Radiology. Cardiothoracic imaging最新文献

{"title":"Cardiac MRI for Preprocedural Assessment in Participants with Nonvalvular Atrial Fibrillation Undergoing Left Atrial Appendage Closure.","authors":"Masahiko Asami, Yu Horiuchi, Jun Tanaka, Naoki Hosoda, Kai Ninomiya, Teruya Akagi, Yosuke Nakatani, Masanori Taniwaki, Kota Komiyama, Hitomi Yuzawa, Kengo Tanabe, Hideki Ishii","doi":"10.1148/ryct.250475","DOIUrl":"10.1148/ryct.250475","url":null,"abstract":"<p><p>Purpose To evaluate the feasibility of cardiac MRI for preprocedural left atrial appendage closure (LAAC) planning and to compare cardiac MRI- and transesophageal echocardiography (TEE)-derived measurements. Materials and Methods Patients with nonvalvular atrial fibrillation who were suitable candidates for LAAC between October 2019 and July 2023 were included in this prospective single-center study. Participants underwent preprocedural TEE and cardiac MRI for the measurement of LAA ostium diameter and depth at four angles (0°, 45°, 90°, and 135°), and measurements were compared between modalities. Participants were stratified by renal function (chronic kidney disease [CKD] group: estimated glomerular filtration rate ([eGFR], <60 mL/min/1.73 m²; non-CKD group: eGFR, ≥60 mL/min/1.73 m²). A subgroup of participants also underwent cardiac CT angiography (CCTA). LAA dimensions were analyzed using Pearson correlation and Bland-Altman analyses. Results A total of 108 participants were included (mean age, 76.5 years ± 7.8 [SD]; 77 male; CKD group, <i>n</i> = 79; non-CKD group, <i>n</i> = 29). TEE- and cardiac MRI-derived LAA ostium diameter measurements showed moderate-to-strong correlation (<i>r</i> = 0.530-0.737), regardless of CKD status. LAA depth measurements showed weak-to-moderate correlation between modalities, with systematically lower measurements for TEE. Agreement between cardiac MRI- and TEE-derived measurements across morphology subtypes was poor. Among the 40 participants who also underwent CCTA, cardiac MRI-derived LAA ostium diameter measurements demonstrated strong correlation with CCTA-derived measurements (<i>r</i> = 0.60-0.82), without systematic bias. Conclusion Cardiac MRI is a reliable, contrast material-free alternative to TEE and CCTA for preprocedural LAAC planning, with measurements unaffected by renal function. <b>Keywords:</b> Left Atrial Appendage Closure, Cardiac MRI, Transesophageal Echocardiography, Cardiac CT Angiography, Chronic Kidney Disease University Hospital Medical Information Network Clinical Trials Registry no. UMIN000040200 <i>Supplemental material is available for this article.</i> © RSNA, 2026.</p>","PeriodicalId":21168,"journal":{"name":"Radiology. Cardiothoracic imaging","volume":"8 2","pages":"e250475"},"PeriodicalIF":4.5,"publicationDate":"2026-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147779841","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Extraskeletal Osteosarcoma of Mediastinal Origin.","authors":"Xinran Huang, Qingchao Meng, Bin Lu","doi":"10.1148/ryct.250271","DOIUrl":"10.1148/ryct.250271","url":null,"abstract":"<p><p>Mediastinal extraskeletal osteosarcoma (ESOS) with cardiac involvement is extremely rare and aggressive. The authors describe a 56-year-old male individual presenting with chest tightness and dyspnea. Imaging revealed a large pericardial mass compressing the right atrium. Surgical resection was performed, and histopathology findings confirmed high-grade ESOS. The patient underwent adjuvant radiation therapy and chemotherapy. At 6 months, pulmonary metastases were detected, prompting treatment adjustment. At 11-month follow-up, the patient remained clinically stable. This case underscores the utility of multimodality imaging and the diagnostic and therapeutic challenges of this rare malignancy. <b>Keywords:</b> Cardiac, Oncology © RSNA, 2026.</p>","PeriodicalId":21168,"journal":{"name":"Radiology. Cardiothoracic imaging","volume":"8 2","pages":"e250271"},"PeriodicalIF":4.5,"publicationDate":"2026-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147487182","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Impact of Radiation Therapy for Breast Cancer on the Coronary Artery Disease Profile at Cardiac CT.","authors":"Johannes Deeg, Michael Swoboda, Pietro G Lacaita, Fabian Barbieri, Valentin Ladenhauf, Yannick Scharll, Anna Luger, Valentin Bilgeri, Britta Forthuber, Leonhard Gruber, Gerlig Widmann, Gudrun M Feuchtner","doi":"10.1148/ryct.250415","DOIUrl":"10.1148/ryct.250415","url":null,"abstract":"<p><p>Purpose To evaluate the coronary artery disease (CAD) profile and valvular and structural alterations seen at coronary CT angiography (CTA) after radiation therapy (RT) for breast cancer in a case-control study. Materials and Methods Patients who underwent clinically indicated coronary CTA were included in this retrospective study. The following parameters were evaluated: coronary artery calcium (CAC) score, Coronary Artery Disease Reporting and Data System (CAD-RADS) score, high-risk plaque (HRP) phenotypes, and extracoronary findings (valvular fibrosis, fibrous adherence). Patients with breast cancer who underwent RT were propensity score-matched with controls (level: <i>P</i> = .05) for age, body mass index, and major cardiovascular risk factors to reduce selection bias and confounding. Results Among 154 female patients (mean age, 65.23 years ± 10.4 [SD]; 77 patients in RT group, 77 patients in control group), there was no evidence of a difference in CAC score between the RT and control groups (201.1 vs 75.4 Agatston units [AU], <i>P</i> = .64). No difference was seen in coronary stenosis severity (CAD-RADS score) (<i>P</i> = .40) or obstructive disease (>50% stenosis) rate (29% [22 of 77] vs 23% [18 of 77], <i>P</i> = .46; odds ratio [OR], 1.31 [95% CI: 0.63, 2.73]). No between-group difference was observed in high-risk plaque phenotype rate (9% [seven of 77] vs 17% [13 of 77], <i>P</i> = .23) or CAC or CAD-RADS scores. There was no evidence of a difference between left versus right RT for CAC (309 vs 120 AU, <i>P</i> = .23), coronary stenosis severity (CAD-RADS score, <i>P</i> = .43), or HRP phenotype rate (left, 11% [four of 36]; right, 6% [two of 34]). The prevalences of valvular fibrosis and calcifications were low (5% [four of 77] vs 3% [two of 77] [<i>P</i> = .68] and 16% [12 of 77] vs 9% [seven of 77] [<i>P</i> = .37], respectively; OR, 1.84 [95% CI: 0.68, 5.25]). The prevalence of fibrous adherence of the left anterior descending coronary artery or right coronary artery to the chambers was 1.4-fold higher in the RT group (29% [22 of 77] vs 13% [17 of 77] [<i>P</i> = .46]; OR, 1.41 [95% CI: 0.68, 2.97]). Conclusion RT for breast cancer was not associated with more severe coronary stenosis, HRP phenotypes, or valvular fibrosis in this case-control population cohort. <b>Keywords:</b> Coronary Arteries, Radiation Effects, CT-Coronary Angiography, Cardiac, Breast, Breast Cancer, Radiation Therapy, Cardiovascular Risk, Computed Tomography, Coronary Artery Disease <i>Supplemental material is available for this article.</i> © RSNA, 2026.</p>","PeriodicalId":21168,"journal":{"name":"Radiology. Cardiothoracic imaging","volume":"8 2","pages":"e250415"},"PeriodicalIF":4.5,"publicationDate":"2026-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147514410","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Diagnosis and Treatment Guided by 3D Imaging and Modeling: A W-shaped Interventricular Septal Phenotype in Hypertrophic Obstructive Cardiomyopathy.","authors":"Uladzimir Andrushchuk, Artsem Niavyhlas, Miłosz Nesterowicz, Wiktoria Dzieżyk, Tomasz Chrostowski, Dorota Sulima, Dzmitry Tretsiakou, Annet Litvinenko, Mikalai Shchatsinka","doi":"10.1148/ryct.250471","DOIUrl":"10.1148/ryct.250471","url":null,"abstract":"<p><p>Surgical treatment of hypertrophic obstructive cardiomyopathy is challenging. It requires balancing adequate myocardial excision against the risk of excessive resection, which can result in an iatrogenic ventricular septal defect. To our knowledge, this is the first reported case of a high-risk septal myectomy in complex anatomy W-shaped hypertrophic obstructive cardiomyopathy with a deep interventricular septum crypt and apical aneurysm. CT angiography-based three-dimensional modeling of the interventricular septum and a virtual myectomy enabled detailed preoperative planning and successful surgery. This planning also informed the choice of a combined transaortic and transapical surgical approach tailored to the patient's anatomy. <b>Keywords:</b> CT Angiography, MR Imaging, Cardiac, Heart, Left Ventricle, Anatomy, Cardiomyopathies, Computer Applications-3D, Computer Applications-Virtual, Segmentation, Modeling, Myocardium, 3D Computer Model, 3D Printing, Cardiac CT Angiography, Cardiac CTA, Cardiac MRI, HOCM, Hypertrophic Obstructive Cardiomyopathy, Septal Myectomy © RSNA, 2026.</p>","PeriodicalId":21168,"journal":{"name":"Radiology. Cardiothoracic imaging","volume":"8 2","pages":"e250471"},"PeriodicalIF":4.5,"publicationDate":"2026-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147434846","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Deep Learning Segmentation of Pectoralis Muscle Volume at CT and Comparison with Pectoralis Muscle Area in COPD.","authors":"Daniel Genkin, Mustansir Verdawala, Sophie É Collins, Wan C Tan, Pei Z Li, Jean Bourbeau, Michael K Stickland, Dennis Jensen, Miranda Kirby","doi":"10.1148/ryct.250060","DOIUrl":"10.1148/ryct.250060","url":null,"abstract":"<p><p>Purpose To develop a deep learning model for segmenting pectoralis muscle volume (PMV) at CT and evaluate the reproducibility, group differences, and associations of pectoralis muscle area (PMA) and PMV with chronic obstructive pulmonary disease (COPD)-related outcomes. Materials and Methods This study was a secondary analysis of the prospective Canadian Cohort Obstructive Lung Disease study (CanCOLD, data collected from November 2009 to July 2015). Randomly sampled CT scans from CanCOLD were used for model training, validation, and internal testing (<i>n</i> = 96, 16, and 32, respectively) and an external dataset for external testing (<i>n</i> = 32). A U-Net model was trained for PMV segmentation, and performance was assessed using the Dice similarity coefficient (DSC). PMA and PMV values were extracted from paired inspiration and expiration scans to assess segmentation reproducibility. Differences between individuals with or without COPD and associations with forced expiratory volume in 1 second (FEV₁), diffusing capacity of the lungs for carbon monoxide (Dlco), and peak oxygen uptake during exercise (VO₂) were reported. Results Individuals included those with (<i>n</i> = 634; mean age, 67.3 years ± 10.1 [SD]; 394 male participants) and without (<i>n</i> = 601; mean age, 65.8 years ± 9.6; 327 male participants) COPD. The model yielded DSCs of 0.94 ± 0.04, 0.93 ± 0.03, and 0.92 ± 0.04 in the training and validation, internal testing, and external testing datasets, respectively. Contrary to PMV (bias, 0.1 cm³; <i>P</i> = .77), PMA showed bias between inspiration and expiration (bias, -2.7 cm²; <i>P</i> < .001). Both PMA and PMV were reduced in patients with COPD (<i>P</i> < .05), but PMV was more strongly associated with FEV₁ (adjusted <i>R</i>² [<i>R</i>_adj²], 0.609/0.598), Dlco (<i>R</i>_adj², 0.645/0.627), and VO₂ (<i>R</i>_adj², 0.680/0.666). Conclusion An accurate and generalizable CT-based deep learning model for pectoralis muscle segmentation was developed. Compared with PMA, PMV showed better reproducibility and stronger associations with COPD outcomes. <b>Keywords:</b> CT, Thorax, Lung, Volume Analysis, Chronic Obstructive Pulmonary Disease, Segmentation ClinicalTrials.gov identifier no. NCT00920348 © RSNA, 2026 <i>Supplemental material is available for this article.</i></p>","PeriodicalId":21168,"journal":{"name":"Radiology. Cardiothoracic imaging","volume":"8 2","pages":"e250060"},"PeriodicalIF":4.5,"publicationDate":"2026-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147356192","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Quantifying the Spectrum of Myocardial Fibrosis with Cardiovascular MRI: A Histopathologic Validation Study in Swine.","authors":"Huaying Zhang, Cui Chen, Wenjing Yang, Di Zhou, Yining Wang, Leyi Zhu, Mengdi Jiang, Qiang Zhang, Shihua Zhao, Stefan K Piechnik, Vanessa M Ferreira, Minjie Lu","doi":"10.1148/ryct.250476","DOIUrl":"10.1148/ryct.250476","url":null,"abstract":"<p><p>Purpose To histologically validate T1 mapping for quantitative assessment of mild-to-severe myocardial fibrosis in a swine model of chronic myocardial infarction (MI). Materials and Methods In this animal study conducted from June 2021 to July 2022, 18 male miniature swine (16 MI animals; two healthy control animals) underwent cardiac MRI, including cine imaging, late gadolinium enhancement (LGE) imaging, T1 mapping, and extracellular volume fraction (ECV) mapping. Two T1 mapping techniques, modified Look-Locker inversion recovery (MOLLI) and shortened MOLLI (ShMOLLI), were evaluated. Pathologic myocardial slices were categorized as infarcted, peri-infarct, remote, and healthy based on triphenyl tetrazolium chloride staining. Fibrosis was quantified using collagen volume fraction (CVF) and classified as severe (CVF, ≥30%), moderate (CVF, >15%-30%), or mild (CVF, 3%-15%). Associations between cardiac MRI parameters and CVF were assessed, and diagnostic performance in detecting myocardial fibrosis was evaluated using the area under the receiver operating characteristic curve (AUC). Results For detection of severe fibrosis, LGE, T1 mapping, and ECV all demonstrated excellent diagnostic performance (AUC range, 0.88-0.96). ECV using ShMOLLI showed significantly higher performance than ECV using MOLLI for detecting severe fibrosis (AUC, 0.96 vs 0.88; <i>P</i> = .03) and MI (AUC, 0.93 vs 0.87; <i>P</i> = .045), as well as the strongest correlation with histologic CVF (<i>r =</i> 0.90 for ECV with ShMOLLI, 0.84 for ECV with MOLLI, 0.74 for T1 with ShMOLLI, 0.77 for T1 with MOLLI, and 0.74 for LGE extent). In remote myocardium with mild fibrosis (CVF, 8.81%) compared with healthy myocardium (CVF, 2.21%), only T1 with ShMOLLI and ECV with ShMOLLI demonstrated significant differences (<i>P</i> < .05), whereas LGE and MOLLI-based parameters did not. Conclusion Cardiac MRI helped detect mild-to-severe myocardial fibrosis in close agreement with histologic findings. While all techniques helped accurately identify severe fibrosis, T1 mapping-particularly ECV using the ShMOLLI sequence-provided unique sensitivity for detecting low-grade fibrosis, underscoring the importance of sequence selection for precise myocardial tissue characterization and clinical trial design. <b>Keywords:</b> Myocardial Fibrosis, Heart, Histological Techniques, Magnetic Resonance Imaging, Swine <i>Supplemental material is available for this article.</i> © RSNA, 2026.</p>","PeriodicalId":21168,"journal":{"name":"Radiology. Cardiothoracic imaging","volume":"8 2","pages":"e250476"},"PeriodicalIF":4.5,"publicationDate":"2026-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147779770","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Chest CT Findings of <i>Pneumocystis jirovecii</i> Pneumonia in a Large Cohort of Patients Who Are Immunocompromised.","authors":"Aaron M Pulsipher, Kealy Ham, Holenarasipur R Vikram, Kyle J Henry, Emily R Thompson, Michael B Gotway","doi":"10.1148/ryct.250361","DOIUrl":"10.1148/ryct.250361","url":null,"abstract":"<p><p>Purpose To assess chest CT imaging manifestations of <i>Pneumocystis jirovecii</i> pneumonia (PJP) in a large, well-characterized cohort of patients who were immunocompromised and determine whether CT findings differ by immunocompromise etiology. Materials and Methods This retrospective study identified patients with proven or probable PJP across a multicenter hospital system over a 7-year period. Available chest CT scans were reviewed for the presence and distribution of ground-glass opacity (GGO), consolidation, interlobular septal thickening, fibrosis, nodules (characterized by size and distribution), and other findings. Imaging features and their evolution at follow-up CT were compared across immunocompromise etiologies and with the overall cohort using the Fisher exact test and Kruskal-Wallis test, as applicable. Results Among 701 evaluated patients, 675 (median age, 65 years [IQR, 54-73 years]; 423 male) had chest CT examinations available for review. Immunocompromise etiologies included hematologic malignancy (32.7%), solid neoplasia receiving chemotherapy (22.5%), autoimmune disease (17.3%), solid organ transplant (13.0%), bone marrow transplant (8.3%), corticosteroid therapy (8.1%), HIV infection (7.6%), and miscellaneous causes (4.6%). Across all etiologies, diffusely distributed GGO without distinguishing features was the most common CT finding (96.7%), with a random axial distribution in 80.1% of patients and peripheral dominance in 14.2%. Consolidation was present in 51.1% of patients. PJP CT findings substantially overlapped across immunocompromise etiologies, with no imaging pattern specific to a particular etiology. Follow-up CT was available in 71.6% of patients (median interval, 31 days; range, 2-1344 days), demonstrating PJP improvement in 66.0%, worsening in 25.5%, no change in 9.1%, and new CT patterns in 11.8%. Respiratory coinfection was present in 31.9% of patients. Conclusion PJP most commonly manifested as diffusely distributed GGO on chest CT scans, regardless of the underlying cause of immunocompromise. CT findings did not distinguish between HIV- and non-HIV-related immunosuppression, and respiratory coinfection was common. <b>Keywords:</b> <i>Pneumocystis jirovecii</i> Pneumonia, Immunosuppression, Immunocompromise, CT, Ground-Glass Opacity <i>Supplemental material is available for this article.</i> © RSNA, 2026.</p>","PeriodicalId":21168,"journal":{"name":"Radiology. Cardiothoracic imaging","volume":"8 2","pages":"e250361"},"PeriodicalIF":4.5,"publicationDate":"2026-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147699631","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Clinical Outcomes of Ground-Glass Nodules Detected in a CT Lung Cancer Screening Program.","authors":"Mark M Hammer, Kathryn A Schulz, Suzanne C Byrne","doi":"10.1148/ryct.250293","DOIUrl":"10.1148/ryct.250293","url":null,"abstract":"<p><p>Purpose To evaluate cancer outcomes, stage distribution, and mortality among patients with ground-glass nodules (GGNs) detected in a lung cancer screening program. Materials and Methods This retrospective study included patients in a CT lung cancer screening program (January 2015-July 2023) with a dominant GGN and a comparison group of patients with Lung Imaging Reporting and Data System (Lung-RADS) 1. All lung cancers in the GGN group were reviewed to determine whether they originated from the dominant nodule. Cancer stage and cause of death were obtained from medical records. Categorical variables were compared using the χ² test, and cancer development over time was compared using the log-rank test. Results Among 1724 patients (mean age, 65 years ± 6 [SD]; 917 female) in the screening program with a dominant GGN, 114 were diagnosed with lung cancer: 70 (61%) from the dominant GGN and 44 (39%) from another nodule. Stage 0 or I cancers were identified in 66 of 70 (94%) cancers arising from the dominant GGN versus 24 of 44 (55%) cancers from another nodule (<i>P</i> < .001). All 10 lung cancer-related deaths occurred from solid nodules unrelated to the GGNs. Patients with a dominant GGN were more likely than those with Lung-RADS 1 to develop cancers not related to the dominant nodule (<i>P</i> = .007). Conclusion Annual CT follow-up of patients with GGNs appears appropriate, as nearly all cancers were diagnosed at an early stage. However, these patients remain at risk for developing additional, separate lung cancers that may lead to mortality. <b>Keywords:</b> CT, Lung, Ground-Glass Nodules © RSNA, 2026.</p>","PeriodicalId":21168,"journal":{"name":"Radiology. Cardiothoracic imaging","volume":"8 1","pages":"e250293"},"PeriodicalIF":4.5,"publicationDate":"2026-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12949415/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145934799","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"AI-enabled Quantitative High-Risk Plaque Attributes for Predicting Coronary Events in Nonculprit Vessels.","authors":"Qian Chen, Xiaofei Gao, Ling Lin, Pengpeng Xu, Tao Pan, Xi Hu, Ya Liu, Yu Gong, Chao Zheng, Zhiwen Yang, Xinwei Tao, Hui Xu, Long Jiang Zhang, Jun-Jie Zhang","doi":"10.1148/ryct.250256","DOIUrl":"https://doi.org/10.1148/ryct.250256","url":null,"abstract":"<p><p>Purpose To assess the prognostic value of artificial intelligence (AI)-derived high-risk features obtained from coronary CT angiography (CCTA) in nonculprit vessels of patients who have undergone percutaneous coronary intervention. Materials and Methods This retrospective study included patients who underwent CCTA at a tertiary hospital between June 2013 and June 2023 followed by percutaneous coronary intervention within 3 months. AI-derived high-risk CCTA features were evaluated, including significant stenosis, high-risk plaque, high plaque volume, low CT fractional flow reserve, and high pericoronary adipose tissue attenuation. The primary end point was nonculprit vessel-related major adverse cardiac events (MACE). The prognostic value of high-risk CCTA features was assessed using multivariable Cox regression analyses. Results A total of 1495 patients (mean age, 66 years ± 10; 1100 male patients) with 2014 nonculprit vessels were analyzed with a median follow-up of 3.3 years. MACE occurred in 100 vessels (5.0%). In a multivariable Cox analysis adjusted for high-risk features, vessel-specific CT fractional flow reserve (adjusted hazard ratio, 0.14; 95% CI: 0.03, 0.76; <i>P</i> = .02) and necrotic core volume (adjusted hazard ratio, 1.30; 95% CI: 1.06, 1.59; <i>P</i> = .01) were independent predictors of MACE and showed an incremental prognostic value when added to clinical risk factors (area under the receiver operating characteristic curve, 0.60 vs 0.67; <i>P</i> < .001). Conclusion AI-derived high-risk features at CCTA provided independent and incremental prognostic values for nonculprit vessel-related MACE. <b>Keywords:</b> Computed Tomographic Angiography, High-Risk Plaque, Percutaneous Coronary Intervention <i>Supplemental material is available for this article.</i> © RSNA, 2026.</p>","PeriodicalId":21168,"journal":{"name":"Radiology. Cardiothoracic imaging","volume":"8 1","pages":"e250256"},"PeriodicalIF":4.2,"publicationDate":"2026-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147290935","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Artificial Intelligence-derived Measurements of Myosteatosis from Coronary Artery Calcium CT Scans to Predict COPD: The Multi-Ethnic Study of Atherosclerosis.","authors":"Amir Azimi, Kyle Atlas, Anthony P Reeves, Chenyu Zhang, Jakob Wasserthal, Seyed Reza Mirjalili, Thomas Atlas, Claudia I Henschke, David F Yankelevitz, Javier J Zulueta, Juan P de-Torres, Luis M Seijo, Jeffrey I Mechanick, Andrea Branch, Ning Ma, Rowena Yip, Wenjun Fan, Sion K Roy, Khurram Nasir, Sabee Molloi, Zahi A Fayad, Michael V McConnell, Ioannis A Kakadiaris, George S Abela, Rozemarijn Vliegenthart, David J Maron, Jagat Narula, Kim A Williams, Prediman K Shah, Matthew J Budoff, Daniel Levy, Emelia J Benjamin, Roxana Mehran, Robert A Kloner, Nathan D Wong, Morteza Naghavi","doi":"10.1148/ryct.250205","DOIUrl":"10.1148/ryct.250205","url":null,"abstract":"<p><p>Purpose To evaluate the predictive value of myosteatosis as an opportunistic finding in coronary artery calcium (CAC) CT scans for clinically diagnosed chronic obstructive pulmonary disease (COPD) and compare it with an artificial intelligence (AI)-measured biomarker of emphysema derived from the same scans. Materials and Methods In this prospective study, baseline CAC CT scans and 20-year follow-up data were analyzed. Myosteatosis was defined as the lowest quartile of thoracic skeletal muscle mean attenuation (males < 33.5 HU, females < 27.0 HU). The emphysema-like lung biomarker was quantified as the percentage of lung voxels below -950 HU in CAC CT scans. COPD was identified using the <i>International Classification of Diseases, Ninth Revision, Clinical Modification</i>, and <i>International Classification of Diseases, 10th Revision, Clinical Modification</i> diagnostic codes from hospital discharge records. Hazard ratios (HRs) for COPD were calculated using proportional hazard regression models, comparing the bottom versus top quartiles of myosteatosis and emphysema-like lung measurements. Results Among 5535 participants in the Multi-Ethnic Study of Atherosclerosis (mean age ± SD, 62.2 years ± 10.3, 47.6% males), 396 (7.1%) were diagnosed with COPD over the 20-year follow-up period. Myosteatosis showed a stronger association with COPD than emphysema (unadjusted HRs, 5.98 [95% CI: 4.14, 8.63] and 2.12 [95% CI: 1.61, 2.78], respectively [<i>P</i> < .001]). After adjusting for covariates (age, sex, smoking status, body mass index, race, asthma, physical activity, inflammatory markers, and insulin resistance), the HRs were reduced to 2.74 (95% CI: 1.81, 4.16) and 1.50 (95% CI: 1.12, 2.00), respectively (<i>P</i> = .02). Conclusion AI-measured myosteatosis in CAC CT scans strongly predicted future diagnosed COPD independently of known risk factors. <b>Keywords:</b> Applications-CT, Pulmonary, Thorax, Adipose Tissue (Obesity Studies), Chronic Obstructive Pulmonary Disease, Metabolic Disorders, Myosteatosis, Coronary Artery Calcium Scan, Emphysema, AI-CVD ClinicalTrials.gov: NCT00005487 <i>Supplemental material is available for this article.</i> © The Author(s) 2026. Published by the Radiological Society of North America under a CC BY 4.0 license.</p>","PeriodicalId":21168,"journal":{"name":"Radiology. Cardiothoracic imaging","volume":"8 1","pages":"e250205"},"PeriodicalIF":4.5,"publicationDate":"2026-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12951201/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146086815","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}