Biology subjects

Alibrando, J. D.

Publications and source records attributed to Alibrando, J. D..

3 recordsLinked to original sources

bioRxiv2026

Tractometry-Based Quantification of Along-Tract White-Matter Hemispheric Asymmetry in Alzheimer's Disease

White-matter hemispheric asymmetry is a fundamental property of human brain organization and is known to change in aging, neurodevelopment, and neurodegenerative disorders. Tractometry analyzes diffusion-derived microstructural measures along the full length of tracts, localizing changes to specific tract-segments rather than collapsing tracts into a single value. Yet, existing frameworks lack a principled way to quantify left-right hemispheric asymmetries along homologous tracts. Here, we introduce an asymmetry-aware tractometry framework that integrates a symmetric white-matter atlas with BUAN (Bundle Analytics) to enable anatomically consistent, along-tract comparison of homologous pathways. By defining homologous bundles with a shared template and consistent orientation, each left-hemisphere segment is directly matched to its right-hemisphere counterpart, enabling principled, segment-wise comparison and revealing spatially localized asymmetries along-tract. Applying this framework to diffusion MRI data from the Alzheimers Disease Neuroimaging Initiative (ADNI) comprising 1,215 subjects, we demonstrate how this approach reveals systematic left-right asymmetries across major white-matter pathways and show how these patterns differentiate cognitively normal (CN) individuals from those with mild cognitive impairment (MCI) and dementia. This method provides a sensitive and anatomically grounded tool for studying hemispheric specialization and its disruption in aging and disease, and establishes a general approach for asymmetry-aware tractometry in population neuroimaging studies.

neuroscience↗

bioRxiv2025

Evaluating Sample-Size Efficiency and Sensitivity of Tractometry in Alzheimer's Disease

Tractometry allows quantitative analysis of white matter microstructure along the brains fiber tracts, but the impact of study design parameters--such as sample size and along-tract resolution--on sensitivity and specificity is not well understood. In this study, we conducted tractometry bootstrap analysis using linear-mixed models across four diffusion tensor imaging (DTI) metrics to systematically evaluate how these factors affect the detection of dementia- and amyloidrelated effects. While coarser along-tract segments yield greater sensitivity and higher mean effect sizes, finer segments tend to produce higher peak effect sizes, revealing more spatially localized effects. Dementia-related effects were more widespread and detectable with fewer subjects, whereas amyloid-related effects were more subtle and localized, requiring larger cohorts to detect them. These findings highlight that tractometry offers improved spatial specificity and can reliably detect small, fine-scale effects, but study design should be tailored to specific research questions, considering the expected spatial extent and magnitude of effects, to optimize sample size efficiency and interpretability.

neuroscience↗

bioRxiv2025

Deterministic versus Probabilistic Tractography: Impact on White Matter Bundle Shape

In diffusion MRI-based tractography, deterministic and probabilistic algorithms reconstruct white matter using distinct strategies, yet their impact on bundle morphology remains uncertain. Using bundle shape similarity analysis, we compared both methods for the left arcuate fasciculus (AF_L) (The left arcuate fasciculus is a critical white matter tract that connects language comprehension and production areas in the human brain, enabling fluent language processing) across four datasets: Alzheimers Disease Neuroimaging Initiative (ADNI), Human Connectome Project-Aging (HCP-A), National Institute of Mental Health and Neurosciences (NIMHANS), and Pediatric Imaging, Neurocognition, and Genetics (PING). Probabilistic tractography consistently produced higher inter-subject shape similarity, by capturing broader anatomical trajectories and enhancing reproducibility. However, this extensive coverage may obscure subtle pathological variations critical for clinical detection. Bundle shape similarity analysis with atlas corroborated these findings, showing stronger alignment for probabilistic tracking and highlighting its utility in quantitative quality control. These results emphasize the need to balance morphological consistency with sensitivity to neuroanatomical variation when selecting tractography methods for research and clinical applications.

neuroscience↗