Radiology. Cardiothoracic imaging最新文献

Purpose To verify the accuracy of clinically used cardiac MRI T1 mapping sequences for measuring extracellular volume fraction (ECV) throughout the spectrum of pathologic values using an independent reference standard. Materials and Methods Acute myocardial ischemia was induced in six pigs using endovascular balloon occlusion in the left anterior descending artery between October 2018 and November 2018. After 7 days of reperfusion, ECV was measured in vivo using four sequences: three modified Look-Locker inversion recovery (MOLLI) and one saturation recovery single-shot acquisition (SASHA) sequences. ECV was also measured using ex vivo SPECT following injection of technetium 99m diethylenetriamine pentaacetic acid. ECV was calculated for corresponding regions of interest of necrosis on cardiac MR and SPECT images and in myocardium remote from injury. Mixed model analysis was used to test for correlation, while the paired t test was used to test for differences in T1 and ECV. Results ECV measurements with all T1 mapping sequences showed high correlation to the reference standard (r² range, 0.71-0.99). Measurements with MOLLI 5(3)3 and MOLLI 5s(3s)3s overestimated ECV in the infarct region compared with the reference standard (bias ± 2 SDs: 8.2% ± 8.5 and 4.9% ± 8.7; P = .005 and P = .04, respectively). All sequences showed overestimation of ECV in the remote region (range of bias, 3%-14% points, all MOLLI P values ≤ .001, SASHA P = .04). Conclusion This study verified the accuracy of clinically used T1 mapping sequences in measuring ECV in absolute values over a spectrum of pathologic values, using an independent radioisotope-based three-dimensionally acquired reference standard. Keywords: Animal Studies, MR Imaging, Cardiac, Edema, Imaging Sequences, Ischemia/Infarction Supplemental material is available for this article. © RSNA, 2025.

Purpose To evaluate the performance of a delayed-phase dynamic contrast-enhanced (dDCE) MRI model in quantitative assessment of myocardial tissue physiology and late gadolinium enhancement (LGE) within 5 minutes after contrast material injection in reperfused myocardial infarction (MI). Materials and Methods This animal study included 11 canines (seven female) with reperfused MI. A dDCE model using dynamic postcontrast T1 maps was adopted to depict an unbiased contrast material washout process. The dDCE parameters derived from the 30-minute contrast material washout process (dDCE_30min) and a 5-minute image subset (dDCE_5min) were compared. LGE images were synthesized from the dDCE_5min maps (LGE_dDCE) and compared LGE extent and transmurality with the standard LGE images acquired at 15 minutes after contrast material injection (LGE_standard). Statistical analyses used paired tests for dependent group comparisons. Results The dDCE_30min map demonstrated that extravascular extracellular volume and capillary permeability surface area product were higher in MI regions than in remote myocardium (61.12% ± 13.65 [SD] vs 13.43% ± 5.00; P = .02; 5.08 mL × g-1 × min-1 ± 4.10 vs 0.42 mL × g-1 × min-1 ± 0.55; P = .02, respectively). There was no evidence of differences between dDCE_5min parameters and dDCE_30min parameters (all P > .05). There was also no evidence of a difference between LGE_dDCE and LGE_standard in LGE area (30.65% ± 11.94 vs 30.66% ± 11.94; P = .99) or transmurality (54.87% ± 15.57 vs 53.27% ± 15.98; P = .06), but LGE_dDCE demonstrated a higher contrast-to-noise ratio (14.62 ± 13.03 vs 1.41 ± 0.97; P < .01). The area under the receiver operating characteristic curve of MI detection using LGE_dDCE was 0.97 (95% CI: 0.94, >0.99), with 94.4% sensitivity and 96.7% specificity. Conclusion The developed dDCE MRI model for myocardial tissue assessment shows potential to enhance lesion contrast, quantify clinically relevant physiologic parameters, and support comprehensive evaluation of myocardial injury in heart disease. Keywords: Dynamic Contrast-enhanced MRI, Myocardial Infarction, MRI, Pharmacokinetics, Ischemic Heart Disease Supplemental material is available for this article. © RSNA, 2025.

Purpose To investigate the prognostic value of left ventricular (LV) and scar entropy for major adverse cardiac events (MACEs) and ventricular arrhythmias (VAs) in patients who have experienced myocardial infarction (MI). Materials and Methods The medical records of patients who underwent late gadolinium enhancement (LGE) cardiac MRI following MI between October 2015 and September 2022 were retrospectively evaluated for MACEs and VAs. LV and scar entropy data were derived from the probability distributions of the pixel signal intensities of the LV myocardium and scar tissue, respectively. Cox proportional hazards regression was performed to investigate the prognostic value of LV and scar entropy for predicting MACEs and VAs. Results A total of 226 patients (mean age, 59 years ± 11 [SD], 170 [75.2%] male; LV ejection fraction, 40% ± 15) were followed for a median of 21 (IQR, 15-31) months and experienced 72 MACEs, which included VAs in 19 patients. Compared with patients in the low-LV entropy group, the risk of MACEs was higher in the high-LV entropy group (P < .001). The multivariable analysis showed that LV entropy was independently associated with MACEs (hazard ratio, 2.50 [95% CI: 1.55, 4.04]; P < .001). Multivariable analysis also showed that scar entropy was a significant predictor of VA (hazard ratio, 3.01 [95% CI: 1.02, 8.87]; P = .045). Conclusion LV entropy and scar entropy derived from LGE cardiac MRI were significant predictors of MACEs and VAs, respectively, in patients who have experienced MI. Keywords: Cardiac Imaging Techniques, MRI, Myocardial Infarction, Prognosis, Major Adverse Cardiac Events Supplemental material is available for this article. © RSNA, 2025.

Purpose To compare functional testing and management after cardiac CT-first versus invasive coronary angiography (ICA)-first strategies in participants with stable chest pain and low to intermediate probability of obstructive coronary artery disease (CAD) initially referred for ICA. Materials and Methods This study was a prespecified secondary analysis of the prospective, multicenter, randomized DISCHARGE (Diagnostic Imaging Strategies for Participants with Stable Chest Pain and Intermediate Risk of Coronary Artery Disease) trial (ClinicalTrials.gov no. NCT02400229) conducted between October 2015 and April 2019. The primary outcome was functional testing rates at each of the study sites after first test; secondary outcomes included revascularization, major postprocedure complications, and angina after a 3.5-year follow-up, all stratified by CAD severity. Comparisons were performed using adjusted multiple regression. Results Of 3561 participants (mean age, 60.1 years ± 10.1 [SD]; 2002 [56.2%] female), 3414 were included in the final analysis. CT-first resulted in more functional testing for obstructive CAD without high-risk anatomy as compared with ICA-first (114 of 214 [53.3%] vs 62 of 255 [24.3%]; adjusted odds ratio [OR], 3.55; 95% CI: 2.40, 5.28; P_interaction < .001). Revascularizations were lower for CT-first in obstructive CAD with high-risk anatomy (146 of 251 [58.2%] vs 161 of 196 [82.1%]; adjusted OR, 0.3; 95% CI: 0.19, 0.47) and without high-risk anatomy (81 of 214 [37.9%] vs 152 of 255 [59.6%]; adjusted OR, 0.41; 95% CI: 0.28, 0.60). ICA-first had more major complications with high-risk anatomy (11 of 196 [5.6%] vs five of 251 [2.0%]) and non-high-risk anatomy (11 of 255 [4.3%] vs two of 214 [0.9%]) than CT-first. Angina rates were similar (38 of 465 [8.2%] vs 32 of 451 [7.1%]; adjusted OR, 1.13; 95% CI: 0.69, 1.86). Conclusion A CT-first strategy increased functional testing, was influenced by CAD severity, and reduced revascularizations and major complications with similar angina rates after a 3.5-year follow-up compared with an ICA-first strategy in participants with stable chest pain. Keywords: CT Coronary Angiography, Coronary Arteries, Percutaneous, MR Perfusion, Cardiac, Heart, Comparative Studies Clinical trial registration no. NCT02400229 Supplemental material is available for this article. © RSNA, 2025.

Purpose To evaluate the diagnostic performance of artificial intelligence (AI) models in detecting and classifying aortic dissection (AD) from CT images through a systematic review and meta-analysis. Materials and Methods PubMed, Web of Science, Embase, and Medline were searched for articles published from January 2010 to October 2023. All primary studies were included. Quality of evidence was assessed using a composite tool based on the METhodological RadiomICs Score (ie, METRICS) and Checklist for Artificial Intelligence in Medical Imaging (ie, CLAIM) checklists, and risk of bias was assessed using the Quality Assessment of Diagnostic Accuracy Studies 2 (ie, QUADAS-2) tool. Univariate and bivariate meta-analyses were performed assessing individual and joint estimates of sensitivity and specificity. Results Thirteen studies were identified, with most using contrast-enhanced CT (CECT) imaging (n = 9) and the remainder using noncontrast CT (NCCT) imaging as their model input. Only three studies presented algorithms classifying AD by Stanford criteria. Univariate analysis of AI detection performance estimated sensitivity at 94% (95% CI: 88, 97; P = .049) and specificity at 88% (95% CI: 79, 94; P < .001). Bivariate analysis showed good overall model performances (area under the receiver operating characteristic curve [AUC], 0.97 [95% CI: 0.95, 0.99]; P = .49). Subgroup analyses revealed good performance for models using CECT images (sensitivity, 97% [95% CI: 81, 100; P = .007]; specificity, 93% [95% CI: 87, 97; P < .001]; AUC, 0.98 [95% CI: 0.93, 0.99; P = .09]) and NCCT images (sensitivity, 91% [95% CI: 83, 96; P = .33); specificity, 84% [95% CI: 69, 93; P < .001); AUC, 0.95 [95% CI: 0.90, 0.99; P = .14]). Most studies were of low quality and had high risk of bias. Conclusion AI can feasibly detect AD but does not demonstrate clinical applicability in its current form. Keywords: CT, Vascular, Cardiac, Aorta, Computer-aided Diagnosis (CAD), Meta-Analysis Supplemental material is available for this article. © RSNA, 2025.

Purpose Pericoronary adipose tissue attenuation (PCATa) measured at coronary CT angiography (CCTA) is an imaging biomarker of coronary inflammation associated with long-term adverse cardiac events. The authors hypothesized that PCATa may independently identify patients at risk for acute coronary syndromes (ACS). Materials and Methods The authors performed a retrospective substudy of the Incident Coronary Syndromes Identified by Computed Tomography (ICONIC) study, a propensity-matched case-control study of patients with CCTA followed by ACS. Two hundred analyzable case and control pairs were identified from the original 234 pairs. PCATa was measured using the adjusted attenuation of fat around proximal coronary vessels. The primary analysis applied conditional Cox models with cluster-robust standard errors to predict patient-level incident ACS, with adjustment for quantitative plaque volumes and clinical reporting-oriented findings of maximal stenosis and high-risk plaque features (HRPF). Results A total of 400 patients with 1174 matched measurable vessels were included. PCATa was not significantly different between patients with future ACS versus controls (-72.99 HU ± 9.42 vs -73.96 HU ± 9.47; P = .08). Conversely, PCATa was significantly associated with incident ACS events in Cox models (adjusted for noncalcified plaque hazard ratio [HR]: 1.015; 95% CI: 1.001, 1.028; P = .03; adjusted for total plaque HR: 1.015; 95% CI: 1.002, 1.029; P = .03; adjusted for stenosis and HRPF HR: 1.014; 95% CI: 1.000, 1.028; P = .049). Conclusion Limited quantitative difference in PCATa between patients and controls matched for risk factors and coronary artery disease suggests that PCATa may not be a useful single marker to identify future ACS. Nonetheless, significant differences seen in adjusted survival models identify a small biologic effect for increased risk of future ACS independent of traditional risk factors. Keywords: CT-Angiography, Inflammation, Coronary Arteries, Acute Coronary Syndrome, Pericoronary Adipose Tissue Attenuation, Noncalcified Plaque, ICONIC Study, Cardiovascular Risk Clinical trials registration no. NCT02959099 Supplemental material is available for this article. © RSNA, 2025.

Purpose To evaluate the effects of exercise on left ventricular parameters using exercise cardiac MRI in healthy adults without known cardiovascular disease and establish reference ranges stratified by age and sex. Materials and Methods This prospective study included healthy adult participants with no known cardiovascular disease or genetic variants associated with cardiomyopathy, enrolled between January 2018 and April 2021, who underwent exercise cardiac MRI evaluation. Participants were imaged at rest and after exercise, and parameters were measured by two readers. Prediction intervals were calculated and compared across sex and age groups. Results The study included 161 participants (mean age, 49 years ± 14 [SD]; 85 female). Compared with the resting state, exercise caused an increase in heart rate (64 beats per minute ± 9 vs 133 beats per minute ± 19, P < .001), left ventricular end-diastolic volume (140 mL ± 32 vs 148 mL ± 35, P < .001), stroke volume (82 mL ± 18 vs 102 mL ± 25, P < .001), ejection fraction (59% ± 6 vs 69% ± 7, P < .001), and cardiac output (5.2 L/min ± 1.1 vs 13.5 L/min ± 3.9, P < .001) and a decrease in left ventricular end-systolic volume (58 mL ± 18 vs 46 mL ± 15, P < .001). There were statistically significant differences in exercise response between groups stratified by sex and age for most parameters. Conclusion In healthy adults, an increase in cardiac output after exercise was driven by an increase in heart rate with both increased ventricular filling and emptying. Normal ranges for exercise response, stratified by age and sex, were established as a reference for the use of exercise cardiac MRI in clinical practice. Keywords: Cardiac, MR Imaging, Heart, Physiological Studies Supplemental material is available for this article. © RSNA, 2025.

Purpose To develop and evaluate a deep learning model for detecting hepatic steatosis using chest radiographs. Materials and Methods This retrospective study included consecutively collected chest radiographs from patients who underwent controlled attenuation parameter (CAP) examinations at two institutions from November 2013 to May 2023. All patients were diagnosed as having or not having hepatic steatosis based on CAP value. Patients from one institution were randomly divided into training, tuning, and internal test sets using an 8:1:1 ratio. Patients from the other institution comprised an external test set. A deep learning-based model to classify hepatic steatosis using chest radiographs was trained, tuned, and evaluated. Model performance on the internal and external test sets was assessed using the area under the receiver operating characteristic curve (AUC), accuracy, sensitivity, and specificity. Results In total, 6599 radiographs associated with 6599 CAP examinations obtained in 4414 patients were included. The internal test set included 529 radiographs from 363 patients (mean age, 56 years ± 11 [SD]; 344 male patients). The external test set included 1100 radiographs from 783 patients (mean age, 58 years ± 16; 604 male patients). The AUC, accuracy, sensitivity, and specificity (with 95% CIs) for the internal test set were 0.83 (0.79, 0.86), 77% (74, 81), 68% (61, 75), and 82% (77, 85), respectively. For the external test set, the values were 0.82 (0.79, 0.85), 76% (73, 78), 76% (69, 81), and 76% (73, 79), respectively. Conclusion The developed deep learning model showed good performance for detecting hepatic steatosis using chest radiographs. Keywords: Liver, Hepatic Steatosis, Chest Radiography, Controlled Attenuation Parameter Supplemental material is available for this article. © RSNA, 2025.

Purpose To evaluate coronary inflammation using pericoronary adipose tissue (PCAT) CT attenuation in patients with Kawasaki disease (KD) and determine the association of PCAT CT attenuation with coronary artery aneurysm (CAA), myocardial perfusion, and future coronary events (CEs). Materials and Methods This retrospective study included patients with KD and healthy controls who underwent coronary CT angiography (CCTA). Some patients also underwent cardiac MRI within 2 weeks of CCTA. Patients were split into subgroups according to presence or absence of CAA. PCAT CT attenuation and cardiac MRI-based myocardial perfusion were measured. CEs, including coronary artery thrombosis, obstruction, stenosis, procedural events, and acute ischemic events, were recorded. Associations were assessed using univariable and multivariable regression analyses and Spearman correlation analysis. Results One hundred patients with KD (mean age, 7.5 years ± 3.6 [SD]; 79 male) and 35 healthy controls (mean age, 8.4 years ± 2.8; 18 male) were included. Mean PCAT CT attenuation was higher in patients with CAA (n = 64) than in patients without CAA (n = 36) and healthy controls (-67.1 HU ± 6.4 vs -75.0 HU ± 8.6 and -77.0 HU ± 8.5, respectively; both P < .001). CAA presence (β = 7.20; P < .001) was independently associated with mean PCAT CT attenuation. Mean PCAT CT attenuation was negatively correlated with the global myocardial perfusion index (n = 18; r = -0.50; P = .02). During a median follow-up period of 19.7 months, 18 of 100 patients (18%) experienced CEs. Both mean PCAT CT attenuation (odds ratio [OR], 1.20 [95% CI: 1.00, 1.30]; P = .007) and the Z-score of the largest CAA (OR, 1.30 [95% CI: 1.10, 1.50]; P = .01) independently predicted CE occurrence. Conclusion In patients with KD, higher mean PCAT CT attenuation was associated with CAA presence and decreased myocardial perfusion and independently predicted occurrence of CEs. Keywords: Kawasaki Disease, Coronary CT Angiography, Pericoronary Adipose Tissue CT Attenuation, Coronary Artery Aneurysm, Myocardial Perfusion, Coronary Events Clinical trial registration no. ChiCTR2300076398 Supplemental material is available for this article. © RSNA, 2025.