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A new vessel segmentation algorithm for robust blood flow quantification from two-dimensional phase-contrast magnetic resonance images.
- Source :
-
Clinical physiology and functional imaging [Clin Physiol Funct Imaging] 2019 Sep; Vol. 39 (5), pp. 327-338. Date of Electronic Publication: 2019 Jun 06. - Publication Year :
- 2019
-
Abstract
- Blood flow measurements in the ascending aorta and pulmonary artery from phase-contrast magnetic resonance images require accurate time-resolved vessel segmentation over the cardiac cycle. Current semi-automatic segmentation methods often involve time-consuming manual correction, relying on user experience for accurate results. The purpose of this study was to develop a semi-automatic vessel segmentation algorithm with shape constraints based on manual vessel delineations for robust segmentation of the ascending aorta and pulmonary artery, to evaluate the proposed method in healthy volunteers and patients with heart failure and congenital heart disease, to validate the method in a pulsatile flow phantom experiment, and to make the method freely available for research purposes. Algorithm shape constraints were extracted from manual reference delineations of the ascending aorta (n = 20) and pulmonary artery (n = 20) and were included in a semi-automatic segmentation method only requiring manual delineation in one image. Bias and variability (bias ± SD) for flow volume of the proposed algorithm versus manual reference delineations were 0·0 ± 1·9 ml in the ascending aorta (n = 151; seven healthy volunteers; 144 heart failure patients) and -1·7 ± 2·9 ml in the pulmonary artery (n = 40; 25 healthy volunteers; 15 patients with atrial septal defect). Interobserver bias and variability were lower (P = 0·008) for the proposed semi-automatic method (-0·1 ± 0·9 ml) compared to manual reference delineations (1·5 ± 5·1 ml). Phantom validation showed good agreement between the proposed method and timer-and-beaker flow volumes (0·4 ± 2·7 ml). In conclusion, the proposed semi-automatic vessel segmentation algorithm can be used for efficient analysis of flow and shunt volumes in the aorta and pulmonary artery.<br /> (© 2019 The Authors. Clinical Physiology and Functional Imaging published by John Wiley & Sons Ltd on behalf of Scandinavian Society of Clinical Physiology and Nuclear Medicine.)
- Subjects :
- Adult
Aged
Aged, 80 and over
Aorta physiopathology
Blood Flow Velocity
Female
Heart Failure physiopathology
Heart Septal Defects, Atrial physiopathology
Humans
Image Interpretation, Computer-Assisted
Male
Middle Aged
Observer Variation
Perfusion Imaging instrumentation
Phantoms, Imaging
Predictive Value of Tests
Pulmonary Artery physiopathology
Reproducibility of Results
Retrospective Studies
Young Adult
Algorithms
Aorta diagnostic imaging
Heart Failure diagnostic imaging
Heart Septal Defects, Atrial diagnostic imaging
Magnetic Resonance Imaging instrumentation
Perfusion Imaging methods
Pulmonary Artery diagnostic imaging
Subjects
Details
- Language :
- English
- ISSN :
- 1475-097X
- Volume :
- 39
- Issue :
- 5
- Database :
- MEDLINE
- Journal :
- Clinical physiology and functional imaging
- Publication Type :
- Academic Journal
- Accession number :
- 31102479
- Full Text :
- https://doi.org/10.1111/cpf.12582