Clinically viable myocardial CCTA segmentation for measuring vessel-specific myocardial blood flow from dynamic PET/CCTA hybrid fusion

• Type of Material: Article
• Authors: Marina Piccinelli, Emory University; Navdeep Dahiya, School of Electrical and Computer Engineering; Jonathon Nye, Emory University; Russell Folks, Emory University School of Medicine; Charles Cooke, Emory University; Daya Manatunga, Emory University School of Medicine; Doyeon Hwang, Seoul National University Hospital; Jin Chul Paeng, Seoul National University Hospital; Sang-Geon Cho, Samsung Medical Center, Sungkyunkwan University; Joo Myung Lee, Chonnam National University; Hee-Seung Bom, Samsung Medical Center, Sungkyunkwan University; Bon-Kwon Koo, Seoul National University Hospital; Anthony Yezzi, School of Electrical and Computer Engineering; Ernesto Garcia, Emory University
• Language: English
• Date: 2022-12-01
• Publisher: Springer Nature
• Publication Version: Final Published Version
• Copyright Statement: © The Author(s) 2022
• License: Creative Commons Attribution 4.0 International
• Final Published Version (URL): http://dx.doi.org/10.1186/s41824-021-00122-1
• Title of Journal or Parent Work: European Journal of Hybrid Imaging
• Volume: 6
• Issue: 1
• Start Page: 4
• End Page: 4
• Grant/Funding Information: Research reported in this publication was supported in part by NIH Grant R01 HL143350-03 from the National Heart, Lung and Blood Institute (PI EV Garcia). The content is the solely responsibility of the authors and does not necessarily represent the official views of NIH.
• Keywords: Absolute myocardial blood flow; Multimodality image fusion; Cardiac PET; Vessel-specific quantification; Coronary CTA
• Research Categories: Engineering, Electronics and Electrical; Health Sciences, Radiology

Abstract

Background: Positron emission tomography (PET)-derived LV MBF quantification is usually measured in standard anatomical vascular territories potentially averaging flow from normally perfused tissue with those from areas with abnormal flow supply. Previously we reported on an image-based tool to noninvasively measure absolute myocardial blood flow at locations just below individual epicardial vessel to help guide revascularization. The aim of this work is to determine the robustness of vessel-specific flow measurements (MBFvs) extracted from the fusion of dynamic PET (dPET) with coronary computed tomography angiography (CCTA) myocardial segmentations, using flow measured from the fusion with CCTA manual segmentation as the reference standard. Methods: Forty-three patients’ 13NH3 dPET, CCTA image datasets were used to measure the agreement of the MBFvs profiles after the fusion of dPET data with three CCTA anatomical models: (1) a manual model, (2) a fully automated segmented model and (3) a corrected model, where major inaccuracies in the automated segmentation were briefly edited. Pairwise accuracy of the normality/abnormality agreement of flow values along differently extracted vessels was determined by comparing, on a point-by-point basis, each vessel’s flow to corresponding vessels’ normal limits using Dice coefficients (DC) as the metric. Results: Of the 43 patients CCTA fully automated mask models, 27 patients’ borders required manual correction before dPET/CCTA image fusion, but this editing process was brief (2–3 min) allowing a 100% success rate of extracting MBFvs in clinically acceptable times. In total, 124 vessels were analyzed after dPET fusion with the manual and corrected CCTA mask models yielding 2225 stress and 2122 rest flow values. Forty-seven vessels were analyzed after fusion with the fully automatic masks producing 840 stress and 825 rest flow samples. All DC coefficients computed globally or by territory were ≥ 0.93. No statistical differences were found in the normal/abnormal flow classifications between manual and corrected or manual and fully automated CCTA masks. Conclusion: Fully automated and manually corrected myocardial CCTA segmentation provides anatomical masks in clinically acceptable times for vessel-specific myocardial blood flow measurements using dynamic PET/CCTA image fusion which are not significantly different in flow accuracy and within clinically acceptable processing times compared to fully manually segmented CCTA myocardial masks.