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
Formato:	article
Lenguaje:	EN
Publicado:	Public Library of Science (PLoS) 2014
Materias:	Medicine R Science Q
Acceso en línea:	https://doaj.org/article/f55af06d1d6346efba2208ede3119fec
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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
work_keys_str_mv	AT wieslawlnowinski populationbasedstrokeatlasforoutcomepredictionmethodandpreliminaryresultsforischemicstrokefromct AT varshagupta populationbasedstrokeatlasforoutcomepredictionmethodandpreliminaryresultsforischemicstrokefromct AT guoyuqian populationbasedstrokeatlasforoutcomepredictionmethodandpreliminaryresultsforischemicstrokefromct AT wojciechambrosius populationbasedstrokeatlasforoutcomepredictionmethodandpreliminaryresultsforischemicstrokefromct AT radoslawkazmierski populationbasedstrokeatlasforoutcomepredictionmethodandpreliminaryresultsforischemicstrokefromct
_version_	1718414257227300864

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

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