CT-derived Noncardiovascular Calcifications May Improve Coronary Heart Disease Prediction in Chronic Kidney Disease: The Multi-Ethnic Study of Atherosclerosis

Purpose To evaluate whether adding costal cartilage calcification (CCC) to coronary artery calcium (CAC) scores from chest CT improves coronary heart disease (CHD) prediction in patients with chronic kidney disease (CKD). Materials and Methods This study was a secondary analysis of the Multi-Ethnic Study of Atherosclerosis. Participants (April 2010 to January 2012) were stratified into low- and high-risk CKD groups based on Kidney Disease Improving Global Outcomes staging. CAC and CCC were measured from noncontrast CT scans. The primary outcome was incident CHD. Cox proportional hazards regression was performed for each group, with clinical risk factors and CAC (conventional CAC model), and with the addition of CCC (CCC model). Discriminative power was assessed using the area under the receiver operating characteristic curve (AUC). Results A total of 2355 participants (1314 female; median age, 68 years; IQR, 62-76) were included. Median baseline CAC scores were 22 (IQR, 0-183) and 133 (IQR, 20-649), and median CCC scores were 2055 (IQR, 900-4405) and 3187 (IQR, 1370-6516), for low- and high-risk CKD groups, respectively (<i>P</i> < .001 for CAC and <i>P</i> < .05 for CCC). The conventional CAC model showed lower discriminative power for CHD among the high-risk group (AUC, 0.70; 95% CI: 0.56, 0.84) versus the low-risk group (AUC, 0.74; 95% CI: 0.70, 0.78). Adding CCC improved the AUC to 0.75 (95% CI: 0.61, 0.89) in the high-risk group (<i>P</i> = .04), although there was no evidence of improved discrimination in the low-risk group (AUC, 0.74; 95% CI: 0.69, 0.78). Conclusion Clinical and conventional CAC models showed lower discriminative power for predicting CHD in the high-risk CKD group versus the low-risk group. In the high-risk group, adding CCC improved prediction over clinical models. <b>Keywords:</b> CT, Cardiac, Coronary Arteries, Coronary Artery Calcium Score, Costal Cartilage Calcification, Chronic Kidney Disease, Cardiovascular Disease, Coronary Heart Disease ClinicalTrials.gov identifier: NCT00005487 © RSNA, 2025.

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Journal
Radiology Cardiothoracic Imaging
Published
2025-12-01
DOI
https://doi.org/10.1148/ryct.240546
Primary Topic
Parathyroid Disorders and Treatments
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article
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article

CT-derived Noncardiovascular Calcifications May Improve Coronary Heart Disease Prediction in Chronic Kidney Disease: The Multi-Ethnic Study of Atherosclerosis

Hamza Ahmed Ibad, Elena Ghotbi, David A. Bluemke, Aarti Mathur et al.
Radiology Cardiothoracic Imaging
Parathyroid Disorders and Treatments
article

CT-derived Noncardiovascular Calcifications May Improve Coronary Heart Disease Prediction in Chronic Kidney Disease: The Multi-Ethnic Study of Atherosclerosis

Hamza Ahmed Ibad, Elena Ghotbi, David A. Bluemke, Aarti Mathur, João A.C. Lima, Wendy S. Post, Quincy A. Hathaway, Sepehr Akhtarkhavari, Shadpour Demehri, Mahsima Shabani, Matthew Jay Budoff, R. Graham Barr
article en

Abstract

Purpose To evaluate whether adding costal cartilage calcification (CCC) to coronary artery calcium (CAC) scores from chest CT improves coronary heart disease (CHD) prediction in patients with chronic kidney disease (CKD). Materials and Methods This study was a secondary analysis of the Multi-Ethnic Study of Atherosclerosis. Participants (April 2010 to January 2012) were stratified into low- and high-risk CKD groups based on Kidney Disease Improving Global Outcomes staging. CAC and CCC were measured from noncontrast CT scans. The primary outcome was incident CHD. Cox proportional hazards regression was performed for each group, with clinical risk factors and CAC (conventional CAC model), and with the addition of CCC (CCC model). Discriminative power was assessed using the area under the receiver operating characteristic curve (AUC). Results A total of 2355 participants (1314 female; median age, 68 years; IQR, 62-76) were included. Median baseline CAC scores were 22 (IQR, 0-183) and 133 (IQR, 20-649), and median CCC scores were 2055 (IQR, 900-4405) and 3187 (IQR, 1370-6516), for low- and high-risk CKD groups, respectively (<i>P</i> < .001 for CAC and <i>P</i> < .05 for CCC). The conventional CAC model showed lower discriminative power for CHD among the high-risk group (AUC, 0.70; 95% CI: 0.56, 0.84) versus the low-risk group (AUC, 0.74; 95% CI: 0.70, 0.78). Adding CCC improved the AUC to 0.75 (95% CI: 0.61, 0.89) in the high-risk group (<i>P</i> = .04), although there was no evidence of improved discrimination in the low-risk group (AUC, 0.74; 95% CI: 0.69, 0.78). Conclusion Clinical and conventional CAC models showed lower discriminative power for predicting CHD in the high-risk CKD group versus the low-risk group. In the high-risk group, adding CCC improved prediction over clinical models. <b>Keywords:</b> CT, Cardiac, Coronary Arteries, Coronary Artery Calcium Score, Costal Cartilage Calcification, Chronic Kidney Disease, Cardiovascular Disease, Coronary Heart Disease ClinicalTrials.gov identifier: NCT00005487 © RSNA, 2025.

Radiology Cardiothoracic ImagingVol. 7(6)
West Virginia University (US), University of Wisconsin–Madison (US), Johns Hopkins University (US), Columbia University Irving Medical Center (US), Johns Hopkins Medicine (US), Los Angeles Biomedical Research Institute (US), Wisconsin Division of Public Health (US), Vanderbilt University Medical Center (US)
Openalex Percentile: Top 52%
Parathyroid Disorders and Treatments
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