Processing Time Reduction: an Application in Living Human High-Resolution Diffusion Magnetic Resonance Imaging Data.

High Angular Resolution Diffusion Imaging (HARDI) is a type of brain imaging that collects a very large amount of data, and if many subjects are considered then it amounts to a big data framework (e.g., the human connectome project has 20 Terabytes of data). HARDI is also becoming increasingly relevant for clinical settings (e.g., detecting early cerebral ischemic changes in acute stroke, and in pre-clinical assessment of white matter-WM anatomy using tractography). Thus, this method is becoming a routine assessment in clinical settings. In such settings, the computation time is critical, and finding forms of reducing the processing time in high computation processes such as Diffusion Spectrum Imaging (DSI), a form of HARDI data, is very relevant to increase data-processing speed. Here we analyze a method for reducing the computation time of the dMRI-based axonal orientation distribution function h by using Monte Carlo sampling-based methods for voxel selection. Results evidenced a robust reduction in required data sampling of about 50 % without losing signal's quality. Moreover, we show that the convergence to the correct value in this type of Monte Carlo HARDI/DSI data-processing has a linear improvement in data-processing speed of the ODF determination. Although further improvements are needed, our results represent a promissory step for future processing time reduction in big data.

Use of Shannon information in treatment of high resolution diffusion MRI.

Diffusion MRI allows the obtaining of an approximation of the water displacement's probability density function (PDF) and orientation distribution function (ODF). Examples of techniques used in obtaining these distributions being q-space imaging (QSI), and q-ball imaging (QBI), respectively. Shannon information quantifies the discriminative power of a symbol based on its probability. We quantified the information amount of a white matter fiber bundle being used to discriminate those fibers using specific diffusion MRI data treatment techniques. The equations developed are new and it is also described how they will help in future experimental calculations. An example of experimental ODF surfaces and ODF based white matter fiber tracking in living humans is also shown to highlight possible future advantages of Shannon information usage in describing crossing white matter fiber bundles.

Obsessive-compulsive disorder as a visual processing impairment.

OCD has been hypothesized to involve the failures in both cognitive and behavioral inhibitory processes. There is evidence that the hyperactivation of cortical-subcortical pathways may be involved in the failure of these inhibitory systems associated with OCD. Despite this consensus on the role of frontal-subcortical pathways in OCD, recent studies have been showing that brain regions other than the frontal-subcortical loops may be needed to understand the different cognitive and emotional deficits in OCD. Some studies have been finding evidence for decreased metabolic activity in areas such as left inferior parietal and parieto-occipital junction suggesting the possible existence of visual processing deficits. While there has been inconsistent data regarding visual processing in OCD, recent studies have been claiming that these patients have abnormal patterns of visual processing social rich stimuli, particularly emotional arousing stimuli. Thus, in this article, we hypothesize that the fronto-subcortical activation consistently found in OCD may be due to a deactivation of occipital/parietal regions associated with visual-perceptual processing of incoming social rich stimuli. Additionally, this dissociation may be more evident as the emotional intensity of the social stimulus increases.

MRI diffusion tensor tracking of a new amygdalo-fusiform and hippocampo-fusiform pathway system in humans.

PURPOSE: To use MRI diffusion-tensor tracking (DTT) to test for the presence of unknown neuronal fiber pathways interconnecting the mid-fusiform cortex and anteromedial temporal lobe in humans. Such pathways are hypothesized to exist because these regions coactivate in functional MRI (fMRI) studies of emotion-valued faces and words, suggesting a functional link that could be mediated by neuronal connections. MATERIALS AND METHODS: A total of 15 normal human subjects were studied using unbiased DTT approaches designed for probing unknown pathways, including whole-brain seeding and large pathway-selection volumes. Several quality-control steps verified the results. RESULTS: Parallel amygdalo-fusiform and hippocampo-fusiform pathways were found in all subjects. The pathways begin/end at the mid-fusiform gyrus above the lateral occipitotemporal sulcus bilaterally. The superior pathway ends/begins at the superolateral amygdala. The inferior pathway crosses medially and ends/begins at the hippocampal head. The pathways are left-lateralized, with consistently larger cross-sectional area, higher anisotropy, and lower minimum eigenvalue (D-min) on the left, where D-min assesses intrinsic cross-fiber diffusivity independent of curvature. CONCLUSION: A previously-undescribed pathway system interconnecting the mid-fusiform region with the amygdala/hippocampus has been revealed. This pathway system may be important for recognition, memory consolidation, and emotional modulation of face, object, and lexical information, which may be disrupted in conditions such as Alzheimer's disease.

Definition of displacement probability and diffusion time in q-space magnetic resonance measurements that use finite-duration diffusion-encoding gradients.

In q-space diffusion NMR, the probability P(r,td) of a molecule having a displacement r in a diffusion time td is obtained under the assumption that the diffusion-encoding gradient g has an infinitesimal duration. However, this assumption may not always hold, particularly in human MRI where the diffusion-encoding gradient duration delta is typically of the same order of magnitude as the time offset Delta between encoding gradients. In this case, finite-delta effects complicate the interpretation of displacement probabilities measured in q-space MRI, and the form by which the signal intensity relates to them. By considering the displacement-specific dephasing, , of a set of spins accumulating a constant displacement vector r in the total time Delta+delta during which diffusion is encoded, the probability recovered by a finite-delta q-space experiment can be interpreted. It is shown theoretically that a data analysis using a modified q-space index q=gammadeltaetag, with gamma the gyromagnetic ratio and eta=square root (Delta-delta/3)/(Delta+delta), recovers the correct displacement probability distribution if diffusion is multi-Gaussian free diffusion. With this analysis, we show that the displacement distribution P(r,texp) is measured at the experimental diffusion-encoding time texp=Delta+delta, and not at the reduced diffusion time tr=Delta-delta/3 as is generally assumed in the NMR and MRI literature. It is also shown that, by defining a probability P(y,Delta) that a time tdeltac then eta is not equal to square root (Delta-delta/3)/(Delta+delta) which implies that we can no longer obtain the correct displacement probability from the displacement distribution. In the case that /g/=18 mT/m and Delta-delta=5 ms, the parameter deltac in ms is given by "deltac=0.49a2+0.24" where a is the sphere's radius expressed in microm. Simulation of q-space restricted diffusion MRI experiments indicate that if eta=square root (Delta-delta/3)/(Delta+delta), the recovered displacement probability is always better than the Gaussian approximation, and the measured diffusion coefficient matches the diffusion coefficient at time texp=Delta+delta better than it matches the diffusion coefficient at time tr=Delta-delta/3. These results indicate that q-space MRI measurements of displacement probability distributions are theoretically possible in biological tissues using finite-duration diffusion-encoding gradients provided certain compartment size and diffusion encoding gradient duration constraints are met.