Quantitative characterization of human subcortical hemodynamic response at 3T and 9.4T (2018)

Introduction: Subcortical brain regions are absolutely essential for normal human cognitive function. Blood oxygen level dependent (BOLD) functional MRI (fMRI) can be a useful tool to understand subcortical neurovascular response. The hemodynamic response function (HRF) is crucial for the interpretation of fMRI results. The HRF is the vascular response evoked by brief (few sec) neural activation and is formed by changes in oxygen uptake and blood flow. The HRF should be a good indicator of brain health, because neurovascular coupling is critical for brain function (Carusone, Srinivasan et al. 2002, Roc, Wang et al. 2006, Bonakdarpour, Parrish et al. 2007). A substantial delayed HRF with lower hyperoxic peak was shown in stroke, mild cognitive impairment, and Alzheimer's disease patients. However, the relationship between the HRF and vascular pathology has not yet been quantitatively characterized. It is clear that we need a better understanding of the underlying physiological processes that gives rise to the HRF in human subcortical regions. Methods: Imaging was performed on a 3T (Baylor College of Medicine) and 9.4T (Max Planck Institute). For 3T, functional images were obtained using a 2-shot spiral acquisition (34-ms acquisition time for each shot) for 1.5 mm3 spatial resolution (TE 35 ms, TR 750 ms, volume acquisition every 1.5 s). Functional images were also obtained at 9.4T using point spread function (PSF)-corrected EPI with 1 mm3 spatial resolution (TE 21 ms, TR 1250 ms). Both of them cover subcortical regions including superior colliculus (SC), inferior colliculus (IC) and lateral geniculate nucleus (LGN). To generate brief periods of neural activity, subjects perform a multi-sensory integration task every 30 s. During a 2-s duration stimulation period, three circular regions (5º radius) filled with flickering colored dots are presented in random order at different screen locations with corresponding band pass-filtered white-noise audio pulses. Subjects performed saccades to fixate on each flickering circle (without moving their heads) and pushed a response button corresponding to the color of the flickering circle. Thus, the task requires subject to integrate auditory and visual inputs to perform visual and somatosensory tasks. This 30-s duration trial was repeated 18 times in each run; 5 runs will be collected. HRFs obtained in the target regions were temporally averaged over the whole of the scanning session. The peak amplitude and time parameters (e.g. time-to-peak, full width at half-maximum) of HRFs were obtained. Results: We were able to measure subcortical HRFs at both 3T and 9T scanners; the signal-to-noise ratios are ~3 at 3T and ~8 at 9.4T. At 3T, peak amplitude and time-to-peak of HRFs are relatively stable and similar throughout SC, and LGN, but IC shows less reliable and spatially discontinuous peak amplitude and relatively slow time-to-peak, Fig. 1. We also compared HRFs in SC with HRFs in early visual areas for both 3T and 9.4T. Faster hyperoxic peaks and narrower full-width-half-max (FWHM) and weak undershoot (Fig 2, blue and red lines) are shown comparing with those in early visual areas (purple and cyan lines). Note that peak amplitude of the HRF in SC at 9.4T is ~20 stronger than that at 3T. Conclusions: We demonstrate reliable HRFs in subcortical regions at both 3T and 9.4T scanners. The HRFs in subcortical regions show significant different from those in early visual cortex, which indicates that dynamics of neurovascular coupling in subcortical regions can be different from early visual areas. This suggests a separate characterization for subcortical HRFs required. Here, our metrics successfully characterize subcortical HRFs, which can be a useful tool for assessment of subcortical vascular health.