European Radiology最新文献

{"title":"ESR Essentials: assessing the radiological response of liver metastases to systemic therapy-practice recommendations by the European Society of Gastrointestinal and Abdominal Radiology.","authors":"Marco Dioguardi Burgio, Maxime Ronot, Valérie Vilgrain","doi":"10.1007/s00330-025-11540-1","DOIUrl":"https://doi.org/10.1007/s00330-025-11540-1","url":null,"abstract":"<p><p>The liver is a common site for metastatic spread, especially in advanced colorectal, breast, and pancreatic cancers. Imaging evaluation of liver metastases after systemic treatments like chemotherapy, targeted therapy, or immunotherapy is essential to distinguish treatment response from disease progression. The widely used response evaluation criteria in solid tumours (RECIST 1.1) focus on lesion size changes to evaluate treatment response. However, newer therapies, mainly targeted therapy and immunotherapy, often induce changes beyond size reduction, such as tumour necrosis, fibrosis, cystic transformation, calcifications, and modifications at the liver-tumour interface. These morphological and enhancement changes can be evaluated on CT and MRI and may better reflect the biological response in specific clinical settings. Overall, RECIST 1.1 criteria are recommended for assessing the radiological response of liver metastases after systemic treatment. The use of alternative radiological criteria validated on CT (such as Chun or Choi criteria) is recommended in specific clinical settings (e.g. metastatic colorectal cancer or metastatic gastrointestinal stromal tumours). Additionally, CT and MR modifications that reflect fibrosis, necrosis, calcifications, and haemorrhage can serve as ancillary indicators of tumoural response. These alternative criteria and radiological findings should be systematically assessed, particularly in liver metastases with minimal size changes, to better identify responders. KEY POINTS: RECIST 1.1 is the standard for evaluating tumour response in solid tumours and is recommended for the assessment of liver metastases after systemic therapy. CT attenuation, enhancement, and liver/tumour interface may correlate better with tumoural response compared to size reduction. CT and MR changes suggesting necrosis, fibrosis, calcifications, and haemorrhage can be used as additional indicators of tumoural response.</p>","PeriodicalId":12076,"journal":{"name":"European Radiology","volume":" ","pages":""},"PeriodicalIF":4.7,"publicationDate":"2025-04-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143788045","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":"Personalized risk-adapted models in prostate cancer during active surveillance using MRI-a narrative review.","authors":"Davide Maffei, Caroline M Moore","doi":"10.1007/s00330-025-11518-z","DOIUrl":"https://doi.org/10.1007/s00330-025-11518-z","url":null,"abstract":"<p><p>The presence of histologically defined prostate cancer (PCa) is common and rises with age. Nevertheless, histological evidence of PCa does not always lead to clinically evident or life-threatening disease, and we know that PSA-based population screening can find twice the prevalence of PCa than would present via clinical routes. The PROTECT study randomized men diagnosed through PSA screening, to surgery, radiotherapy, or active monitoring. At 15 years, PCa-related deaths ranged from 2.1% in the surgery group to 2.9% in the active monitoring group, while the risk of death from other causes was 22%. Modern PCa diagnosis uses MRI to determine who needs a biopsy and how it is done. Multiparametric MRI can selectively detect PCa of higher grade and volume, which is more likely to be associated with progression, metastases, and death, and hence to benefit from treatment. MRI and MRI-targeted biopsies are recommended prior to enrolment in active surveillance (AS) programs for accurate risk classification. The UCLH AS cohort based on per-cause MRI evaluations has shown baseline Gleason grade and MRI index lesion visibility to be strong predictors of progression to treatment. Serial evaluation with MRI has been codified with the PRECISE recommendations to support MRI-based monitoring during AS. AS recommendations have extended to certain favorable-intermediate risk cancers. The Movember International Consensus Meeting has determined a dynamic risk-stratified AS approach to be the highest-ranked research priority. We review the impact of MRI on AS from patient selection to risk stratification, and the development of MRI-led personalized AS protocols. KEY POINTS: Question Standardized protocols are not able to address the heterogeneity of men on active surveillance for PCa and are burdened by unnecessary examinations. Findings MRI can improve the selection of men for active surveillance, predict time to treatment, and risk-stratify patients at risk of progression. Clinical relevance MRI-led risk-adapted protocols may reduce the burden of active surveillance on patients, improve adherence, and reduce healthcare costs.</p>","PeriodicalId":12076,"journal":{"name":"European Radiology","volume":" ","pages":""},"PeriodicalIF":4.7,"publicationDate":"2025-04-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143788082","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":"https://doi.org/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":""},"PeriodicalIF":4.7,"publicationDate":"2025-04-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","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":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"An interpretable radiomics-based machine learning model for predicting reverse left ventricular remodeling in STEMI patients using late gadolinium enhancement of myocardial scar.","authors":"Xiuzheng Yue, Jianing Cui, Sicong Huang, Wenjia Liu, Jing Qi, Kunlun He, Tao Li","doi":"10.1007/s00330-025-11419-1","DOIUrl":"https://doi.org/10.1007/s00330-025-11419-1","url":null,"abstract":"<p><strong>Objectives: </strong>To evaluate the added value of the late gadolinium enhancement (LGE)-scar radiomics features in predicting reverse left ventricular remodeling (r-LVR) in ST-segment elevation myocardial infarction (STEMI) patients using machine learning (ML).</p><p><strong>Materials and methods: </strong>This retrospective study included 105 STEMI patients who underwent CMR within 7 days and 5 months post-percutaneous coronary intervention (PCI) on 1.5-T or 3.0-T MRI scanners (January 2014-2023). Radiomics features from LGE scar images and routine CMR markers were analyzed using a LightGBM model enhanced by Shapley Additive exPlanations (SHAP) for interpretability. Patients were divided into training (80) and test (25) sets. Three predictive models were developed: traditional CMR, LGE-scar radiomics, and a combined model integrating both. Model performance was assessed using ROC curves and AUC analysis.</p><p><strong>Results: </strong>In the training set, the traditional CMR model achieved an AUC of 0.745 (95% CI: 0.62-0.86), the LGE-scar radiomics model had an AUC of 0.712 (95% CI: 0.58-0.83), and the combined model showed the highest AUC of 0.754 (95% CI: 0.63-0.86). In the test set, the traditional CMR model's AUC decreased to 0.656 (95% CI: 0.42-0.88), while the LGE-scar radiomics model improved to 0.818 (95% CI: 0.59-1.00). The combined model achieved the highest AUC of 0.890 (95% CI: 0.75-1.00). SHAP analysis highlighted significant predictors such as infarct percentage of LV mass and wavelet-transformed texture features.</p><p><strong>Conclusion: </strong>Integrating LGE scar radiomics features with traditional CMR parameters in a LightGBM model enhances predictive accuracy for r-LVR in STEMI patients, potentially improving patient stratification and treatment personalization.</p><p><strong>Key points: </strong>Question Predicting r-LVR in STEMI patients remains challenging due to limitations in current imaging approaches. Findings Integrating LGE-scar radiomics and cardiac magnetic resonance markers in the LightGBM model significantly improves prediction accuracy for r-LVR. Clinical relevance This interpretable ML model enhances r-LVR prediction, supporting patient stratification and optimizing treatment strategies to improve patient outcomes.</p>","PeriodicalId":12076,"journal":{"name":"European Radiology","volume":" ","pages":""},"PeriodicalIF":4.7,"publicationDate":"2025-04-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143779539","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":"Embracing graphical abstracts in European Radiology.","authors":"Brendan S Kelly","doi":"10.1007/s00330-025-11555-8","DOIUrl":"https://doi.org/10.1007/s00330-025-11555-8","url":null,"abstract":"","PeriodicalId":12076,"journal":{"name":"European Radiology","volume":" ","pages":""},"PeriodicalIF":4.7,"publicationDate":"2025-04-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143771872","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":"Congruency between publicly available pictorial displays of medial temporal lobe atrophy.","authors":"Felicia Forseni Flodin, Sven Haller, Leo Poom, David Fällmar","doi":"10.1007/s00330-025-11529-w","DOIUrl":"https://doi.org/10.1007/s00330-025-11529-w","url":null,"abstract":"<p><p>The medial temporal lobe atrophy (MTA) score is used for visual assessment of MTA on radiological images in suspected neurodegenerative dementia. Although volumetric tools are available, many radiologists still use visual scoring and compare to reference images. Numerous such example images are found online on educational websites and in scientific articles. The aim of this study was to compare congruencies between MTA scores of publicly available sample images with normalized heights and areas of relevant brain structures, measured in the same images.</p><p><strong>Method: </strong>Systematic online searches yielded 148 individual sample images. The height and area of relevant brain structures were manually delineated, normalized, and compared with regard to the displayed MTA score.</p><p><strong>Results: </strong>The normalized heights and areas showed correlation with MTA but with considerable overlap between adjacent scores, especially when comparing heights. Also, displays of the MTA score were more consistent with the area of the temporal horn than with the hippocampal area.</p><p><strong>Conclusion: </strong>There is considerable overlap between adjacent scores in publicly available pictorial displays of the MTA grading system. Insufficient congruency leads to confusion and reduces inter-rater reliability. We also found that publicly available images are more consistent with temporal horn area than the hippocampus, which means that ventricular size may bias the grading. This can impede relevant differential diagnostics, especially regarding normal pressure hydrocephalus. Here, we present lectotype images selected specifically with regard to the hippocampal area.</p><p><strong>Key points: </strong>Question Overlap between publicly available example images of medial temporal atrophy causes confusion and limits reliability. Findings Available images are more consistent with ventricular dilatation than hippocampal atrophy; this article provides lectotype images selected specifically regarding the hippocampal area. Clinical relevance Visual assessment of medial temporal atrophy is used daily and worldwide in radiological examinations regarding suspected dementia. In clinical routine, many radiologists experience uncertainty, and hydrocephalus is often overlooked. This may be caused by insufficient congruency between educational sample images.</p>","PeriodicalId":12076,"journal":{"name":"European Radiology","volume":" ","pages":""},"PeriodicalIF":4.7,"publicationDate":"2025-04-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143779542","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":"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":"https://doi.org/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":""},"PeriodicalIF":4.7,"publicationDate":"2025-04-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","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":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"External validation of inter-reader reliability of the Prostate Imaging after Focal Ablation (PI-FAB) scoring system following focal cryoablation and focal high-intensity focused ultrasound.","authors":"Michael C Ivey, Sriram Deivasigamani, Srinath Kotamarti, Mahdi Mottaghi, Alireza Ghoreifi, Eric S Adams, Hasan Jhaveri, Cary N Robertson, Danielle E Kruse, Kevin R Kalisz, Daniele Marin, Sarah P Thomas, Thomas J Polascik, Rajan T Gupta","doi":"10.1007/s00330-025-11513-4","DOIUrl":"https://doi.org/10.1007/s00330-025-11513-4","url":null,"abstract":"<p><strong>Objectives: </strong>The efficacy of focal therapy (FT) has improved with the use of multiparametric MRI (mpMRI) for lesion identification, though standardized mpMRI reporting post-FT is lacking. The Prostate Imaging after Focal Ablation (PI-FAB) scoring system was recently introduced to standardize mpMRI interpretation for local recurrence post-FT. This study evaluates the diagnostic performance and inter-reader reliability of PI-FAB following cryoablation and high-intensity focused ultrasound (HIFU) modalities.</p><p><strong>Materials and methods: </strong>This retrospective, single-institution study included all patients treated with FT from 2007 to 2023 with available follow-up mpMRI and subsequent prostate biopsy. Three fellowship-trained radiologists scored these images using the PI-FAB system. The primary objective was inter-reader agreeability of PI-FAB scores, and the secondary objective assessed performance metrics, including sensitivity, specificity, positive predictive and negative predictive value.</p><p><strong>Results: </strong>91 patients with 113 mpMRI exams (95 post-cryotherapy; 18 post-HIFU) were reviewed. There was substantial agreement between the readers (Fleiss' Kappa (κ): 0.71, p < 0.001; Gwet AC2: 0.70, p < 0.03). A PI-FAB score 3 had a significant ability to rule-in csPCa with high specificity (88%, 86%, and 93% per reader, respectively), and PI-FAB score 1 had high sensitivity to rule out csPCa (88%, 78%, and 84% per reader, respectively) in surveillance imaging (14-16 months median follow-up).</p><p><strong>Conclusions: </strong>Our study suggests that the PI-FAB scoring system can be effectively used to evaluate mpMRI recurrence post-FT, with substantial inter-reader reliability and high specificity for predicting in-field clinically significant prostate cancer recurrence post-cryotherapy and HIFU. Larger, multi-institutional studies are essential to confirm PI-FAB's utility in clinical practice.</p><p><strong>Key points: </strong>Question There is no widely accepted and validated standardized scoring system to predict the local recurrence of clinically significant prostate cancer after focal therapy with ablative modalities. Findings The Prostate Imaging after Focal Ablation (PI-FAB) scoring system effectively predicts in-field recurrence of prostate cancer after focal therapy with substantial inter-reader reliability and specificity. Clinical relevance As patient requests for focal therapy to treat localized low- to- intermediate risk prostate cancer become more common, based on its performance metrics, PI-FAB will aid in identifying in-field recurrence within this patient population.</p>","PeriodicalId":12076,"journal":{"name":"European Radiology","volume":" ","pages":""},"PeriodicalIF":4.7,"publicationDate":"2025-04-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143763527","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":"Visual ordinal grading of aortic valve calcification on routine non-gated chest CT predicts prognosis and alters management.","authors":"Samuel G S Gunning, John Graby, Yashesh Mody, Pia F P Charters, Tim A Burnett, David Murphy, Ali Khavandi, Jonathan C L Rodrigues","doi":"10.1007/s00330-025-11553-w","DOIUrl":"https://doi.org/10.1007/s00330-025-11553-w","url":null,"abstract":"<p><strong>Objective: </strong>BSCI/BSTI guidelines recommend reporting aortic valve calcification (AVC) on all chest CTs regardless of indication. We assessed AVC frequency, severity, and association with aortic stenosis (AS) on echocardiography and its prognostic implications.</p><p><strong>Methods: </strong>Retrospective, single-centre analysis of consecutive chest CTs (January-December 2015) for 200 patients per age group (< 40, 40-49, 50-59, 60-69, 70-79, 80-89, ≥ 90) performed for medical, surgical, and oncological indications. CTs were re-reviewed for the presence and graded severity of AVC and coronary artery calcification (CAC). Corresponding echocardiography reports (within 5 years) reviewed for AS. Comorbidities and clinical outcomes were recorded.</p><p><strong>Results: </strong>One thousand three hundred seventy-seven patients were included (mean age 64 ± 20 years, 55% female). AVC was present in 25% (350/1377) and was more prevalent in males (p < 0.001). Frequency and severity increased with age (p < 0.001). 38% (524/1377) had an echocardiogram (median inter-test interval 4.3 months [IQR 0.4-17.5]). Sixteen per cent (29/178) with AVC had AS of any severity (8% [15/178] mild; 8% [14/178] moderate; 0% [0/178] severe). Sensitivity and specificity for AVC predicting AS were 91% and 70%, respectively. Extrapolating findings, 8% of individuals with AVC and without an echocardiogram may have undiagnosed AS. All-cause mortality occurred in 53% (734/1377), which AVC predicted independently of CAC and age (p < 0.001). Adjusting for confounders, severe AVC predicted all-cause mortality (HR 1.56 [1.10-2.22], p = 0.013).</p><p><strong>Conclusions: </strong>AVC identified AS in 16% of patients. Additionally, severe AVC is an independent predictor of all-cause mortality in multivariable analysis. Validation in a prospective cohort is required to inform clinical practice guidelines.</p><p><strong>Key points: </strong>Question New guidelines recommend reporting AVC on all non-gated chest CTs, the prognostic and clinical relevance of which is uncertain. Findings There are associations between visually quantified AVC, AS on echocardiography, and all-cause mortality in an unselected population referred for routine chest CT. Clinical relevance These results support the reporting of all severities of AVC, especially severe AVC, as a prognostic marker in all age groups. The clinical implications require further clarification in a prospective cohort.</p>","PeriodicalId":12076,"journal":{"name":"European Radiology","volume":" ","pages":""},"PeriodicalIF":4.7,"publicationDate":"2025-04-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143763542","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":"The pericoronary fat attenuation index in cardio-oncology: a promising imaging biomarker and a need for standardization.","authors":"Costanza Lisi, Matthias Eberhard","doi":"10.1007/s00330-025-11481-9","DOIUrl":"https://doi.org/10.1007/s00330-025-11481-9","url":null,"abstract":"","PeriodicalId":12076,"journal":{"name":"European Radiology","volume":" ","pages":""},"PeriodicalIF":4.7,"publicationDate":"2025-04-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143763501","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}