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MidRISH: Unbiased harmonization of rotationally invariant harmonics of the diffusion signal
OBJECTIVE: Data harmonization is necessary for removing confounding effects in multi-site diffusion image analysis. One such harmonization method, LinearRISH, scales rotationally invariant spherical harmonic (RISH) features from one site (“target”) to the second (“reference”) to reduce confounding s...
Autores principales: | , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Cold Spring Harbor Laboratory
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10462069/ https://www.ncbi.nlm.nih.gov/pubmed/37645973 http://dx.doi.org/10.1101/2023.08.12.553099 |
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author | Newlin, Nancy R. Kim, Michael E. Kanakaraj, Praitayini Yao, Tianyuan Hohman, Timothy Pechman, Kimberly R. Beason-Held, Lori L. Resnick, Susan M. Archer, Derek Jefferson, Angela Landman, Bennett A. Moyer, Daniel |
author_facet | Newlin, Nancy R. Kim, Michael E. Kanakaraj, Praitayini Yao, Tianyuan Hohman, Timothy Pechman, Kimberly R. Beason-Held, Lori L. Resnick, Susan M. Archer, Derek Jefferson, Angela Landman, Bennett A. Moyer, Daniel |
author_sort | Newlin, Nancy R. |
collection | PubMed |
description | OBJECTIVE: Data harmonization is necessary for removing confounding effects in multi-site diffusion image analysis. One such harmonization method, LinearRISH, scales rotationally invariant spherical harmonic (RISH) features from one site (“target”) to the second (“reference”) to reduce confounding scanner effects. However, reference and target site designations are not arbitrary and resultant diffusion metrics (fractional anisotropy, mean diffusivity) are biased by this choice. In this work we propose MidRISH: rather than scaling reference RISH features to target RISH features, we project both sites to a mid-space. METHODS: We validate MidRISH with the following experiments: harmonizing scanner differences from 37 matched patients free of cognitive impairment, and harmonizing acquisition and study differences on 117 matched patients free of cognitive impairment. CONCLUSION: MidRISH reduces bias of reference selection while preserving harmonization efficacy of LinearRISH. SIGNIFICANCE: Users should be cautious when performing LinearRISH harmonization. To select a reference site is to choose diffusion metric effect-size. Our proposed method eliminates the bias-inducing site selection step. |
format | Online Article Text |
id | pubmed-10462069 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Cold Spring Harbor Laboratory |
record_format | MEDLINE/PubMed |
spelling | pubmed-104620692023-08-29 MidRISH: Unbiased harmonization of rotationally invariant harmonics of the diffusion signal Newlin, Nancy R. Kim, Michael E. Kanakaraj, Praitayini Yao, Tianyuan Hohman, Timothy Pechman, Kimberly R. Beason-Held, Lori L. Resnick, Susan M. Archer, Derek Jefferson, Angela Landman, Bennett A. Moyer, Daniel bioRxiv Article OBJECTIVE: Data harmonization is necessary for removing confounding effects in multi-site diffusion image analysis. One such harmonization method, LinearRISH, scales rotationally invariant spherical harmonic (RISH) features from one site (“target”) to the second (“reference”) to reduce confounding scanner effects. However, reference and target site designations are not arbitrary and resultant diffusion metrics (fractional anisotropy, mean diffusivity) are biased by this choice. In this work we propose MidRISH: rather than scaling reference RISH features to target RISH features, we project both sites to a mid-space. METHODS: We validate MidRISH with the following experiments: harmonizing scanner differences from 37 matched patients free of cognitive impairment, and harmonizing acquisition and study differences on 117 matched patients free of cognitive impairment. CONCLUSION: MidRISH reduces bias of reference selection while preserving harmonization efficacy of LinearRISH. SIGNIFICANCE: Users should be cautious when performing LinearRISH harmonization. To select a reference site is to choose diffusion metric effect-size. Our proposed method eliminates the bias-inducing site selection step. Cold Spring Harbor Laboratory 2023-08-15 /pmc/articles/PMC10462069/ /pubmed/37645973 http://dx.doi.org/10.1101/2023.08.12.553099 Text en https://creativecommons.org/licenses/by-nd/4.0/This work is licensed under a Creative Commons Attribution-NoDerivatives 4.0 International License (https://creativecommons.org/licenses/by-nd/4.0/) , which allows reusers to copy and distribute the material in any medium or format in unadapted form only, and only so long as attribution is given to the creator. The license allows for commercial use. |
spellingShingle | Article Newlin, Nancy R. Kim, Michael E. Kanakaraj, Praitayini Yao, Tianyuan Hohman, Timothy Pechman, Kimberly R. Beason-Held, Lori L. Resnick, Susan M. Archer, Derek Jefferson, Angela Landman, Bennett A. Moyer, Daniel MidRISH: Unbiased harmonization of rotationally invariant harmonics of the diffusion signal |
title | MidRISH: Unbiased harmonization of rotationally invariant harmonics of the diffusion signal |
title_full | MidRISH: Unbiased harmonization of rotationally invariant harmonics of the diffusion signal |
title_fullStr | MidRISH: Unbiased harmonization of rotationally invariant harmonics of the diffusion signal |
title_full_unstemmed | MidRISH: Unbiased harmonization of rotationally invariant harmonics of the diffusion signal |
title_short | MidRISH: Unbiased harmonization of rotationally invariant harmonics of the diffusion signal |
title_sort | midrish: unbiased harmonization of rotationally invariant harmonics of the diffusion signal |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10462069/ https://www.ncbi.nlm.nih.gov/pubmed/37645973 http://dx.doi.org/10.1101/2023.08.12.553099 |
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