial artery dilatation (BAD) is associated with changes in lung perfusion.</p><p><strong>Materials and methods: </strong>Morpho-functional MRI was prospectively acquired in 75 patients with CF (18.7 ± 7.6 years, range 6-39 years). Lungs and perfusion defects were segmented automatically to quantify perfusion defects in percent (QDP). Pulmonary blood flow (PBF), mean transit time (MTT), and perfusion delay were calculated for the whole lung, inside normally perfused and perfusion defect areas. Chest MRI score and BAD were assessed visually.</p><p><strong>Results: </strong>QDP and PBF correlated with MRI global score (r = 0.58 and -0.53, p < 0.001). In normally perfused lung, PBF was higher (161.2 ± 77.9 mL/100 mL/min vs. 57.5 ± 26.4 mL/100 mL/min, p < 0.001), and MTT (5.4 ± 1.7 s vs. 6.9 ± 2.3 s, p < 0.001) and perfusion delay were shorter than in perfusion defect areas (4.6 ± 5.3 s vs. 13.4 ± 16.2 s, p < 0.001). 48 (64.0%) patients showed BAD, had higher QDP (44.6 ± 20.8% vs. 17.3 ± 11.0%, p < 0.001) and lower PBF (91.9 ± 54.8 mL/100 mL/min vs. 178.3 ± 77.4 mL/100 mL/min, p < 0.001) than patients without BAD. MTT was shorter (6.3 ± 1.9 s vs. 8.0 ± 2.6 s, p < 0.001), and perfusion delay was longer (13.8 ± 10.1 s vs. 12.8 ± 23.7 s, p < 0.02) inside perfusion defects of patients with BAD compared to without BAD.</p><p><strong>Conclusion: </strong>Perfusion parameters correlate with lung disease severity, and perfusion defects showed delayed perfusion in patients with CF. BAD was associated with more extensive perfusion defects and reduced PBF.</p><p><strong>Key points: </strong>Question Dilated bronchial arteries are a common comorbidity in cystic fibrosis (CF), which can cause hemoptysis, but their quantitative contribution to lung perfusion is little researched. Findings Perfusion defects in percent (QDP) enabled objective assessment of perfusion abnormalities in CF patients, while perfusion delay and arterial correlation showed bronchial artery perfusion contribution. Clinical relevance The usage of quantitative perfusion metrics in CF may help tracking disease progression. By also including the proposed metrics perfusion delay and arterial correlation, bronchial artery inflow could be assessed and used to detect early onset of bronchial artery dilation.</p>","PeriodicalId":12076,"journal":{"name":"European Radiology","volume":" ","pages":"6217-6228"},"PeriodicalIF":4.7,"publicationDate":"2025-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12417259/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143984730","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}