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Multicenter Study
. 2022 Mar 1;7(3):309-319.
doi: 10.1001/jamacardio.2021.5705.

Association of Plaque Location and Vessel Geometry Determined by Coronary Computed Tomographic Angiography With Future Acute Coronary Syndrome-Causing Culprit Lesions

Donghee Han  1 , Andrew Lin  1 , Keiichiro Kuronuma  1 , Evangelos Tzolos  2 , Alan C Kwan  1 , Eyal Klein  1 , Daniele Andreini  3 , Jeroen J Bax  4 , Filippo Cademartiri  5 , Kavitha Chinnaiyan  6 , Benjamin J W Chow  7 , Edoardo Conte  3 , Ricardo C Cury  8 , Gudrun Feuchtner  9 , Martin Hadamitzky  10 , Yong-Jin Kim  11 , Jonathon A Leipsic  12 , Erica Maffei  13 , Hugo Marques  14 , Fabian Plank  9 , Gianluca Pontone  3 , Todd C Villines  15 , Mouaz H Al-Mallah  16 , Pedro de Araújo Gonçalves  14 , Ibrahim Danad  17 , Heidi Gransar  1 , Yao Lu  18 , Ji-Hyun Lee  19 , Sang-Eun Lee  20 , Lohendran Baskaran  21 , Subhi J Al'Aref  22 , Yeonyee E Yoon  18 , Alexander Van Rosendael  18 , Matthew J Budoff  23 , Habib Samady  24 , Peter H Stone  25 , Renu Virmani  26 , Stephan Achenbach  27 , Jagat Narula  28 , Hyuk-Jae Chang  29 , James K Min  30 , Fay Y Lin  18 , Leslee J Shaw  18 , Piotr J Slomka  1 , Damini Dey  1 , Daniel S Berman  1
Affiliations
Multicenter Study

Association of Plaque Location and Vessel Geometry Determined by Coronary Computed Tomographic Angiography With Future Acute Coronary Syndrome-Causing Culprit Lesions

Donghee Han et al. JAMA Cardiol. .

Abstract

Importance: Distinct plaque locations and vessel geometric features predispose to altered coronary flow hemodynamics. The association between these lesion-level characteristics assessed by coronary computed tomographic angiography (CCTA) and risk of future acute coronary syndrome (ACS) is unknown.

Objective: To examine whether CCTA-derived adverse geometric characteristics (AGCs) of coronary lesions describing location and vessel geometry add to plaque morphology and burden for identifying culprit lesion precursors associated with future ACS.

Design, setting, and participants: This substudy of ICONIC (Incident Coronary Syndromes Identified by Computed Tomography), a multicenter nested case-control cohort study, included patients with ACS and a culprit lesion precursor identified on baseline CCTA (n = 116) and propensity score-matched non-ACS controls (n = 116). Data were collected from July 20, 2012, to April 30, 2017, and analyzed from October 1, 2020, to October 31, 2021.

Exposures: Coronary lesions were evaluated for the following 3 AGCs: (1) distance from the coronary ostium to lesion; (2) location at vessel bifurcations; and (3) vessel tortuosity, defined as the presence of 1 bend of greater than 90° or 3 curves of 45° to 90° using a 3-point angle within the lesion.

Main outcomes and measures: Association between lesion-level AGCs and risk of future ACS-causing culprit lesions.

Results: Of 548 lesions, 116 culprit lesion precursors were identified in 116 patients (80 [69.0%] men; mean [SD], age 62.7 [11.5] years). Compared with nonculprit lesions, culprit lesion precursors had a shorter distance from the ostium (median, 35.1 [IQR, 23.6-48.4] mm vs 44.5 [IQR, 28.2-70.8] mm), more frequently localized to bifurcations (85 [73.3%] vs 168 [38.9%]), and had more tortuous vessel segments (5 [4.3%] vs 6 [1.4%]; all P < .05). In multivariable Cox regression analysis, an increasing number of AGCs was associated with a greater risk of future culprit lesions (hazard ratio [HR] for 1 AGC, 2.90 [95% CI, 1.38-6.08]; P = .005; HR for ≥2 AGCs, 6.84 [95% CI, 3.33-14.04]; P < .001). Adverse geometric characteristics provided incremental discriminatory value for culprit lesion precursors when added to a model containing stenosis severity, adverse morphological plaque characteristics, and quantitative plaque characteristics (area under the curve, 0.766 [95% CI, 0.718-0.814] vs 0.733 [95% CI, 0.685-0.782]). In per-patient comparison, patients with ACS had a higher frequency of lesions with adverse plaque characteristics, AGCs, or both compared with control patients (≥2 adverse plaque characteristics, 70 [60.3%] vs 50 [43.1%]; ≥2 AGCs, 92 [79.3%] vs 60 [51.7%]; ≥2 of both, 37 [31.9%] vs 20 [17.2%]; all P < .05).

Conclusions and relevance: These findings support the concept that CCTA-derived AGCs capturing lesion location and vessel geometry are associated with risk of future ACS-causing culprit lesions. Adverse geometric characteristics may provide additive prognostic information beyond plaque assessment in CCTA.

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Conflict of interest statement

Conflict of Interest Disclosures: Dr Kwan reported receiving grants from the Doris Duke Charitable Foundation during the conduct of the study. Dr Bax reported receiving speaker fees from Abbott Laboratories, Edwards Lifesciences, research grants from Abbott Laboratories, Edwards Lifesciences, Medtronic plc, Boston Scientific Corporation, and Biotronik outside the submitted work. Dr Chinnaiyan reported receiving institutional grants from HeartfFlow Inc during the conduct of the study. Dr Chow reported research collaboration and support from Artrya Ltd, grants from AusculSciences and TD Bank, nonfinancial research support from Siemens AG, and equity interest from GE Healthcare during the conduct of the study. Dr Cury reported consulting for Covera Health, GE Healthcare, and Cleerly Inc outside the submitted work. Dr Leipsic reported consulting for and having stock options from HeartFlow Inc, speaking fees from Philips, and institutional grants from GE Healthcare outside the submitted work. Dr Al-Mallah reported receiving grants from Siemens AG outside the submitted work. Dr Al’Aref reported receiving grants from the National Institutes of Health (NIH) during the conduct of the study and textbook royalties from Elsevier outside the submitted work. Dr Samady reported receiving personal fees from Philips, Abbott Vascular, and Medtronic plc during the conduct of the study, being a cofounder and equity holder of Covanos Inc, and equity holder of SIG outside the submitted work. Dr Virmani reported receiving grants from the NIH, Leducq Foundation, 4C Medical, 4Tech, Abbott Vascular, Ablative Solutions, Absorption Systems, Advanced NanoTherapies, Aerwave Medical Inc, Alivas, Amgen Inc, Asahi Medical, Aurios Medical, Avantec Vascular, BD Bioscences, Biosensors, Biotronik, Biotyx Medical, Bolt Medical Inc, Boston Scientific, Canon Inc, Cardiac Implants LLC, Cardiawave, CardioMech, Cardionomic, CeloNova BioSciences Inc, Cerus Endovascular Inc, Chansu Vascular Technologies LLC, Children’s National Medical Center, Concept Medical, Cook Medical, Cooper Health, Cormaze Technologies GmbH, CRL/AccelLab, CroíValve, CSI, DexCom Inc, Edwards Lifesciences, Elucid Bioimaging, eLum Technologies Inc, Emboline Inc, Endotronix, Envision, Filterlex, Imperative Care Inc, Innovative Cardiovascular Solutions LLC, Intact Vascular Inc, Interface Biolgics, InterShunt Technologies Inc, Invatin Technologies, Lahav CRO, LimFlow, L & J Biosciences, Lutonix, Lyra Therapeutics Inc, Mayo Clinic, Maywell, MD Start, MedAlliance, Medanex Clinic, Medtronic plc, Mercator Limited, MicroPort, MicroVention, Neovasc Inc, Nephronyx Ltd, Nova Vascular, Nyra Medical, Occultech, Olympus Therapeutics, OhioHealth, OrbusNeich, Ossio, phenox Inc, Pi-Cardia, Polares Medical, PolyVascular, Profusa Inc, ProKidney LLC, Protembis, Pulse Biosciences Inc, Qool Therapeutics, Recombinetics, ReCor Medical Inc, Regencor Inc, Renata Medical, Restore Medical Ltd, Ripple Therapeutics, Rush University, Sanofi SA, Shockwave Medical, Sahajanand Medical Technologies Limited, SoundPipe, Spartan Micro, SpectraWAVE Inc, Surmodics Inc, Terumo Corporation, Jacobs Institute, Transmural Systems LLC, Transverse Medical Inc, TruLeaf Medical, University of California, San Francisco, University of Pennsylvania Medical Center, Vascudyne Inc, Vesper, Vetex Medical, WhiteSwell, WL Gore & Associates Inc, and Xeltis and personal fees from Abbott Vascular, Boston Scientific, CeloNova BioSciences Inc, OrbusNeich, Terumo Corporation, W. L. Gore & Associates Inc, Edwards Lifesciences, Cook Medical, CSI, ReCor Medical, Sino Medical Sciences Technology Inc, Surmodics Inc, Bard BD, Medtronic plc, and Xeltis outside the submitted work. Dr Min reported serving on the medical advisory board of Arineta during the conduct of the study, having an equity interest and serving on the medical advisory board of Arineta, and having an equity interest and being an employee of Cleerly Inc outside the submitted work. Dr F. Y. Lin reported receiving grants from GE Healthcare outside the submitted work. Dr Slomka reported software royalties from Cedars-Sinai Medical Center during the conduct of the study; grants from the NIH and Siemens AG outside the submitted work; and patents for US8885905B2 and WO2011069120A1 issued. Dr Dey reported receiving software royalties from Cedars-Sinai Medical Center and a patent outside the submitted work. Dr Berman reported a patent for software with royalties paid from Cedars-Sinai Medical Center. No other disclosures were reported.

Figures

Figure 1.
Figure 1.. Frequency of Culprit Lesions According to Number of Adverse Plaque Characteristics (APCs) and Adverse Geometric Characteristics (AGCs)
The prevalence of culprit lesion precursors increased with an increasing number of APCs and AGCs. Lesions containing neither APCs nor AGCs did not develop into culprit lesions. aP < .001 compared with 0 AGCs.
Figure 2.
Figure 2.. Kaplan-Meier Curve for Culprit Lesion Risk According to Number of Adverse Geometric Characteristics (AGCs) and Presence of Adverse Plaque Characteristics (APCs) and/or AGCs
A, The risk of plaques developing into culprit lesions increased with the number of AGCs. B, Plaques with both APCs and AGCs had the greatest probability of becoming culprit lesions compared to plaques with either APCs or AGCs alone, or plaques with neither APCs nor AGCs.
Figure 3.
Figure 3.. Performance of Plaque Characteristics for Identifying Future Culprit Lesions
Receiver operator characteristic curves show the discriminatory value of plaque characteristics for identifying future culprit lesions. The addition of adverse geometric characteristics (AGCs; including positive remodeling, low attenuation plaque, spotty calcification, and napkin-ring sign) to a model containing diameter stenosis (DS), adverse plaque characteristics (APCs; including ostium to lesion distance, bifurcation, and tortuosity), and quantitative plaque characteristics (QPCs; including plaque area at maximal stenosis section, minimum lumen area, total plaque, noncalcified plaque, and necrotic core volume) yielded a higher area under the curve (AUC).
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