Donghee Han1, Andrew Lin1, Keiichiro Kuronuma1, Evangelos Tzolos2, Alan C Kwan1, Eyal Klein1, Daniele Andreini3, Jeroen J Bax4, Filippo Cademartiri5, Kavitha Chinnaiyan6, Benjamin J W Chow7, Edoardo Conte3, Ricardo C Cury8, Gudrun Feuchtner9, Martin Hadamitzky10, Yong-Jin Kim11, Jonathon A Leipsic12, Erica Maffei13, Hugo Marques14, Fabian Plank9, Gianluca Pontone3, Todd C Villines15, Mouaz H Al-Mallah16, Pedro de Araújo Gonçalves14, Ibrahim Danad17, Heidi Gransar1, Yao Lu18, Ji-Hyun Lee19, Sang-Eun Lee20, Lohendran Baskaran21, Subhi J Al'Aref22, Yeonyee E Yoon18, Alexander Van Rosendael18, Matthew J Budoff23, Habib Samady24, Peter H Stone25, Renu Virmani26, Stephan Achenbach27, Jagat Narula28, Hyuk-Jae Chang29, James K Min30, Fay Y Lin18, Leslee J Shaw18, Piotr J Slomka1, Damini Dey1, Daniel S Berman1. 1. Department of Imaging, Medicine, and Biomedical Sciences, Cedars-Sinai Medical Center, Los Angeles, California. 2. BHF Centre for Cardiovascular Science, University of Edinburgh, Edinburgh, United Kingdom. 3. Department of Clinical Sciences and Community Health, University of Milan, Centro Cardiologico Monzino, Istituto di Ricovero e Cura a Carattere Scientifico (IRCCS), Milan, Italy. 4. Department of Cardiology, Heart Lung Center, Leiden University Medical Center, Leiden, the Netherlands. 5. Cardiovascular Imaging Center, SDN IRCCS, Naples, Italy. 6. Department of Cardiology, William Beaumont Hospital, Royal Oaks, Michigan. 7. Department of Medicine and Radiology, University of Ottawa, Ottawa, Ontario, Canada. 8. Baptist Cardiac and Vascular Institute, Miami, Florida. 9. Department of Radiology, Medical University of Innsbruck, Innsbruck, Austria. 10. Department of Radiology and Nuclear Medicine, German Heart Center, Munich, Germany. 11. Seoul National University College of Medicine, Seoul National University Hospital, Seoul, South Korea. 12. Department of Medicine and Radiology, University of British Columbia, Vancouver, British Columbia, Canada. 13. Department of Radiology, Marche, Urbino, Italy. 14. UNICA, Unit of Cardiovascular Imaging, Hospital da Luz, Lisboa, Portugal. 15. Cardiology Service, Walter Reed National Military Center, Bethesda, Maryland. 16. Houston Methodist DeBakey Heart & Vascular Center, Houston Methodist Hospital, Houston, Texas. 17. Department of Cardiology, VU University Medical Center, Amsterdam, the Netherlands. 18. Dalio Institute of Cardiovascular Imaging, Department of Radiology, New York-Presbyterian Hospital and Weill Cornell Medicine, New York. 19. Division of Cardiology, Department of Internal Medicine, Myongji Hospital, Hanyang University College of Medicine, Goyang, Republic of Korea. 20. Department of Cardiology, Ewha Womans University Seoul Hospital, Seoul, South Korea. 21. Department of Cardiovascular Medicine, National Heart Centre, Singapore. 22. Division of Cardiology, Department of Medicine, University of Arkansas for Medical Sciences, Little Rock. 23. Department of Medicine, Lundquist Institute at Harbor-UCLA (University of California, Los Angeles), Torrance, California. 24. Division of Cardiology, Emory University School of Medicine, Atlanta, Georgia. 25. Cardiovascular Division, Brigham and Women's Hospital, Harvard Medical School, Boston, Massachusetts. 26. Department of Pathology, CVPath Institute, Gaithersburg, Maryland. 27. Department of Cardiology, University of Erlangen, Erlangen, Germany. 28. Department of Cardiology, Icahn School of Medicine at Mt Sinai Hospital, New York, New York. 29. Division of Cardiology, Severance Cardiovascular Hospital, Integrative Cardiovascular Imaging Center, Yonsei University College of Medicine, Seoul, South Korea. 30. Cleerly Inc, New York, New York.
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.
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.
Authors: Ramyashree Tummala; Donghee Han; John Friedman; Sean Hayes; Louise Thomson; Heidi Gransar; Piotr Slomka; Alan Rozanski; Damini Dey; Daniel Berman Journal: Am J Prev Cardiol Date: 2022-09-27