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Detecting microstructural deviations in individuals with deep diffusion MRI tractometry

Most diffusion magnetic resonance imaging studies of disease rely on statistical comparisons between large groups of patients and healthy participants to infer altered tissue states in the brain; however, clinical heterogeneity can greatly challenge their discriminative power. There is currently an...

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Autores principales: Chamberland, Maxime, Genc, Sila, Tax, Chantal M. W., Shastin, Dmitri, Koller, Kristin, Raven, Erika P., Cunningham, Adam, Doherty, Joanne, van den Bree, Marianne B. M., Parker, Greg D., Hamandi, Khalid, Gray, William P., Jones, Derek K.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7613101/
https://www.ncbi.nlm.nih.gov/pubmed/35865756
http://dx.doi.org/10.1038/s43588-021-00126-8
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author Chamberland, Maxime
Genc, Sila
Tax, Chantal M. W.
Shastin, Dmitri
Koller, Kristin
Raven, Erika P.
Cunningham, Adam
Doherty, Joanne
van den Bree, Marianne B. M.
Parker, Greg D.
Hamandi, Khalid
Gray, William P.
Jones, Derek K.
author_facet Chamberland, Maxime
Genc, Sila
Tax, Chantal M. W.
Shastin, Dmitri
Koller, Kristin
Raven, Erika P.
Cunningham, Adam
Doherty, Joanne
van den Bree, Marianne B. M.
Parker, Greg D.
Hamandi, Khalid
Gray, William P.
Jones, Derek K.
author_sort Chamberland, Maxime
collection PubMed
description Most diffusion magnetic resonance imaging studies of disease rely on statistical comparisons between large groups of patients and healthy participants to infer altered tissue states in the brain; however, clinical heterogeneity can greatly challenge their discriminative power. There is currently an unmet need to move away from the current approach of group-wise comparisons to methods with the sensitivity to detect altered tissue states at the individual level. This would ultimately enable the early detection and interpretation of microstructural abnormalities in individual patients, an important step towards personalized medicine in translational imaging. To this end, Detect was developed to advance diffusion magnetic resonance imaging tractometry towards single-patient analysis. By operating on the manifold of white-matter pathways and learning normative microstructural features, our framework captures idiosyncrasies in patterns along white-matter pathways. Our approach paves the way from traditional group-based comparisons to true personalized radiology, taking microstructural imaging from the bench to the bedside.
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spelling pubmed-76131012022-07-20 Detecting microstructural deviations in individuals with deep diffusion MRI tractometry Chamberland, Maxime Genc, Sila Tax, Chantal M. W. Shastin, Dmitri Koller, Kristin Raven, Erika P. Cunningham, Adam Doherty, Joanne van den Bree, Marianne B. M. Parker, Greg D. Hamandi, Khalid Gray, William P. Jones, Derek K. Nat Comput Sci Article Most diffusion magnetic resonance imaging studies of disease rely on statistical comparisons between large groups of patients and healthy participants to infer altered tissue states in the brain; however, clinical heterogeneity can greatly challenge their discriminative power. There is currently an unmet need to move away from the current approach of group-wise comparisons to methods with the sensitivity to detect altered tissue states at the individual level. This would ultimately enable the early detection and interpretation of microstructural abnormalities in individual patients, an important step towards personalized medicine in translational imaging. To this end, Detect was developed to advance diffusion magnetic resonance imaging tractometry towards single-patient analysis. By operating on the manifold of white-matter pathways and learning normative microstructural features, our framework captures idiosyncrasies in patterns along white-matter pathways. Our approach paves the way from traditional group-based comparisons to true personalized radiology, taking microstructural imaging from the bench to the bedside. 2021-09 2021-09-22 /pmc/articles/PMC7613101/ /pubmed/35865756 http://dx.doi.org/10.1038/s43588-021-00126-8 Text en https://creativecommons.org/licenses/by/4.0/This work is licensed under a CC BY 4.0 (https://creativecommons.org/licenses/by/4.0/) International license.
spellingShingle Article
Chamberland, Maxime
Genc, Sila
Tax, Chantal M. W.
Shastin, Dmitri
Koller, Kristin
Raven, Erika P.
Cunningham, Adam
Doherty, Joanne
van den Bree, Marianne B. M.
Parker, Greg D.
Hamandi, Khalid
Gray, William P.
Jones, Derek K.
Detecting microstructural deviations in individuals with deep diffusion MRI tractometry
title Detecting microstructural deviations in individuals with deep diffusion MRI tractometry
title_full Detecting microstructural deviations in individuals with deep diffusion MRI tractometry
title_fullStr Detecting microstructural deviations in individuals with deep diffusion MRI tractometry
title_full_unstemmed Detecting microstructural deviations in individuals with deep diffusion MRI tractometry
title_short Detecting microstructural deviations in individuals with deep diffusion MRI tractometry
title_sort detecting microstructural deviations in individuals with deep diffusion mri tractometry
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7613101/
https://www.ncbi.nlm.nih.gov/pubmed/35865756
http://dx.doi.org/10.1038/s43588-021-00126-8
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