Cerebral blood flow estimation in vivo using local tissue reference functions

Abstract

Purpose: To evaluate the use of bolus signals obtained from tissue as reference functions (or local reference functions [LRFs]) rather than arterial input functions (AIFs) when deriving cross-calibrated cerebral blood flow (CBF(CC)) estimates via deconvolution.

Materials and methods: AIF and white matter (WM) LRF CBF(CC) maps (cross-calibrated so that normal WM was 23.7 mL/minute/100 g) derived using singular value decomposition (SVD) were examined in 28 ischemic stroke patients. Median CBF(CC) estimates from normal gray matter (GM) and ischemic tissue were obtained.

Results: AIF and LRF median CBF(CC) estimates resembled one another for all 28 patients (average paired CBF(CC) difference 0.4 +/- 1.7 mL/minute/100 g and -0.4 +/- 1.4 mL/minute/100 g in GM and ischemic tissue, respectively). Wilcoxon signed-rank comparisons of patient median CBF(CC) measurements revealed no statistically significant differences between using AIFs and LRFs (P > 0.05).

Conclusion: If CBF is quantified using a patient-specific cross-calibration factor, then LRF CBF estimates are at least as accurate as those from AIFs. Therefore, until AIF quantification is achievable in vivo, perfusion protocols tailored for LRFs would simplify the methodology and provide more reliable perfusion information.