Noncontrast mapping of arterial delay and functional connectivity using resting-state functional MRI: a study in Moyamoya patients

Abstract

Purpose: To investigate if delays in resting-state spontaneous fluctuations of the BOLD (sfBOLD) signal can be used to create maps similar to time-to-maximum of the residue function (Tmax) in Moyamoya patients and to determine whether sfBOLD delays affect the results of brain connectivity mapping.

Materials and methods: Ten patients were scanned at 3 Tesla using a gradient-echo echo planar imaging sequence for sfBOLD imaging. Cross correlation analysis was performed between each brain voxel signal and a reference signal comprised of either the superior sagittal sinus (SSS) or whole brain (WB) average time course. sfBOLD delay maps were created based on the time shift necessary to maximize the correlation coefficient, and compared with dynamic susceptibility contrast Tmax maps. Standard and time-shifted resting-state BOLD connectivity analyses of the default mode network were compared.

Results: Good linear correlations were found between sfBOLD delays and Tmax using the SSS as reference (r(2) = 0.8, slope = 1.4, intercept = -4.6) or WB (r(2) = 0.7, slope = 0.8, intercept = -3.2). New nodes of connectivity were found in delayed regions when accounting for delays in the analysis.

Conclusion: Resting-state sfBOLD imaging can create delay maps similar to Tmax maps without the use of contrast agents in Moyamoya patients. Accounting for these delays may affect the results of functional connectivity maps.

Keywords: BOLD contrast; MRI; Moyamoya disease; functional connectivity; perfusion; resting-state fMRI.

Figure 1

Temporal correlation of resting-state BOLD spontaneous fluctuations in one patient with Moyamoya disease. a) Gradient-echo echo-planar image (EPI) image at a single time point, Tmax map obtained with gadolinium-based dynamic susceptibility contrast, and corresponding sfBOLD delay map obtained without contrast agent injection. b) sfBOLD signal time courses corresponding to the ROIs defined in (a): red: affected hemisphere, blue: unaffected hemisphere, black: SSS seed region. Note that different scales are used for easier visualization. c) Cross correlation analysis between ROI signal in tissue ROI’s (red and blue) with the SSS seed region (black). Maximum correlation is found at −2TR for the affected tissue (red) while +3TR is found for healthy tissue (blue). Dashed lines denote the confidence interval. Both maxima have a correlation coefficient (R²=0.25, R²=0.30 for blue and red ROI respectively) higher than the 95% confidence bound (R²=0.18). The (d) Tmax map (obtained with DSC) and (e) sfBOLD delay maps (obtained with the SSS as the seed region) from the same patient display similar characteristics, with delays present in the left hemisphere.

Figure 2

Multislice comparison between Tmax maps and resting-state sfBOLD delay maps in 3 Moyamoya patients with unilateral (patient 1 and patient 2) or mild bilateral (patient 9) delays. While good agreement was found between both approaches, white arrows indicate regions showing high Tmax values but normal sfBOLD delays.

Figure 3

Correlation between Tmax and sfBOLD delay maps in one patient using different reference seed regions: (a) SSS, (b) whole brain average. Points correspond to hemispheric ROI’s obtained in 10 central slices. Corresponding correlation coefficients and linear fit equations are also indicated. c) Correlation coefficients for similar plots obtained for all patients. Except for patient 7, sfBOLD delay maps using the SSS seed approach had higher correlation to Tmax delay maps than those created with the whole brain average time series used as the reference region.

Figure 4

Resting-state connectivity analysis in two patients. Default mode network was probed using a seed based approach with the reference signal chosen in the precuneus. While our acquisition was suboptimal for functional analysis (<4min), most of the network can be seen (red colorbar, in phase). Interestingly, accounting for the delays in the reference signal leads to the identification of new nodes (blue colorbar, delayed) in the affected hemisphere (see white arrows in connectivity maps and corresponding Tmax maps). This suggests that functionally connected networks may not be identified in their entirety in such patients if processing does not account for the intrinsic delays present.