Towards individualized cortical thickness assessment for clinical routine

Abstract Background Cortical thickness measures the width of gray matter of the human cortex. It can be calculated from T1-weighted magnetic resonance images (MRI). In group studies, this measure has been shown to correlate with the diagnosis/prognosis of a number of neurologic and psychiatric condi...

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Main Author: Marlene Tahedl
Format: Article
Language:English
Published: BMC 2020-04-01
Series:Journal of Translational Medicine
Subjects:
Online Access:http://link.springer.com/article/10.1186/s12967-020-02317-9
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spelling doaj-e41459c080754baa9550ee3e642c45092020-11-25T02:58:21ZengBMCJournal of Translational Medicine1479-58762020-04-0118111210.1186/s12967-020-02317-9Towards individualized cortical thickness assessment for clinical routineMarlene Tahedl0Department of Psychiatry and Psychotherapy, University of RegensburgAbstract Background Cortical thickness measures the width of gray matter of the human cortex. It can be calculated from T1-weighted magnetic resonance images (MRI). In group studies, this measure has been shown to correlate with the diagnosis/prognosis of a number of neurologic and psychiatric conditions, but has not been widely adapted for clinical routine. One of the reasons for this might be that there is no reference system which allows to rate individual cortical thickness data with respect to a control population. Methods To address this problem, this study compared different methods to assess statistical significance of cortical thinning, i.e. atrophy. All compared methods were nonparametric and encompassed rating an individual subject’s data set with respect to a control data population. Null distributions were calculated using data from the Human Connectome Project (HCP, n = 1000), and an additional HCP data set (n = 113) was used to calculate sensitivity and specificity to compare the different methods, whereas atrophy was simulated for sensitivity assessment. Validation measures were calculated for the entire cortex (“cumulative”) and distinct brain regions (“regional”) where possible. Results The approach yielding the highest combination of specificity and sensitivity implemented generating null distributions for anatomically distinct brain regions, based on the most extreme values observed in the population. With that method, while regional variations were observed, cumulative specificity of 98.9% and cumulative sensitivity at 80% was achieved for simulated atrophy of 23%. Conclusions This study shows that validated rating of individual cortical thickness measures is possible, which can help clinicians in their daily routine to discover signs of atrophy before they become visually apparent on an unprocessed MRI. Furthermore, given different pathologies present with distinct atrophy patterns, the regional validation proposed here allows to detect distinct patterns of atrophy, which can further enhance differential diagnosis/prognosis.http://link.springer.com/article/10.1186/s12967-020-02317-9Cortical thicknessNeuroimagingMagnetic resonance imaging (MRI)Individual diagnosisAtrophyNeurological assessment
collection DOAJ
language English
format Article
sources DOAJ
author Marlene Tahedl
spellingShingle Marlene Tahedl
Towards individualized cortical thickness assessment for clinical routine
Journal of Translational Medicine
Cortical thickness
Neuroimaging
Magnetic resonance imaging (MRI)
Individual diagnosis
Atrophy
Neurological assessment
author_facet Marlene Tahedl
author_sort Marlene Tahedl
title Towards individualized cortical thickness assessment for clinical routine
title_short Towards individualized cortical thickness assessment for clinical routine
title_full Towards individualized cortical thickness assessment for clinical routine
title_fullStr Towards individualized cortical thickness assessment for clinical routine
title_full_unstemmed Towards individualized cortical thickness assessment for clinical routine
title_sort towards individualized cortical thickness assessment for clinical routine
publisher BMC
series Journal of Translational Medicine
issn 1479-5876
publishDate 2020-04-01
description Abstract Background Cortical thickness measures the width of gray matter of the human cortex. It can be calculated from T1-weighted magnetic resonance images (MRI). In group studies, this measure has been shown to correlate with the diagnosis/prognosis of a number of neurologic and psychiatric conditions, but has not been widely adapted for clinical routine. One of the reasons for this might be that there is no reference system which allows to rate individual cortical thickness data with respect to a control population. Methods To address this problem, this study compared different methods to assess statistical significance of cortical thinning, i.e. atrophy. All compared methods were nonparametric and encompassed rating an individual subject’s data set with respect to a control data population. Null distributions were calculated using data from the Human Connectome Project (HCP, n = 1000), and an additional HCP data set (n = 113) was used to calculate sensitivity and specificity to compare the different methods, whereas atrophy was simulated for sensitivity assessment. Validation measures were calculated for the entire cortex (“cumulative”) and distinct brain regions (“regional”) where possible. Results The approach yielding the highest combination of specificity and sensitivity implemented generating null distributions for anatomically distinct brain regions, based on the most extreme values observed in the population. With that method, while regional variations were observed, cumulative specificity of 98.9% and cumulative sensitivity at 80% was achieved for simulated atrophy of 23%. Conclusions This study shows that validated rating of individual cortical thickness measures is possible, which can help clinicians in their daily routine to discover signs of atrophy before they become visually apparent on an unprocessed MRI. Furthermore, given different pathologies present with distinct atrophy patterns, the regional validation proposed here allows to detect distinct patterns of atrophy, which can further enhance differential diagnosis/prognosis.
topic Cortical thickness
Neuroimaging
Magnetic resonance imaging (MRI)
Individual diagnosis
Atrophy
Neurological assessment
url http://link.springer.com/article/10.1186/s12967-020-02317-9
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