Prediction of infarction volume and infarction growth rate in acute ischemic stroke

Abstract The prediction of infarction volume after stroke onset depends on the shape of the growth dynamics of the infarction. To understand growth patterns that predict lesion volume changes, we studied currently available models described in literature and compared the models with Adaptive Neuro-F...

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Autores principales:	Saadat Kamran, Naveed Akhtar, Ayman Alboudi, Kainat Kamran, Arsalan Ahmad, Jihad Inshasi, Abdul Salam, Ashfaq Shuaib, Uvais Qidwai
Formato:	article
Lenguaje:	EN
Publicado:	Nature Portfolio 2017
Materias:	Medicine R Science Q
Acceso en línea:	https://doaj.org/article/99729aea0b044d8d92be92ee0e9a2e53
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spelling	oai:doaj.org-article:99729aea0b044d8d92be92ee0e9a2e532021-12-02T12:30:19ZPrediction of infarction volume and infarction growth rate in acute ischemic stroke10.1038/s41598-017-08044-42045-2322https://doaj.org/article/99729aea0b044d8d92be92ee0e9a2e532017-08-01T00:00:00Zhttps://doi.org/10.1038/s41598-017-08044-4https://doaj.org/toc/2045-2322Abstract The prediction of infarction volume after stroke onset depends on the shape of the growth dynamics of the infarction. To understand growth patterns that predict lesion volume changes, we studied currently available models described in literature and compared the models with Adaptive Neuro-Fuzzy Inference System [ANFIS], a method previously unused in the prediction of infarction growth and infarction volume (IV). We included 67 patients with malignant middle cerebral artery [MMCA] stroke who underwent decompressive hemicraniectomy. All patients had at least three cranial CT scans prior to the surgery. The rate of growth and volume of infarction measured on the third CT was predicted with ANFIS without statistically significant difference compared to the ground truth [P = 0.489]. This was not possible with linear, logarithmic or exponential methods. ANFIS was able to predict infarction volume [IV3] over a wide range of volume [163.7–600 cm3] and time [22–110 hours]. The cross correlation [CRR] indicated similarity between the ANFIS-predicted IV3 and original data of 82% for ANFIS, followed by logarithmic 70%, exponential 63% and linear 48% respectively. Our study shows that ANFIS is superior to previously defined methods in the prediction of infarction growth rate (IGR) with reasonable accuracy, over wide time and volume range.Saadat KamranNaveed AkhtarAyman AlboudiKainat KamranArsalan AhmadJihad InshasiAbdul SalamAshfaq ShuaibUvais QidwaiNature PortfolioarticleMedicineRScienceQENScientific Reports, Vol 7, Iss 1, Pp 1-8 (2017)
institution	DOAJ
collection	DOAJ
language	EN
topic	Medicine R Science Q
spellingShingle	Medicine R Science Q Saadat Kamran Naveed Akhtar Ayman Alboudi Kainat Kamran Arsalan Ahmad Jihad Inshasi Abdul Salam Ashfaq Shuaib Uvais Qidwai Prediction of infarction volume and infarction growth rate in acute ischemic stroke
description	Abstract The prediction of infarction volume after stroke onset depends on the shape of the growth dynamics of the infarction. To understand growth patterns that predict lesion volume changes, we studied currently available models described in literature and compared the models with Adaptive Neuro-Fuzzy Inference System [ANFIS], a method previously unused in the prediction of infarction growth and infarction volume (IV). We included 67 patients with malignant middle cerebral artery [MMCA] stroke who underwent decompressive hemicraniectomy. All patients had at least three cranial CT scans prior to the surgery. The rate of growth and volume of infarction measured on the third CT was predicted with ANFIS without statistically significant difference compared to the ground truth [P = 0.489]. This was not possible with linear, logarithmic or exponential methods. ANFIS was able to predict infarction volume [IV3] over a wide range of volume [163.7–600 cm3] and time [22–110 hours]. The cross correlation [CRR] indicated similarity between the ANFIS-predicted IV3 and original data of 82% for ANFIS, followed by logarithmic 70%, exponential 63% and linear 48% respectively. Our study shows that ANFIS is superior to previously defined methods in the prediction of infarction growth rate (IGR) with reasonable accuracy, over wide time and volume range.
format	article
author	Saadat Kamran Naveed Akhtar Ayman Alboudi Kainat Kamran Arsalan Ahmad Jihad Inshasi Abdul Salam Ashfaq Shuaib Uvais Qidwai
author_facet	Saadat Kamran Naveed Akhtar Ayman Alboudi Kainat Kamran Arsalan Ahmad Jihad Inshasi Abdul Salam Ashfaq Shuaib Uvais Qidwai
author_sort	Saadat Kamran
title	Prediction of infarction volume and infarction growth rate in acute ischemic stroke
title_short	Prediction of infarction volume and infarction growth rate in acute ischemic stroke
title_full	Prediction of infarction volume and infarction growth rate in acute ischemic stroke
title_fullStr	Prediction of infarction volume and infarction growth rate in acute ischemic stroke
title_full_unstemmed	Prediction of infarction volume and infarction growth rate in acute ischemic stroke
title_sort	prediction of infarction volume and infarction growth rate in acute ischemic stroke
publisher	Nature Portfolio
publishDate	2017
url	https://doaj.org/article/99729aea0b044d8d92be92ee0e9a2e53
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Prediction of infarction volume and infarction growth rate in acute ischemic stroke

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