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Improving the clinical correlation of multiple sclerosis black hole volume change by paired-scan analysis()
The change in T(1)-hypointense lesion (“black hole”) volume is an important marker of pathological progression in multiple sclerosis (MS). Black hole boundaries often have low contrast and are difficult to determine accurately and most (semi‐)automated segmentation methods first compute the T(2)-hyp...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier
2012
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3757731/ https://www.ncbi.nlm.nih.gov/pubmed/24179734 http://dx.doi.org/10.1016/j.nicl.2012.08.004 |
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author | Tam, Roger C. Traboulsee, Anthony Riddehough, Andrew Li, David K.B. |
author_facet | Tam, Roger C. Traboulsee, Anthony Riddehough, Andrew Li, David K.B. |
author_sort | Tam, Roger C. |
collection | PubMed |
description | The change in T(1)-hypointense lesion (“black hole”) volume is an important marker of pathological progression in multiple sclerosis (MS). Black hole boundaries often have low contrast and are difficult to determine accurately and most (semi‐)automated segmentation methods first compute the T(2)-hyperintense lesions, which are a superset of the black holes and are typically more distinct, to form a search space for the T(1)w lesions. Two main potential sources of measurement noise in longitudinal black hole volume computation are partial volume and variability in the T(2)w lesion segmentation. A paired analysis approach is proposed herein that uses registration to equalize partial volume and lesion mask processing to combine T(2)w lesion segmentations across time. The scans of 247 MS patients are used to compare a selected black hole computation method with an enhanced version incorporating paired analysis, using rank correlation to a clinical variable (MS functional composite) as the primary outcome measure. The comparison is done at nine different levels of intensity as a previous study suggests that darker black holes may yield stronger correlations. The results demonstrate that paired analysis can strongly improve longitudinal correlation (from -0.148 to -0.303 in this sample) and may produce segmentations that are more sensitive to clinically relevant changes. |
format | Online Article Text |
id | pubmed-3757731 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2012 |
publisher | Elsevier |
record_format | MEDLINE/PubMed |
spelling | pubmed-37577312013-10-31 Improving the clinical correlation of multiple sclerosis black hole volume change by paired-scan analysis() Tam, Roger C. Traboulsee, Anthony Riddehough, Andrew Li, David K.B. Neuroimage Clin Article The change in T(1)-hypointense lesion (“black hole”) volume is an important marker of pathological progression in multiple sclerosis (MS). Black hole boundaries often have low contrast and are difficult to determine accurately and most (semi‐)automated segmentation methods first compute the T(2)-hyperintense lesions, which are a superset of the black holes and are typically more distinct, to form a search space for the T(1)w lesions. Two main potential sources of measurement noise in longitudinal black hole volume computation are partial volume and variability in the T(2)w lesion segmentation. A paired analysis approach is proposed herein that uses registration to equalize partial volume and lesion mask processing to combine T(2)w lesion segmentations across time. The scans of 247 MS patients are used to compare a selected black hole computation method with an enhanced version incorporating paired analysis, using rank correlation to a clinical variable (MS functional composite) as the primary outcome measure. The comparison is done at nine different levels of intensity as a previous study suggests that darker black holes may yield stronger correlations. The results demonstrate that paired analysis can strongly improve longitudinal correlation (from -0.148 to -0.303 in this sample) and may produce segmentations that are more sensitive to clinically relevant changes. Elsevier 2012-09-05 /pmc/articles/PMC3757731/ /pubmed/24179734 http://dx.doi.org/10.1016/j.nicl.2012.08.004 Text en © 2012 The Authors http://creativecommons.org/licenses/by-nc-sa/3.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution-NonCommercial-ShareAlike License, which permits non-commercial use, distribution, and reproduction in any medium, provided the original author and source are credited. |
spellingShingle | Article Tam, Roger C. Traboulsee, Anthony Riddehough, Andrew Li, David K.B. Improving the clinical correlation of multiple sclerosis black hole volume change by paired-scan analysis() |
title | Improving the clinical correlation of multiple sclerosis black hole volume change by paired-scan analysis() |
title_full | Improving the clinical correlation of multiple sclerosis black hole volume change by paired-scan analysis() |
title_fullStr | Improving the clinical correlation of multiple sclerosis black hole volume change by paired-scan analysis() |
title_full_unstemmed | Improving the clinical correlation of multiple sclerosis black hole volume change by paired-scan analysis() |
title_short | Improving the clinical correlation of multiple sclerosis black hole volume change by paired-scan analysis() |
title_sort | improving the clinical correlation of multiple sclerosis black hole volume change by paired-scan analysis() |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3757731/ https://www.ncbi.nlm.nih.gov/pubmed/24179734 http://dx.doi.org/10.1016/j.nicl.2012.08.004 |
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