Dependence of vessel area accuracy and precision as a function of MR imaging parameters and boundary detection algorithm
- 22 May 2007
- journal article
- Published by Wiley in Journal of Magnetic Resonance Imaging
- Vol. 25 (6) , 1226-1234
- https://doi.org/10.1002/jmri.20918
Abstract
To determine the appropriate image acquisition parameters for an accurate measurement of vessel cross-sectional area from MR angiography (MRA) images. A series of images with different vessel cross-sectional areas, resolutions, and signal-to-noise ratios (SNRs) were simulated and validated experimentally. Dynamic programming (DP) was employed to determine the accuracy and precision of the vessel cross-sectional area as a function of vessel size, sampling matrix, acquisition time, and postprocessing parameters such as zooming and bias correction. We show that there is an optimal value of lambda (the ratio of vessel diameter to resolution) for a given intrinsic SNR that yields the most accurate and precise area measurement. Specifically, when the SNR is > or =10:1, this value of lambda is 8 and yields a cross-sectional area error of or =2. The predicted ideal result of lambda = 8 is within reach with current technology to image vessels such as the carotid artery or aorta. It is possible to determine the ideal resolution that minimizes errors in the measurement of the vessel cross-sectional area for a given SNR, processing algorithm, and vessel of interest.Keywords
This publication has 20 references indexed in Scilit:
- Quantification of Atherosclerosis with MRI and Image Processing in Spontaneously Hyperlipidemic RabbitsJournal of Cardiovascular Magnetic Resonance, 2004
- Computerized quantification of carotid artery stenosis using MRA axial imagesMagnetic Resonance Imaging, 2004
- Automated segmentation and analysis of vascular structures in magnetic resonance angiographic imagesMagnetic Resonance in Medicine, 2003
- Measurement of Carotid Wall Volume and Maximum Area with Contrast-enhanced 3D MR Imaging: Initial ObservationsRadiology, 2003
- Enhanced image detail using continuity in the MIP Z‐buffer: Applications to magnetic resonance angiographyJournal of Magnetic Resonance Imaging, 2000
- Automatic vessel segmentation using active contours in cine phase contrast flow measurementsJournal of Magnetic Resonance Imaging, 1999
- Detection of Carotid StenosisStroke, 1995
- Automated local maximum‐intensity projection with three‐dimensional vessel trackingJournal of Magnetic Resonance Imaging, 1992
- Gadolinium‐enhanced high‐resolution MR angiography with adaptive vessel tracking: Preliminary results in the intracranial circulationJournal of Magnetic Resonance Imaging, 1992
- Lumen definition in MR angiographyJournal of Magnetic Resonance Imaging, 1991