Browsing by Author "Chang, Hyuk Jae"
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- Corrigendum to ‘Relation of Gender to Atherosclerotic Plaque Characteristics by Differing Angiographic Stenosis Severity’ The American Journal of Cardiology, Volume 204, 1 October 2023, Pages 276-283 (The American Journal of Cardiology (2023) 204 (276–283), (S0002914923005325), (10.1016/j.amjcard.2023.07.004))Publication . Jonas, Rebecca; Patel, Toral; Crabtree, Tami R.; Jennings, Robert S.; Heo, Ran; Park, Hyung Bok; Marques, Hugo; Chang, Hyuk Jae; Stuijfzand, Wijnand J.; Rosendael, Alexander R.van; Choi, Jung Hyun; Doh, Joon Hyung; Her, Ae Young; Koo, Bon Kwon; Nam, Chang Wook; Shin, Sang Hoon; Cole, Jason; Gimelli, Alessia; Khan, Muhammad Akram; Lu, Bin; Gao, Yang; Nabi, Faisal; Al-Mallah, Mouaz H.; Nakazato, Ryo; Schoepf, U. Joseph; Driessen, Roel S.; Bom, Michiel J.; Thompson, Randall C.; Jang, James J.; Ridner, Michael; Rowan, Chris; Avelar, Erick; Généreux, Philippe; Knaapen, Paul; de Waard, Guus A.; Pontone, Gianluca; Andreini, Daniele; Bax, Jeroen J.; Choi, Andrew D.; Earls, James P.; Hoffmann, Udo; Min, James K.; Villines, Todd C.The authors regret that the original version was published with the wrong ac affiliation. The affiliation has now been corrected. The authors regret any inconvenience caused.
- Development and validation of a quantitative coronary CT Angiography model for diagnosis of vessel-specific coronary ischemiaPublication . CREDENCE and PACIFIC-1 Investigators; Nurmohamed, Nick S.; Danad, Ibrahim; Jukema, Ruurt A.; Winter, Ruben W. de; Groot, Robin J. de; Driessen, Roel S.; Bom, Michiel J.; Diemen, Pepijn van; Pontone, Gianluca; Andreini, Daniele; Chang, Hyuk Jae; Katz, Richard J.; Stroes, Erik S. G.; Wang, Hao; Chan, Chung; Crabtree, Tami; Aquino, Melissa; Min, James K.; Earls, James P.; Bax, Jeroen J.; Choi, Andrew D.; Knaapen, Paul; Rosendael, Alexander R. van; Heo, Ran; Park, Hyung Bok; Marques, Hugo; Stuijfzand, Wijnand J.; Choi, Jung Hyun; Doh, Joon Hyung; Her, Ae Young; Koo, Bon Kwon; Nam, Chang Wook; Shin, Sang Hoon; Cole, Jason; Gimelli, Alessia; Khan, Muhammad Akram; Lu, Bin; Gao, Yang; Nabi, Faisal; Al-Mallah, Mouaz H.; Nakazato, Ryo; Schoepf, U. Joseph; Thompson, Randall C.; Jang, James J.; Ridner, Michael; Rowan, Chris; Avelar, Erick; Généreux, Philippe; Waard, Guus A. de; Sprengers, Ralf W.Background: Noninvasive stress testing is commonly used for detection of coronary ischemia but possesses variable accuracy and may result in excessive health care costs. Objectives: This study aimed to derive and validate an artificial intelligence-guided quantitative coronary computed tomography angiography (AI-QCT) model for the diagnosis of coronary ischemia that integrates atherosclerosis and vascular morphology measures (AI-QCTISCHEMIA) and to evaluate its prognostic utility for major adverse cardiovascular events (MACE). Methods: A post hoc analysis of the CREDENCE (Computed Tomographic Evaluation of Atherosclerotic Determinants of Myocardial Ischemia) and PACIFIC-1 (Comparison of Coronary Computed Tomography Angiography, Single Photon Emission Computed Tomography [SPECT], Positron Emission Tomography [PET], and Hybrid Imaging for Diagnosis of Ischemic Heart Disease Determined by Fractional Flow Reserve) studies was performed. In both studies, symptomatic patients with suspected stable coronary artery disease had prospectively undergone coronary computed tomography angiography (CTA), myocardial perfusion imaging (MPI), SPECT, or PET, fractional flow reserve by CT (FFRCT), and invasive coronary angiography in conjunction with invasive FFR measurements. The AI-QCTISCHEMIA model was developed in the derivation cohort of the CREDENCE study, and its diagnostic performance for coronary ischemia (FFR ≤0.80) was evaluated in the CREDENCE validation cohort and PACIFIC-1. Its prognostic value was investigated in PACIFIC-1. Results: In CREDENCE validation (n = 305, age 64.4 ± 9.8 years, 210 [69%] male), the diagnostic performance by area under the receiver-operating characteristics curve (AUC) on per-patient level was 0.80 (95% CI: 0.75-0.85) for AI-QCTISCHEMIA, 0.69 (95% CI: 0.63-0.74; P < 0.001) for FFRCT, and 0.65 (95% CI: 0.59-0.71; P < 0.001) for MPI. In PACIFIC-1 (n = 208, age 58.1 ± 8.7 years, 132 [63%] male), the AUCs were 0.85 (95% CI: 0.79-0.91) for AI-QCTISCHEMIA, 0.78 (95% CI: 0.72-0.84; P = 0.037) for FFRCT, 0.89 (95% CI: 0.84-0.93; P = 0.262) for PET, and 0.72 (95% CI: 0.67-0.78; P < 0.001) for SPECT. Adjusted for clinical risk factors and coronary CTA-determined obstructive stenosis, a positive AI-QCTISCHEMIA test was associated with an HR of 7.6 (95% CI: 1.2-47.0; P = 0.030) for MACE. Conclusions: This newly developed coronary CTA-based ischemia model using coronary atherosclerosis and vascular morphology characteristics accurately diagnoses coronary ischemia by invasive FFR and provides robust prognostic utility for MACE beyond presence of stenosis.
- Relation of gender to atherosclerotic plaque characteristics by differing angiographic stenosis severityPublication . Jonas, Rebecca; Patel, Toral; Crabtree, Tami R.; Jennings, Robert S.; Heo, Ran; Park, Hyung Bok; Marques, Hugo; Chang, Hyuk Jae; Stuijfzand, Wijnand J.; van Rosendael, Alexander R.; Choi, Jung Hyun; Doh, Joon Hyung; Her, Ae Young; Koo, Bon Kwon; Nam, Chang Wook; Shin, Sang Hoon; Cole, Jason; Gimelli, Alessia; Khan, Muhammad Akram; Lu, Bin; Gao, Yang; Nabi, Faisal; Al-Mallah, Mouaz H.; Nakazato, Ryo; Schoepf, U. Joseph; Driessen, Roel S.; Bom, Michiel J.; Thompson, Randall C.; Jang, James J.; Ridner, Michael; Rowan, Chris; Avelar, Erick; Généreux, Philippe; Knaapen, Paul; de Waard, Guus A.; Pontone, Gianluca; Andreini, Daniele; Bax, Jeroen J.; Choi, Andrew D.; Earls, James P.; Hoffmann, Udo; Min, James K.; Villines, Todd C.It is unknown whether gender influences the atherosclerotic plaque characteristics (APCs) of lesions of varying angiographic stenosis severity. This study evaluated the imaging data of 303 symptomatic patients from the derivation arm of the CREDENCE (Computed TomogRaphic Evaluation of Atherosclerotic Determinants of Myocardial IsChEmia) trial, all of whom underwent coronary computed tomographic angiography and clinically indicated nonemergent invasive coronary angiography upon study enrollment. Index tests were interpreted by 2 blinded core laboratories, one of which performed quantitative coronary computed tomographic angiography using an artificial intelligence application to characterize and quantify APCs, including percent atheroma volume (PAV), low-density noncalcified plaque (LD-NCP), noncalcified plaque (NCP), calcified plaque (CP), lesion length, positive arterial remodeling, and high-risk plaque (a combination of LD-NCP and positive remodeling ≥1.10); the other classified lesions as obstructive (≥50% diameter stenosis) or nonobstructive (<50% diameter stenosis) based on quantitative invasive coronary angiography. The relation between APCs and angiographic stenosis was further examined by gender. The mean age of the study cohort was 64.4 ± 10.2 years (29.0% female). In patients with obstructive disease, men had more LD-NCP PAV (0.5 ± 0.4 vs 0.3 ± 0.8, p = 0.03) and women had more CP PAV (11.7 ± 1.6 vs 8.0 ± 0.8, p = 0.04). Obstructive lesions had more NCP PAV compared with their nonobstructive lesions in both genders, however, obstructive lesions in women also demonstrated greater LD-NCP PAV (0.4 ± 0.5 vs 1.0 ± 1.8, p = 0.03), and CP PAV (17.4 ± 16.5 vs 25.9 ± 18.7, p = 0.03) than nonobstructive lesions. Comparing the composition of obstructive lesions by gender, women had more CP PAV (26.3 ± 3.4 vs 15.8 ± 1.5, p = 0.005) whereas men had more NCP PAV (33.0 ± 1.6 vs 26.7 ± 2.5, p = 0.04). Men had more LD-NCP PAV in nonobstructive lesions compared with women (1.2 ± 0.2 vs 0.6 ± 0.2, p = 0.02). In conclusion, there are gender-specific differences in plaque composition based on stenosis severity.
- Risk factors based vessel-specific prediction for stages of coronary artery disease using Bayesian quantile regression machine learning method: results from the PARADIGM registryPublication . Park, Hyung Bok; Lee, Jina; Hong, Yongtaek; Byungchang, So; Kim, Wonse; Lee, Byoung K.; Lin, Fay Y.; Hadamitzky, Martin; Kim, Yong Jin; Conte, Edoardo; Andreini, Daniele; Pontone, Gianluca; Budoff, Matthew J.; Gottlieb, Ilan; Chun, Eun Ju; Cademartiri, Filippo; Maffei, Erica; Marques, Hugo; Gonçalves, Pedro de A.; Leipsic, Jonathon A.; Shin, Sanghoon; Choi, Jung H.; Virmani, Renu; Samady, Habib; Chinnaiyan, Kavitha; Stone, Peter H.; Berman, Daniel S.; Narula, Jagat; Shaw, Leslee J.; Bax, Jeroen J.; Min, James K.; Kook, Woong; Chang, Hyuk JaeBackground and Hypothesis: The recently introduced Bayesian quantile regression (BQR) machine-learning method enables comprehensive analyzing the relationship among complex clinical variables. We analyzed the relationship between multiple cardiovascular (CV) risk factors and different stages of coronary artery disease (CAD) using the BQR model in a vessel-specific manner. Methods: From the data of 1,463 patients obtained from the PARADIGM (NCT02803411) registry, we analyzed the lumen diameter stenosis (DS) of the three vessels: left anterior descending (LAD), left circumflex (LCx), and right coronary artery (RCA). Two models for predicting DS and DS changes were developed. Baseline CV risk factors, symptoms, and laboratory test results were used as the inputs. The conditional 10%, 25%, 50%, 75%, and 90% quantile functions of the maximum DS and DS change of the three vessels were estimated using the BQR model. Results: The 90th percentiles of the DS of the three vessels and their maximum DS change were 41%–50% and 5.6%–7.3%, respectively. Typical anginal symptoms were associated with the highest quantile (90%) of DS in the LAD; diabetes with higher quantiles (75% and 90%) of DS in the LCx; dyslipidemia with the highest quantile (90%) of DS in the RCA; and shortness of breath showed some association with the LCx and RCA. Interestingly, High-density lipoprotein cholesterol showed a dynamic association along DS change in the per-patient analysis. Conclusions: This study demonstrates the clinical utility of the BQR model for evaluating the comprehensive relationship between risk factors and baseline-grade CAD and its progression.
- Sex and age-specific interactions of coronary atherosclerotic plaque onset and prognosis from coronary computed tomographyPublication . Rosendael, Sophie E. Van; Bax, A. Maxim; Lin, Fay Y.; Achenbach, Stephan; Andreini, Daniele; Budoff, Matthew J.; Cademartiri, Filippo; Callister, Tracy Q.; Chinnaiyan, Kavitha; Chow, Benjamin J. W.; Cury, Ricardo C.; DeLago, Augustin J.; Feuchtner, Gudrun; Hadamitzky, Martin; Hausleiter, Joerg; Kaufmann, Philipp A.; Kim, Yong Jin; Leipsic, Jonathon A.; Maffei, Erica; Marques, Hugo; Gonçalves, Pedro de Araújo; Pontone, Gianluca; Raff, Gilbert L.; Rubinshtein, Ronen; Villines, Todd C.; Chang, Hyuk Jae; Berman, Daniel S.; Min, James K.; Bax, Jeroen J.; Shaw, Leslee J.; Rosendael, Alexander R. VanAims: The totality of atherosclerotic plaque derived from coronary computed tomography angiography (CCTA) emerges as a comprehensive measure to assess the intensity of medical treatment that patients need. This study examines the differences in age onset and prognostic significance of atherosclerotic plaque burden between sexes. Methods and results: From a large multi-center CCTA registry the Leiden CCTA score was calculated in 24 950 individuals. A total of 11 678 women (58.5 ± 12.4 years) and 13 272 men (55.6 ± 12.5 years) were followed for 3.7 years for major adverse cardiovascular events (MACE) (death or myocardial infarction). The age where the median risk score was above zero was 12 years higher in women vs. men (64-68 years vs. 52-56 years, respectively, P < 0.001). The Leiden CCTA risk score was independently associated with MACE: score 6-20: HR 2.29 (1.69-3.10); score > 20: HR 6.71 (4.36-10.32) in women, and score 6-20: HR 1.64 (1.29-2.08); score > 20: HR 2.38 (1.73-3.29) in men. The risk was significantly higher for women within the highest score group (adjusted P-interaction = 0.003). In pre-menopausal women, the risk score was equally predictive and comparable with men. In post-menopausal women, the prognostic value was higher for women [score 6-20: HR 2.21 (1.57-3.11); score > 20: HR 6.11 (3.84-9.70) in women; score 6-20: HR 1.57 (1.19-2.09); score > 20: HR 2.25 (1.58-3.22) in men], with a significant interaction for the highest risk group (adjusted P-interaction = 0.004). Conclusion: Women developed coronary atherosclerosis approximately 12 years later than men. Post-menopausal women within the highest atherosclerotic burden group were at significantly higher risk for MACE than their male counterparts, which may have implications for the medical treatment intensity.