Fine tuning breath-hold-based cerebrovascular reactivity analysis models.

Abstract

IntroductionWe elaborate on existing analysis methods for breath‐hold (BH)‐derived cerebrovascular reactivity (CVR) measurements and describe novel insights and models toward more exact CVR interpretation.MethodsFive blood‐oxygen‐level‐dependent (BOLD) fMRI datasets of neurovascular patients with unilateral hemispheric hemodynamic impairment were used to test various BH CVR analysis methods. Temporal lag (phase), percent BOLD signal change (CVR), and explained variance (coherence) maps were calculated using three different sine models and two novel “Optimal Signal” model‐free methods based on the unaffected hemisphere and the sagittal sinus fMRI signal time series, respectively.ResultsAll models showed significant differences in CVR and coherence between the affected—hemodynamic impaired—and unaffected hemisphere. Voxel‐wise phase determination significantly increases CVR (0.60 ± 0.18 vs. 0.82 ± 0.27; P < 0.05). Incorporating different durations of breath hold and resting period in one sine model (two‐task) did increase coherence in the unaffected hemisphere, as well as eliminating negative phase commonly obtained by one‐task frequency models. The novel model‐free “optimal signal” methods both explained the BOLD MR data similar to the two task sine model.ConclusionsOur CVR analysis demonstrates an improved CVR and coherence after implementation of voxel‐wise phase and frequency adjustment. The novel “optimal signal” methods provide a robust and feasible alternative to the sine models, as both are model‐free and independent of compliance. Here, the sagittal sinus model may be advantageous, as it is independent of hemispheric CVR impairment.