Population-based Stroke Atlas for outcome prediction: method and preliminary results for ischemic stroke from CT.

<h4>Background and purpose</h4>Knowledge of outcome prediction is important in stroke management. We propose a lesion size and location-driven method for stroke outcome prediction using a Population-based Stroke Atlas (PSA) linking neurological parameters with neuroimaging in population....

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Autores principales: Wieslaw L Nowinski, Varsha Gupta, Guoyu Qian, Wojciech Ambrosius, Radoslaw Kazmierski
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Publicado: Public Library of Science (PLoS) 2014
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spelling oai:doaj.org-article:f55af06d1d6346efba2208ede3119fec2021-11-25T06:04:42ZPopulation-based Stroke Atlas for outcome prediction: method and preliminary results for ischemic stroke from CT.1932-620310.1371/journal.pone.0102048https://doaj.org/article/f55af06d1d6346efba2208ede3119fec2014-01-01T00:00:00Zhttps://www.ncbi.nlm.nih.gov/pmc/articles/pmid/25121979/pdf/?tool=EBIhttps://doaj.org/toc/1932-6203<h4>Background and purpose</h4>Knowledge of outcome prediction is important in stroke management. We propose a lesion size and location-driven method for stroke outcome prediction using a Population-based Stroke Atlas (PSA) linking neurological parameters with neuroimaging in population. The PSA aggregates data from previously treated patients and applies them to currently treated patients. The PSA parameter distribution in the infarct region of a treated patient enables prediction. We introduce a method for PSA calculation, quantify its performance, and use it to illustrate ischemic stroke outcome prediction of modified Rankin Scale (mRS) and Barthel Index (BI).<h4>Methods</h4>The preliminary PSA was constructed from 128 ischemic stroke cases calculated for 8 variants (various data aggregation schemes) and 3 case selection variables (infarct volume, NIHSS at admission, and NIHSS at day 7), each in 4 ranges. Outcome prediction for 9 parameters (mRS at 7th, and mRS and BI at 30th, 90th, 180th, 360th day) was studied using a leave-one-out approach, requiring 589,824 PSA maps to be analyzed.<h4>Results</h4>Outcomes predicted for different PSA variants are statistically equivalent, so the simplest and most efficient variant aiming at parameter averaging is employed. This variant allows the PSA to be pre-calculated before prediction. The PSA constrained by infarct volume and NIHSS reduces the average prediction error (absolute difference between the predicted and actual values) by a fraction of 0.796; the use of 3 patient-specific variables further lowers it by 0.538. The PSA-based prediction error for mild and severe outcomes (mRS  =  [2]-[5]) is (0.5-0.7). Prediction takes about 8 seconds.<h4>Conclusions</h4>PSA-based prediction of individual and group mRS and BI scores over time is feasible, fast and simple, but its clinical usefulness requires further studies. The case selection operation improves PSA predictability. A multiplicity of PSAs can be computed independently for different datasets at various centers and easily merged, which enables building powerful PSAs over the community.Wieslaw L NowinskiVarsha GuptaGuoyu QianWojciech AmbrosiusRadoslaw KazmierskiPublic Library of Science (PLoS)articleMedicineRScienceQENPLoS ONE, Vol 9, Iss 8, p e102048 (2014)
institution DOAJ
collection DOAJ
language EN
topic Medicine
R
Science
Q
spellingShingle Medicine
R
Science
Q
Wieslaw L Nowinski
Varsha Gupta
Guoyu Qian
Wojciech Ambrosius
Radoslaw Kazmierski
Population-based Stroke Atlas for outcome prediction: method and preliminary results for ischemic stroke from CT.
description <h4>Background and purpose</h4>Knowledge of outcome prediction is important in stroke management. We propose a lesion size and location-driven method for stroke outcome prediction using a Population-based Stroke Atlas (PSA) linking neurological parameters with neuroimaging in population. The PSA aggregates data from previously treated patients and applies them to currently treated patients. The PSA parameter distribution in the infarct region of a treated patient enables prediction. We introduce a method for PSA calculation, quantify its performance, and use it to illustrate ischemic stroke outcome prediction of modified Rankin Scale (mRS) and Barthel Index (BI).<h4>Methods</h4>The preliminary PSA was constructed from 128 ischemic stroke cases calculated for 8 variants (various data aggregation schemes) and 3 case selection variables (infarct volume, NIHSS at admission, and NIHSS at day 7), each in 4 ranges. Outcome prediction for 9 parameters (mRS at 7th, and mRS and BI at 30th, 90th, 180th, 360th day) was studied using a leave-one-out approach, requiring 589,824 PSA maps to be analyzed.<h4>Results</h4>Outcomes predicted for different PSA variants are statistically equivalent, so the simplest and most efficient variant aiming at parameter averaging is employed. This variant allows the PSA to be pre-calculated before prediction. The PSA constrained by infarct volume and NIHSS reduces the average prediction error (absolute difference between the predicted and actual values) by a fraction of 0.796; the use of 3 patient-specific variables further lowers it by 0.538. The PSA-based prediction error for mild and severe outcomes (mRS  =  [2]-[5]) is (0.5-0.7). Prediction takes about 8 seconds.<h4>Conclusions</h4>PSA-based prediction of individual and group mRS and BI scores over time is feasible, fast and simple, but its clinical usefulness requires further studies. The case selection operation improves PSA predictability. A multiplicity of PSAs can be computed independently for different datasets at various centers and easily merged, which enables building powerful PSAs over the community.
format article
author Wieslaw L Nowinski
Varsha Gupta
Guoyu Qian
Wojciech Ambrosius
Radoslaw Kazmierski
author_facet Wieslaw L Nowinski
Varsha Gupta
Guoyu Qian
Wojciech Ambrosius
Radoslaw Kazmierski
author_sort Wieslaw L Nowinski
title Population-based Stroke Atlas for outcome prediction: method and preliminary results for ischemic stroke from CT.
title_short Population-based Stroke Atlas for outcome prediction: method and preliminary results for ischemic stroke from CT.
title_full Population-based Stroke Atlas for outcome prediction: method and preliminary results for ischemic stroke from CT.
title_fullStr Population-based Stroke Atlas for outcome prediction: method and preliminary results for ischemic stroke from CT.
title_full_unstemmed Population-based Stroke Atlas for outcome prediction: method and preliminary results for ischemic stroke from CT.
title_sort population-based stroke atlas for outcome prediction: method and preliminary results for ischemic stroke from ct.
publisher Public Library of Science (PLoS)
publishDate 2014
url https://doaj.org/article/f55af06d1d6346efba2208ede3119fec
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AT guoyuqian populationbasedstrokeatlasforoutcomepredictionmethodandpreliminaryresultsforischemicstrokefromct
AT wojciechambrosius populationbasedstrokeatlasforoutcomepredictionmethodandpreliminaryresultsforischemicstrokefromct
AT radoslawkazmierski populationbasedstrokeatlasforoutcomepredictionmethodandpreliminaryresultsforischemicstrokefromct
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