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Automatic evaluation of vessel diameter variation from 2D X-ray angiography.

Authors :
M'hiri F
Duong L
Desrosiers C
Dahdah N
MirĂ³ J
Cheriet M
Source :
International journal of computer assisted radiology and surgery [Int J Comput Assist Radiol Surg] 2017 Nov; Vol. 12 (11), pp. 1867-1876. Date of Electronic Publication: 2017 Jul 13.
Publication Year :
2017

Abstract

Purpose: Early detection of blood vessel pathologies can be made through the evaluation of functional and structural abnormalities in the arteries, including the arterial distensibility measure. We propose a feasibility study on computing arterial distensibility automatically from monoplane 2D X-ray sequences for both small arteries (such as coronary arteries) and larger arteries (such as the aorta).<br />Methods: To compute the distensibility measure, three steps were developed: First, the segment of an artery is extracted using our graph-based segmentation method. Then, the same segment is tracked in the moving sequence using our spatio-temporal segmentation method: the Temporal Vessel Walker. Finally, the diameter of the artery is measured automatically at each frame of the sequence based on the segmentation results.<br />Results: The method was evaluated using one simulated sequence and 4 patients' angiograms depicting the coronary arteries and three depicting the ascending aorta. Results of the simulated sequence achieved a Dice index of 98%, with a mean squared error in diameter measurement of [Formula: see text] mm. Results obtained from patients' X-ray sequences are consistent with manual assessment of the diameter by experts.<br />Conclusions: The proposed method measures changes in diameter of a specific segment of a blood vessel during the cardiac sequence, automatically based on monoplane 2D X-ray sequence. Such information might become a key to help physicians in the detection of variations of arterial stiffness associated with early stages of various vasculopathies.

Details

Language :
English
ISSN :
1861-6429
Volume :
12
Issue :
11
Database :
MEDLINE
Journal :
International journal of computer assisted radiology and surgery
Publication Type :
Academic Journal
Accession number :
28707212
Full Text :
https://doi.org/10.1007/s11548-017-1639-9