Iterative delay correction improves breath-hold cerebrovascular reactivity mapping in clinical populations

Abstract Cerebrovascular reactivity (CVR), the ability of cerebral blood vessels to dilate or constrict in response to a vasoactive stimulus, is an important measure of cerebrovascular health. Accurate CVR estimation requires accounting for the time required for the vasoactive stimulus to reach each brain region and the time it takes for local arterioles to modulate cerebral blood flow. The temporal search range used to calculate this spatially varying offset can substantially impact CVR estimates, and the appropriate search range may vary across populations, acquisition protocols, and even brain regions. Here, we present an iterative approach for automatically determining the appropriate maximum shift, using breath-hold fMRI data acquired in a cohort of stroke survivors. This approach selectively expands the delay search range only for voxels with estimated delays at the boundary (i.e., near the minimum or maximum shift) until the estimated delay is no longer constrained or a predefined value is reached. In the context of stroke, this approach significantly increased the number of voxels with statistically significant CVR among those initially at the boundary. It also resulted in CVR polarity reversals in voxels originally at the early-response boundary and amplified negative CVR values in voxels originally at the late-response boundary, suggesting that using an iterative maximum shift can critically impact CVR interpretation. This approach is broadly applicable beyond stroke, but careful parameter tuning is required, as illustrated by our demonstration of the parameter tuning process for a participant with Moyamoya disease. Together, these findings suggest that iterative delay correction allows for improved CVR assessments in clinical populations. Competing Interest Statement The authors have declared no competing interest. Footnotes Fixed a typo on the cover page Data & Code Availability Code for calculating CVR using the iterative delay correction approach is available at https://github.com/BrightLab-ANVIL/phys2cvr_Iterative and is being submitted as a pull request on GitHub to be incorporated into the main phys2cvr code (https://github.com/smoia/phys2cvr). Imaging data are not publicly available as they are part of a study that is still ongoing. Access may be considered subject to inter-institutional agreements once the study objectives have been achieved.