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Plasma neurofilament light chain (NfL)'s link to dementia may be mediated through white matter integrity (WMI). In this study, we examined plasma NfL's relationships with diffusion tensor magnetic resonance imaging markers: global and cortical white matter fractional anisotropy (FA) and trace (TR). Plasma NfL measurements at 2 times (v 1 : 2004–2009 and v 2 : 2009–2013) and ancillary dMRI (v scan : 2011–2015) were considered (n = 163, mean time v 1 to v scan = 5.4 years and v 2 to v scan : 1.1 years). Multivariable-adjusted regression models, correcting for multiple-testing revealed that, overall, higher NfL v1 was associated with greater global TR (β ± SE: +0.0000560 ± 0.0000186, b = 0.27, p = 0.003, q = 0.012), left frontal WM TR (β ± SE: + 0.0000706 ± 0.0000201, b ± 0.30, p = 0.001, q = 0.0093) and right frontal WM TR (β ± SE: + 0.0000767 ± 0.000021, b ± 0.31, p < 0.001, q = 0.0093). These associations were mainly among males and White adults. Among African American adults only, NfL v2 was associated with greater left temporal lobe TR. "Tracking high" in NfL was associated with reduced left frontal FA (Model 2, body mass index-adjusted: β ± SE:-0.01084 ± 0.00408, p = 0.009). Plasma NfL is a promising biomarker predicting future brain white matter integrity (WMI) in middle-aged adults. [ABSTRACT FROM AUTHOR]

• Greater RDW v1 was associated with poorer WMI, among males only, particularly in terms of lower mean global fractional anisotropy (FA). • No such associations were found for anemia and δRDW (overall or sex-specific), or for RDW exposures among females and the non-anemic group. Anemia (blood hemoglobin [Hb] <13 g/dL among males; <12 g/dL among females) and elevated red cell distribution width (RDW) are potential risk factors for reduced brain white matter integrity (WMI), reflected by lower fractional anisotropy or increased mean diffusivity. Cross-sectional data with exposure-outcome lag time was used, whereby hematological exposures (RDW and Hb) and covariates were compiled from the Healthy Aging in Neighborhoods of Diversity across the Life Span (HANDLS) study with available visit 1 (v 1 ; 2004–2009) and/or v 2 (2009–2013) data; while diffusion tensor magnetic resonance imaging (dMRI) outcome data were collected at HANDLS SCAN visit (v scan : 2011–2015, n = 214, mean follow-up from v 1 ±SD: 5.6 ± 1.8 year). Multivariable-adjusted linear regression analyses were conducted, overall, stratifying by sex, and further restricting to the nonanemic for RDW exposures in part of the analyses. Among males, RDW (v1) was linked with lower global mean fractional anisotropy (standardized effect size b = −0.30, p = 0.003, q < 0.05; basic model), an association only slightly attenuated with further covariate adjustment. Anemia was not a risk factor for poor WMI, independently of RDW. Ultimately, pending further longitudinal evidence, initial RDW appears to be associated with poorer WMI among males. [ABSTRACT FROM AUTHOR]

Pronounced spin phase artifacts appear in diffusion-weighted imaging (DWI) with only minor subject motion. While DWI data corruption is often identified as signal drop out in diffusion-weighted (DW) magnitude images, DW phase images may have higher sensitivity for detecting subtle subject motion. This article describes a novel method to return a metric of subject motion, computed using an image texture analysis of the DW phase image. This Phase Image Texture Analysis for Motion Detection in dMRI (PITA-MDD) method is computationally fast and reliably detects subject motion from diffusion-weighted images. A threshold of the motion metric was identified to remove motion-corrupted slices, and the effect of removing corrupted slices was assessed on the reconstructed FA maps and fiber tracts. Using a motion-metric threshold to remove the motion-corrupted slices results in superior fiber tracts and fractional anisotropy maps. When further compared to a state-of-the-art magnitude-based motion correction method, PITA-MDD was able to detect comparable corrupted slices in a more computationally efficient manner. In this study, we evaluated the use of DW phase images to detect motion corruption. The proposed method can be a robust and fast alternative for automatic motion detection in the brain with multiple applications to inform prospective motion correction or as real-time feedback for data quality control during scanning, as well as after data is already acquired. [ABSTRACT FROM AUTHOR]