Quantitative perfusion mapping with induced transient hypoxia using BOLD MRI

Abstract

Purpose: Gadolinium-based dynamic susceptibility contrast (DSC) is commonly used to characterize blood flow in patients with stroke and brain tumors. Unfortunately, gadolinium contrast administration has been associated with adverse reactions and long-term accumulation in tissues. In this work, we propose an alternative deoxygenation-based DSC (dDSC) method that uses a transient hypoxia gas paradigm to deliver a bolus of paramagnetic deoxygenated hemoglobin to the cerebral vasculature for perfusion imaging.

Methods: Through traditional DSC tracer kinetic modeling, the MR signal change induced by this hypoxic bolus can be used to generate regional perfusion maps of cerebral blood flow, cerebral blood volume, and mean transit time. This gas paradigm and blood-oxygen-level-dependent (BOLD)-MRI were performed concurrently on a cohort of 66 healthy and chronically anemic subjects (age 23.5 ± 9.7, female 64%).

Results: Our results showed reasonable global and regional agreement between dDSC and other flow techniques, such as phase contrast and arterial spin labeling.

Conclusion: In this proof-of-concept study, we demonstrated the feasibility of using transient hypoxia to generate a contrast bolus that mimics the effect of gadolinium and yields reasonable perfusion estimates. Looking forward, optimization of the hypoxia boluses and measurement of the arterial-input function is necessary to improve the accuracy of dDSC. Additionally, a cross-validation study of dDSC and DSC in brain tumor and ischemic stroke subjects is warranted to evaluate the clinical diagnostic utility of this approach.

Keywords: arterial spin labeling; deoxyhemoglobin contrast; dynamic susceptibility contrast; phase contrast; transient hypoxia.

FIGURE 1

Experimental setup for transient hypoxia gas paradigm and concurrent peripheral saturation S_pO₂ and MRI BOLD acquisitions. During the experiment, the subjects breathed through the mouthpiece through a 2-L reservoir rebreathing circuit that included one-way valves to prevent partial gas mixtures. The subject also wore a respiratory bellows to display the breathing pattern and frequency

FIGURE 2

Transient hypoxia model. A, Representative recording of S_pO₂ signal during 100% nitrogen paradigm. B, S_pO₂ signal from the same patient prior to gas paradigm while patient was sleeping during anatomic scanning. C, Representative time series of global BOLD-MR signal and S_pO₂ signals during hypoxia paradigm. D, Representative $\mathrm{\Delta }{R}_2^{*}$ time curve and its time integral (area under curve)

FIGURE 3

Localization of input functions from the difference image created by subtraction of baseline and hypoxic gradient-echo images. A, Representative individual AIF extracted from MCA. B, Representative individual VOF extracted from superior sagittal sinus. C, Representative AIF and VOF during hypoxia demonstrated the process of rescaling the AIF by the time integral of the VOF to minimize partial volume effects

FIGURE 4

Agreement between CBF_dDSC and alternative flow methods. Correlation (A) and Bland-Altman (B) analyses between CBF_dDSC and PC flow. Correlation (C) and Bland-Altman (D) analyses between CBF_dDSC and ASL blood flow in the gray matter (GM). Correlation (E) and Bland-Altman (F) analyses between CBF_dDSC and ASL blood flow in the white matter (WM)

FIGURE 5

Group average perfusion and fit evaluation maps. A, CBF. B, CBV. MTT (C) and root-mean-square percentage error (RMSPE) (D) maps derived from the dDSC protocol. RMSPE maps showed adherence to the a priori hypoxia model of linear rise and exponential decay

FIGURE 6

Regional agreement between gray matter dDSC and ASL flow methods. Correlation and Bland-Altman analyses between gray matter CBF_dDSC and ASL blood flow in the ACA (A,B), MCA (C,D), and PCA (E,F) territories