Radiology. Cardiothoracic imaging最新文献

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.

Purpose To evaluate the performance of a high-dynamic-range quantitative susceptibility mapping (HDR-QSM) cardiac MRI technique to detect intramyocardial hemorrhage (IMH) and quantify iron content using phantom and canine models. Materials and Methods A free-running whole-heart HDR-QSM technique for IMH assessment was developed and evaluated in calibrated iron phantoms and 14 IMH female canine models. IMH detection and iron content quantification performance of this technique was compared with the conventional iron imaging approaches, R2*(1/T2*) maps, using measurements from ex vivo imaging as the reference standard. Results Phantom studies confirmed HDR-QSM's accurate iron content quantification and artifact mitigation ability by revealing a strong linear relationship between iron concentration and QSM values (R², 0.98). In in vivo studies, HDR-QSM showed significantly improved image quality and susceptibility homogeneity in nonaffected myocardium by alleviating motion and off-resonance artifacts (HDR-QSM vs R2*: coefficient of variation, 0.31 ± 0.16 [SD] vs 0.73 ± 0.36 [P < .001]; image quality score [five-point Likert scale:], 3.58 ± 0.75 vs 2.87 ± 0.51 [P < .001]). Comparison between in vivo susceptibility maps and ex vivo measurements showed higher performance of HDR-QSM compared with R2* mapping for IMH detection (area under the receiver operating characteristic curve, 0.96 vs 0.75; P < .001) and iron content quantification (R², 0.71 vs 0.14). Conclusion In a canine model of IMH, the fast and free-running cardiac QSM technique accurately detected IMH and quantified intramyocardial iron content of the entire heart within 5 minutes without requiring breath holding. Keywords: High-Dynamic-Range Quantitative Susceptibility Mapping, Myocardial Infarction, Intramyocardial Hemorrhage, MRI Supplemental material is available for this article. ©RSNA, 2024.

Syphilis is a sexually transmitted infection characterized by multiple stages. Cardiovascular involvement is a manifestation of tertiary syphilis, occurring between 10 and 40 years after the primary infection. The authors present a case of atypical presentation of tertiary syphilis in a 49-year-old male patient who was admitted to the hospital with bilateral transient loss of vision. Contrast-enhanced CT imaging revealed thoracic aortitis with carotid occlusion, coronary artery stenosis, ischemic stroke, myocardial infarction, and multiple intracardiac thrombi. A postmortem autopsy revealed positive laboratory results for syphilis, which was corroborated by medical autopsy findings of syphilitic aortitis. Keywords: CT-Angiography, Aorta, Cardiac, Vascular, Tertiary Syphilis © RSNA, 2024.

Purpose To explore the role of cardiac MRI feature tracking (FT) and T1 mapping in predicting sustained ventricular arrhythmias (VA) in patients with arrhythmogenic right ventricular cardiomyopathy (ARVC) and to investigate their possible incremental value beyond ARVC risk score. Materials and Methods The retrospective study analyzed 91 patients with ARVC (median age, 36 years [IQR, 27-50 years]; 60 male, 31 female) who underwent cardiac MRI examinations between November 2010 and March 2022. The primary end point was the first occurrence of sustained VA after cardiac MRI to first VA, with censoring of patients who were alive without VA at last follow-up. Cox regression analysis was performed to assess the association between variables and time to sustained VA. Time-dependent receiver operating characteristic (ROC) analysis was performed to determine the incremental value of cardiac MRI FT and T1 mapping. Results During a median follow-up of 55.0 months (IQR, 37.0-76.0 months), 36 of 91 (40%) patients experienced sustained VA. A 1% worsening in left ventricular global longitudinal peak strain (GLS), 1% worsening in right ventricular GLS, and a 1% increase in extracellular volume fraction (ECV) were associated with increased risk of sustained VA, with hazard ratios of 1.14 (95% CI: 1.06, 1.23; P = .001), 1.09 (95% CI: 1.02, 1.16; P = .02), and 1.13 (95% CI: 1.08, 1.18; P < .001), respectively, after adjustment for ARVC risk score. Adding both biventricular GLS and ECV to ARVC risk score showed significant incremental value for predicting sustained VA (area under the ROC curve: 0.73 vs 0.65; P < .001). Conclusion Cardiac MRI-derived biventricular GLS and ECV provided independent and incremental value for predicting sustained VA beyond ARVC risk score alone in patients with ARVC. Keywords: Cardiovascular MRI, Feature Tracking, T1 Mapping, Arrhythmogenic Right Ventricular Cardiomyopathy, Sustained Ventricular Arrhythmias Supplemental material is available for this article Published under a CC BY 4.0 license.

Purpose To determine the prevalence of clinically relevant extracardiac findings at cardiac CT and MRI examinations from a multicenter, multinational MR/CT registry and the relationship of prevalence with examination indications and patient characteristics. Materials and Methods This was a retrospective analysis of data from the European Society of Cardiovascular Radiology MR/CT Registry. Data from 208 506 cardiac CT examinations (median patient age, 66 years [IQR, 55-77]; 121 617 [58.33%] male patients) and 228 462 cardiac MRI examinations (median patient age, 57 years [IQR, 42-69]; 145 792 [63.81%] male patients) entered into the registry between January 2011 and November 2023 were analyzed. Clinically relevant extracardiac findings were defined as findings requiring follow-up examinations or influencing clinical management. The association of examination indication and patient characteristics, including age, with prevalence of extracardiac findings was evaluated using incidence rate ratios (IRRs) derived from multivariable Poisson regression models. Results The prevalence of clinically relevant extracardiac findings was 3.28% (6832 of 208 506) at cardiac CT and 1.50% (3421 of 228 462) at cardiac MRI examinations. Extracardiac findings were more common at CT examinations performed for transcatheter aortic valve replacement (IRR, 2.07; P < .001) and structural heart disease (IRR, 1.44; P < .001) compared with CT performed for coronary artery disease (IRR, 1; reference). Extracardiac findings were more common at MRI examinations performed for myocarditis (IRR, 1.36; P < .001) and structural heart disease (IRR, 1.16; P < .001) than for coronary artery disease. Older patient age was also significantly associated with higher prevalence of extracardiac findings, with an IRR for both CT and MRI examinations of 1.02 (P < .001). Conclusion Data from the multicenter, multinational MR/CT registry indicate that clinically relevant extracardiac findings are present at cardiovascular CT and MRI examinations, and the prevalence of these findings is associated with examination indication and patient age. Keywords: Cardiac Imaging Techniques, Incidental Findings, MRI, CT Angiography, CT, Heart Disease Supplemental material is available for this article. © RSNA, 2024.