Diagnostic and prognostic value of coronary artery flow and morphology in a multicentre randomised trial of computed tomography versus invasive angiography: clinical radiomics analysis

计算机断层扫描与侵入性血管造影多中心随机试验中冠状动脉血流和形态的诊断和预后价值：临床放射组学分析

• 批准号: 428223139
• 负责人: Professor Dr. Marc Dewey, since 2/2023
• 金额: --
• 依托单位: Institut für Radiologie (CCM) (aufgelöst)
• 依托单位国家: 德国
• 项目类别: Priority Programmes
• 财政年份: 2019
• 资助国家: 德国
• 起止时间: 2018-12-31 至 2023-12-31
• 项目状态: 已结题
• 来源: https://gepris.dfg.de/gepris/projekt/428223139?language=en
• 关键词: Diagnostic; prognostic; value; coronary; artery

Background and Objective: Computed tomography angiography (CTA) allows reliably and noninvasively excluding coronary artery stenosis when using invasive coronary angiography (ICA) as the diagnostic reference standard. There is also early evidence that coronary flow values can be derived from CTA using computational fluid dynamics (CFD) or machine learning (ML) with accuracy similar to adenosine-based flow reserve in ICA. By applying similar models of CFD to the morphological information from ICA, the quantitative flow ratio (QFR) can be computed without the necessity of a pressure wire. However, the prognostic value of CTA using CFD or ML and ICA using QFR has not been determined in a randomised trial; yet such a randomised comparison would be crucial for clinical translation and implementation. We propose to analyze CTA using advanced image processing with prospectively obtained data from randomised trials. In this project, we will explore the capabilities of CFD and ML to improve diagnosis and prognosis of coronary CTA in patients with suspected coronary artery stenosis. Methods and Work Programme: We conducted two randomised trials of CTA and ICA in patients with suspected coronary artery stenosis: the single-centre CAD-Man study in 340 patients and the multicentre DISCHARGE trial in 3546 patients. Both trials included an initial diagnostic management phase after CTA and ICA as well as a long-term clinical follow-up after a maximum of four years which provides clearly defined endpoints for comparing the diagnostic and prognostic value of CT using CFD and ML and ICA using QFR. To achieve this comparison we will first prepare and pre-process existing imaging data from patients randomised to CTA and ICA in DISCHARGE. This ensures homogenisation of CTA and ICA data, which stem from 26 different European sites, to achieve robust and generalizable results for stenosis and flow reserve quantification. Second, we will conduct feature extraction for advanced image processing of CTA and ICA data from the DISCHARGE trial data for stenosis and flow quantification. Third, these features will be used in the core of this project, which is the implementation and exploration of the radiomics analysis to compare the diagnostic and prognostic value of CTA and ICA. This will be done using endpoints prospectively defined including stenosis and flow results for diagnostic values as well as myocardial infarction, stroke, and cardiovascular death for prognostic value. The quantitative results of image analysis will be made available as a database within and beyond the SPP. Anticipated Gain of Knowledge: We anticipated novel insights into the association of CTA-derived features of coronary flow and morphology with diagnostic and prognostic outcomes of patients. The randomised comparison with ICA ensures that the results can lead to direct clinical translation and implementation of coronary CTA in the work-up for patients with suspected coronary artery stenosis.

背景和目的：以有创冠状动脉造影术(ICA)为诊断标准，CT血管造影术(CTA)可以可靠、无创地排除冠状动脉狭窄。也有早期证据表明，可以使用计算流体动力学(CFD)或机器学习(ML)从CTA获得冠脉血流值，其准确性类似于ICA中基于腺苷的血流储备。通过将类似的CFD模型应用于ICA的形态信息，可以计算出定量流量比(QFR)，而不需要压力线。然而，使用CFD或ML的CTA和使用QFR的ICA的预后价值尚未在随机试验中确定；然而，这种随机比较对临床翻译和实施至关重要。我们建议利用从随机试验中获得的预期数据，使用先进的图像处理技术来分析CTA。在这个项目中，我们将探索CFD和ML在改善可疑冠状动脉狭窄患者的冠状动脉CTA诊断和预后方面的能力。方法和工作计划：我们在疑似冠状动脉狭窄的患者中进行了两项CTA和ICA的随机试验：340名患者的单中心CAD-Man研究和3546名患者的多中心出院试验。这两项试验都包括CTA和ICA后的初始诊断管理阶段，以及最长四年后的长期临床随访，这为比较使用CFD和ML的CT和使用QFR的ICA的诊断和预后价值提供了明确的终点。为了实现这一比较，我们将首先准备和预处理现有的影像数据，这些数据来自出院时随机分为CTA和ICA的患者。这确保了CTA和ICA数据的同质化，这些数据来自26个不同的欧洲站点，以获得关于狭窄和血流储备量化的可靠和可推广的结果。其次，我们将从狭窄和血流定量的流量试验数据中对CTA和ICA数据进行高级图像处理的特征提取。第三，这些特征将被用于本项目的核心，即实施和探索放射组学分析，比较CTA和ICA的诊断和预后价值。这将使用预期定义的终点来完成，包括用于诊断价值的狭窄和血流结果以及用于预后价值的心肌梗死、中风和心血管死亡。图像分析的定量结果将作为最不发达国家方案内外的数据库提供。预期获得的知识：我们期待对冠状动脉血流和形态的CTA衍生特征与患者的诊断和预后结果之间的关系有新的见解。与ICA的随机比较确保了结果可以直接在临床上转换和实施冠状动脉CTA在可疑冠状动脉狭窄患者的工作中。