This R21 project will develop and validate a novel method of imaging hemodynamic parameters (CBV and CBF) in vivo, based on crossmodal processing of concurrently recorded fMRI and NIRS data using Regressor Interpolation at Progressive Time Delays (RIPTiDe). This new, non-invasive imaging technique allows the routine generation of quantitative CBF and CBV images simultaneously with BOLD imaging data, and avoids many pitfalls of existing methods (DSC MRI, ASL and VASO). Background: RIPTiDe imaging exploits the fact the NIRS and fMRI both measure blood oxygenation and concentration fluctuations, but share no instrumental noise mechanisms. Therefore the temporal crosscorrelation of the NIRS and BOLD data represents the strength and timing of the propagation of endogenous fluctuations in blood oxygenation and volume through the vasculature. We can quantify the amplitude and arrival time of these signals in single subjects during brief scans at high signal to noise(1), and have used this technique for filtering physiological noise from BOLD data (2), and measuring cerebrovascular reactivity to a breathhold challenge (3). Using existing biophysical models of the BOLD effect, we propose using this data to quantitatively estimate cerebral blood flow and volume at high spatial resolution. Measurements can be made concurrently with conventional fMRI acquisitions, and require no special fMRI acquisition sequences or parameters. Moreover, the near infrared acquisition hardware required for this type of measurement can in principal be quite inexpensive, making it practical to add it to existing MR scanners. We will reduce this measurement to practice, and compare its results and data quality to ASL and VASO. Significance: Simultaneously acquired fMRI/NIRS data processed using RIPTiDe allows us to isolate the contribution of hemodynamic fluctuations to the BOLD signal in every voxel. This permits significant reduction in the physiological noise in the BOLD data, and simultaneously yields an estimate of blood flow and volume at every location. This allows truly concurrent acquisition of high quality BOLD, CBV, and CBF information.
Specific Aims : 1) Compare data quality obtained using NIRS from four different recording locations. The location of NIRS recording affects the purity of the measured hemodynamic signal. RIPTiDe images will be calculated using NIRS data from four probe locations, and compared to choose a standard recording location;2) Evaluate the use of RIPTiDe data as input to the Balloon Model to generate quantitative estimates of blood flow and volume. We will use the RIPTiDe data (optimally delayed NIRS [HbR] and [tHb], and BOLD) as inputs to the balloon model, calculate CBV and CBF, and compare results and SNR/unit time with ASL and VASO;3) Implement a RIPTiDe processing package.
This aim will develop a streamlined data recording and analysis suite to simplify the use of RIPTiDe data, and allow other researchers to use this method.

Public Health Relevance

The goal of this project is to improve existing multimodal processing of concurrently acquired NIRS and fMRI data to yield quantitative cerebral hemodynamic data (cerebral blood volume, cerebral blood flow, and mean transit time). The technique will be tested on 20 healthy subjects, and compared with arterial spin labeling and vascular space occupancy measurements.

National Institute of Health (NIH)
National Institute on Drug Abuse (NIDA)
Exploratory/Developmental Grants (R21)
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Biomedical Imaging Technology Study Section (BMIT)
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Bjork, James M
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Mclean Hospital
United States
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Tong, Yunjie; Frederick, Blaise deB (2014) Tracking cerebral blood flow in BOLD fMRI using recursively generated regressors. Hum Brain Mapp 35:5471-85