Aims The incremental impact of Atherosclerosis Imaging-Quantitative Computed Tomography (AI-QCT) on diagnostic certainty and downstream patient management is not yet known. The aim of the present study was to compare the clinical utility of routine implementation of AI-QCT versus conventional visual coronary CT angiography (CCTA) interpretation. Methods and Results In this multicenter crossover study in 5 expert CCTA sites, 750 consecutive adult patients referred for CCTA were prospectively recruited. Blinded to the AI-QCT analysis, site physicians established patient diagnosis and plans for downstream non-invasive testing, coronary intervention and medication management based on the conventional site assessment. Next, physicians were asked to repeat their assessments based upon AI-QCT results. The included patients had an age of 63.8 ± 12.2 years, 433 (57.7%) were male. Compared to conventional site CCTA evaluation, AI-QCT analysis improved physician’s confidence 2-5-fold at every step of the care pathway and was associated with change in diagnosis or management in the majority of patients (428; 57.1%; p < 0.001), including for such measures as Coronary Artery Disease-Reporting and Data System (CAD-RADS) (295; 39.3%; p < 0.001) and plaque burden (197; 26.3%; p < 0.001). After AI-QCT including ischemia assessment, the need for downstream non-invasive and invasive testing was reduced by 37.1% (p < 0.001), compared with the conventional site CCTA evaluation. Incremental to the site CCTA evaluation alone, AI-QCT resulted in statin initiation/increase an aspirin initiation in an additional 28.1% (p < 0.001) and 23.0% (p < 0.001) of patients, respectively. Conclusions Use of AI-QCT improves diagnostic certainty, and may result in reduced downstream need for non-invasive testing and increased rates of preventive medical therapy.

中文翻译：

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动脉粥样硬化成像定量计算机断层扫描对诊断确定性、下游检测、冠状动脉血运重建和药物治疗的影响：CERTAIN 研究

目标 动脉粥样硬化成像定量计算机断层扫描 (AI-QCT) 对诊断确定性和下游患者管理的增量影响尚不清楚。本研究的目的是比较常规实施 AI-QCT 与传统可视冠状动脉 CT 血管造影 (CCTA) 解释的临床效用。方法和结果 在这项 5 个 CCTA 专家中心的多中心交叉研究中，前瞻性招募了 750 名转诊接受 CCTA 的连续成年患者。在不了解 AI-QCT 分析的情况下，现场医生根据传统的现场评估确定了患者诊断并制定了下游无创检测、冠状动脉介入和药物管理的计划。接下来，医生被要求根据 AI-QCT 结果重复评估。纳入患者年龄为63.8±12.2岁，其中男性433例（57.7%）。与传统现场 CCTA 评估相比，AI-QCT 分析将医生在护理路径每个步骤的信心提高了 2-5 倍，并且与大多数患者的诊断或管理变化相关（428；57.1%；p < 0.001） ），包括冠状动脉疾病报告和数据系统（CAD-RADS）（295；39.3%；p < 0.001）和斑块负荷（197；26.3%；p < 0.001）等措施。包括缺血评估在内的 AI-QCT 后，与传统现场 CCTA 评估相比，下游无创和有创测试的需求减少了 37.1% (p < 0.001)。作为单独现场 CCTA 评估的增量，AI-QCT 分别导致另外 28.1% (p < 0.001) 和 23.0% (p < 0.001) 的患者开始服用他汀类药物/增加服用阿司匹林。结论 AI-QCT 的使用提高了诊断确定性，并可能减少下游对无创检测的需求并提高预防性药物治疗的比率。