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Chunming Li

Bio: Chunming Li is an academic researcher from Shanghai Jiao Tong University. The author has contributed to research in topics: Medicine & Internal medicine. The author has co-authored 1 publications.

Papers
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Journal ArticleDOI
01 Sep 2021
TL;DR: A novel approach is evaluated for automatic coregistration of optical coherence tomography (OCT) and coronary angiography and Lumen diameters and side branches from both coro...
Abstract: This study sought to evaluate a novel approach for automatic coregistration of optical coherence tomography (OCT) and coronary angiography. Lumen diameters and side branches from both coro...

6 citations

Journal ArticleDOI
TL;DR: In this article , the authors compared the diagnostic accuracy of computational quantitative flow ratio (QFR) based on single vs 2 angiographic views in patients with intermediate coronary stenosis, and concluded that 3D-μQFR had comparably good diagnostic performance as 2-view 3DQFR (0.95, P < .001).

4 citations

Journal ArticleDOI
TL;DR: Angiography-derived RWS was significantly correlated with plaque composition and known OCT features of plaque vulnerability in patients with intermediate coronary stenosis.
Abstract: BACKGROUND The lipid-to-cap ratio (LCR) and thin-cap fibroatheroma (TCFA) derived from optical coherence tomography (OCT) are indicative of plaque vulnerability. AIMS We aimed to explore the association of a novel method to estimate radial wall strain (RWS) from angiography with plaque composition and features of vulnerability assessed by OCT. METHODS Anonymised data from patients with intermediate stenosis who underwent coronary angiography (CAG) and OCT were analysed in a core laboratory. Angiography-derived RWSmax was computed as the maximum deformation of lumen diameter throughout the cardiac cycle, expressed as a percentage of the largest lumen diameter. The LCR and TCFA were automatically determined on OCT images by a recently validated algorithm based on artificial intelligence. RESULTS OCT and CAG images from 114 patients (124 vessels) were analysed. The average time for the analysis of RWSmax was 57 (39-82) seconds. The RWSmax in the interrogated plaques was 12% (10-15%) and correlated positively with the LCR (r=0.584; p<0.001) and lipidic plaque burden (r=0.411; p<0.001), and negatively with fibrous cap thickness (r= -0.439; p<0.001). An RWSmax >12% was an angiographic predictor for an LCR >0.33 (area under the curve [AUC]=0.86, 95% confidence interval [CI]: 0.78-0.91; p<0.001) and TCFA (AUC=0.72, 95% CI: 0.63-0.80; p<0.001). Lesions with RWSmax >12% had a higher prevalence of TCFA (22.0% versus 1.5%; p<0.001), thinner fibrous cap thickness (71 μm versus 101 μm; p<0.001), larger lipidic plaque burden (23.3% versus 15.4%; p<0.001), and higher maximum LCR (0.41 versus 0.18; p<0.001) compared to lesions with RWSmax ≤12%. CONCLUSIONS Angiography-derived RWS was significantly correlated with plaque composition and known OCT features of plaque vulnerability in patients with intermediate coronary stenosis.

3 citations

Journal ArticleDOI
TL;DR: In this paper , the authors investigated the association between angiography-derived radial wall strain (RWS) and future acute myocardial infarction (AMI) events in mild to intermediate lesions.
Abstract: The radial wall strain (RWS) is a novel angiography-based method to assess the biomechanical property of the coronary artery and whether it can predict future acute myocardial infarction (AMI) events remains to be elucidated.This study aimed to investigate the association between angiography-derived RWS and future AMI events in mild to intermediate lesions.We performed a matched case-control analysis nested in a retrospective cohort of patients who had received prior angiography (the index procedure) at least 1 month before and were hospitalized again for repeat angiography. Patients with at least 1 de novo mild to intermediate lesion identified at the index procedure and eligible for RWS analysis were enrolled. The study identified cases with target lesion-related AMI diagnosed at the repeat angiography, matching each case to 3 control subjects without AMI.Altogether 44 patients with lesion-related AMI and 132 matched controls were enrolled. The median diameter stenosis of the overall interrogated lesions was 34.0%. The baseline maximum RWS (RWSmax), which was defined as the highest RWS in the stenotic segment, was significantly higher in lesions responsible for AMI than those that remained quiescent (median 13% vs 10%; P < 0.001). RWSmax was predictive of lesion-related AMI, with an area under the curve of 0.83 (95% CI: 0.76-0.90; P < 0.001) and an optimal cutoff >12%. RWSmax >12% was found to be independently associated with subsequent AMI events with a risk ratio of 7.25 (95% CI: 3.94-13.37; P < 0.001).Among angiographically mild to intermediate lesions, a high-strain pattern identified by angiography-derived RWS was associated with an increased risk of AMI events.

1 citations

Journal ArticleDOI
TL;DR: In this paper , the agreement between radial wall strain from coronary angiography (RWSAngio and RWS derived from optical coherence tomography (OCT) followed by finite element analysis was determined.

1 citations


Cited by
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Journal ArticleDOI
TL;DR: In this paper , the authors explore the association of a novel method to estimate radial wall strain (RWS) from angiography with plaque composition and features of vulnerability assessed by OCT.
Abstract: The lipid-to-cap ratio (LCR) and thin-cap fibroatheroma (TCFA) derived from optical coherence tomography (OCT) are indicative of plaque vulnerability.We aimed to explore the association of a novel method to estimate radial wall strain (RWS) from angiography with plaque composition and features of vulnerability assessed by OCT.Anonymised data from patients with intermediate stenosis who underwent coronary angiography (CAG) and OCT were analysed in a core laboratory. Angiography-derived RWSmax was computed as the maximum deformation of lumen diameter throughout the cardiac cycle, expressed as a percentage of the largest lumen diameter. The LCR and TCFA were automatically determined on OCT images by a recently validated algorithm based on artificial intelligence.OCT and CAG images from 114 patients (124 vessels) were analysed. The average time for the analysis of RWSmax was 57 (39-82) seconds. The RWSmax in the interrogated plaques was 12% (10-15%) and correlated positively with the LCR (r=0.584; p<0.001) and lipidic plaque burden (r=0.411; p<0.001), and negatively with fibrous cap thickness (r= -0.439; p<0.001). An RWSmax >12% was an angiographic predictor for an LCR >0.33 (area under the curve [AUC]=0.86, 95% confidence interval [CI]: 0.78-0.91; p<0.001) and TCFA (AUC=0.72, 95% CI: 0.63-0.80; p<0.001). Lesions with RWSmax >12% had a higher prevalence of TCFA (22.0% versus 1.5%; p<0.001), thinner fibrous cap thickness (71 μm versus 101 μm; p<0.001), larger lipidic plaque burden (23.3% versus 15.4%; p<0.001), and higher maximum LCR (0.41 versus 0.18; p<0.001) compared to lesions with RWSmax ≤12%.Angiography-derived RWS was significantly correlated with plaque composition and known OCT features of plaque vulnerability in patients with intermediate coronary stenosis.

5 citations

Journal ArticleDOI
TL;DR: Angiography-derived RWS was significantly correlated with plaque composition and known OCT features of plaque vulnerability in patients with intermediate coronary stenosis.
Abstract: BACKGROUND The lipid-to-cap ratio (LCR) and thin-cap fibroatheroma (TCFA) derived from optical coherence tomography (OCT) are indicative of plaque vulnerability. AIMS We aimed to explore the association of a novel method to estimate radial wall strain (RWS) from angiography with plaque composition and features of vulnerability assessed by OCT. METHODS Anonymised data from patients with intermediate stenosis who underwent coronary angiography (CAG) and OCT were analysed in a core laboratory. Angiography-derived RWSmax was computed as the maximum deformation of lumen diameter throughout the cardiac cycle, expressed as a percentage of the largest lumen diameter. The LCR and TCFA were automatically determined on OCT images by a recently validated algorithm based on artificial intelligence. RESULTS OCT and CAG images from 114 patients (124 vessels) were analysed. The average time for the analysis of RWSmax was 57 (39-82) seconds. The RWSmax in the interrogated plaques was 12% (10-15%) and correlated positively with the LCR (r=0.584; p<0.001) and lipidic plaque burden (r=0.411; p<0.001), and negatively with fibrous cap thickness (r= -0.439; p<0.001). An RWSmax >12% was an angiographic predictor for an LCR >0.33 (area under the curve [AUC]=0.86, 95% confidence interval [CI]: 0.78-0.91; p<0.001) and TCFA (AUC=0.72, 95% CI: 0.63-0.80; p<0.001). Lesions with RWSmax >12% had a higher prevalence of TCFA (22.0% versus 1.5%; p<0.001), thinner fibrous cap thickness (71 μm versus 101 μm; p<0.001), larger lipidic plaque burden (23.3% versus 15.4%; p<0.001), and higher maximum LCR (0.41 versus 0.18; p<0.001) compared to lesions with RWSmax ≤12%. CONCLUSIONS Angiography-derived RWS was significantly correlated with plaque composition and known OCT features of plaque vulnerability in patients with intermediate coronary stenosis.

3 citations

Journal ArticleDOI
TL;DR: In this paper , the authors investigated the association between angiography-derived radial wall strain (RWS) and future acute myocardial infarction (AMI) events in mild to intermediate lesions.
Abstract: The radial wall strain (RWS) is a novel angiography-based method to assess the biomechanical property of the coronary artery and whether it can predict future acute myocardial infarction (AMI) events remains to be elucidated.This study aimed to investigate the association between angiography-derived RWS and future AMI events in mild to intermediate lesions.We performed a matched case-control analysis nested in a retrospective cohort of patients who had received prior angiography (the index procedure) at least 1 month before and were hospitalized again for repeat angiography. Patients with at least 1 de novo mild to intermediate lesion identified at the index procedure and eligible for RWS analysis were enrolled. The study identified cases with target lesion-related AMI diagnosed at the repeat angiography, matching each case to 3 control subjects without AMI.Altogether 44 patients with lesion-related AMI and 132 matched controls were enrolled. The median diameter stenosis of the overall interrogated lesions was 34.0%. The baseline maximum RWS (RWSmax), which was defined as the highest RWS in the stenotic segment, was significantly higher in lesions responsible for AMI than those that remained quiescent (median 13% vs 10%; P < 0.001). RWSmax was predictive of lesion-related AMI, with an area under the curve of 0.83 (95% CI: 0.76-0.90; P < 0.001) and an optimal cutoff >12%. RWSmax >12% was found to be independently associated with subsequent AMI events with a risk ratio of 7.25 (95% CI: 3.94-13.37; P < 0.001).Among angiographically mild to intermediate lesions, a high-strain pattern identified by angiography-derived RWS was associated with an increased risk of AMI events.

1 citations

Journal ArticleDOI
TL;DR: In this article , a review of the development of deep learning algorithms and their corresponding evaluation metrics together with their clinical applications is presented, where the authors discuss the advantages of using deep learning for precise diagnosis and tailored treatment for patients with coronary artery disease.

1 citations

Journal ArticleDOI
TL;DR: In this article , the incremental value of angiography-derived radial wall strain (RWS) in risk stratification of non-flow-limiting mild coronary narrowings was evaluated.

1 citations