Abstract
Today, the 10-year cardiovascular risk largely relies on conventional cardiovascular risk factors (CCVRFs) and suffers from the effect of atherosclerotic wall changes. In this study, we present a novel risk calculator AtheroEdge Composite Risk Score (AECRS1.0), designed by fusing CCVRF with ultrasound image-based phenotypes. Ten-year risk was computed using the Framingham Risk Score (FRS), United Kingdom Prospective Diabetes Study 56 (UKPDS56), UKPDS60, Reynolds Risk Score (RRS), and pooled composite risk (PCR) score. AECRS1.0 was computed by measuring the 10-year five carotid phenotypes such as IMT (ave., max., min.), IMT variability, and total plaque area (TPA) by fusing eight CCVRFs and then compositing them. AECRS1.0 was then benchmarked against the five conventional cardiovascular risk calculators by computing the receiver operating characteristics (ROC) and area under curve (AUC) values with a 95% CI. Two hundred four IRB-approved Japanese patients’ left/right common carotid arteries (407 ultrasound scans) were collected with a mean age of 69 ± 11 years. The calculators gave the following AUC: FRS, 0.615; UKPDS56, 0.576; UKPDS60, 0.580; RRS, 0.590; PCRS, 0.613; and AECRS1.0, 0.990. When fusing CCVRF, TPA reported the highest AUC of 0.81. The patients were risk-stratified into low, moderate, and high risk using the standardized thresholds. The AECRS1.0 demonstrated the best performance on a Japanese diabetes cohort when compared with five conventional calculators.
Similar content being viewed by others
Notes
As it is coined from original research article
As it is coined from original research article
References
Acharya UR, Sree SV, Krishnan MMR, Molinari F, Saba L, Ho SYS, Ahuja AT, Ho SC, Nicolaides A, Suri JS (2012) Atherosclerotic risk stratification strategy for carotid arteries using texture-based features. Ultrasound Med Biol 38:899–915
Alsulaimani S, Gardener H, Elkind MS, Cheung K, Sacco RL, Rundek T (2013) Elevated homocysteine and carotid plaque area and densitometry in the Northern Manhattan Study. Stroke 44:457–461. https://doi.org/10.1161/strokeaha.112.676155
Anderson TJ, Grégoire J, Hegele RA, Couture P, Mancini GJ, McPherson R, Francis GA, Poirier P, Lau DC, Grover S (2013) 2012 update of the Canadian Cardiovascular Society guidelines for the diagnosis and treatment of dyslipidemia for the prevention of cardiovascular disease in the adult. Can J Cardiol 29:151–167
Baradaran H, Ng CR, Gupta A, Noor NM, Al-Dasuqi KW, Mtui EE, Rijal OM, Giannopoulos A, Nicolaides A, Laird JR (2017) Extracranial internal carotid artery calcium volume measurement using computer tomography. Int Angiol 36:445–461
Biswas M, Kuppili V, Araki T, Edla DR, Godia EC, Saba L, Suri HS, Omerzu T, Laird JR, Khanna NN, Nicolaides A, Suri JS (2018) Deep learning strategy for accurate carotid intima-media thickness measurement: an ultrasound study on Japanese diabetic cohort. Comput Biol Med 98:100–117. https://doi.org/10.1016/j.compbiomed.2018.05.014
Bots ML, Hoes AW, Koudstaal PJ, Hofman A, Grobbee DE (1997) Common carotid intima-media thickness and risk of stroke and myocardial infarction: the Rotterdam Study. Circulation 96:1432–1437
Chambless LE, Heiss G, Folsom AR, Rosamond W, Szklo M, Sharrett AR, Clegg LX (1997) Association of coronary heart disease incidence with carotid arterial wall thickness and major risk factors: the Atherosclerosis Risk in Communities (ARIC) Study, 1987–1993. Am J Epidemiol 146:483–494
Chambless LE, Folsom AR, Clegg LX, Sharrett AR, Shahar E, Nieto FJ, Rosamond WD, Evans G (2000) Carotid wall thickness is predictive of incident clinical stroke: the Atherosclerosis Risk in Communities (ARIC) study. Am J Epidemiol 151:478–487
Conroy R, Pyörälä K, Fitzgerald AE, Sans S, Menotti A, De Backer G, De Bacquer D, Ducimetiere P, Jousilahti P, Keil U (2003) Estimation of ten-year risk of fatal cardiovascular disease in Europe: the SCORE project. Eur Heart J 24:987–1003
Cuadrado-Godia E, Maniruzzaman M, Araki T, Puvvula A, Rahman MJ, Saba L, Suri HS, Gupta A, Banchhor SK, Teji JS (2018) Morphologic TPA (mTPA) and composite risk score for moderate carotid atherosclerotic plaque is strongly associated with HbA1c in diabetes cohort. Comput Biol Med 101:128–145
Cuadrado-Godia E, Srivastava SK, Saba L, Araki T, Suri HS, Giannopolulos A, Omerzu T, Laird J, Khanna NN, Mavrogeni S, Kitas GD, Nicolaides A, Suri JS (2018) Geometric total plaque area is an equally powerful phenotype compared with carotid intima-media thickness for stroke risk assessment: a deep learning approach. J Vasc Ultrasound 1544316718806421. https://doi.org/10.1177/1544316718806421
Cuadrado-Godia E, Jamthikar AD, Gupta D, et al (2019) Ranking of stroke and cardiovascular risk factors for an optimal risk calculator design. Logistic regression approach. Computers in biology and medicine. https://doi.org/10.1016/j.compbiomed.2019.03.020
D’Agostino RB, Vasan RS, Pencina MJ, Wolf PA, Cobain M, Massaro JM, Kannel WB (2008) General cardiovascular risk profile for use in primary care: the Framingham Heart Study. Circulation 117:743–753
Den Ruijter HM, Peters SA, Anderson TJ, Britton AR, Dekker JM, Eijkemans MJ, Engstrom G, Evans GW, de Graaf J, Grobbee DE, Hedblad B, Hofman A, Holewijn S, Ikeda A, Kavousi M, Kitagawa K, Kitamura A, Koffijberg H, Lonn EM, Lorenz MW, Mathiesen EB, Nijpels G, Okazaki S, O’Leary DH, Polak JF, Price JF, Robertson C, Rembold CM, Rosvall M, Rundek T, Salonen JT, Sitzer M, Stehouwer CD, Witteman JC, Moons KG, Bots ML (2012) Common carotid intima-media thickness measurements in cardiovascular risk prediction: a meta-analysis. JAMA 308:796–803. https://doi.org/10.1001/jama.2012.9630
Dong J-Y, Zhang Y-H, Qin L-Q (2011) Erectile dysfunction and risk of cardiovascular disease. J Am Coll Cardiol 58:1378–1385
Duerden M, O’Flynn N, Qureshi N (2015) Cardiovascular risk assessment and lipid modification: NICE guideline. Br J Gen Pract 65:378–380
Fan W, Ping Y (2011) Association of risk factors for cardiovascular disease and glomerular filtration rate: a community-based study of 4925 adults in Beijing. Heart 97:A95
Goff DC, Lloyd-Jones DM, Bennett G, Coady S, D’agostino RB, Gibbons R, Greenland P, Lackland DT, Levy D, O’donnell CJ (2014) 2013 ACC/AHA guideline on the assessment of cardiovascular risk: a report of the American College of Cardiology/American Heart Association Task Force on Practice Guidelines. J Am Coll Cardiol 63:2935–2959
Helfand M, Buckley DI, Freeman M, Fu R, Rogers K, Fleming C, Humphrey LL (2009) Emerging risk factors for coronary heart disease: a summary of systematic reviews conducted for the U.S. Preventive Services Task Force. Ann Intern Med 151:496–507
Hippisley-Cox J, Coupland C, Vinogradova Y, Robson J, Minhas R, Sheikh A, Brindle P (2008) Predicting cardiovascular risk in England and Wales: prospective derivation and validation of QRISK2. BMJ 336:1475–1482
Hippisley-Cox J, Coupland C, Brindle P (2017) Development and validation of QRISK3 risk prediction algorithms to estimate future risk of cardiovascular disease: prospective cohort study. BMJ 357:1-12. https://doi.org/10.1136/bmj.j2099
Ikeda N, Saba L, Molinari F, Piga M, Meiburger K, Sugi K, Porcu M, Bocchiddi L, Acharya UR, Nakamura M, Nakano M, Nicolaides A, Suri JS (2013) Automated carotid intima-media thickness and its link for prediction of SYNTAX score in Japanese coronary artery disease patients. Int Angiol 32:339–348
Ikeda N, Araki T, Sugi K, Nakamura M, Deidda M, Molinari F, Meiburger KM, Acharya UR, Saba L, Bassareo PP, Di Martino M, Nagashima Y, Mercuro G, Nakano M, Nicolaides A, Suri JS (2014) Ankle-brachial index and its link to automated carotid ultrasound measurement of intima-media thickness variability in 500 Japanese coronary artery disease patients. Curr Atheroscler Rep 16:393. https://doi.org/10.1007/s11883-013-0393-x
Johnsen SH, Mathiesen EB, Joakimsen O, Stensland E, Wilsgaard T, Løchen M-L, Njølstad I, Arnesen E (2007) Carotid atherosclerosis is a stronger predictor of myocardial infarction in women than in men: a 6-year follow-up study of 6226 persons: the Tromsø Study. Stroke 38:2873–2880
Kothari V, Stevens RJ, Adler AI, Stratton IM, Manley SE, Neil HA, Holman RR (2002) UKPDS 60: risk of stroke in type 2 diabetes estimated by the UK Prospective Diabetes Study risk engine. Stroke 33:1776–1781
Kumar PK, Araki T, Rajan J, Saba L, Lavra F, Ikeda N, Sharma AM, Shafique S, Nicolaides A, Laird JR (2017) Accurate lumen diameter measurement in curved vessels in carotid ultrasound: an iterative scale-space and spatial transformation approach. Med Biol Eng Comput 55:1415–1434
Lorenz MW, von Kegler S, Steinmetz H, Markus HS, Sitzer M (2006) Carotid intima-media thickening indicates a higher vascular risk across a wide age range: prospective data from the Carotid Atherosclerosis Progression Study (CAPS). Stroke 37:87–92
Lorenz MW, Polak JF, Kavousi M, Mathiesen EB, Völzke H, Tuomainen T-P, Sander D, Plichart M, Catapano AL, Robertson CM (2012) Carotid intima-media thickness progression to predict cardiovascular events in the general population (the PROG-IMT collaborative project): a meta-analysis of individual participant data. Lancet 379:2053–2062
Lucatelli P, Raz E, Saba L, Argiolas GM, Montisci R, Wintermark M, King KS, Molinari F, Ikeda N, Siotto P (2016) Relationship between leukoaraiosis, carotid intima-media thickness and intima-media thickness variability: preliminary results. Eur Radiol 26:4423–4431
Mathiesen Ellisiv B, Johnsen Stein H, Wilsgaard T, Bønaa Kaare H, Løchen M-L, Njølstad I (2011) Carotid plaque area and intima-media thickness in prediction of first-ever ischemic stroke. Stroke 42:972–978. https://doi.org/10.1161/STROKEAHA.110.589754
Molinari F, Zeng G, Suri JS (2010) Intima-media thickness: setting a standard for a completely automated method of ultrasound measurement. IEEE Trans Ultrason Ferroelectr Freq Control 57:1112–1124. https://doi.org/10.1109/TUFFC.2010.1522
Molinari F, Zeng G, Suri JS (2010) A state of the art review on intima-media thickness (IMT) measurement and wall segmentation techniques for carotid ultrasound. Comput Methods Prog Biomed 100:201–221. https://doi.org/10.1016/j.cmpb.2010.04.007
Molinari F, Meiburger KM, Saba L, Zeng G, Acharya UR, Ledda M, Nicolaides A, Suri JS (2012) Fully automated dual-snake formulation for carotid intima-media thickness measurement: a new approach. J Ultrasound Med 31:1123–1136
Molinari F, Meiburger KM, Zeng G, Acharya UR, Liboni W, Nicolaides A, Suri JS (2012) Carotid artery recognition system: a comparison of three automated paradigms for ultrasound images. Med Phys 39:378–391. https://doi.org/10.1118/1.3670373
Molinari F, Meiburger KM, Zeng G, Saba L, Rajendra Acharya U, Famiglietti L, Georgiou N, Nicolaides A, Sriswan Mamidi R, Kuper H, Suri JS (2012) Automated carotid IMT measurement and its validation in low contrast ultrasound database of 885 patient Indian population epidemiological study: results of AtheroEdge software. Int Angiol 31:42–53
Molinari F, Pattichis CS, Zeng G, Saba L, Acharya UR, Sanfilippo R, Nicolaides A, Suri JS (2012) Completely automated multiresolution edge snapper—a new technique for an accurate carotid ultrasound IMT measurement: clinical validation and benchmarking on a multi-institutional database. IEEE Trans Image Process 21:1211–1222
Nambi V, Chambless L, Folsom AR, He M, Hu Y, Mosley T, Volcik K, Boerwinkle E, Ballantyne CM (2010) Carotid intima-media thickness and presence or absence of plaque improves prediction of coronary heart disease risk: the ARIC (Atherosclerosis Risk In Communities) study. J Am Coll Cardiol 55:1600–1607
O’Donnell MJ, Xavier D, Liu L, Zhang H, Chin SL, Rao-Melacini P, Rangarajan S, Islam S, Pais P, McQueen MJ (2010) Risk factors for ischaemic and intracerebral haemorrhagic stroke in 22 countries (the INTERSTROKE study): a case-control study. Lancet 376:112–123
O’Leary DH, Bots ML (2010) Imaging of atherosclerosis: carotid intima–media thickness. Eur Heart J 31:1682–1689
O’Leary DH, Polak JF, Kronmal RA, Manolio TA, Burke GL, Wolfson SK Jr (1999) Carotid-artery intima and media thickness as a risk factor for myocardial infarction and stroke in older adults. N Engl J Med 340:14–22
Polak JF, Pencina MJ, Pencina KM, O’Donnell CJ, Wolf PA, D’Agostino RB Sr (2011) Carotid-wall intima-media thickness and cardiovascular events. N Engl J Med 365:213–221. https://doi.org/10.1056/NEJMoa1012592
Ridker PM, Buring JE, Rifai N, Cook NR (2007) Development and validation of improved algorithms for the assessment of global cardiovascular risk in women: the Reynolds Risk Score. Jama 297:611–619
Ridker PM, Paynter NP, Rifai N, Gaziano JM, Cook NR (2008) C-reactive protein and parental history improve global cardiovascular risk prediction: the Reynolds Risk Score for men. Circulation 118:2243–2251
Romanens M, Mortensen MB, Sudano I, Szucs T, Adams A (2017) Extensive carotid atherosclerosis and the diagnostic accuracy of coronary risk calculators. Prev Med Rep 6:182–186. https://doi.org/10.1016/j.pmedr.2017.03.006
Rosengren A, Hawken S, Ôunpuu S, Sliwa K, Zubaid M, Almahmeed WA, Blackett KN, Sitthi-amorn C, Sato H, Yusuf S (2004) Association of psychosocial risk factors with risk of acute myocardial infarction in 11 119 cases and 13 648 controls from 52 countries (the INTERHEART study): case-control study. Lancet 364:953–962
Rosvall M, Janzon L, Berglund G, Engström G, Hedblad B (2005) Incident coronary events and case fatality in relation to common carotid intima-media thickness. J Intern Med 257:430–437
Rundek T, Spence JD (2013) Ultrasonographic measure of carotid plaque burden. JACC Cardiovasc Imaging 6:129
Saba L, Mallarini G, Sanfilippo R, Zeng G, Montisci R, Suri J (2012) Intima media thickness variability (IMTV) and its association with cerebrovascular events: a novel marker of carotid therosclerosis? Cardiovasc Diagn Ther 2:10–18. https://doi.org/10.3978/j.issn.2223-3652.2011.11.01
Saba L, Molinari F, Meiburger KM, Piga M, Zeng G, Rajendra Achraya U, Nicolaides A, Suri JS (2012) What is the correct distance measurement metric when measuring carotid ultrasound intima-media thickness automatically? Int Angiol 31:483–489
Saba L, Montisci R, Molinari F, Tallapally N, Zeng G, Mallarini G, Suri JS (2012) Comparison between manual and automated analysis for the quantification of carotid wall by using sonography. A validation study with CT. Eur J Radiol 81:911–918. https://doi.org/10.1016/j.ejrad.2011.02.047
Saba L, Banchhor SK, Suri HS, Londhe ND, Araki T, Ikeda N, Viskovic K, Shafique S, Laird JR, Gupta A (2016) Accurate cloud-based smart IMT measurement, its validation and stroke risk stratification in carotid ultrasound: a web-based point-of-care tool for multicenter clinical trial. Comput Biol Med 75:217–234
Saba L, Jain PK, Suri HS, Ikeda N, Araki T, Singh BK, Nicolaides A, Shafique S, Gupta A, Laird JR (2017) Plaque tissue morphology-based stroke risk stratification using carotid ultrasound: a polling-based PCA learning paradigm. J Med Syst 41:98
Saba L, Banchhor SK, Araki T, et al (2018) Intraand Inter-operator Reproducibility Analysis of Automated Cloud-based Carotid Intima Media Thickness Ultrasound Measurement. Journal of Clinical & Diagnostic Research, 12(2):KC01-KC11. https://doi.org/10.7860/JCDR/2018/34311.11217
Saba L, Banchhor SK, Araki T, Viskovic K, Londhe ND, Laird JR, Suri HS, Suri JS (2018) Intra-and inter-operator reproducibility of automated cloud-based carotid lumen diameter ultrasound measurement. Indian Heart J 70:649–664
Salonen JT, Salonen R (1991) Ultrasonographically assessed carotid morphology and the risk of coronary heart disease. Arterioscler Thromb Vasc Biol 11:1245–1249
Seabra J, Sanches JM (2012) RF ultrasound estimation from b-mode images. In Ultrasound Imaging. Springer 3-24
Sharma AM, Gupta A, Kumar PK, Rajan J, Saba L, Nobutaka I, Laird JR, Nicolades A, Suri JS (2015) A review on carotid ultrasound atherosclerotic tissue characterization and stroke risk stratification in machine learning framework. Curr Atheroscler Rep 17:55
Spence JD, Solo K (2017) Resistant atherosclerosis: the need for monitoring of plaque burden. Stroke 48:1624–1629
Spence JD, Eliasziw M, DiCicco M, Hackam DG, Galil R, Lohmann T (2002) Carotid plaque area: a tool for targeting and evaluating vascular preventive therapy. Stroke 33:2916–2922
Stein JH, Korcarz CE, Hurst RT, Lonn E, Kendall CB, Mohler ER, Najjar SS, Rembold CM, Post WS (2008) Use of carotid ultrasound to identify subclinical vascular disease and evaluate cardiovascular disease risk: a consensus statement from the American Society of Echocardiography Carotid Intima-Media Thickness Task Force endorsed by the Society for Vascular Medicine. J Am Soc Echocardiogr 21:93–111
Stevens RJ, Kothari V, Adler AI, Stratton IM, Holman RR (2001) The UKPDS risk engine: a model for the risk of coronary heart disease in type II diabetes (UKPDS 56). Clin Sci 101:671–679
Stone NJ, Robinson JG, Lichtenstein AH, Merz CNB, Blum CB, Eckel RH, Goldberg AC, Gordon D, Levy D, Lloyd-Jones DM (2014) 2013 ACC/AHA guideline on the treatment of blood cholesterol to reduce atherosclerotic cardiovascular risk in adults: a report of the American College of Cardiology/American Heart Association Task Force on Practice Guidelines. J Am Coll Cardiol 63:2889–2934
Sturlaugsdottir R, Aspelund T, Bjornsdottir G, Sigurdsson S, Thorsson B, Eiriksdottir G, Gudnason V (2018) Predictors of carotid plaque progression over a 4-year follow-up in the Reykjavik REFINE-study. Atherosclerosis 269:57–62
Suri JS, Haralick RM, Sheehan FH (2000) Greedy algorithm for error correction in automatically produced boundaries from low contrast ventriculograms. Pattern Anal Applic 3:39–60
U.S. Preventive Services Task Force (2009) Using nontraditional risk factors in coronary heart disease risk assessment: U.S. Preventive Services Task Force recommendation statement. Ann Intern Med 151:474–482
WHO. Cardiovascular disease http://www.who.int/cardiovascular_diseases/en/. Accessed 1 Oct 2018
Yang X, So W-Y, Kong AP, Ho C-S, Lam CW, Stevens RJ, Lyu RR, Yin DD, Cockram CS, Tong PC (2007) Development and validation of stroke risk equation for Hong Kong Chinese patients with type 2 diabetes: the Hong Kong Diabetes Registry. Diabetes Care 30:65–70
Yayan J (2012) Erythrocyte sedimentation rate as a marker for coronary heart disease. Vasc Health Risk Manag 8:219
Yousuf O, Mohanty BD, Martin SS, Joshi PH, Blaha MJ, Nasir K, Blumenthal RS, Budoff MJ (2013) High-sensitivity C-reactive protein and cardiovascular disease. J Am Coll Cardiol 62:397–408
Zingg S, Collet T-H, Locatelli I, Nanchen D, Depairon M, Bovet P, Cornuz J, Rodondi N (2015) Associations between cardiovascular risk factors, inflammation, and progression of carotid atherosclerosis among smokers. Nicotine Tob Res 18:1533–1538
Author information
Authors and Affiliations
Corresponding author
Ethics declarations
Disclosure
Dr. Jasjit Suri is affiliated to AtheroPoint™, focused on the area of stroke and cardiovascular imaging.
Conflict of interest
The authors declare that they have no conflict of interest.
Additional information
Publisher’s note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Electronic supplementary material
ESM 1
(DOCX 28 kb)
Rights and permissions
About this article
Cite this article
Khanna, N.N., Jamthikar, A.D., Gupta, D. et al. Effect of carotid image-based phenotypes on cardiovascular risk calculator: AECRS1.0. Med Biol Eng Comput 57, 1553–1566 (2019). https://doi.org/10.1007/s11517-019-01975-2
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s11517-019-01975-2