Prior studies show that obesity is associated with accelerated brain aging and specific patterns of brain atrophy. Finerscale mapping of the effects of obesity on the brain would help to understand how it promotes or interacts with disease effects, but so far, the influence of the obesity on finer-scale maps of anatomy remains unclear. In this study, we propose a deep transfer learning network based on Optimal Mass Transport (OMTNet) to classify individuals with normal versus overweight/obese body mass index (BMI) using vertex-wise brain shape metrics extracted from structural MRI scans from the UK Biobank study. First, an area-preserving mapping was used to project 3D brain surface meshes onto 2D planar meshes. Vertex-wise maps of brain metrics such as cortical thickness were mapped into 2D planar images for each brain surface extracted from each person’s MRI scan. Second, several popular networks pretrained on the ImageNet database, i.e., VGG19, ResNet152 and DenseNet201, were used for transfer learning of brain shape metrics. We combined all shape metrics and generated a metric ensemble classification, and then combined all three networks and generated a network ensemble classification. The results reveal that transfer learning always outperforms direct learning, and we obtained accuracies of 65.6±0.7% and 62.7±0.7% for transfer and direct learning in the network ensemble classification, respectively. Moreover, surface area and cortical thickness, especially in the left hemisphere, consistently achieved the highest classification accuracies, together with subcortical shape metrics. The findings suggest a significant and classifiable influence of obesity on brain shape. Our proposed OMTNet method may offer a powerful transfer learning framework that can be extended to other vertex-wise brain structural and functional imaging measures.
Parkinson's disease (PD) is a progressive neurodegenerative disorder in which patients show progressively worsening motor symptoms, often followed by cognitive impairment and dementia. Brain MRI can be used to identify patterns of neurodegeneration that are characteristic of PD, but the spatial pattern of brain abnormalities is still not well understood. “Sulcus-based morphometry” provides measures of the cortical fissures of the brain that reflect degenerative changes in relation to neuropsychiatric disease. Extracting sulci requires good contrast between the gray matter and the CSF, and less well-defined sulci may be difficult to extract reliably. Before embarking on a study of sulcal abnormalities in PD, we set out to determine the reliability of measures from 123 sulci, defined by an existing atlas, using publicly available test-retest data from 8 cohorts. Of the 123 atlas-defined sulci, several major sulci were broken down into smaller regions (e.g., the superior temporal sulcus was divided into the main STS, the anterior terminal ascending branch of STS and the posterior terminal ascending branch of STS); we assessed reliability in each individually, and after merging the portions of the sulci together, in a newly defined, concatenated atlas. For 467 subjects from the PPMI cohort (http://www.ppmiinfo. org ;age range: 61.5 ± 10.1 years), we segmented and labeled major sulci and extracted 4 shape descriptors for each: length, depth, surface area, and width. We then aimed to establish the profile of case-control differences for 3 candidate sulci of interest: the central sulcus, superior temporal sulcus and the calcarine fissure. These sulci were among the more robust in terms of reproducibility; we found that the calcarine width was associated with PD, offering new features for genetic and interventional studies of PD.
Mild traumatic brain injury (mTBI) is characterized clinically by a closed head injury involving differential or rotational movement of the brain inside the skull. Over 3 million mTBIs occur annually in the United States alone. Many of the individuals who sustain an mTBI go on to recover fully, but around 20% experience persistent symptoms. These symptoms often last for many weeks to several months. The thalamus, a structure known to serve as a global networking or relay system for the rest of the brain, may play a critical role in neurorehabiliation and its integrity and connectivity after injury may also affect cognitive outcomes. To examine the thalamus, conventional tractography methods to map corticothalamic pathways with diffusion-weighted MRI (DWI) lead to sparse reconstructions that may contain false positive fibers that are anatomically inaccurate. Using a specialized method to zero in on corticothalamic pathways with greater robustness, we noninvasively examined corticothalamic fiber projections using DWI, in 68 service members. We found significantly lower fractional anisotropy (FA), a measure of white matter microstructural integrity, in pathways projecting to the left pre- and postcentral gyri – consistent with sensorimotor deficits often found post-mTBI. Mapping of neural circuitry in mTBI may help to further our understanding of mechanisms underlying recovery post-TBI.
Background: Increases in cancer survival have made understanding the basis of cancer-related cognitive impairment (CRCI) more important. CRCI neuroimaging studies have traditionally used dedicated research brain MRIs in breast cancer survivors with small sample sizes; little is known about other non-CNS cancers. However, there is a wealth of unused data from clinically-indicated MRIs that could be used to study CRCI. Objective: Evaluate brain cortical structural differences in those with non-CNS cancers using clinically-indicated MRIs. Design: Cross-sectional Patients: Adult non-CNS cancer and non-cancer control (C) patients who underwent clinically-indicated MRIs. Methods: Brain cortical surface area and thickness were measured using 3D T1-weighted images. An age-adjusted linear regression model was used and the Benjamini and Hochberg false discovery rate (FDR) corrected for multiple comparisons. Group comparisons were: cancer cases with chemotherapy (Ch+), cancer cases without chemotherapy (Ch-) and subgroup of lung cancer cases with and without chemotherapy vs C. Results: Sixty-four subjects were analyzed: 22 Ch+, 23 Ch- and 19 C patients. Subgroup analysis of 16 LCa was also performed. Statistically significant decreases in either cortical surface area or thickness were found in multiple ROIs primarily within the frontal and temporal lobes for all comparisons. Limitations: Several limitations were apparent including a small sample size that precluded adjustment for other covariates. Conclusions: Our preliminary results suggest that various types of non-CNS cancers, both with and without chemotherapy, may result in brain structural abnormalities. Also, there is a wealth of untapped clinical MRIs that could be used for future CRCI studies.
Outcome after a traumatic brain injury (TBI) is quite variable, and this variability is not solely accounted for by severity or demographics. Identifying sub-groups of patients who recover faster or more fully will help researchers and clinicians understand sources of this variability, and hopefully lead to new therapies for patients with a more prolonged recovery profile. We have previously identified two subgroups within the pediatric TBI patient population with different recovery profiles based on an ERP-derived (event-related potential) measure of interhemispheric transfer time (IHTT). Here we examine structural network topology across both patient groups and healthy controls, focusing on the ‘rich-club’ - the core of the network, marked by high degree nodes. These analyses were done at two points post-injury - 2-5 months (post-acute), and 13-19 months (chronic). In the post-acute time-point, we found that the TBI-slow group, those showing longitudinal degeneration, showed hyperconnectivity within the rich-club nodes relative to the healthy controls, at the expense of local connectivity. There were minimal differences between the healthy controls and the TBI-normal group (those patients who show signs of recovery). At the chronic phase, these disruptions were no longer significant, but closer analysis showed that this was likely due to the loss of power from a smaller sample size at the chronic time-point, rather than a sign of recovery. We have previously shown disruptions to white matter (WM) integrity that persist and progress over time in the TBI-slow group, and here we again find differences in the TBI-slow group that fail to resolve over the first year post-injury.
Emily Dennis, Jeffry Alger, Talin Babikian, Faisal Rashid, Julio Villalon-Reina, Richard Mink, Christopher Babbitt, Jeffrey Johnson, Christopher Giza, Robert Asarnow, Paul Thompson
Traumatic brain injury (TBI) causes extensive damage to the white matter (WM) of the brain, which can be evaluated with diffusion-weighted magnetic resonance imaging (dMRI). Diffusion MRI can be used to map the WM tracts and their integrity, but offers limited understanding of the biochemical basis of any differences. Magnetic resonance spectroscopy (MRS) measures neural metabolites that reflect neuronal health, inflammation, demyelination, and other consequences of TBI. We combined whole-brain MRS with dMRI to investigate WM dysfunction following pediatric TBI, using “tract-based spectroscopy”. Deficits in N-acetylaspartate (NAA) correspond to regions of deficits in WM integrity, but choline showed minimal overlap with WM deficits. NAA is a marker of neuronal health, while choline is an inflammatory marker. A partial F-test showed that MRS measures improved our ability to predict long-term cognitive function. This is the first paper to combine MRS with dMRI-derived tracts on a whole-brain scale, offering insights into the biochemical correlates of WM tract dysfunction, following injury and potentially in other WM disorders.
Access to the requested content is limited to institutions that have purchased or subscribe to SPIE eBooks.
You are receiving this notice because your organization may not have SPIE eBooks access.*
*Shibboleth/Open Athens users─please
sign in
to access your institution's subscriptions.
To obtain this item, you may purchase the complete book in print or electronic format on
SPIE.org.
INSTITUTIONAL Select your institution to access the SPIE Digital Library.
PERSONAL Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.