Xiaojun Cheng1,2, Avery J L Berman2, Jonathan R Polimeni2,3, Richard B Buxton4, Louis Gagnon2,5, Anna Devor2,4,6, Sava Sakadžić2, David A Boas1,2. 1. Neurophotonics Center, Department of Biomedical Engineering, Boston University, Massachusetts. 2. Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Charlestown, Massachusetts. 3. Division of Health Sciences and Technology, Massachusetts Institute of Technology, Cambridge, Massachusetts. 4. Department of Radiology, University of California, San Diego, La Jolla, California. 5. Department of Radiology and Nuclear Medicine, Faculty of Medicine, Laval University, Quebec, Canada. 6. Department of Neurosciences, University of California, San Diego, La Jolla, California.
Abstract
PURPOSE: The primary goal of this study was to estimate the value of β , the exponent in the power law relating changes of the transverse relaxation rate and intra-extravascular local magnetic susceptibility differences as Δ R 2 ∗ ∝ ( Δ χ ) β . The secondary objective was to evaluate any differences that might exist in the value of β obtained using a deoxyhemoglobin-weighted Δ χ distribution versus a constant Δ χ distribution assumed in earlier computations. The third objective was to estimate the value of β that is relevant for methods based on susceptibility contrast agents with a concentration of Δ χ higher than that used for BOLD fMRI calculations. METHODS: Our recently developed model of real microvascular anatomical networks is used to extend the original simplified Monte-Carlo simulations to compute β from the first principles. RESULTS: Our results show that β = 1 for most BOLD fMRI measurements of real vascular networks, as opposed to earlier predictions of β = 1 .5 using uniform Δ χ distributions. For perfusion or fMRI methods based on contrast agents, which generate larger values for Δ χ , β = 1 for B 0 ≤ 9.4 T, whereas at 14 T β can drop below 1 and the variation across subjects is large, indicating that a lower concentration of contrast agent with a lower value of Δ χ is desired for experiments at high B0 . CONCLUSION: These results improve our understanding of the relationship between R2 * and the underlying microvascular properties. The findings will help to infer the cerebral metabolic rate of oxygen and cerebral blood volume from BOLD and perfusion MRI, respectively.
PURPOSE: The primary goal of this study was to estimate the value of β , the exponent in the power law relating changes of the transverse relaxation rate and intra-extravascular local magnetic susceptibility differences as Δ R 2 ∗ ∝ ( Δ χ ) β . The secondary objective was to evaluate any differences that might exist in the value of β obtained using a deoxyhemoglobin-weighted Δ χ distribution versus a constant Δ χ distribution assumed in earlier computations. The third objective was to estimate the value of β that is relevant for methods based on susceptibility contrast agents with a concentration of Δ χ higher than that used for BOLD fMRI calculations. METHODS: Our recently developed model of real microvascular anatomical networks is used to extend the original simplified Monte-Carlo simulations to compute β from the first principles. RESULTS: Our results show that β = 1 for most BOLD fMRI measurements of real vascular networks, as opposed to earlier predictions of β = 1 .5 using uniform Δ χ distributions. For perfusion or fMRI methods based on contrast agents, which generate larger values for Δ χ , β = 1 for B 0 ≤ 9.4 T, whereas at 14 T β can drop below 1 and the variation across subjects is large, indicating that a lower concentration of contrast agent with a lower value of Δ χ is desired for experiments at high B0 . CONCLUSION: These results improve our understanding of the relationship between R2 * and the underlying microvascular properties. The findings will help to infer the cerebral metabolic rate of oxygen and cerebral blood volume from BOLD and perfusion MRI, respectively.
Authors: K K Kwong; J W Belliveau; D A Chesler; I E Goldberg; R M Weisskoff; B P Poncelet; D N Kennedy; B E Hoppel; M S Cohen; R Turner Journal: Proc Natl Acad Sci U S A Date: 1992-06-15 Impact factor: 11.205
Authors: Louis Gagnon; Sava Sakadžić; Frédéric Lesage; Joseph J Musacchia; Joël Lefebvre; Qianqian Fang; Meryem A Yücel; Karleyton C Evans; Emiri T Mandeville; Jülien Cohen-Adad; Jonathan R Polimeni; Mohammad A Yaseen; Eng H Lo; Douglas N Greve; Richard B Buxton; Anders M Dale; Anna Devor; David A Boas Journal: J Neurosci Date: 2015-02-25 Impact factor: 6.167
Authors: Louis Gagnon; Sava Sakadžić; Frédéric Lesage; Philippe Pouliot; Anders M Dale; Anna Devor; Richard B Buxton; David A Boas Journal: Philos Trans R Soc Lond B Biol Sci Date: 2016-10-05 Impact factor: 6.237
Authors: Mario Gilberto Báez-Yánez; Philipp Ehses; Christian Mirkes; Philbert S Tsai; David Kleinfeld; Klaus Scheffler Journal: Neuroimage Date: 2017-09-08 Impact factor: 6.556
Authors: Sreenath P Kyathanahally; Michela Azzarito; Jan Rosner; Vince D Calhoun; Claudia Blaiotta; John Ashburner; Nikolaus Weiskopf; Katja Wiech; Karl Friston; Gabriel Ziegler; Patrick Freund Journal: J Neurol Neurosurg Psychiatry Date: 2021-05-26 Impact factor: 10.154