Radiology. Cardiothoracic imaging最新文献

Purpose To assess the predictive value of left atrial (LA) fast long-axis strain derived from cardiac MRI for thrombotic events (TEs) in individuals with hypertrophic cardiomyopathy (HCM). Materials and Methods This secondary analysis of an ongoing prospective trial (Chinese Clinical Trial Registry: ChiCTR1900024094) included consecutive participants with HCM without atrial fibrillation (AF) who underwent cardiac MRI from January 2012 to December 2020. The LA fast long-axis strain was obtained by semiautomatically tracking the distance between the atrioventricular junction and the midposterior LA wall. The primary end point was the occurrence of TEs, including ischemic stroke, transient ischemic attack, and systemic thromboembolism. The predictive value of LA strain was determined with Cox analysis. Results Overall, 714 participants with HCM (mean age ± SD, 50.1 years ± 14.3; 441 men, 273 women; obstructive HCM, n = 289; apical HCM, n = 144) were included (median follow-up: 51 months). Twenty-eight (3.9%) participants with HCM experienced TEs, 60% (17 of 28) of whom had no new-onset AF. Those who experienced TEs had lower LA reservoir and conduit strains (16.2% ± 7.3 vs 21.8% ± 8.3, P = .001; 5.9% ± 3.5 vs 9.7% ± 5.5, P = .01, respectively), with no evidence of a difference in LA booster strain between groups. LA reservoir and conduit strain were independent predictors of TEs in different multivariable models, even after adjusting for age, diabetes, and left ventricular ejection fraction (adjusted hazard ratios: reservoir strain [per 5% decrease], 1.29-1.34 [95% CI: 1.05, 1.50]; conduit strain [per 5% decrease], 1.42-1.47 [95% CI: 1.04, 1.67]). Conclusion Cardiac MRI-derived LA reservoir and conduit strain were independent predictors for the occurrence of TEs in individuals with HCM without AF. Keywords: MR-Imaging, Left Atrium, Cardiomyopathies, Hypertrophic Cardiomyopathy, Thromboembolism, Cardiac Magnetic Resonance Chinese Clinical Trial Registry no. ChiCTR1900024094 Supplemental material is available for this article. © RSNA, 2025.

Purpose To compare the acquisition time, image quality, and late gadolinium enhancement (LGE) visualization and quantification on phase-sensitive inversion recovery (PSIR) images using 5.0-T versus 3.0-T cardiac MRI. Materials and Methods In this prospective crossover study, 49 participants (mean ± SD age, 43.7 years ± 13.1; 39 men) suspected or diagnosed with nonischemic cardiomyopathy were enrolled from April 2023 to March 2024 and randomly assigned to group 1 (5.0-T followed by 3.0-T LGE cardiac MRI) or group 2 (3.0-T followed by 5.0-T LGE cardiac MRI). PSIR images were acquired at spatial resolutions of 1.2, 0.9, and 1.6 mm. Image quality and LGE were qualitatively evaluated using a five-point Likert scale by two readers, and signal-to-noise ratio, contrast-to-noise ratio, and LGE mass were quantitatively assessed. Bland-Altman plots were used to evaluate interreader agreement. Results There was no evidence of a difference in the acquisition time for obtaining a single-layer PSIR image at 5.0 T compared with 3.0 T (P > .05 for all), irrespective of resolutions at 1.2, 0.9, and 1.6 mm. The 5.0-T PSIR images demonstrated better image quality and LGE visualization compared with 3.0-T images, particularly at 1.2 mm (image quality: median 5 [IQR, 5-5] vs median 5 [IQR, 4-5]; P = .004; LGE score: median 5 [IQR, 5-5] vs median 4.25 [IQR, 4-5]; P < .001). No evidence of differences in image quality or LGE scores was found between 5.0-T and 3.0-T cardiac MRI at 1.6-mm resolution. Signal-to-noise ratio and contrast-to-noise ratio were higher on 5.0-T PSIR images across all resolutions compared with 3.0-T images (P < .001 for all), but no evidence of a difference was found in LGE mass measurements. Conclusion The study demonstrates that 5.0-T PSIR imaging offers better image quality and LGE visualization than 3.0-T PSIR, particularly at a 1.2-mm resolution, in individuals with nonischemic cardiomyopathy. Keywords: MRI, Cardiac, Heart, Comparative Studies, Nonischemic Cardiomyopathy, Late Gadolinium Enhancement, Phase-Sensitive Inversion Recovery Supplemental material is available for this article. ©RSNA, 2024.

Purpose To provide reference values for four-dimensional (4D) flow MRI in healthy fetuses and evaluate reliability of fetal 4D flow MRI hemodynamics in third trimester fetuses with normal cardiovascular development or suspected coarctation of the aorta (CoA). Materials and Methods Pregnant patients with healthy fetuses or fetuses with echocardiographic concern for CoA were prospectively recruited between May 2021 and October 2023. Doppler US-gated fetal 4D flow MRI was performed at 3 T. Repeated 4D flow (time permitting) and two-dimensional (2D) phase contrast (PC) MRI data were acquired. Net flow was quantified, and the reliability of 4D flow measurement was evaluated by using precision across adjacent measurement planes, internal consistency based on conservation of mass, comparison of net flow from 4D flow MRI versus 2D PC MRI, and repeatability of 4D flow from separate acquisitions. Results Data were obtained in 34 pregnant participants (mean maternal age, 33 years ± 5 [SD]; mean gestational age, 35 weeks ± 2; n = 22 healthy fetuses and 12 fetuses with suspected CoA). Precision was high across all vascular segments (mean within-subject coefficient of variation = 7%). For mass conservation, there was an average difference of 19% ± 12 between ductus arteriosus plus isthmus flow versus descending aorta flow (r = 0.76). Net flow measured with 4D flow MRI correlated with that measured with 2D PC MRI (r = 0.51) but was underestimated relative to 2D PC MRI by approximately 34%. Hemodynamic parameters quantified from repeated 4D flow acquisitions had good agreement, with an intraclass correlation coefficient of 0.94 between test and retest data. Conclusion Hemodynamic measurements derived from fetal 4D flow MRI were reliable, showing good internal consistency, precision, and repeatability; however, as expected, 4D flow MRI underestimated absolute blood flow relative to 2D PC MRI. Keywords: Fetal MRI, Cardiac, Aorta, Hemodynamics/Flow Dynamics, Pulmonary Arteries Supplemental material is available for this article. © RSNA, 2024.

Purpose To measure the benefit of single-phase CT, inspiratory-expiratory CT, and clinical data for convolutional neural network (CNN)-based chronic obstructive pulmonary disease (COPD) staging. Materials and Methods This retrospective study included inspiratory and expiratory lung CT images and spirometry measurements acquired between November 2007 and April 2011 from 8893 participants (mean age, 59.6 years ± 9.0 [SD]; 53.3% [4738 of 8893] male) in the COPDGene phase I cohort (ClinicalTrials.gov: NCT00608764). CNNs were trained to predict spirometry measurements (forced expiratory volume in 1 second [FEV₁], FEV₁ percent predicted, and ratio of FEV₁ to forced vital capacity [FEV₁/FVC]) using clinical data and either single-phase or multiphase CT. Spirometry predictions were then used to predict Global Initiative for Chronic Obstructive Lung Disease (GOLD) stage. Agreement between CNN-predicted and reference standard spirometry measurements and GOLD stage was assessed using intraclass correlation coefficient (ICC) and compared using bootstrapping. Accuracy for predicting GOLD stage, within-one GOLD stage, and GOLD 0 versus 1-4 was calculated. Results CNN-predicted and reference standard spirometry measurements showed moderate to good agreement (ICC, 0.66-0.79), which improved by inclusion of clinical data (ICC, 0.70-0.85; P ≤ .04), except for FEV₁/FVC in the inspiratory-phase CNN model with clinical data (P = .35) and FEV₁ in the expiratory-phase CNN model with clinical data (P = .33). Single-phase CNN accuracies for GOLD stage, within-one stage, and diagnosis ranged from 59.8% to 84.1% (682-959 of 1140), with moderate to good agreement (ICC, 0.68-0.70). Accuracies of CNN models using inspiratory and expiratory images ranged from 60.0% to 86.3% (684-984 of 1140), with moderate to good agreement (ICC, 0.72). Inclusion of clinical data improved agreement and accuracy for both the single-phase CNNs (ICC, 0.72; P ≤ .001; accuracy, 65.2%-85.8% [743-978 of 1140]) and inspiratory-expiratory CNNs (ICC, 0.77-0.78; P ≤ .001; accuracy, 67.6%-88.0% [771-1003 of 1140]), except expiratory CNN with clinical data (no change in GOLD stage ICC; P = .08). Conclusion CNN-based COPD diagnosis and staging using single-phase CT provides comparable accuracy with inspiratory-expiratory CT when provided clinical data relevant to staging. Keywords: Convolutional Neural Network, Chronic Obstructive Pulmonary Disease, CT, Severity Staging, Attention Map Supplemental material is available for this article. © RSNA, 2024.

Purpose To assess the diagnostic performance of a coronary CT angiography (CCTA) artificial intelligence (AI)-enabled tool (AI-QCPA; HeartFlow) to quantify plaque volume, as compared with intravascular US (IVUS). Materials and Methods A retrospective subanalysis of a single-center prospective registry study was conducted in participants with ST-elevation myocardial infarction treated with primary percutaneous coronary intervention of the culprit vessel. Participants with greater than 50% stenosis in nonculprit vessels underwent CCTA, invasive coronary angiography, and IVUS of nonculprit lesion(s) between 2 and 40 days after primary percutaneous coronary intervention. Comparisons of plaque volumes obtained using AI-QCPA (HeartFlow) and IVUS were assessed using Spearman rank correlation (ρ) and Bland-Altman analysis. Results Thirty-three participants (mean age, 59.1 years ± 8.8 [SD]; 27 [82%] male and six [18%] female participants) and 67 vessels were included for analysis. There was strong agreement between AI-QCPA and IVUS in vessel (ρ = 0.94) and lumen volumes (ρ = 0.97). High agreement between AI-QCPA and IVUS was also found for total plaque volume (ρ = 0.92), noncalcified plaque (ρ = 0.91), and calcified plaque (ρ = 0.87). Bland-Altman analysis demonstrated AI-QCPA underestimated total plaque volume (-9.4 mm³) and calcified plaque (-11.4 mm³) and overestimated for noncalcified plaque (2.0 mm³) when compared with IVUS. Conclusion An AI-enabled automated plaque quantification tool for CCTA had high agreement with IVUS for quantifying plaque volume and characterizing plaque. Keywords: Coronary Plaque, Intravascular US, Coronary CT Angiography, Artificial Intelligence Supplemental material is available for this article. ClinicalTrials.gov registration no. NCT02926755 © RSNA, 2024.

Purpose To determine the prevalence of mitral annular disjunction (MAD) in patients undergoing cardiac MRI for various clinical indications and to assess the association of MAD with arrhythmia, mitral valve prolapse (MVP), and myocardial alteration. Materials and Methods This study analyzed data from a retrospective observational registry of consecutive patients undergoing cardiac MRI for different clinical indications. Cardiac MRI examinations were performed from January 2019 to June 2019 at 13 Italian hospitals. Images underwent double reading by expert cardiac radiologists from the enrolling center and the core laboratory to assess the presence of MAD. Presence and maximum length of MAD and its association to MVP pattern, functional and structural myocardial alteration, and arrhythmia were evaluated using nonparametric and parametric tests. Logistic regression models were used to identify predictors of arrhythmia. Results Cardiac MRI studies from 2611 consecutive patients (1730, 66% male; median age, 53 years; IQR, 39-65 years) were evaluated. Prevalence of MAD was 5.44% (142 of 2611). MAD was an incidental finding in 74.6% (106 of 142) of patients. Patients with MAD had a higher prevalence of arrhythmias compared with patients without MAD (40% [57 of 142] vs 18% [444 of 2469]; P < .001). Patients with MAD and bileaflet MVP showed a longer MAD compared with patients with single-leaflet or absent MVP (median, 7 mm [IQR, 3-9.5 mm] vs 4 mm [IQR, 3-5 mm]; P < .001), a higher prevalence of systolic curling (75% [21 of 28] vs 30.7% [35 of 114]; P < .001), higher extracellular volume values (30% [IQR, 28%-32%] vs 27% [IQR, 25%-30%]; P = .04), and a higher prevalence of arrhythmia (64.2% [18 of 28] vs 34.2% [39 of 114]; P = .006). MAD length of at least 5 mm was an independent predictor of arrhythmia (odds ratio 3.96; 95% CI: 1.93, 8.15; P < .001). Conclusion MAD was a frequent incidental finding on cardiac MRI scans from a multicenter registry. MAD length of at least 5 mm and coexisting bileaflet MVP showed a higher risk of arrhythmia. Keywords: MR Imaging, Cardiac, Mitral Annular Disjunction Supplemental material is available for this article. ©RSNA, 2024.

Purpose To establish a COronary Risk Score in WOmen (CORSWO) to predict major adverse coronary events (MACE). Materials and Methods This retrospective analysis included 2226 female individuals (mean age, 66.7 years ± 11.6 [SD]) from a cohort of 25 943 consecutive patients referred for clinical gated SPECT myocardial perfusion imaging (gSPECT MPI). During the follow-up (mean, 4 years ± 2.7) after gSPECT MPI, occurrence of MACE (unstable angina requiring hospitalization, nonfatal myocardial infarction, coronary revascularization, cardiac death) was assessed. The patients were divided into training (n = 1460) and validation (n = 766) groups. To obtain the predictor model, multiple Cox regression analyses were performed. Results In the training group, 148 female individuals had MACE (2.6% per year). The best model (area under the receiver operating characteristic curve [AUC]: 0.80 [95% CI: 0.74, 0.83]; Brier score: 0.08) to predict MACE in female individuals included the following variables: age older than 69 years (hazard ratio [HR]: 1.58, P = .01), diabetes mellitus (HR: 1.47, P = .03), pharmacologic test (HR: 1.63, P = .01), ST-segment depression (≥1 mm) (HR: 2.02, P < .001), myocardial ischemia greater than 5% (HR: 2.21, P < .001), perfusion defect at rest greater than 9% (HR: 1.96, P = .009), perfusion defect at stress greater than 6% (HR: 1.63, P = .03), and end-systolic volume index greater than 15 mL (HR: 2.04, P < .001). During validation, the model achieved moderate performance (AUC: 0.78 [95% CI: 0.70, 0.83]). CORSWO obtained from these variables allowed for stratification of female individuals into four risk levels: low (score: 0-3, HR: 1), moderate (score: 4-6, HR: 1.58), high (score: 7-11, HR: 4.13), and very high (score: >11, HR: 13.87). The high and very high risk levels (HR: 5.29) predicted MACE in female individuals, with excellent performance (AUC: 0.78 [95% CI: 0.72, 0.80]). Conclusion With clinical, stress test, and gSPECT MPI variables, CORSWO effectively stratified female individuals according to coronary risk and was able to detect those with high and very high risk. Keywords: SPECT, Cardiac, Coronary Arteries, Women, Risk Stratification, Cardiac Event, CORSWO, MACE, Gated SPECT Supplemental material is available for this article. ©RSNA, 2024.