MK-Curve improves sensitivity to identify white matter alterations in clinical high risk for psychosis

Diffusion kurtosis imaging (DKI) is a diffusion MRI approach that enables the measurement of brain microstructural properties, reflecting molecular restrictions and tissue heterogeneity. DKI parameters such as mean kurtosis (MK) provide additional subtle information to that provided by popular diffu...

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Main Authors: Fan Zhang, Kang Ik Kevin Cho, Yingying Tang, Tianhong Zhang, Sinead Kelly, Maria Di Biase, Lihua Xu, Huijun Li, Keshevan Matcheri, Susan Whitfield-Gabrieli, Margaret Niznikiewicz, William S. Stone, Jijun Wang, Martha E. Shenton, Ofer Pasternak
Format: Article
Language:English
Published: Elsevier 2021-02-01
Series:NeuroImage
Online Access:http://www.sciencedirect.com/science/article/pii/S1053811920310491
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author Fan Zhang
Kang Ik Kevin Cho
Yingying Tang
Tianhong Zhang
Sinead Kelly
Maria Di Biase
Lihua Xu
Huijun Li
Keshevan Matcheri
Susan Whitfield-Gabrieli
Margaret Niznikiewicz
William S. Stone
Jijun Wang
Martha E. Shenton
Ofer Pasternak
spellingShingle Fan Zhang
Kang Ik Kevin Cho
Yingying Tang
Tianhong Zhang
Sinead Kelly
Maria Di Biase
Lihua Xu
Huijun Li
Keshevan Matcheri
Susan Whitfield-Gabrieli
Margaret Niznikiewicz
William S. Stone
Jijun Wang
Martha E. Shenton
Ofer Pasternak
MK-Curve improves sensitivity to identify white matter alterations in clinical high risk for psychosis
NeuroImage
author_facet Fan Zhang
Kang Ik Kevin Cho
Yingying Tang
Tianhong Zhang
Sinead Kelly
Maria Di Biase
Lihua Xu
Huijun Li
Keshevan Matcheri
Susan Whitfield-Gabrieli
Margaret Niznikiewicz
William S. Stone
Jijun Wang
Martha E. Shenton
Ofer Pasternak
author_sort Fan Zhang
title MK-Curve improves sensitivity to identify white matter alterations in clinical high risk for psychosis
title_short MK-Curve improves sensitivity to identify white matter alterations in clinical high risk for psychosis
title_full MK-Curve improves sensitivity to identify white matter alterations in clinical high risk for psychosis
title_fullStr MK-Curve improves sensitivity to identify white matter alterations in clinical high risk for psychosis
title_full_unstemmed MK-Curve improves sensitivity to identify white matter alterations in clinical high risk for psychosis
title_sort mk-curve improves sensitivity to identify white matter alterations in clinical high risk for psychosis
publisher Elsevier
series NeuroImage
issn 1095-9572
publishDate 2021-02-01
description Diffusion kurtosis imaging (DKI) is a diffusion MRI approach that enables the measurement of brain microstructural properties, reflecting molecular restrictions and tissue heterogeneity. DKI parameters such as mean kurtosis (MK) provide additional subtle information to that provided by popular diffusion tensor imaging (DTI) parameters, and thus have been considered useful to detect white matter abnormalities, especially in populations that are not expected to show severe brain pathologies. However, DKI parameters often yield artifactual output values that are outside of the biologically plausible range, which diminish sensitivity to identify true microstructural changes. Recently we have proposed the mean-kurtosis-curve (MK-Curve) method to correct voxels with implausible DKI parameters, and demonstrated its improved performance against other approaches that correct artifacts in DKI. In this work, we aimed to evaluate the utility of the MK-Curve method to improve the identification of white matter abnormalities in group comparisons. To do so, we compared group differences, with and without the MK-Curve correction, between 115 individuals at clinical high risk for psychosis (CHR) and 93 healthy controls (HCs). We also compared the correlation of the corrected and uncorrected DKI parameters with clinical characteristics. Following the MK-curve correction, the group differences had larger effect sizes and higher statistical significance (i.e., lower p-values), demonstrating increased sensitivity to detect group differences, in particular in MK. Furthermore, the MK-curve-corrected DKI parameters displayed stronger correlations with clinical variables in CHR individuals, demonstrating the clinical relevance of the corrected parameters. Overall, following the MK-curve correction our analyses found widespread lower MK in CHR that overlapped with lower fractional anisotropy (FA), and both measures were significantly correlated with a decline in functioning and with more severe symptoms. These observations further characterize white matter alterations in the CHR stage, demonstrating that MK and FA abnormalities are widespread, and mostly overlap. The improvement in group differences and stronger correlation with clinical variables suggest that applying MK-curve would be beneficial for the detection and characterization of subtle group differences in other experiments as well.
url http://www.sciencedirect.com/science/article/pii/S1053811920310491
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spelling doaj-583e3dc79e7147bba3473af0040ea8632020-12-13T04:18:08ZengElsevierNeuroImage1095-95722021-02-01226117564MK-Curve improves sensitivity to identify white matter alterations in clinical high risk for psychosisFan Zhang0Kang Ik Kevin Cho1Yingying Tang2Tianhong Zhang3Sinead Kelly4Maria Di Biase5Lihua Xu6Huijun Li7Keshevan Matcheri8Susan Whitfield-Gabrieli9Margaret Niznikiewicz10William S. Stone11Jijun Wang12Martha E. Shenton13Ofer Pasternak14Department of Radiology, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USADepartment of Psychiatry, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USAShanghai Key Laboratory of Psychotic Disorders, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, China; Brain Science and Technology Research Center, Shanghai Jiao Tong University, Shanghai, ChinaShanghai Key Laboratory of Psychotic Disorders, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, ChinaDepartment of Psychiatry, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA; The Massachusetts Mental Health Center, Public Psychiatry Division, Beth Israel Deaconess Medical Center, and Harvard Medical School, Boston, MA, USADepartment of Psychiatry, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA; Melbourne Neuropsychiatry Centre, Department of Psychiatry, The University of Melbourne and Melbourne Health, Carlton South, Victoria, AustraliaShanghai Key Laboratory of Psychotic Disorders, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, China; Brain Science and Technology Research Center, Shanghai Jiao Tong University, Shanghai, ChinaDepartment of Psychology, Florida A&M University, Tallahassee, FL,USAThe Massachusetts Mental Health Center, Public Psychiatry Division, Beth Israel Deaconess Medical Center, and Harvard Medical School, Boston, MA, USADepartment of Psychology, Northeastern University, Boston, MA, USA; The McGovern Institute for Brain Research and the Poitras Center for Affective Disorders Research, Massachusetts Institute of Technology, Cambridge, MA, USAThe Department of Psychiatry, Veterans Affairs Boston Healthcare System, Brockton Division, Brockton, MA, USAThe Massachusetts Mental Health Center, Public Psychiatry Division, Beth Israel Deaconess Medical Center, and Harvard Medical School, Boston, MA, USAShanghai Key Laboratory of Psychotic Disorders, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, China; Brain Science and Technology Research Center, Shanghai Jiao Tong University, Shanghai, China; Corresponding author.Department of Psychiatry, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA; Melbourne Neuropsychiatry Centre, Department of Psychiatry, The University of Melbourne and Melbourne Health, Carlton South, Victoria, AustraliaDepartment of Radiology, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA; Department of Psychiatry, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA; Corresponding author.Diffusion kurtosis imaging (DKI) is a diffusion MRI approach that enables the measurement of brain microstructural properties, reflecting molecular restrictions and tissue heterogeneity. DKI parameters such as mean kurtosis (MK) provide additional subtle information to that provided by popular diffusion tensor imaging (DTI) parameters, and thus have been considered useful to detect white matter abnormalities, especially in populations that are not expected to show severe brain pathologies. However, DKI parameters often yield artifactual output values that are outside of the biologically plausible range, which diminish sensitivity to identify true microstructural changes. Recently we have proposed the mean-kurtosis-curve (MK-Curve) method to correct voxels with implausible DKI parameters, and demonstrated its improved performance against other approaches that correct artifacts in DKI. In this work, we aimed to evaluate the utility of the MK-Curve method to improve the identification of white matter abnormalities in group comparisons. To do so, we compared group differences, with and without the MK-Curve correction, between 115 individuals at clinical high risk for psychosis (CHR) and 93 healthy controls (HCs). We also compared the correlation of the corrected and uncorrected DKI parameters with clinical characteristics. Following the MK-curve correction, the group differences had larger effect sizes and higher statistical significance (i.e., lower p-values), demonstrating increased sensitivity to detect group differences, in particular in MK. Furthermore, the MK-curve-corrected DKI parameters displayed stronger correlations with clinical variables in CHR individuals, demonstrating the clinical relevance of the corrected parameters. Overall, following the MK-curve correction our analyses found widespread lower MK in CHR that overlapped with lower fractional anisotropy (FA), and both measures were significantly correlated with a decline in functioning and with more severe symptoms. These observations further characterize white matter alterations in the CHR stage, demonstrating that MK and FA abnormalities are widespread, and mostly overlap. The improvement in group differences and stronger correlation with clinical variables suggest that applying MK-curve would be beneficial for the detection and characterization of subtle group differences in other experiments as well.http://www.sciencedirect.com/science/article/pii/S1053811920310491