International Symposium on Medical Information Processing and Analysis (SIPAIM)NeurosciencePeer-reviewed journal article
Multi-Site Statistical Mapping of Along-Tract Microstructural Abnormalities in Bipolar Disorder with Diffusion MRI Tractometry
Leila NabulsiiD, Bramsh Q. ChandioiD, Genevieve McPhilemyiD, Fiona M. MartyniD, Gloria M.P. RobertsiD, Brian P. HallahaniD, Udo DannlowskiiD, Tilo T. J. KircheriD, Benno C. M. HaarmaniD, Philip Bowden MitchelliD, Colm McDonaldiD, Dara M. CannoniD, Ole A. AndreasseniD, Christopher R. K. ChingiD, Paul M. ThompsoniD
Abstract
Investigating alterations in brain circuitry associated with bipolar disorder (BD) may offer a valuable approach to discover brain biomarkers for genetic and interventional studies of the disorder and related mental illnesses. Some diffusion MRI studies report evidence of microstructural abnormalities in white matter regions of interest, but we lack a fine-scale spatial mapping of brain microstructural differences along tracts in BD. We also lack large-scale studies that integrate tractometry data from multiple sites, as larger datasets can greatly enhance power to detect subtle effects and assess whether effects replicate across larger international datasets. In this multisite diffusion MRI study, we used BUndle ANalytics (BUAN, Chandio 2020), a recently developed analytic approach for tractography, to extract, map, and visualize profiles of microstructural abnormalities on 3D models of fiber tracts in 148 participants with BD and 259 healthy controls from 6 independent scan sites. Modeling site differences as random effects, we investigated along-tract white matter (WM) microstructural differences between diagnostic groups. QQ plots showed that group differences were gradually enhanced as more sites were added. Using the BUAN pipeline, BD was associated with lower mean fractional anisotropy (FA) in fronto-limbic, interhemispheric, and posterior pathways; higher FA was also noted in posterior bundles, relative to controls. By integrating tractography and anatomical information, BUAN effectively captures unique effects along white matter (WM) tracts, providing valuable insights into anatomical variations that may assist in the classification of diseases.
- organism: human
- assay: multiome
- research focus: differential expression
- research focus: spatial domain detection
- research focus: benchmarking
- research focus: database / resource
- approach: statistical model
- Citations
- 7
- FWCI
- 4.85
- Field percentile
- top 4%
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