Prediction of the Statin responders with radiomics.

Journal of cardiovascular computed tomography Pub Date : 2026-06-04 DOI:10.1016/j.jcct.2026.05.010

Sang-Eun Lee, Youngtaek Hong, Juyeong Jung, Ji Min Sung, Daniele Andreini, Mouaz H Al-Mallah, Matthew J Budoff, Filippo Cademartiri, Kavitha Chinnaiyan, Jung Hyun Choi, Eun Ju Chun, Edoardo Conte, Ilan Gottlieb, Martin Hadamitzky, Yong Jin Kim, Byoung Kwon Lee, Jonathon A Leipsic, Erica Maffei, Hugo Marques, Pedro de Araújo Gonçalves, Gianluca Pontone, Sanghoon Shin, Peter H Stone, Habib Samady, Renu Virmani, Jagat Narula, Leslee J Shaw, Jeroen J Bax, Fay Y Lin, James K Min, Hyuk-Jae Chang

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Abstract

Background: Statins are a cornerstone medication for coronary atherosclerosis. This study assessed whether radiomic analysis of coronary computed tomography angiography (CCTA) could predict patient response to statin therapy.

Methods: Patients from a multinational registry with serial CCTA (≥2-year intervals) on statin therapy were analyzed. Radiomic scores were calculated, categorizing patients as statin responders or non-responders (≥1.0% increase in percent atheroma volume (PAV) per year indicated non-response). Data were split into training (79%) and test (21%) sets based on sites. Four predictive models were developed: Model 1 used clinical risk factors (CRF), Model 2 included CRF, calcified and non-calcified PAV, and number of high-risk plaques. Model 3 used only the radiomic score, and Model 4 combined Models 2 and 3.

Results: A total of 386 statin responders (mean age 61.2 ± 8.4 years, 60.1% male) and 177 statin non-responders (mean age 63.2 ± 9.0 years, 44.1% male) were analyzed. Model 3, based solely on the radiomic score, demonstrated superior predictive power compared to Model 1 (area under the receiver operating characteristic curve [AUC] [95% confidence interval (CI)]: 0.75 [0.67-0.83] vs 0.54 [0.45-0.63], p < 0.05) and was comparable to Model 2 (AUC [95% CI]: 0.82 [0.74-0.88], p > 0.05) in the test set. Model 4 exhibited the highest power (AUC [95% CI]: 0.84 [0.77-0.90], all p < 0.05 compared to Model 2 and Model 3).

Conclusion: CCTA radiomic features show proof-of-concept for predicting statin response, warranting further validation.

Clinical trial registration: ClinicalTrials.gov NCT0280341.

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放射组学预测他汀类药物应答者。

背景：他汀类药物是治疗冠状动脉粥样硬化的基础药物。本研究评估了冠状动脉计算机断层血管造影（CCTA）放射组学分析是否可以预测患者对他汀类药物治疗的反应。方法：对来自多国注册的连续CCTA（≥2年间隔）接受他汀类药物治疗的患者进行分析。计算放射组评分，将患者分为他汀类药物反应者或无反应者（动脉粥样瘤体积百分比（PAV）每年增加≥1.0%表示无反应）。数据根据地点分为训练集（79%）和测试集（21%）。建立了四种预测模型：模型1使用临床危险因素（CRF），模型2包括CRF、钙化和非钙化PAV以及高危斑块数量。模型3仅使用放射学评分，模型4结合模型2和模型3。结果：共分析了386例他汀类药物应答者（平均年龄61.2±8.4岁，男性60.1%）和177例他汀类药物无应答者（平均年龄63.2±9.0岁，男性44.1%）。模型3仅基于放射组学评分，与模型1相比（受试者工作特征曲线下面积[AUC][95%置信区间（CI）]: 0.75 [0.67-0.83] vs 0.54 [0.45-0.63], p < 0.05），在测试集中与模型2 （AUC [95% CI]: 0.82 [0.74-0.88], p > 0.05）相当。模型4的功率最高（AUC [95% CI]: 0.84[0.77 ~ 0.90]，与模型2和模型3比较，p均< 0.05）。结论：CCTA放射学特征显示了预测他汀类药物反应的概念验证，需要进一步验证。临床试验注册：ClinicalTrials.gov NCT0280341。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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Journal of cardiovascular computed tomography

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