Quantification of the focal progression of coronary atherosclerosis through automated co-registration of virtual histology-intravascular ultrasound imaging data

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• 作者：Lucas H. Timmins ; David S. Molony…
• 关键词：Coronary artery disease ; Intravascular imaging ; Radiofrequency intravascular ultrasound ; Serial imaging ; Image processing
• 刊名：The International Journal of Cardiovascular Imaging
• 出版年：2017
• 出版时间：January 2017
• 年：2017
• 卷：33
• 期：1
• 页码：13-24
• 全文大小：
• 刊物类别：Medicine
• 刊物主题：Cardiology; Imaging / Radiology; Cardiac Imaging;
• 出版者：Springer Netherlands
• ISSN：1573-0743
• 卷排序：33

文摘

The goal of this study was to evaluate the accuracy of a novel algorithm that circumferentially co-registers serial virtual histology-intravascular ultrasound (VH-IVUS) data for the focal assessment of coronary atherosclerosis progression. Thirty-three patients with an abnormal non-invasive cardiac stress test or stable angina underwent baseline and follow-up (6 or 12 months) invasive evaluation that included acquisition of VH-IVUS image data. Baseline and follow-up image pairs (n = 4194) were automatically co-registered in the circumferential direction via a multi-variate cross-correlation algorithm. Algorithm stability and accuracy were assessed by comparing results from multiple iterations of the algorithm (iteration 1 vs. iteration 2) and against values determined manually by two expert VH-IVUS readers (algorithm vs. two expert readers). Furthermore, focal plaque progression values were compared between the algorithm and expert readers following co-registration by the independently determined angles. Strong agreement in circumferential co-registration angles were observed across multiple iterations of the algorithm (stability) and between the algorithm and expert readers (accuracy; all concordance correlation coefficients >0.98). Furthermore, circumferential co-registration angles determined by the algorithm were not statistically when compared to values determined by two expert readers (p = 0. 99). Bland–Altman analysis indicated minimal bias when comparing focal VH-IVUS defined plaque progression in corresponding sectors following circumferential co-registration between the algorithm and expert readers. Finally, average differences in changes in total plaque and constituent areas between the algorithm and readers were within the average range of difference between readers (interobserver variability). We present a stable and validated algorithm to automatically circumferentially co-register serial VH-IVUS imaging data for the focal quantification of coronary atherosclerosis progression.