Optimizing Filter-Probe Diffusion Weighting in the Rat Spinal Cord for Human Translation

Diffusion tensor imaging (DTI) is a promising biomarker of spinal cord injury (SCI). In the acute aftermath, DTI in SCI animal models consistently demonstrates high sensitivity and prognostic performance, yet translation of DTI to acute human SCI has been limited. In addition to technical challenges, interpretation of the resulting metrics is ambiguous, with contributions in the acute setting from both axonal injury and edema. Novel diffusion MRI acquisition strategies such as double diffusion encoding (DDE) have recently enabled detection of features not available with DTI or similar methods. In this work, we perform a systematic optimization of DDE using simulations and an in vivo rat model of SCI and subsequently implement the protocol to the healthy human spinal cord. First, two complementary DDE approaches were evaluated using an orientationally invariant or a filter-probe diffusion encoding approach. While the two methods were similar in their ability to detect acute SCI, the filter-probe DDE approach had greater predictive power for functional outcomes. Next, the filter-probe DDE was compared to an analogous single diffusion encoding (SDE) approach, with the results indicating that in the spinal cord, SDE provides similar contrast with improved signal to noise. In the SCI rat model, the filter-probe SDE scheme was coupled with a reduced field of view (rFOV) excitation, and the results demonstrate high quality maps of the spinal cord without contamination from edema and cerebrospinal fluid, thereby providing high sensitivity to injury severity. The optimized protocol was demonstrated in the healthy human spinal cord using the commercially-available diffusion MRI sequence with modifications only to the diffusion encoding directions. Maps of axial diffusivity devoid of CSF partial volume effects were obtained in a clinically feasible imaging time with a straightforward analysis and variability comparable to axial diffusivity derived from DTI. Overall, the results and optimizations describe a protocol that mitigates several difficulties with DTI of the spinal cord. Detection of acute axonal damage in the injured or diseased spinal cord will benefit the optimized filter-probe diffusion MRI protocol outlined here

On Functional Activations in Deep Neural Networks

Background: Deep neural networks have proven to be powerful computational tools for modeling, prediction, and generation. However, the workings of these models have generally been opaque. Recent work has shown that the performance of some models are modulated by overlapping functional networks of connections within the models. Here the techniques of functional neuroimaging are applied to an exemplary large language model to probe its functional structure. Methods: A series of block-designed task-based prompt sequences were generated to probe the Facebook Galactica-125M model. Tasks included prompts relating to political science, medical imaging, paleontology, archeology, pathology, and random strings presented in an off/on/off pattern with prompts about other random topics. For the generation of each output token, all layer output values were saved to create an effective time series. General linear models were fit to the data to identify layer output values which were active with the tasks. Results: Distinct, overlapping networks were identified with each task. Most overlap was observed between medical imaging and pathology networks. These networks were repeatable across repeated performance of related tasks, and correspondence of identified functional networks and activation in tasks not used to define the functional networks was shown to accurately identify the presented task. Conclusion: The techniques of functional neuroimaging can be applied to deep neural networks as a means to probe their workings. Identified functional networks hold the potential for use in model alignment, modulation of model output, and identifying weights to target in fine-tuning

In vivo MRI volumetric measurement of prostate regression and growth in mice

BackgroundMouse models for treatment of late-stage prostate cancer are valuable tools, but assessing the extent of growth of the prostate and particularly its regression due to therapeutic intervention or castration is difficult due to the location, small size and interdigitated anatomy of the prostate gland in situ. Temporal monitoring of mouse prostate regression requires multiple animals and examination of histological sections.MethodsInitially, T2-weighted magnetic resonance imaging (MRI) was performed on normal year-old C57/BL6 mice. Individual mice were repeatedly imaged using inhalation anesthesia to establish the reproducibility of the method and to follow hormone manipulation of the prostate volume. Subsequently, MRI fat signal was suppressed using a chemical shift-selective (CHESS) pulse to avoid signal contamination and enhance discrimination of the prostate.ResultsHigh field (7T) MRI provides high resolution (117 x 117 microm in plane), highly reproducible images of the normal mouse prostate. Despite long imaging times, animals can be imaged repeatedly to establish reliability of volume measurements. Prostate volume declines following castration and subsequently returns to normal with androgen administration in the same animal. CHESS imaging allowed discrimination of both the margins of the prostate and the dorsal-lateral lobes of the prostate (DLP) from the ventral lobes (VP). Castration results in a 40% reduction in the volume of the DLP and a 75% reduction in the volume of the VP.ConclusionMRI assessment of the volume of the mouse prostate is precise and reproducible. MRI improves volumetric determination of the extent of regression and monitoring of the same mouse over time during the course of treatment is possible. Since assessing groups of animals at each time point is avoided, this improves the accuracy of the measurement of any manipulation effect and reduces the number of animals required

The brain anatomy of attention-deficit/hyperactivity disorder in young adults - a magnetic resonance imaging study.

This is one of the first studies to examine the structural brain anatomy and connectivity associated with an ADHD diagnosis and child as well as adult ADHD symptoms in young adults. It was hypothesized that an adult ADHD diagnosis and in particular childhood symptoms, are associated with widespread changes in the brain macro- and microstructure, which can be used to develop a morphometric biomarker for ADHD.Voxel-wise linear regression models were used to examine structural and diffusion-weighted MRI data in 72 participants (31 young adults with ADHD and 41 controls without ADHD) in relation to diagnosis and the number of self-reported child and adult symptoms.Findings revealed significant associations between ADHD diagnosis and widespread changes to the maturation of white matter fiber bundles and gray matter density in the brain, such as structural shape changes (incomplete maturation) of the middle and superior temporal gyrus, and fronto-basal portions of both frontal lobes. ADHD symptoms in childhood showed the strongest association with brain macro- and microstructural abnormalities. At the brain circuitry level, the superior longitudinal fasciculus (SLF) and cortico-limbic areas are dysfunctional in individuals with ADHD. The morphometric findings predicted an ADHD diagnosis correctly up to 83% of all cases.An adult ADHD diagnosis and in particular childhood symptoms are associated with widespread micro- and macrostructural changes. The SLF and cortico-limbic findings suggest complex audio-visual, motivational, and emotional dysfunctions associated with ADHD in young adults. The sensitivity of the morphometric findings in predicting an ADHD diagnosis was sufficient, which indicates that MRI-based assessments are a promising strategy for the development of a biomarker

Development of white matter pathways in typically developing preadolescent children

The first phase of major neuronal rearrangements in the brain takes place during the prenatal period. While the brain continues maturation throughout childhood, a critical second phase of synaptic overproduction and elimination takes place during the preadolescent period. Despite the importance of this developmental phase, few studies have evaluated neural changes taking place during this period. In this study, MRI Diffusion Tensor Imaging data from a normative sample of 126 preadolescent children (59 girls and 67 boys) between the ages of 6 and 10 years were analyzed in order to characterize age-relationships in the white matter microstructure. Tract Based Spatial Statistics (TBSS) method was used for whole brain analysis of white matter tracts without a priori assumption about the location of age associated differences. Our results demonstrate significant age-associated differences in most of the major fiber tracts bilaterally and along the whole body of the tracts. In contrast, developmental differences in the cingulum at the level of the parahippocampal region were only observed in the right hemisphere. We suggest that these age-relationships with a widespread distribution seen during the preadolescent years maybe relevant for the implementation of cognitive and social behaviors needed for a normal development into adulthood

Association of concussion history with psychiatric symptoms, limbic system structure, and kynurenine pathway metabolites in healthy, collegiate-aged athletes

Psychiatric outcomes are commonly observed in individuals with repeated concussions, though their underlying mechanism is unknown. One potential mechanism linking concussion with psychiatric symptoms is inflammation-induced activation of the kynurenine pathway, which is thought to play a role in the pathogenesis of mood disorders. Here, we investigated the association of prior concussion with multiple psychiatric-related outcomes in otherwise healthy male and female collegiate-aged athletes (N = 212) with varying histories of concussion recruited from the community. Specially, we tested the hypotheses that concussion history is associated with worse psychiatric symptoms, limbic system structural abnormalities (hippocampal volume, white matter microstructure assessed using neurite orientation dispersion and density imaging; NODDI), and elevations in kynurenine pathway (KP) metabolites (e.g., Quinolinic acid; QuinA). Given known sex-effects on concussion risk and recovery, psychiatric outcomes, and the kynurenine pathway, the moderating effect of sex was considered for all analyses. More concussions were associated with greater depression, anxiety, and anhedonia symptoms in female athletes (ps ≤ 0.005) and greater depression symptoms in male athletes (p = 0.011). More concussions were associated with smaller bilateral hippocampal tail (ps &lt; 0.010) and left hippocampal body (p &lt; 0.001) volumes across male and female athletes. Prior concussion was also associated with elevations in the orientation dispersion index (ODI) and lower intracellular volume fraction in several white matter tracts including the in uncinate fasciculus, cingulum-gyrus, and forceps major and minor, with evidence of female-specific associations in select regions. Regarding serum KP metabolites, more concussions were associated with elevated QuinA in females and lower tryptophan in males (ps ≤ 0.010). Finally, serum levels of QuinA were associated with elevated ODI (male and female athletes) and worse anxiety symptoms (females only), while higher ODI in female athletes and smaller hippocampal volumes in male athletes were associated with more severe anxiety and depression symptoms (ps ≤ 0.05). These data suggest that cumulative concussion is associated with psychiatric symptoms and limbic system structure in healthy athletes, with increased susceptibility to these effects in female athletes. Moreover, the associations of outcomes with serum KP metabolites highlight the KP as one potential molecular pathway underlying these observations.</p