Abstract
Medical imaging modalities, such as four-dimensional arterial spin label magnetic resonance angiography (4D ASL MRA), can acquire blood flow data of the cerebrovascular system. These datasets are useful to determine criteria of normality and diagnose, study, and follow-up on the treatment progress of cerebrovascular diseases. In particular, variations in the arterial transit time (ATT) are related to hemodynamic impairment as a consequence of vascular diseases. In order to obtain accurate ATT estimations, the acquisition parameters of the applied image modality need to be properly tuned. In case of 4D ASL MRA, two important acquisition parameters are the blood labeling duration and the temporal resolution. This paper evaluates the effect of different settings for the two mentioned parameters on the accuracy of the ATT estimation in 4D ASL MRA datasets. Six 4D ASL MRA datasets of a pipe containing a mixture of glycerine and water, circulated with constant flow rate using a pump, are acquired with different labeling duration and temporal resolution. A mathematical model is then fitted to the observed signal in order to estimate the ATT. The results indicate that the lowest average absolute error between the ground-truth and estimated ATT is achieved when the longest labeling duration of 1000 ms and the highest temporal resolution of 60 ms are used. The insight obtained from the experiments using a flow phantom, under controlled conditions, can be extended to tune acquisition parameters of 4D ASL MRA datasets of human subjects.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Phellan, R., Lindner, T., Helle, M., Falcão, A.X., Forkert, N.D.: Automatic temporal segmentation of vessels of the brain using 4D ASL MRA images. IEEE Trans. Biomed. Eng. 65(7), 1486–1494 (2018)
Wang, J., et al.: Arterial transit time imaging with flow encoding arterial spin tagging (FEAST). Magn. Reson. Med. 50(3), 599–607 (2003)
Ducos de Lahitte, M., Marc-Vergnes, J., Rascol, A., Guiraud, B., Manelfe, C.: Intravenous angiography of the extracranial cerebral arteries. Radiology 137(3), 705–711 (1980)
Heinz, E., et al.: Examination of the extracranial carotid bifurcation by thin-section dynamicCT: direct visualization of intimal atheroma in man (Part 1). Am. J. Neuroradiol. 5(4), 355–359 (1984)
Bi, X., Weale, P., Schmitt, P., Zuehlsdorff, S., Jerecic, R.: Non-contrast-enhanced four-dimensional (4D) intracranial MR angiography: a feasibility study. Magn. Reson. Med. 63(3), 835–841 (2010)
Forkert, N.D., Fiehler, J., Illies, T., Möller, D.P., Handels, H., Säring, D.: 4D blood flow visualization fusing 3D and 4D MRA image sequences. J. Magn. Reson. Imaging 36(2), 443–453 (2012)
Okell, T.W., Chappell, M.A., Schulz, U.G., Jezzard, P.: A kinetic model for vessel-encoded dynamic angiography with arterial spin labeling. Magn. Reson. Med. 68(3), 969–979 (2012)
Hua, J., Qin, Q., Pekar, J.J., van Zijl, P.C.: Measurement of absolute arterial cerebral blood volume in human brain without using a contrast agent. Nucl. Magn. Reson. Biomed. 24(10), 1313–1325 (2011)
Ruppert, G.C., et al.: Medical image registration based on watershed transform from greyscale marker and multi-scale parameter search. Comput. Methods Biomech. Biomed. Eng. Imaging Vis., 1–19 (2015)
Nguyen, T., Biadillah, Y., Mongrain, R., Brunette, J., Tardif, J.C., Bertrand, O.: A method for matching the refractive index and kinematic viscosity of a blood analog for flow visualization in hydraulic cardiovascular models. J. Biomech. Eng. 126(4), 529–535 (2004)
Kim, S.J., et al.: Effects of MR parameter changes on the quantification of diffusion anisotropy and apparent diffusion coefficient in diffusion tensor imaging: evaluation using a diffusional anisotropic phantom. Korean J. Radiol. 16(2), 297–303 (2015)
Yoo, T.S., et al.: Engineering and algorithm design for an image processing API: a technical report on ITK-the insight toolkit. Studies in Health Technology and Informatics, 586–592 (2002)
Saver, J.L.: Time is brain-quantified. Stroke 37(1), 263–266 (2006)
Acknowledgements
This work was supported by Natural Sciences and Engineering Research Council of Canada (NSERC), Hotchkiss Brain Institute (HBI), and Alberta Innovates. Dr. Nils D. Forkert is funded by Canada Research Chairs. Dr. Alexandre X. Falcão thanks CNPq 303808/2018-7 and FAPESP 2014/12236-1.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2019 Springer Nature Switzerland AG
About this paper
Cite this paper
Phellan, R., Lindner, T., Helle, M., Falcão, A.X., Forkert, N.D. (2019). The Effect of Labeling Duration and Temporal Resolution on Arterial Transit Time Estimation Accuracy in 4D ASL MRA Datasets - A Flow Phantom Study. In: Liao, H., et al. Machine Learning and Medical Engineering for Cardiovascular Health and Intravascular Imaging and Computer Assisted Stenting. MLMECH CVII-STENT 2019 2019. Lecture Notes in Computer Science(), vol 11794. Springer, Cham. https://doi.org/10.1007/978-3-030-33327-0_17
Download citation
DOI: https://doi.org/10.1007/978-3-030-33327-0_17
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-030-33326-3
Online ISBN: 978-3-030-33327-0
eBook Packages: Computer ScienceComputer Science (R0)