Nomogram for evaluating coronary revascularisation necessity based on multi-parameter coronary CT angiography

To build a nomogram model to improve the evaluation of revascularisation necessity using multi-parameter coronary computed tomography (CT) angiography (CCTA). In this retrospective study, 335 patients who underwent CCTA and required revascularisation within 1 month were selected and allocated to the...

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Published in:Clinical radiology Vol. 78; no. 7; pp. e526 - e534
Main Authors: Wang, J., Wu, Q.-X., Zeng, S.-Y., Zhou, L.-J., Zhang, X.-P., Fang, X.-M.
Format: Journal Article
Language:English
Published: England Elsevier Ltd 01.07.2023
Subjects:
Computed Tomography Angiography - methods
Constriction, Pathologic
Coronary Angiography - methods
Coronary Artery Disease - complications
Coronary Artery Disease - diagnostic imaging
Coronary Artery Disease - surgery
Coronary Stenosis - diagnostic imaging
Coronary Stenosis - surgery
Fractional Flow Reserve, Myocardial
Humans
Nomograms
Plaque, Atherosclerotic - complications
Predictive Value of Tests
Radiology
Retrospective Studies
ROC Curve
Tomography, X-Ray Computed
ISSN:0009-9260, 1365-229X, 1365-229X
Online Access:Get full text
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Summary:To build a nomogram model to improve the evaluation of revascularisation necessity using multi-parameter coronary computed tomography (CT) angiography (CCTA). In this retrospective study, 335 patients who underwent CCTA and required revascularisation within 1 month were selected and allocated to the revascularisation group; 208 patients who did not undergo revascularisation were allocated to the non-revascularisation group. CCTA parameters, including CCTA stenosis, plaque qualitative–quantitative characteristics, and fractional flow reserve derived from CT angiography (CT-FFR), for both groups were analysed and compared. Independent risk factors for evaluating revascularisation were obtained using univariate and multivariable regression analysis, after which multi-parameter models were built. Finally, a nomogram was created with these independent risk factors using the R programming language. Plaque analysis was performed successfully for 543 patients with 1,072 target plaques. The performance of the multi-parameter model (AUC 0.894, p<0.001) was significantly higher than that of models based on stenosis (AUC 0.804, p<0.001), plaque qualitative/quantitative characteristics (AUC 0.754/0.789, p<0.001), or CT-FFR (AUC 0.848, p<0.001) alone, to evaluate the necessity of revascularisation. The independent risk factors were CCTA stenosis (OR 1.004, p=0.04), positive remodelling (OR 2.474, p<0.001), total plaque volume (OR 1.001, p<0.001), non-calcified plaque volume proportion (OR 1.019, p<0.001), and CT-FFR (OR 0.001, p<0.001). Subsequently, a nomogram based on these factors was created. The multi-parameter CCTA model improved performance in evaluating revascularisation necessity. The nomogram based on these factors is shows promise in clinical settings. •The multi-parameter CCTA model has good performance for evaluting revascularization.•Nomogram we created is promising in the clinical setting.•ParaMeters in nomogram were CCTA stenosis, PR, TPV, NCPVP, and CT-FFR.
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ISSN:0009-9260
1365-229X
1365-229X
DOI:10.1016/j.crad.2023.03.012