Dataset Information

Evidence for a vascular contribution to diffusion FMRI at high b value.

ABSTRACT: Recent work has suggested that diffusion-weighted functional magnetic resonance imaging (FMRI) with strong diffusion weighting (high b value) detects neuronal swelling that is directly related to neuronal firing. This would constitute a much more direct measure of brain activity than current methods and represent a major advance in neuroimaging. However, it has not been firmly established that the observed signal changes do not reflect residual vascular effects, which are known to exist at low b value. This study measures the vascular component of diffusion FMRI directly by using hypercapnia, which induces blood flow changes in the absence of a change in neuronal firing. Hypercapnia elicits a similar diffusion FMRI response to a visual stimulus including a rise in percent signal change with increasing b value, which was reported for visual activation. Analysis of the response timing found no evidence for an early response at high b value, which has been reported as evidence for a nonhemodynamic response. These results suggest that a large component of the diffusion FMRI signal at high b value is vascular rather than neuronal.

SUBMITTER: Miller KL

PROVIDER: S-EPMC2409250 | biostudies-other | 2007 Dec

REPOSITORIES: biostudies-other

ACCESS DATA

Publications

Evidence for a vascular contribution to diffusion FMRI at high b value.

Miller Karla L KL Bulte Daniel P DP Devlin Hannah H Robson Matthew D MD Wise Richard G RG Woolrich Mark W MW Jezzard Peter P Behrens Timothy E J TE

Proceedings of the National Academy of Sciences of the United States of America 20071219 52

Recent work has suggested that diffusion-weighted functional magnetic resonance imaging (FMRI) with strong diffusion weighting (high b value) detects neuronal swelling that is directly related to neuronal firing. This would constitute a much more direct measure of brain activity than current methods and represent a major advance in neuroimaging. However, it has not been firmly established that the observed signal changes do not reflect residual vascular effects, which are known to exist at low b ...[more]

PMID: 18093924

Similar Datasets

Project description:BACKGROUND AND PURPOSE:Imaging-based tumor grading is highly desirable but faces challenges in sensitivity, specificity, and diagnostic accuracy. A recently proposed diffusion imaging method by using a fractional order calculus model offers a set of new parameters to probe not only the diffusion process itself but also intravoxel tissue structures, providing new opportunities for noninvasive tumor grading. This study aimed to demonstrate the feasibility of using the fractional order calculus model to differentiate low- from high-grade gliomas in adult patients and illustrate its improved performance over a conventional diffusion imaging method using ADC (or D). MATERIALS AND METHODS:Fifty-four adult patients (18-70 years of age) with histology-proved gliomas were enrolled and divided into low-grade (n = 24) and high-grade (n = 30) groups. Multi-b-value diffusion MR imaging was performed with 17 b-values (0-4000 s/mm(2)) and was analyzed by using a fractional order calculus model. Mean values and SDs of 3 fractional order calculus parameters (D, ?, and ?) were calculated from the normal contralateral thalamus (as a control) and the tumors, respectively. On the basis of these values, the low- and high-grade glioma groups were compared by using a Mann-Whitney U test. Receiver operating characteristic analysis was performed to assess the performance of individual parameters and the combination of multiple parameters for low- versus high-grade differentiation. RESULTS:Each of the 3 fractional order calculus parameters exhibited a statistically higher value (P ? .011) in the low-grade than in the high-grade gliomas, whereas there was no difference in the normal contralateral thalamus (P ? .706). The receiver operating characteristic analysis showed that ? (area under the curve = 0.853) produced a higher area under the curve than D (0.781) or ? (0.703) and offered a sensitivity of 87.5%, specificity of 76.7%, and diagnostic accuracy of 82.1%. CONCLUSIONS:The study demonstrated the feasibility of using a non-Gaussian fractional order calculus diffusion model to differentiate low- and high-grade gliomas. While all 3 fractional order calculus parameters showed statistically significant differences between the 2 groups, ? exhibited a better performance than the other 2 parameters, including ADC (or D).

Dataset Information

Evidence for a vascular contribution to diffusion FMRI at high b value.

Publications

Evidence for a vascular contribution to diffusion FMRI at high b value.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets