Xinpei Gao1, Sara Boccalini2, Pieter H Kitslaar3, Ricardo P J Budde4, Mohamed Attrach5, Shengxian Tu6, Michiel A de Graaf7, Tomas Ondrus8, Martin Penicka9, Arthur J H A Scholte10, Boudewijn P F Lelieveldt11, Jouke Dijkstra12, Johan H C Reiber13. 1. Division of Image Processing, Dept. of Radiology, Leiden University Medical Center, Leiden, The Netherlands. Electronic address: X.Gao@lumc.nl. 2. Dept. of Radiology, University Medical Center Rotterdam, Rotterdam, The Netherlands. Electronic address: s.boccalini@erasmusmc.nl. 3. Division of Image Processing, Dept. of Radiology, Leiden University Medical Center, Leiden, The Netherlands; Medis Medical Imaging System, b.v., Leiden, The Netherlands. Electronic address: P.H.Kitslaar@lumc.nl. 4. Dept. of Radiology, University Medical Center Rotterdam, Rotterdam, The Netherlands. Electronic address: r.budde@erasmusmc.nl. 5. Dept. of Radiology, University Medical Center Rotterdam, Rotterdam, The Netherlands. Electronic address: m.attrach@erasmusmc.nl. 6. Biomedical Instrument Institute, School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai, China. Electronic address: sxtu@sjtu.edu.cn. 7. Dept. of Cardiology, Leiden University Medical Center, Leiden, The Netherlands. Electronic address: M.A.de_Graaf@lumc.nl. 8. Cardiovascular Center, OLV Clinic, Aalst, Belgium. Electronic address: tomas.ondrus@gmail.com. 9. Cardiovascular Center, OLV Clinic, Aalst, Belgium. Electronic address: Martin.Penicka@olvz-aalst.be. 10. Dept. of Cardiology, Leiden University Medical Center, Leiden, The Netherlands. Electronic address: A.J.H.A.Scholte@lumc.nl. 11. Division of Image Processing, Dept. of Radiology, Leiden University Medical Center, Leiden, The Netherlands. Electronic address: B.P.F.Lelieveldt@lumc.nl. 12. Division of Image Processing, Dept. of Radiology, Leiden University Medical Center, Leiden, The Netherlands. Electronic address: J.Dijkstra@lumc.nl. 13. Division of Image Processing, Dept. of Radiology, Leiden University Medical Center, Leiden, The Netherlands; Medis Medical Imaging System, b.v., Leiden, The Netherlands. Electronic address: J.H.C.Reiber@lumc.nl.
Abstract
BACKGROUND: Automatic accurate measuring of the aortic annulus and determination of the optimal angulation of X-ray projection are important for the trans-catheter aortic valve replacement (TAVR) procedure. The objective of this study was to present a novel fully automatic methodology for the quantification of the aortic annulus in computed tomography angiography (CTA) images. METHODS: CTA datasets of 26 patients were analyzed retrospectively with the proposed methodology, which consists of a knowledge-based segmentation of the aortic root and detection of the orientation and size of the aortic annulus. The accuracy of the methodology was determined by comparing the automatically derived results with the reference standard obtained by semi-automatic delineation of the aortic root and manual definition of the annulus plane. RESULTS: The difference between the automatic annulus diameter and the reference standard by observer 1 was 0.2±1.0mm, with an inter-observer variability of 1.2±0.6mm. The Pearson correlation coefficient for the diameter was good (0.92 for observer 1). For the first time, a fully automatic tool to assess the optimal projection curves was presented and validated. The mean difference between the optimal projection curves calculated based on the automatically defined annulus plane and the reference standard was 6.4° in the cranial/caudal (CRA/CAU) direction. The mean computation time was short with around 60s per dataset. CONCLUSION: The new fully automatic and fast methodology described in this manuscript not only provided precise measurements about the aortic annulus size with results comparable to experienced observers, but also predicted optimal X-ray projection curves from CTA images.
BACKGROUND: Automatic accurate measuring of the aortic annulus and determination of the optimal angulation of X-ray projection are important for the trans-catheter aortic valve replacement (TAVR) procedure. The objective of this study was to present a novel fully automatic methodology for the quantification of the aortic annulus in computed tomography angiography (CTA) images. METHODS: CTA datasets of 26 patients were analyzed retrospectively with the proposed methodology, which consists of a knowledge-based segmentation of the aortic root and detection of the orientation and size of the aortic annulus. The accuracy of the methodology was determined by comparing the automatically derived results with the reference standard obtained by semi-automatic delineation of the aortic root and manual definition of the annulus plane. RESULTS: The difference between the automatic annulus diameter and the reference standard by observer 1 was 0.2±1.0mm, with an inter-observer variability of 1.2±0.6mm. The Pearson correlation coefficient for the diameter was good (0.92 for observer 1). For the first time, a fully automatic tool to assess the optimal projection curves was presented and validated. The mean difference between the optimal projection curves calculated based on the automatically defined annulus plane and the reference standard was 6.4° in the cranial/caudal (CRA/CAU) direction. The mean computation time was short with around 60s per dataset. CONCLUSION: The new fully automatic and fast methodology described in this manuscript not only provided precise measurements about the aortic annulus size with results comparable to experienced observers, but also predicted optimal X-ray projection curves from CTA images.
Authors: Leon Lenchik; Laura Heacock; Ashley A Weaver; Robert D Boutin; Tessa S Cook; Jason Itri; Christopher G Filippi; Rao P Gullapalli; James Lee; Marianna Zagurovskaya; Tara Retson; Kendra Godwin; Joey Nicholson; Ponnada A Narayana Journal: Acad Radiol Date: 2019-08-10 Impact factor: 3.173
Authors: Fabiola Bezerra de Carvalho Macruz; Charles Lu; Julia Strout; Angelo Takigami; Rupert Brooks; Sean Doyle; Min Yun; Varun Buch; Sandeep Hedgire; Brian Ghoshhajra Journal: Radiol Artif Intell Date: 2022-02-23
Authors: Zahra Sedghi Gamechi; Lidia R Bons; Marco Giordano; Daniel Bos; Ricardo P J Budde; Klaus F Kofoed; Jesper Holst Pedersen; Jolien W Roos-Hesselink; Marleen de Bruijne Journal: Eur Radiol Date: 2019-01-23 Impact factor: 5.315
Authors: Christoph Artzner; Malte N Bongers; Rainer Kärgel; Sebastian Faby; Gerald Hefferman; Judith Herrmann; Svenja L Nopper; Regine M Perl; Sven S Walter Journal: Diagnostics (Basel) Date: 2022-07-23