Haipeng Tang1, Robert R Bober2, Chen Zhao3, Chaoyang Zhang1, Huiqing Zhu4, Zhuo He3, Zhihui Xu5, Weihua Zhou6,7. 1. School of Computing Sciences and Computer Engineering, University of Southern Mississippi, Hattiesburg, MS, 39406, USA. 2. Department of Cardiology, Ochsner Medical Center, New Orleans, LA, 70121, USA. 3. Department of Applied Computing, Michigan Technological University, 1400 Townsend Dr, Houghton, MI, 49931, USA. 4. School of Mathematics and Natural Sciences, University of Southern Mississippi, Hattiesburg, MS, 39406, USA. 5. Department of Cardiology, The First Affiliated Hospital of Nanjing Medical University, 300 Guangzhou Rd, Nanjing, 210000, China. wx_xzh@njmu.edu.cn. 6. Department of Applied Computing, Michigan Technological University, 1400 Townsend Dr, Houghton, MI, 49931, USA. whzhou@mtu.edu. 7. Center of Biocomputing and Digital Health, Institute of Computing and Cybersystems, and Health Research Institute, Michigan Technological University, Houghton, MI, 49931, USA. whzhou@mtu.edu.
Abstract
BACKGROUND: Percutaneous coronary intervention (PCI) in stable coronary artery disease (CAD) is commonly triggered by abnormal myocardial perfusion imaging (MPI). However, due to the possibilities of multivessel disease, serial stenoses and variability of coronary artery perfusion distribution, an opportunity exists to better align anatomic stenosis with perfusion abnormalities to improve revascularization decisions. This study aims to develop a multi-modality fusion approach to assist decision-making for PCI. METHODS AND RESULTS: Coronary arteries from fluoroscopic angiography (FA) were reconstructed into 3D artery anatomy. Left ventricular (LV) epicardial surface was extracted from SPECT. The artery anatomy and epicardial surface were non-rigidly fused. The accuracy of the 3D fusion was evaluated via both computer simulation and real patient data. Simulated FA and MPI were integrated and then compared with the ground truth from a digital phantom. The distance-based mismatch errors between simulated fluoroscopy and phantom arteries were 1.86 ± 1.43 mm for left coronary arteries (LCA) and 2.21 ± 2.50 mm for right coronary arteries (RCA). FA and SPECT images in 30 patients were integrated and then compared with the ground truth from CT angiograms. The distance-based mismatch errors between the fluoroscopy and CT arteries were 3.84 ± 3.15 mm for LCA and 5.55 ± 3.64 mm for RCA. The presence of the corresponding fluoroscopy and CT arteries in the AHA-17-segment model agreed well with a Kappa value of 0.91 (CI 0.89-0.93) for LCA and a Kappa value of 0.80 (CI 0.67-0.92) for RCA. CONCLUSIONS: Our fusion approach is technically accurate to assist PCI decision-making and is clinically feasible to be used in the catheterization laboratory. Future studies are necessary to determine if fusion improves PCI-related outcomes.
BACKGROUND: Percutaneous coronary intervention (PCI) in stable coronary artery disease (CAD) is commonly triggered by abnormal myocardial perfusion imaging (MPI). However, due to the possibilities of multivessel disease, serial stenoses and variability of coronary artery perfusion distribution, an opportunity exists to better align anatomic stenosis with perfusion abnormalities to improve revascularization decisions. This study aims to develop a multi-modality fusion approach to assist decision-making for PCI. METHODS AND RESULTS: Coronary arteries from fluoroscopic angiography (FA) were reconstructed into 3D artery anatomy. Left ventricular (LV) epicardial surface was extracted from SPECT. The artery anatomy and epicardial surface were non-rigidly fused. The accuracy of the 3D fusion was evaluated via both computer simulation and real patient data. Simulated FA and MPI were integrated and then compared with the ground truth from a digital phantom. The distance-based mismatch errors between simulated fluoroscopy and phantom arteries were 1.86 ± 1.43 mm for left coronary arteries (LCA) and 2.21 ± 2.50 mm for right coronary arteries (RCA). FA and SPECT images in 30 patients were integrated and then compared with the ground truth from CT angiograms. The distance-based mismatch errors between the fluoroscopy and CT arteries were 3.84 ± 3.15 mm for LCA and 5.55 ± 3.64 mm for RCA. The presence of the corresponding fluoroscopy and CT arteries in the AHA-17-segment model agreed well with a Kappa value of 0.91 (CI 0.89-0.93) for LCA and a Kappa value of 0.80 (CI 0.67-0.92) for RCA. CONCLUSIONS: Our fusion approach is technically accurate to assist PCI decision-making and is clinically feasible to be used in the catheterization laboratory. Future studies are necessary to determine if fusion improves PCI-related outcomes.
Authors: He S Yang; Sabrina E Racine-Brzostek; Mohsen Karbaschi; Jim Yee; Alicia Dillard; Peter A D Steel; William S Lee; Kathleen A McDonough; Yuqing Qiu; Thomas J Ketas; Eric Francomano; P J Klasse; Layla Hatem; Lars F Westblade; Heng Wu; Haode Chen; Robert Zuk; Hong Tan; Roxanne Girardin; Alan P Dupuis; Anne F Payne; John P Moore; Melissa M Cushing; Amy Chadburn; Zhen Zhao Journal: medRxiv Date: 2020-11-22
Authors: Tracy L Faber; Cesar A Santana; Ernest V Garcia; Jaume Candell-Riera; Russell D Folks; John W Peifer; Andrew Hopper; Santiago Aguade; Joan Angel; J Larry Klein Journal: J Nucl Med Date: 2004-05 Impact factor: 10.057