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Blood oxygenation level-dependent functional MRI signal turbulence caused by ultrahigh spatial resolution: numerical simulation and theoretical explanation.

ABSTRACT: High-spatial-resolution functional MRI (fMRI) can enhance image contrast and improve spatial specificity for brain activity mapping. As the voxel size is reduced, an irregular magnetic fieldmap will emerge as a result of less local averaging, and will lead to abnormal fMRI signal evolution with respect to the image acquisition TE. In this article, we report this signal turbulence phenomenon observed in simulations of ultrahigh-spatial-resolution blood oxygenation level-dependent (BOLD) fMRI (voxel size of less than 50 × 50 × 50 µm³). We present a four-level coarse-to-fine multiresolution BOLD fMRI signal simulation. Based on the statistical histogram of an intravoxel fieldmap, we reformulate the intravoxel dephasing summation (a form of Riemann sum) into a new formula that is a discrete Fourier transformation of the intravoxel fieldmap histogram (a form of Lebesgue sum). We interpret the BOLD signal formation by relating its magnitude (phase) to the even (odd) symmetry of the fieldmap histogram. Based on multiresolution BOLD signal simulation, we find that the signal turbulence mainly emerges at the vessel boundary, and that there are only a few voxels (less than 10%) in an ultrahigh-resolution image that reveal turbulence in the form of sparse point noise. Our simulation also shows that, for typical human brain imaging of the cerebral cortex with millimeter resolution, TE < 30 ms and B₀ = 3 T, we are unlikely to observe BOLD signal turbulence. Overall, the main causes of voxel signal turbulence include a high spatial resolution, high field, long TE and large vessel.

SUBMITTER: Chen Z

PROVIDER: S-EPMC4435714 | biostudies-other | 2013 Mar

REPOSITORIES: biostudies-other

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Project description:Numerical body models of children are used for designing medical devices, including but not limited to optical imaging, ultrasound, CT, EEG/MEG, and MRI. These models are used in many clinical and neuroscience research applications, such as radiation safety dosimetric studies and source localization. Although several such adult models have been reported, there are few reports of full-body pediatric models, and those described have several limitations. Some, for example, are either morphed from older children or do not have detailed segmentations. Here, we introduce a 29-month-old male whole-body native numerical model, "MARTIN", that includes 28 head and 86 body tissue compartments, segmented directly from the high spatial resolution MRI and CT images. An advanced auto-segmentation tool was used for the deep-brain structures, whereas 3D Slicer was used to segment the non-brain structures and to refine the segmentation for all of the tissue compartments. Our MARTIN model was developed and validated using three separate approaches, through an iterative process, as follows. First, the calculated volumes, weights, and dimensions of selected structures were adjusted and confirmed to be within 6% of the literature values for the 2-3-year-old age-range. Second, all structural segmentations were adjusted and confirmed by two experienced, sub-specialty certified neuro-radiologists, also through an interactive process. Third, an additional validation was performed with a Bloch simulator to create synthetic MR image from our MARTIN model and compare the image contrast of the resulting synthetic image with that of the original MRI data; this resulted in a "structural resemblance" index of 0.97. Finally, we used our model to perform pilot MRI safety simulations of an Active Implantable Medical Device (AIMD) using a commercially available software platform (Sim4Life), incorporating the latest International Standards Organization guidelines. This model will be made available on the Athinoula A. Martinos Center for Biomedical Imaging website.

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Blood oxygenation level-dependent functional MRI signal turbulence caused by ultrahigh spatial resolution: numerical simulation and theoretical explanation.

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