Agreement of wall shear stress distribution between two core laboratories using three-dimensional quantitative coronary angiography — Shigetaka Kageyama (2023) | RDL Network
Agreement of wall shear stress distribution between two core laboratories using three-dimensional quantitative coronary angiography
The International Journal of Cardiovascular Imaging 39(8): 1581-1592
Article 2023 English
Authors
SK
Shigetaka Kageyama
VT
Vincenzo Tufaro
RT
Ryo Torii
Abstract
1 min read
Wall shear stress (WSS) estimated in models reconstructed from intravascular imaging and 3-dimensional-quantitative coronary angiography (3D-QCA) data provides important prognostic information and enables identification of high-risk lesions. However, these analyses are time-consuming and require expertise, limiting WSS adoption in clinical practice. Recently, a novel software has been developed for real-time computation of time-averaged WSS (TAWSS) and multidirectional WSS distribution. This study aims to examine its inter-corelab reproducibility. Sixty lesions (20 coronary bifurcations) with a borderline negative fractional flow reserve were processed using the CAAS Workstation WSS prototype to estimate WSS and multi-directional WSS values. Analysis was performed by two corelabs and their estimations for the WSS in 3 mm segments across each reconstructed vessel was extracted and compared. In total 700 segments (256 located in bifurcated vessels) were included in the analysis. A high intra-class correlation was noted for all the 3D-QCA and TAWSS metrics between the estimations of the two corelabs irrespective of the presence (range: 0.90-0.92) or absence (range: 0.89-0.90) of a coronary bifurcation, while the ICC was good-moderate for the multidirectional WSS (range: 0.72-0.86). Lesion level analysis demonstrated a high agreement of the two corelabls for detecting lesions exposed to an unfavourable haemodynamic environment (WSS > 8.24 Pa, κ = 0.77) that had a high-risk morphology (area stenosis > 61.3%, κ = 0.71) and were prone to progress and cause events. The CAAS Workstation WSS enables reproducible 3D-QCA reconstruction and computation of WSS metrics. Further research is needed to explore its value in detecting high-risk lesions.
Shigetaka Kageyama, Vincenzo Tufaro, Ryo Torii, Grigoris V. Karamasis, Roby Rakhit, Eric Poon, Jean‐Paul Aben, Andreas Baumbach, Patrick W. Serruys, Yoshinobu Onuma, Christos V. Bourantas
Shigetaka Kageyama, Vincenzo Tufaro, Ryo Torii, Grigoris V. Karamasis, Roby Rakhit, Eric Poon, Jean-Paul Aben, Andreas Baumbach, Patrick W. Serruys, Yoshinobu Onuma, Christos V. Bourantas
Vincenzo Tufaro, Ryo Torii, Emrah Erdoğan, Pieter Kitslaar, Bon‐Kwon Koo, Roby Rakhit, Grigoris V. Karamasis, Christos Costa, Patrick W. Serruys, Daniel A. Jones, Anthony Mathur, Andreas Baumbach, Jean‐Paul Aben, Christos V. Bourantas
Vincenzo Tufaro, Ryo Torii, Jean‐Paul Aben, Ramya Parasa, Bon‐Kwon Koo, Roby Rakhit, Grigoris V. Karamasis, İbrahım Halıl Tanboğa, Ameer Khan, Michael McKenna, Murat Çap, Mazen Abou Gamrah, Patrick W. Serruys, Yoshinobu Onuma, Giulio Stefanini, Daniel A. Jones, Krishnaraj S. Rathod, Anthony Mathur, Andreas Baumbach, Christos V. Bourantas
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