Relating Acute Lesion Loads to Chronic Outcome in Ischemic Stroke–An Exploratory Comparison of Mismatch Patterns and Predictive Modeling
Objectives: To investigate the relationship between imaging features derived from lesion loads and 3 month clinical assessments in ischemic stroke patients. To support clinically implementable predictive modeling with information from lesion-load features.Methods: A retrospective cohort of ischemic...
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Frontiers Media S.A.
2018-09-01
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Online Access: | https://www.frontiersin.org/article/10.3389/fneur.2018.00737/full |
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Article |
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DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Simon Habegger Roland Wiest Bruno J. Weder Pasquale Mordasini Jan Gralla Levin Häni Simon Jung Simon Jung Mauricio Reyes Richard McKinley |
spellingShingle |
Simon Habegger Roland Wiest Bruno J. Weder Pasquale Mordasini Jan Gralla Levin Häni Simon Jung Simon Jung Mauricio Reyes Richard McKinley Relating Acute Lesion Loads to Chronic Outcome in Ischemic Stroke–An Exploratory Comparison of Mismatch Patterns and Predictive Modeling Frontiers in Neurology stroke recovery lesion load correlation FASTER atlas-based regional image analysis |
author_facet |
Simon Habegger Roland Wiest Bruno J. Weder Pasquale Mordasini Jan Gralla Levin Häni Simon Jung Simon Jung Mauricio Reyes Richard McKinley |
author_sort |
Simon Habegger |
title |
Relating Acute Lesion Loads to Chronic Outcome in Ischemic Stroke–An Exploratory Comparison of Mismatch Patterns and Predictive Modeling |
title_short |
Relating Acute Lesion Loads to Chronic Outcome in Ischemic Stroke–An Exploratory Comparison of Mismatch Patterns and Predictive Modeling |
title_full |
Relating Acute Lesion Loads to Chronic Outcome in Ischemic Stroke–An Exploratory Comparison of Mismatch Patterns and Predictive Modeling |
title_fullStr |
Relating Acute Lesion Loads to Chronic Outcome in Ischemic Stroke–An Exploratory Comparison of Mismatch Patterns and Predictive Modeling |
title_full_unstemmed |
Relating Acute Lesion Loads to Chronic Outcome in Ischemic Stroke–An Exploratory Comparison of Mismatch Patterns and Predictive Modeling |
title_sort |
relating acute lesion loads to chronic outcome in ischemic stroke–an exploratory comparison of mismatch patterns and predictive modeling |
publisher |
Frontiers Media S.A. |
series |
Frontiers in Neurology |
issn |
1664-2295 |
publishDate |
2018-09-01 |
description |
Objectives: To investigate the relationship between imaging features derived from lesion loads and 3 month clinical assessments in ischemic stroke patients. To support clinically implementable predictive modeling with information from lesion-load features.Methods: A retrospective cohort of ischemic stroke patients was studied. The dataset was dichotomized based on revascularization treatment outcome (TICI score). Three lesion delineations were derived from magnetic resonance imaging in each group: two clinically implementable (threshold based and fully automatic prediction) and 90-day follow-up as final groundtruth. Lesion load imaging features were created through overlay of the lesion delineations on a histological brain atlas, and were correlated with the clinical assessment (NIHSS). Significance of the correlations was assessed by constructing confidence intervals using bootstrap sampling.Results: Overall, high correlations between lesion loads and clinical score were observed (up to 0.859). Delineations derived from acute imaging yielded on average somewhat lower correlations than delineations derived from 90-day follow-up imaging. Correlations suggest that both total lesion volume and corticospinal tract lesion load are associated with functional outcome, and in addition highlight other potential areas associated with poor clinical outcome, including the primary somatosensory cortex BA3a. Fully automatic prediction was comparable to ADC threshold-based delineation on the successfully treated cohort and superior to the Tmax threshold-based delineation in the unsuccessfully treated cohort.Conclusions: The confirmation of established predictors for stroke outcome (e.g., corticospinal tract integrity and total lesion volume) gives support to the proposed methodology—relating acute lesion loads to 3 month outcome assessments by way of correlation. Furthermore, the preliminary results indicate an association of further brain regions and structures with three month NIHSS outcome assessments. Hence, prediction models might observe an increased accuracy when incorporating regional (instead of global) lesion loads. Also, the results lend support to the clinical utilization of the automatically predicted volumes from FASTER, rather than the simpler DWI and PWI lesion delineations. |
topic |
stroke recovery lesion load correlation FASTER atlas-based regional image analysis |
url |
https://www.frontiersin.org/article/10.3389/fneur.2018.00737/full |
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doaj-4f7cfba67ebc46eda40bcfba52e858632020-11-24T22:36:36ZengFrontiers Media S.A.Frontiers in Neurology1664-22952018-09-01910.3389/fneur.2018.00737362111Relating Acute Lesion Loads to Chronic Outcome in Ischemic Stroke–An Exploratory Comparison of Mismatch Patterns and Predictive ModelingSimon Habegger0Roland Wiest1Bruno J. Weder2Pasquale Mordasini3Jan Gralla4Levin Häni5Simon Jung6Simon Jung7Mauricio Reyes8Richard McKinley9Support Center for Advanced Neuroimaging, Institute for Diagnostic and Interventional Neuroradiology, Inselspital, University of Bern, Bern, SwitzerlandSupport Center for Advanced Neuroimaging, Institute for Diagnostic and Interventional Neuroradiology, Inselspital, University of Bern, Bern, SwitzerlandSupport Center for Advanced Neuroimaging, Institute for Diagnostic and Interventional Neuroradiology, Inselspital, University of Bern, Bern, SwitzerlandSupport Center for Advanced Neuroimaging, Institute for Diagnostic and Interventional Neuroradiology, Inselspital, University of Bern, Bern, SwitzerlandSupport Center for Advanced Neuroimaging, Institute for Diagnostic and Interventional Neuroradiology, Inselspital, University of Bern, Bern, SwitzerlandDepartment of Neurosurgery, Inselspital, University of Bern, Bern, SwitzerlandDepartment of Neurology, Inselspital, University of Bern, Bern, SwitzerlandNeurovascular Imaging Research Core, Department of Neurology, University of California, Los Angeles, Los Angeles, CA, United StatesInstitute for Surgical Technology and Biomechanics, University of Bern, Bern, SwitzerlandSupport Center for Advanced Neuroimaging, Institute for Diagnostic and Interventional Neuroradiology, Inselspital, University of Bern, Bern, SwitzerlandObjectives: To investigate the relationship between imaging features derived from lesion loads and 3 month clinical assessments in ischemic stroke patients. To support clinically implementable predictive modeling with information from lesion-load features.Methods: A retrospective cohort of ischemic stroke patients was studied. The dataset was dichotomized based on revascularization treatment outcome (TICI score). Three lesion delineations were derived from magnetic resonance imaging in each group: two clinically implementable (threshold based and fully automatic prediction) and 90-day follow-up as final groundtruth. Lesion load imaging features were created through overlay of the lesion delineations on a histological brain atlas, and were correlated with the clinical assessment (NIHSS). Significance of the correlations was assessed by constructing confidence intervals using bootstrap sampling.Results: Overall, high correlations between lesion loads and clinical score were observed (up to 0.859). Delineations derived from acute imaging yielded on average somewhat lower correlations than delineations derived from 90-day follow-up imaging. Correlations suggest that both total lesion volume and corticospinal tract lesion load are associated with functional outcome, and in addition highlight other potential areas associated with poor clinical outcome, including the primary somatosensory cortex BA3a. Fully automatic prediction was comparable to ADC threshold-based delineation on the successfully treated cohort and superior to the Tmax threshold-based delineation in the unsuccessfully treated cohort.Conclusions: The confirmation of established predictors for stroke outcome (e.g., corticospinal tract integrity and total lesion volume) gives support to the proposed methodology—relating acute lesion loads to 3 month outcome assessments by way of correlation. Furthermore, the preliminary results indicate an association of further brain regions and structures with three month NIHSS outcome assessments. Hence, prediction models might observe an increased accuracy when incorporating regional (instead of global) lesion loads. Also, the results lend support to the clinical utilization of the automatically predicted volumes from FASTER, rather than the simpler DWI and PWI lesion delineations.https://www.frontiersin.org/article/10.3389/fneur.2018.00737/fullstroke recoverylesion loadcorrelationFASTERatlas-based regional image analysis |