The Coronary Artery Disease–Reporting and Data System (CAD-RADS)

Xie, Joe; Cury, Ricardo C.; Leipsic, Jonathon; Crim, Matthew T; Berman, Daniel S.; Gransar, Heidi; Budoff, Matthew J.; Achenbach, Stephan; Hartaigh, Bríain ó; Callister, Tracy Q.; Marques, Hugo; Rubinshtein, Ronen; Al‐Mallah, Mouaz H.; Andreini, Daniele; Pontone, Gianluca; Cademartiri, Filippo; Maffei, Erica; Chinnaiyan, Kavitha M.; Raff, Gilbert; Hadamitzky, Martin; Hausleiter, Jöerg; Feuchtner, Gudrun; Dunning, Allison; Delago, Augustin; Kim, Yong Jin; Kaufmann, Philipp A.; Villines, Todd C.; Chow, Benjamin J.W.; Hindoyan, Niree; Gomez, Millie; Lin, Fay Y.; Jones, Edward; Min, James K.; Shaw, Leslee J.

doi:10.1016/j.jcmg.2017.08.026

Cited by 99 publications

(30 citation statements)

References 33 publications

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“…Degree of stenosis, plaque morphology, image quality, stents, and coronary artery bypass grafts are evaluated to decide the final CAD-RADS category (CAD-RADS 0 to CAD-RADS 5). Although the CAD-RAD scoring provides important prognostic information in patient undergoing evaluation for coronary artery disease (Xie et al, 2018), this needs to be confirmed using larger registries, and all analysis should incorporate the presence of modifiers (vulnerability, stent, and coronary artery bypass grafting (CABG)) in addition to stenosis severity. While this scoring system has been endorsed by the Society of Cardiovascular Computed Tomography (SCCT), American college of radiology (ACR), and North American society of cardiovascular imaging (NASCI) (Cury et al, 2016), it remains mainly a research tool and requires further refinement prior to routine clinical implementation.…”

Section: Obstructive Versus Non-obstructive Diseasementioning

confidence: 99%

Detecting unstable plaques in humans using cardiac CT: Can it guide treatments?

Daghem

Newby

2020

British J Pharmacology

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Advances in imaging technology have driven the rapid expansion in the use of CT in the assessment of coronary atherosclerotic plaque. Based on a rapidly growing evidence base, current guidelines recommend coronary CT angiography as the first‐line diagnostic test for patients presenting with stable chest pain. There is a growing need to refine current methods for diagnosis and risk stratification to improve the individualisation of preventative therapies. Imaging assessments of high‐risk plaque with CT can be used to differentiate stable from unstable patterns of coronary atherosclerosis and potentially to improve patient risk stratification. This review will focus on coronary imaging with CT with a specific focus on the detection of coronary atherosclerosis, high‐risk plaque features, and the implications for patient management.

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Section: Obstructive Versus Non-obstructive Diseasementioning

confidence: 99%

Detecting unstable plaques in humans using cardiac CT: Can it guide treatments?

Daghem

Newby

2020

British J Pharmacology

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“…CAD-RADS can now guide clinical decision-making using CCTA and may play a significant role in connecting lesion detections with optimal patient care. The recent multinational CONFIRM study revealed that standardized CCTA reports incorporated with CAD-RADS might promote the development of evidence-based care post-CCTA 29 . BAC predicted a CAD-RADS grade ≥ 3 in the present study.…”

Section: Discussionmentioning

confidence: 99%

The correlation of deep learning-based CAD-RADS evaluated by coronary computed tomography angiography with breast arterial calcification on mammography

Huang

Xiao

Xie

et al. 2020

Sci Rep

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This study sought to evaluate the association of breast arterial calcification (BAC) on breast screening mammography with the Coronary Artery Disease-Reporting and Data System (CAD-RADS) based on Deep Learning-coronary computed tomography angiography (CCTA). This prospective single institution study included asymptomatic women over 40 who underwent CCTA and breast cancer screening mammography between July 2018 and April 2019. CAD-RADS was scored based on Deep Learning (DL). Mammograms were assessed visually for the presence of BAC. A total of 213 patients were included in the analysis. In comparison to the low CAD-RADS (CAD-RADS < 3) group, the high CAD-RADS (CAD-RADS ≥ 3) group, more often had a history of hypertension ( P = 0.036), diabetes ( P = 0.017), and chronic kidney disease ( P = 0.006). They also had a significantly higher level of LDL-C ( P = 0.024), while HDL-C was lower than in the low CAD-RADS group ( P = 0.003). BAC was also significantly higher in the high CAD-RADS group ( P = 0.002). In multivariate analysis, the presence of BAC [odd ratio (OR) 10.22, 95% CI 2.86–36.49, P < 0.001] maintained a significant associations with CAD-RADS after adjustment by meaningful variable. The same tendency was also found after adjustment by all covariates. There was a significant correlation between the severities of CAD detected by DL based CCTA and BAC in women undergoing breast screening mammography. BAC may be used as an additional diagnostic tool to predict the severity of CAD in this population.

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“…Coronary arteries with a diameter ≥2 mm were evaluated according to a 17-segment coronary artery model using axial, multi-planar reformation, maximum intensity projection, and cross-sectional images [17]. CAD-RADS 0, 1, 2, 3, 4A, 4B, and 5 were de ned as 0% (absence of CAD) stenosis; 1-24% stenosis; 25-49% stenosis; 50-69% stenosis; 70-99% stenosis in one or two vessels; 70-99% stenosis in three vessels or left main coronary artery stenosis ≥50%; and 100% stenosis (total coronary occlusion), respectively (Figure 1) [13][14][15]. The most severe stenosis was considered if a single vessel had multiple lesions.…”

Section: Assessment Of Coronary Artery Stenosis and Plaquementioning

confidence: 99%

“…The CAD reporting and data system (CAD-RADS) was established to standardize and facilitate the reporting of CCTA data regarding CAD [13,14]. The prognostic value of CAD-RADS for predicting major adverse cardiac events (MACE) in stable CAD patients remains controversial compared with traditional classi cations [14,15]. Moreover, it is unknown whether the combination of CAD-RADS and MFR is helpful in predicting MACE.…”

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confidence: 99%

Risk stratification in coronary artery disease using NH3-PET myocardial flow reserve and CAD-RADS on coronary CT angiography

Yamamoto

Nagao

Ando

et al. 2021

Int J Cardiovasc Imaging

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Myocardial ow reserve (MFR) derived from 13 N-ammonia positron emission tomography (NH 3 -PET) can predict the prognosis of patients with various heart diseases. Coronary computed tomography angiography (CCTA) is a non-invasive investigation for ischemic heart disease. The coronary artery disease reporting and data system (CAD-RADS) was established to standardize and facilitate the reporting of CCTA data regarding CAD. This study aimed to investigate the prognostic value of CAD-RADS and MFR. MethodsA total of 133 patients who underwent NH 3 -PET and CCTA within 3 months were enrolled. Patients were divided into groups with CAD-RADS 0-2 and ≥3 and into groups with MFR ≥2.0 and <2.0. The endpoint was major adverse cardiac events (MACE) comprising all-cause death, acute coronary syndrome, hospitalization due to heart failure, and cerebrovascular disease. The ability of CAD-RADS and MFR to predict MACE was analyzed using Kaplan-Meier analysis. ResultsThere was no signi cant difference in MFR between patients with CAD-RADS 0-2 and ≥3 (2.3±0.9 vs. 2.2±0.7, p=0.50). The MACE rate for patients with CAD-RADS 0-2 and ≥3 was equivalent (log-rank test, p=0.64). Patients with MFR <2.0 had a signi cantly higher MACE rate than those with MFR ≥2.0 (p=0.017). In patients with CAD-RADS ≥3, patients with MFR <2.0 had a signi cantly higher MACE rate than those with MFR ≥2.0 (p=0.034). ConclusionCAD-RADS did not contribute to MACE prediction. Conversely, MFR was useful in predicting MACE, allowing for further risk strati cation in addition to CAD-RADS.

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The Coronary Artery Disease–Reporting and Data System (CAD-RADS)

Cited by 99 publications

References 33 publications

Detecting unstable plaques in humans using cardiac CT: Can it guide treatments?

Detecting unstable plaques in humans using cardiac CT: Can it guide treatments?

The correlation of deep learning-based CAD-RADS evaluated by coronary computed tomography angiography with breast arterial calcification on mammography

Risk stratification in coronary artery disease using NH3-PET myocardial flow reserve and CAD-RADS on coronary CT angiography

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