Validating an image-based fNIRS approach with fMRI and a working memory task

In the current study, we extend a previous methodological pipeline by adding a novel image reconstruction approach to move functional near-infrared (fNIRS) signals from channel-space on the surface of the head to voxel-space within the brain volume. We validate this methodology by comparing voxel-wise fNIRS results to functional magnetic resonance imaging (fMRI) results from a visual working memory (VWM) task using two approaches. In the first approach, significant voxel-wise correlations were observed between fNIRS and fMRI measures for all experimental conditions across brain regions in the fronto-parieto-temporal cortices. In the second approach, we conducted separate multi-factorial ANOVAs on fNIRS and fMRI measures and then examined the correspondence between main and interaction effects within common regions of interest. Both fMRI and fNIRS showed similar trends in activation within the VWM network when the number of items held in working memory increases. These results validate the image-based fNIRS approach

Evaluation of rigid registration methods for whole head imaging in diffuse optical tomography

Functional brain imaging has become an important neuroimaging technique for the study of brain organization and development. Compared to other imaging techniques, diffuse optical tomography (DOT) is a portable and low-cost technique that can be applied to infants and hospitalized patients using an atlas-based light model. For DOT imaging, the accuracy of the forward model has a direct effect on the resulting recovered brain function within a field of view and so the accuracy of the spatially normalized atlas-based forward models must be evaluated. Herein, the accuracy of atlas-based DOT is evaluated on models that are spatially normalized via a number of different rigid registration methods on 24 subjects. A multileveled approach is developed to evaluate the correlation of the geometrical and sensitivity accuracies across the full field of view as well as within specific functional subregions. Results demonstrate that different registration methods are optimal for recovery of different sets of functional brain regions. However, the “nearest point to point” registration method, based on the EEG 19 landmark system, is shown to be the most appropriate registration method for image quality throughout the field of view of the high-density cap that covers the whole of the optically accessible cortex

小動物におけるEEGとfMRIの同時計測法の確立

Tohoku University川島隆太課

Direct Estimation of Evoked Hemoglobin Changes by Multimodality Fusion Imaging

In the last two decades, both diffuse optical tomography (DOT) and blood oxygen level dependent (BOLD)-based functional magnetic resonance imaging (fMRI) methods have been developed as noninvasive tools for imaging evoked cerebral hemodynamic changes in studies of brain activity. Although these two technologies measure functional contrast from similar physiological sources, i.e., changes in hemoglobin levels, these two modalities are based on distinct physical and biophysical principles leading to both limitations and strengths to each method. In this work, we describe a unified linear model to combine the complimentary spatial, temporal, and spectroscopic resolutions of concurrently measured optical tomography and fMRI signals. Using numerical simulations, we demonstrate that concurrent optical and BOLD measurements can be used to create cross-calibrated estimates of absolute micromolar deoxyhemoglobin changes. We apply this new analysis tool to experimental data acquired simultaneously with both DOT and BOLD imaging during a motor task, demonstrate the ability to more robustly estimate hemoglobin changes in comparison to DOT alone, and show how this approach can provide cross-calibrated estimates of hemoglobin changes. Using this multimodal method, we estimate the calibration of the 3tesla BOLD signal to be −0.55%±0.40% signal change per micromolar change of deoxyhemoglobin

Application of resting-state fMRI methods to acute ischemic stroke

Diffusion weighted imaging (DWI) and dynamic susceptibility contrast-enhanced (DSC) perfusion-weighted imaging (PWI) are commonly employed in clinical practice and in research to give pathophysiological information for patients with acute ischemic stroke. DWI is thought to roughly reflect the severely damaged infarct core, while DSC-PWI reflects the area of hypoperfusion. The volumetric difference between DWI and DSC-PWI is termed the PWI/DWI-mismatch, and has been suggested as an MRI surrogate of the ischemic penumbra. However, due to the application of a contrast agent, which has potentially severe side-effects (e.g., nephrogenic systemic fibrosis), the DSC-PWI precludes repetitive examinations for monitoring purposes. New approaches are being sought to overcome this shortcoming. BOLD (blood oxygen-level dependent) signal can reflect the metabolism of blood oxygen in the brain and hemodynamics can be assessed with resting-state fMRI. The aim of this thesis was to use resting-state fMRI as a new approach to give similar information as DSC-PWI. This thesis comprises two studies: In the first study (see Chapter 2), two resting-state fMRI methods, local methods which compare low frequency amplitudes between two hemispheres and a k-means clustering approach, were applied to investigate the functional damage of patients with acute ischemic stroke both in the time domain and frequency domain. We found that the lesion areas had lower amplitudes than contralateral homotopic healthy tissues. We also differentiated the lesion areas from healthy tissues using a k-means clustering approach. In the second study (see Chapter 3), time-shift analysis (TSA), which assesses time delays of the spontaneous low frequency fluctuations of the resting-state BOLD signal, was applied to give similar pathophysiological information as DSC-PWI in the acute phase of stroke. We found that areas which showed a pronounced time delay to the respective mean time course were very similar to the hypoperfusion area. In summary, we suggest that the resting-state fMRI methods, especially the time-shift analysis (TSA), may provide comparable information to DSC-PWI and thus serve as a useful diagnostic tool for stroke MRI without the need for the application of a contrast agent

Serial Correlations in Single-Subject fMRI with Sub-Second TR

When performing statistical analysis of single-subject fMRI data, serial correlations need to be taken into account to allow for valid inference. Otherwise, the variability in the parameter estimates might be under-estimated resulting in increased false-positive rates. Serial correlations in fMRI data are commonly characterized in terms of a first-order autoregressive (AR) process and then removed via pre-whitening. The required noise model for the pre-whitening depends on a number of parameters, particularly the repetition time (TR). Here we investigate how the sub-second temporal resolution provided by simultaneous multislice (SMS) imaging changes the noise structure in fMRI time series. We fit a higher-order AR model and then estimate the optimal AR model order for a sequence with a TR of less than 600 ms providing whole brain coverage. We show that physiological noise modelling successfully reduces the required AR model order, but remaining serial correlations necessitate an advanced noise model. We conclude that commonly used noise models, such as the AR(1) model, are inadequate for modelling serial correlations in fMRI using sub-second TRs. Rather, physiological noise modelling in combination with advanced pre-whitening schemes enable valid inference in single-subject analysis using fast fMRI sequences

The Integration of Positron Emission Tomography With Magnetic Resonance Imaging

A number of laboratories and companies are currently exploring the development of integrated imaging systems for magnetic resonance imaging (MRI) and positron emission tomography (PET). Scanners for both preclinical and human research applications are being pursued. In contrast to the widely distributed and now quite mature PET/computed tomography technology, most PET/MRI designs allow for simultaneous rather than sequential acquisition of PET and MRI data. While this offers the possibility of novel imaging strategies, it also creates considerable challenges for acquiring artifact-free images from both modalities. This paper discusses the motivation for developing combined PET/MRI technology, outlines the obstacles in realizing such an integrated instrument, and presents recent progress in the development of both the instrumentation and of novel imaging agents for combined PET/MRI studies. The performance of the first-generation PET/MRI systems is described. Finally, a range of possible biomedical applications for PET/MRI are outlined