Biology subjects

Villalon-Reina, J. E.

Publications and source records attributed to Villalon-Reina, J. E..

24 records · Page 2Linked to original sources

bioRxiv2024

Deep Normative Tractometry for Identifying Joint White Matter Macro- and Micro-structural Abnormalities in Alzheimer's Disease

This study introduces the Deep Normative Tractometry (DNT) framework, that encodes the joint distribution of both macrostructural and microstructural profiles of the brain white matter tracts through a variational autoencoder (VAE). By training on data from healthy controls, DNT learns the normative distribution of tract data, and can delineate along-tract micro- and macro-structural abnormalities. Leveraging a large sample size via generative pre-training, we assess DNTs generalizability using transfer learning on data from an independent cohort acquired in India. Our findings demonstrate DNTs capacity to detect widespread diffusivity abnormalities along tracts in mild cognitive impairment and Alzheimers disease, aligning closely with results from the Bundle Analytics (BUAN) tractometry pipeline. By incorporating tract geometry information, DNT may be able to distinguish disease-related abnormalities in anisotropy from tract macrostructure, and shows promise in enhancing fine-scale mapping and detection of white matter alterations in neurodegenerative conditions.

neuroscience↗

bioRxiv2024

Bundle Analytics based Data Harmonization for Multi-Site Diffusion MRI Tractometry

The neural pathways of the living human brain can be tracked using diffusion MRI-based tractometry. Alongtract statistical analysis of microstructural metrics can reveal the effects of neurological and psychiatric diseases with 3D spatial precision. To maximize statistical power to detect disease effects and factors that influence them, data from multiple sites and scanners must often be combined, yet scanning protocols and hardware may vary widely. For simple scalar metrics, data harmonization methods - such as ComBat and its variants - allow modeling of disease effects on derived brain metrics, while adjusting for effects of scanning site or protocol. Here, we extend this method to pointwise segment analyses of 3D fiber bundles by integrating ComBat into the BUndle ANalytics (BUAN) tractometry pipeline. In a study of the effects of mild cognitive impairment (MCI) and Alzheimers disease (AD) on 38 white matter tracts, we merge data from 7 different scanning protocols used in the Alzheimers Disease Neuroimaging Initiative, which vary in voxel size and angular resolution. By incorporating ComBat harmonization, we model site- and scanner-specific effects, ensuring the reliability and comparability of results by mitigating confounding variables. We also evaluate choices that arise in extending batch adjustment to tracts, such as the regions used to estimate the correction. We also compare the approach to the simpler approach of modeling the site as a random effect. To the best of our knowledge, this is one of the first applications to adapt harmonization to 3D tractometry.

neuroscience↗

bioRxiv2023

BundleCleaner: Unsupervised Denoising and Subsampling of Diffusion MRI-Derived Tractography Data

We present BundleCleaner, an unsupervised multi-step frame-work that can filter, denoise and subsample bundles derived from diffusion MRI-based whole-brain tractography. Our approach considers both the global bundle structure and local streamline-wise features. We apply BundleCleaner to bundles generated from single-shell diffusion MRI data in an independent clinical sample of older adults from India using probabilistic tractography and the resulting cleaned bundles can better align with the atlas bundles with reduced overreach. In a downstream tractometry analysis, we show that the cleaned bundles, represented with less than 20% of the original set of points, can robustly localize along-tract microstructural differences between 32 healthy controls and 34 participants with Alzheimers disease ranging in age from 55 to 84 years old. Our approach can help reduce memory burden and improving computational efficiency when working with tractography data, and shows promise for large-scale multi-site tractometry.

neuroscience↗

bioRxiv2020

Exogenous sex hormone effects on brain microstructure in women: a diffusion MRI study in the UK Biobank

Changes in estrogen levels in women have been associated with increased risk for age-related neurodegenerative diseases, including Alzheimers disease, but the impact of exogenous estrogen exposure on the brain is poorly understood. Oral contraceptives (OC) and hormone therapy (HT) and are both common sources of exogenous estrogen for women in reproductive and post-menopausal years, respectively. Here we examined the association of exogenous sex hormone exposure with the brains white matter (WM) aging trajectories in postmenopausal women using and not using OC and HT (HT users: n=3,033, non-users n=5,093; OC users: n=6,964; non-users n=1,156), while also investigating multiple dMRI models. Cross-sectional brain dMRI data was analyzed from the UK Biobank using conventional diffusion tensor imaging (DTI), the tensor distribution function (TDF), and neurite orientation dispersion and density imaging (NODDI). Mean skeletonized diffusivity measures were extracted across the whole brain, and fractional polynomial regressions were used to characterize age-related trajectories for WM microstructural measures. Advanced dMRI model NODDI revealed a steeper WM aging trajectory in HT users relative to non-users, and for those using unopposed estrogens relative to combined estrogens treatment. By contrast, no interaction was detected between OC status and age effects on the diffusivity measures we examined. Exogenous sex hormone exposure may negatively impact WM microstructure aging in postmenopausal women. We also present normative reference curves for white matter microarchitectural parameters in women, to help identify individuals with microstructural anomalies.

neuroscience↗

bioRxiv2020

Advanced diffusion-weighted MRI metrics detect sex differences in aging among 15,000 adults in the UK Biobank

A comprehensive characterization of the brains white matter is critical for improving our understanding of healthy and diseased aging. Here we used diffusion-weighted magnetic resonance imaging (dMRI) to estimate age and sex effects on white matter microstructure in a cross-sectional sample of 15,628 adults aged 45-80 years old (47.6% male, 52.4% female). Microstructure was assessed using the following four models: a conventional single-shell model, diffusion tensor imaging (DTI); a more advanced single-shell model, the tensor distribution function (TDF); an advanced multi-shell model, neurite orientation dispersion and density imaging (NODDI); and another advanced multi-shell model, mean apparent propagator MRI (MAPMRI). Age was modeled using a data-driven statistical approach, and normative centile curves were created to provide sex-stratified white matter reference charts. Participant age and sex substantially impacted many aspects of white matter microstructure across the brain, with the advanced dMRI models TDF and NODDI detecting such effects the most sensitively. These findings and the normative reference curves provide an important foundation for the study of healthy and diseased brain aging.

neuroscience↗

bioRxiv2017

White matter differences in Parkinson’s disease mapped using tractometry

Neurodegenerative disorders are characterized by a progressive loss of brain function. Improved precision in mapping the altered brain pathways can provide a deep understanding of the trajectory of decline. We propose a tractometry workflow for conducting group statistical analyses of point-wise microstructural measures along white matter fasciculi to identify patterns of abnormalities associated with disease. We combined state-of-the-art tools including fiber registration, tract simplification and fiber matching for accurate point-wise statistical analyses across populations. We test the utility of this method by identifying group differences between Parkinsons disease (PD) patients and healthy controls. We find statistically significant group differences in diffusion MRI derived measures along the anterior thalamic radiations (ATR), corticospinal tract (CST) and regions of the corpus callosum (CC). These pathways are essential for motor control systems within cortico-cortical and cortico-subcortical brain networks. Moreover, the reported pathological changes were not widespread but rather localized along several tracts. Point-wise tract analyses may therefore offer an advantage in anatomical specificity over traditional methods that assess mean microstructural measures across large regions of interest.

neuroscience↗