Fixel-Based Analysis and Free Water Corrected DTI Evaluation of HIV-Associated Neurocognitive Disorders

Background: White matter (WM) damage is a consistent finding in HIV-infected (HIV+) individuals. Previous studies have evaluated WM fiber tract-specific brain regions in HIV-associated neurocognitive disorders (HAND) using diffusion tensor imaging (DTI). However, DTI might lack an accurate biologica...

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Autores principales:	Alan Finkelstein, Abrar Faiyaz, Miriam T. Weber, Xing Qiu, Md Nasir Uddin, Jianhui Zhong, Giovanni Schifitto
Formato:	article
Lenguaje:	EN
Publicado:	Frontiers Media S.A. 2021
Materias:	HIV diffusion MRI (dMRI) fixel-based analysis free water imaging machine learning cognitive impairment Neurology. Diseases of the nervous system RC346-429
Acceso en línea:	https://doaj.org/article/5235abea075b4787a3481f493c214cd1
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spelling	oai:doaj.org-article:5235abea075b4787a3481f493c214cd12021-11-04T09:17:10ZFixel-Based Analysis and Free Water Corrected DTI Evaluation of HIV-Associated Neurocognitive Disorders1664-229510.3389/fneur.2021.725059https://doaj.org/article/5235abea075b4787a3481f493c214cd12021-11-01T00:00:00Zhttps://www.frontiersin.org/articles/10.3389/fneur.2021.725059/fullhttps://doaj.org/toc/1664-2295Background: White matter (WM) damage is a consistent finding in HIV-infected (HIV+) individuals. Previous studies have evaluated WM fiber tract-specific brain regions in HIV-associated neurocognitive disorders (HAND) using diffusion tensor imaging (DTI). However, DTI might lack an accurate biological interpretation, and the technique suffers from several limitations. Fixel-based analysis (FBA) and free water corrected DTI (fwcDTI) have recently emerged as useful techniques to quantify abnormalities in WM. Here, we sought to evaluate FBA and fwcDTI metrics between HIV+ and healthy controls (HIV−) individuals. Using machine learning classifiers, we compared the specificity of both FBA and fwcDTI metrics in their ability to distinguish between individuals with and without cognitive impairment in HIV+ individuals.Methods: Forty-two HIV+ and 52 HIV– participants underwent MRI exam, clinical, and neuropsychological assessments. FBA metrics included fiber density (FD), fiber bundle cross section (FC), and fiber density and cross section (FDC). We also obtained fwcDTI metrics such as fractional anisotropy (FAT) and mean diffusivity (MDT). Tract-based spatial statistics (TBSS) was performed on FAT and MDT. We evaluated the correlations between MRI metrics with cognitive performance and blood markers, such as neurofilament light chain (NfL), and Tau protein. Four different binary classifiers were used to show the specificity of the MRI metrics for classifying cognitive impairment in HIV+ individuals.Results: Whole-brain FBA showed significant reductions (up to 15%) in various fiber bundles, specifically the cerebral peduncle, posterior limb of internal capsule, middle cerebellar peduncle, and superior corona radiata. TBSS of fwcDTI metrics revealed decreased FAT in HIV+ individuals compared to HIV– individuals in areas consistent with those observed in FBA, but these were not significant. Machine learning classifiers were consistently better able to distinguish between cognitively normal patients and those with cognitive impairment when using fixel-based metrics as input features as compared to fwcDTI metrics.Conclusion: Our findings lend support that FBA may serve as a potential in vivo biomarker for evaluating and monitoring axonal degeneration in HIV+ patients at risk for neurocognitive impairment.Alan FinkelsteinAbrar FaiyazMiriam T. WeberXing QiuMd Nasir UddinJianhui ZhongJianhui ZhongJianhui ZhongGiovanni SchifittoGiovanni SchifittoGiovanni SchifittoFrontiers Media S.A.articleHIVdiffusion MRI (dMRI)fixel-based analysisfree water imagingmachine learningcognitive impairmentNeurology. Diseases of the nervous systemRC346-429ENFrontiers in Neurology, Vol 12 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	HIV diffusion MRI (dMRI) fixel-based analysis free water imaging machine learning cognitive impairment Neurology. Diseases of the nervous system RC346-429
spellingShingle	HIV diffusion MRI (dMRI) fixel-based analysis free water imaging machine learning cognitive impairment Neurology. Diseases of the nervous system RC346-429 Alan Finkelstein Abrar Faiyaz Miriam T. Weber Xing Qiu Md Nasir Uddin Jianhui Zhong Jianhui Zhong Jianhui Zhong Giovanni Schifitto Giovanni Schifitto Giovanni Schifitto Fixel-Based Analysis and Free Water Corrected DTI Evaluation of HIV-Associated Neurocognitive Disorders
description	Background: White matter (WM) damage is a consistent finding in HIV-infected (HIV+) individuals. Previous studies have evaluated WM fiber tract-specific brain regions in HIV-associated neurocognitive disorders (HAND) using diffusion tensor imaging (DTI). However, DTI might lack an accurate biological interpretation, and the technique suffers from several limitations. Fixel-based analysis (FBA) and free water corrected DTI (fwcDTI) have recently emerged as useful techniques to quantify abnormalities in WM. Here, we sought to evaluate FBA and fwcDTI metrics between HIV+ and healthy controls (HIV−) individuals. Using machine learning classifiers, we compared the specificity of both FBA and fwcDTI metrics in their ability to distinguish between individuals with and without cognitive impairment in HIV+ individuals.Methods: Forty-two HIV+ and 52 HIV– participants underwent MRI exam, clinical, and neuropsychological assessments. FBA metrics included fiber density (FD), fiber bundle cross section (FC), and fiber density and cross section (FDC). We also obtained fwcDTI metrics such as fractional anisotropy (FAT) and mean diffusivity (MDT). Tract-based spatial statistics (TBSS) was performed on FAT and MDT. We evaluated the correlations between MRI metrics with cognitive performance and blood markers, such as neurofilament light chain (NfL), and Tau protein. Four different binary classifiers were used to show the specificity of the MRI metrics for classifying cognitive impairment in HIV+ individuals.Results: Whole-brain FBA showed significant reductions (up to 15%) in various fiber bundles, specifically the cerebral peduncle, posterior limb of internal capsule, middle cerebellar peduncle, and superior corona radiata. TBSS of fwcDTI metrics revealed decreased FAT in HIV+ individuals compared to HIV– individuals in areas consistent with those observed in FBA, but these were not significant. Machine learning classifiers were consistently better able to distinguish between cognitively normal patients and those with cognitive impairment when using fixel-based metrics as input features as compared to fwcDTI metrics.Conclusion: Our findings lend support that FBA may serve as a potential in vivo biomarker for evaluating and monitoring axonal degeneration in HIV+ patients at risk for neurocognitive impairment.
format	article
author	Alan Finkelstein Abrar Faiyaz Miriam T. Weber Xing Qiu Md Nasir Uddin Jianhui Zhong Jianhui Zhong Jianhui Zhong Giovanni Schifitto Giovanni Schifitto Giovanni Schifitto
author_facet	Alan Finkelstein Abrar Faiyaz Miriam T. Weber Xing Qiu Md Nasir Uddin Jianhui Zhong Jianhui Zhong Jianhui Zhong Giovanni Schifitto Giovanni Schifitto Giovanni Schifitto
author_sort	Alan Finkelstein
title	Fixel-Based Analysis and Free Water Corrected DTI Evaluation of HIV-Associated Neurocognitive Disorders
title_short	Fixel-Based Analysis and Free Water Corrected DTI Evaluation of HIV-Associated Neurocognitive Disorders
title_full	Fixel-Based Analysis and Free Water Corrected DTI Evaluation of HIV-Associated Neurocognitive Disorders
title_fullStr	Fixel-Based Analysis and Free Water Corrected DTI Evaluation of HIV-Associated Neurocognitive Disorders
title_full_unstemmed	Fixel-Based Analysis and Free Water Corrected DTI Evaluation of HIV-Associated Neurocognitive Disorders
title_sort	fixel-based analysis and free water corrected dti evaluation of hiv-associated neurocognitive disorders
publisher	Frontiers Media S.A.
publishDate	2021
url	https://doaj.org/article/5235abea075b4787a3481f493c214cd1
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Fixel-Based Analysis and Free Water Corrected DTI Evaluation of HIV-Associated Neurocognitive Disorders

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