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Introduction: Diffusion weighted imaging (DWI) methods can noninvasively ascertain cerebral microstructure by examining pattern and directions of water diffusion in the brain. We calculated heritability for DWI parameters in cerebral white (WM) and gray matter (GM) to study the genetic contribution to the diffusion signals across tissue boundaries.
Methods: Using Old Order Amish (OOA) population isolate with large family pedigrees and high environmental homogeneity, we compared the heritability of measures derived from three representative DWI methods targeting the corpus callosum WM and cingulate gyrus GM: diffusion tensor imaging (DTI), the permeability-diffusivity (PD) model, and the neurite orientation dispersion and density imaging (NODDI) model. These successively more complex models represent the diffusion signal modeling using one, two, and three diffusion compartments, respectively.
Results: We replicated the high heritability of the DTI-based fractional anisotropy (h(2) = 0.67) and radial diffusivity (h(2) = 0.72) in WM. High heritability in both WM and GM tissues were observed for the permeability-diffusivity index from the PD model (h(2) = 0.64 and 0.84), and the neurite density from the NODDI model (h(2) = 0.70 and 0.55). The orientation dispersion index from the NODDI model was only significantly heritable in GM (h(2) = 0.68).
Conclusion: DWI measures from multicompartmental models were significantly heritable in WM and GM. DWI can offer valuable phenotypes for genetic research; and genes thus identified may reveal mechanisms contributing to mental and neurological disorders in which diffusion imaging anomalies are consistently found. Hum Brain Mapp 37:525-535, 2016. © 2015 Wiley Periodicals, Inc.
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http://dx.doi.org/10.1002/hbm.23047 | DOI Listing |
Diffusion MRI (dMRI) is a powerful tool to assess white matter (WM) microstructural abnormalities in Alzheimer's disease (AD). The fourth phase of the Alzheimer's Disease Neuroimaging Initiative (ADNI) now includes multiple multishell dMRI protocols, enabling both traditional and advanced dMRI model analyses. There is a need to evaluate whether multishell data offer deeper insights into WM pathology in AD than more widely available single-shell data by overcoming single-shell model limitations.
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September 2025
Department of Radiology, The First Affiliated Hospital, Sun Yat-sen University, Guangzhou, China.
Background: Ki-67 labelling index (LI), a critical marker of tumor proliferation, is vital for grading adult-type diffuse gliomas and predicting patient survival. However, its accurate assessment currently relies on invasive biopsy or surgical resection. This makes it challenging to non-invasively predict Ki-67 LI and subsequent prognosis.
View Article and Find Full Text PDFEpilepsia
August 2025
Department of Cell, Developmental and Integrative Biology, University of Alabama at Birmingham Heersink School of Medicine, Birmingham, Alabama, USA.
Objective: Studies in temporal lobe epilepsy (TLE) have shown that focal inflammation is a key contributor to seizure initiation and maintenance. However, most in vivo studies to date have focused on positron emission tomography (PET) findings. In this exploratory study, we assessed the relationship between multicompartment Neurite Orientation Dispersion and Density Imaging (NODDI) measures (FISO [extracellular/free water], FICVF [neurite density], and ODI [neurite dispersion]) and peripheral immune cells and inflammatory biomarkers.
View Article and Find Full Text PDFGenom Psychiatry
May 2025
University of Pittsburgh School of Medicine, Department of Psychiatry, Pittsburgh, PA.
There are rapid changes in negative and positive emotionality (NE, PE) and emotional regulation (e.g., soothability) during the first year of life.
View Article and Find Full Text PDFImaging Neurosci (Camb)
February 2025
UCL Centre for Advanced Biomedical Imaging, Division of Medicine, University College London, London, United Kingdom.
Glioblastoma (GBM) is the most common and aggressive brain tumour with starkresistance to available therapies, leading to relapse and a median survival of<15 months. A key cause of therapy resistance is diffuse infiltration oftumour cells into brain regions surrounding the tumour, which presents a majorclinical challenge as existing imaging techniques offer limited detection of theresectable margin. Here, we use diffusion weighted imaging (DWI) and apply themultiple echo time neurite orientation dispersion and density imaging(MTE-NODDI) model as a tool to detect tumour cells in the hard-to-distinguishmargin.
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