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        Non-Contrast Cine Cardiac Magnetic Resonance Derived-Radiomics for the Prediction of Left Ventricular Adverse Remodeling in Patients With ST-Segment Elevation Myocardial Infarction

        A Xin,Liu Mingliang,Chen Tong,Chen Feng,Qian Geng,Zhang Ying,Chen Yundai 대한영상의학회 2023 Korean Journal of Radiology Vol.24 No.9

        Objective: To investigate the predictive value of radiomics features based on cardiac magnetic resonance (CMR) cine images for left ventricular adverse remodeling (LVAR) after acute ST-segment elevation myocardial infarction (STEMI). Materials and Methods: We conducted a retrospective, single-center, cohort study involving 244 patients (random-split into 170 and 74 for training and testing, respectively) having an acute STEMI (88.5% males, 57.0 ± 10.3 years of age) who underwent CMR examination at one week and six months after percutaneous coronary intervention. LVAR was defined as a 20% increase in left ventricular end-diastolic volume 6 months after acute STEMI. Radiomics features were extracted from the oneweek CMR cine images using the least absolute shrinkage and selection operator regression (LASSO) analysis. The predictive performance of the selected features was evaluated using receiver operating characteristic curve analysis and the area under the curve (AUC). Results: Nine radiomics features with non-zero coefficients were included in the LASSO regression of the radiomics score (RAD score). Infarct size (odds ratio [OR]: 1.04 (1.00–1.07); P = 0.031) and RAD score (OR: 3.43 (2.34–5.28); P < 0.001) were independent predictors of LVAR. The RAD score predicted LVAR, with an AUC (95% confidence interval [CI]) of 0.82 (0.75–0.89) in the training set and 0.75 (0.62–0.89) in the testing set. Combining the RAD score with infarct size yielded favorable performance in predicting LVAR, with an AUC of 0.84 (0.72–0.95). Moreover, the addition of the RAD score to the left ventricular ejection fraction (LVEF) significantly increased the AUC from 0.68 (0.52–0.84) to 0.82 (0.70–0.93) (P = 0.018), which was also comparable to the prediction provided by the combined microvascular obstruction, infarct size, and LVEF with an AUC of 0.79 (0.65–0.94) (P = 0.727). Conclusion: Radiomics analysis using non-contrast cine CMR can predict LVAR after STEMI independently and incrementally to LVEF and may provide an alternative to traditional CMR parameters.

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        Characteristics Detected on Computed Tomography Angiography Predict Coronary Artery Plaque Progression in Non-Culprit Lesions

        Yahang Tan,Jia Zhou,Ying Zhou,Xiaobo Yang,Junjie Yang,Yundai Chen 대한영상의학회 2017 Korean Journal of Radiology Vol.18 No.3

        Objective: This study sought to determine whether variables detected on coronary computed tomography angiography (CCTA) would predict plaque progression in non-culprit lesions (NCL). Materials and Methods: In this single-center trial, we analyzed 103 consecutive patients who were undergoing CCTA and percutaneous coronary intervention (PCI) for culprit lesions. Follow-up CCTA was scheduled 12 months after the PCI, and all patients were followed for 3 years after their second CCTA examination. High-risk plaque features and epicardial adipose tissue (EAT) volume were assessed by CCTA. Each NCL stenosis grade was compared visually between two CCTA scans to detect plaque progression, and patients were stratified into two groups based on this. Logistic regression analysis was used to evaluate the factors that were independently associated with plaque progression in NCLs. Time-to-event curves were compared using the log-rank statistic. Results: Overall, 34 of 103 patients exhibited NCL plaque progression (33%). Logistic regression analyses showed that the NCL progression was associated with a history of ST-elevated myocardial infarction (odds ratio [OR] = 5.855, 95% confidence interval [CI] = 1.391–24.635, p = 0.016), follow-up low-density lipoprotein cholesterol level (OR = 6.832, 95% CI = 2.103–22.200, p = 0.001), baseline low-attenuation plaque (OR = 7.311, 95% CI = 1.242–43.028, p = 0.028) and EAT (OR = 1.015, 95% CI = 1.000–1.029, p = 0.044). Following the second CCTA examination, major adverse cardiac events (MACEs) were observed in 12 patients, and NCL plaque progression was significantly associated with future MACEs (log rank p = 0.006). Conclusion: Noninvasive assessment of NCLs by CCTA has potential prognostic value.

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        CT-Based Leiden Score Outperforms Confirm Score in Predicting Major Adverse Cardiovascular Events for Diabetic Patients with Suspected Coronary Artery Disease

        Liu Zinuan,Ding Yipu,Dou Guanhua,Wang Xi,Shan Dongkai,He Bai,Jing Jing,Chen Yundai,Yang Junjie 대한영상의학회 2022 Korean Journal of Radiology Vol.23 No.10

        Objective: Evidence supports the efficacy of coronary computed tomography angiography (CCTA)-based risk scores in cardiovascular risk stratification of patients with suspected coronary artery disease (CAD). We aimed to compare two CCTAbased risk score algorithms, Leiden and Confirm scores, in patients with diabetes mellitus (DM) and suspected CAD. Materials and Methods: This single-center prospective cohort study consecutively included 1241 DM patients (54.1% male, 60.2 ± 10.4 years) referred for CCTA for suspected CAD in 2015–2017. Leiden and Confirm scores were calculated and stratified as < 5 (reference), 5–20, and > 20 for Leiden and < 14.3 (reference), 14.3–19.5, and > 19.5 for Confirm. Major adverse cardiovascular events (MACE) were defined as the composite outcomes of cardiovascular death, nonfatal myocardial infarction (MI), stroke, and unstable angina requiring hospitalization. The Cox model and Kaplan–Meier method were used to evaluate the effect size of the risk scores on MACE. The area under the curve (AUC) at the median follow-up time was also compared between score algorithms. Results: During a median follow-up of 31 months (interquartile range, 27.6–37.3 months), 131 of MACE were recorded, including 17 cardiovascular deaths, 28 nonfatal MIs, 64 unstable anginas requiring hospitalization, and 22 strokes. An incremental incidence of MACE was observed in both Leiden and Confirm scores, with an increase in the scores (log-rank p < 0.001). In the multivariable analysis, compared with Leiden score < 5, the hazard ratios for Leiden scores of 5–20 and > 20 were 2.37 (95% confidence interval [CI]: 1.53–3.69; p < 0.001) and 4.39 (95% CI: 2.40–8.01; p < 0.001), respectively, while the Confirm score did not demonstrate a statistically significant association with the risk of MACE. The Leiden score showed a greater AUC of 0.840 compared to 0.777 for the Confirm score (p < 0.001). Conclusion: CCTA-based risk score algorithms could be used as reliable cardiovascular risk predictors in patients with DM and suspected CAD, among which the Leiden score outperformed the Confirm score in predicting MACE.

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