Texture analysis of apparent diffusion coefficient maps in predicting the clinical functional outcomes of acute ischemic stroke
PurposeTo investigate texture analysis (TA) based on apparent diffusion coefficient (ADC) map in predicting acute ischemic stroke (AIS) prognosis and discriminating TA features in stroke subtypes.MethodsThis retrospective study included patients with AIS between January 2018 and April 2021. The pati...
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| Format: | Article |
| Language: | English |
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Frontiers Media S.A.
2023-05-01
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| Series: | Frontiers in Neurology |
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| Online Access: | https://www.frontiersin.org/articles/10.3389/fneur.2023.1132318/full |
| _version_ | 1797828923290025984 |
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| author | Yi Sun Yuzhong Zhuang Jie Zhu Bin Song Hao Wang |
| author_facet | Yi Sun Yuzhong Zhuang Jie Zhu Bin Song Hao Wang |
| author_sort | Yi Sun |
| collection | DOAJ |
| description | PurposeTo investigate texture analysis (TA) based on apparent diffusion coefficient (ADC) map in predicting acute ischemic stroke (AIS) prognosis and discriminating TA features in stroke subtypes.MethodsThis retrospective study included patients with AIS between January 2018 and April 2021. The patients were assigned to the favorable [modified Rankin Scale (mRS) score ≤ 2] and unfavorable (mRS score > 2) outcome groups. All patients underwent stroke subtyping according to the Trial of Org 10,172 in Acute Stroke Treatment (TOAST) classification. The TA features were extracted from infarction lesions on the ADC map. The demographic characteristics, clinical characteristics, and texture features were used to construct prediction models with recurrent neural network (RNN). The receiver operating characteristic (ROC) curves were implemented to evaluate the performance of the predictive models.ResultsA total of 1,003 patients (682 male; mean age 65.90 ± 12.44) with AIS having documented the 90-day mRS score were identified, including 840 with favorable outcomes. In the validation set, the area under the curve (AUC) of the predictive model using only clinical characteristics achieved an AUC of 0.56, texture model 0.77, the model combining both clinical and texture features showed better with an AUC of 0.78. The texture feature profiles differed between large artery atherosclerosis (LAA) and small artery occlusion (SAO) subtypes (all p < 0.05). The AUC of combined prediction models for LAA and SAO subtypes was 0.80 and 0.81.ConclusionTexture analysis based on ADC map could be useful as an adjunctive tool for predicting ischemic stroke prognosis. |
| first_indexed | 2024-04-09T13:12:11Z |
| format | Article |
| id | doaj.art-3e47423400ab4f62954a672bca862d40 |
| institution | Directory Open Access Journal |
| issn | 1664-2295 |
| language | English |
| last_indexed | 2024-04-09T13:12:11Z |
| publishDate | 2023-05-01 |
| publisher | Frontiers Media S.A. |
| record_format | Article |
| series | Frontiers in Neurology |
| spelling | doaj.art-3e47423400ab4f62954a672bca862d402023-05-12T06:31:23ZengFrontiers Media S.A.Frontiers in Neurology1664-22952023-05-011410.3389/fneur.2023.11323181132318Texture analysis of apparent diffusion coefficient maps in predicting the clinical functional outcomes of acute ischemic strokeYi SunYuzhong ZhuangJie ZhuBin SongHao WangPurposeTo investigate texture analysis (TA) based on apparent diffusion coefficient (ADC) map in predicting acute ischemic stroke (AIS) prognosis and discriminating TA features in stroke subtypes.MethodsThis retrospective study included patients with AIS between January 2018 and April 2021. The patients were assigned to the favorable [modified Rankin Scale (mRS) score ≤ 2] and unfavorable (mRS score > 2) outcome groups. All patients underwent stroke subtyping according to the Trial of Org 10,172 in Acute Stroke Treatment (TOAST) classification. The TA features were extracted from infarction lesions on the ADC map. The demographic characteristics, clinical characteristics, and texture features were used to construct prediction models with recurrent neural network (RNN). The receiver operating characteristic (ROC) curves were implemented to evaluate the performance of the predictive models.ResultsA total of 1,003 patients (682 male; mean age 65.90 ± 12.44) with AIS having documented the 90-day mRS score were identified, including 840 with favorable outcomes. In the validation set, the area under the curve (AUC) of the predictive model using only clinical characteristics achieved an AUC of 0.56, texture model 0.77, the model combining both clinical and texture features showed better with an AUC of 0.78. The texture feature profiles differed between large artery atherosclerosis (LAA) and small artery occlusion (SAO) subtypes (all p < 0.05). The AUC of combined prediction models for LAA and SAO subtypes was 0.80 and 0.81.ConclusionTexture analysis based on ADC map could be useful as an adjunctive tool for predicting ischemic stroke prognosis.https://www.frontiersin.org/articles/10.3389/fneur.2023.1132318/fullischemic strokeradiologydiffusion magnetic resonance imagingtexture analysisprognosis |
| spellingShingle | Yi Sun Yuzhong Zhuang Jie Zhu Bin Song Hao Wang Texture analysis of apparent diffusion coefficient maps in predicting the clinical functional outcomes of acute ischemic stroke Frontiers in Neurology ischemic stroke radiology diffusion magnetic resonance imaging texture analysis prognosis |
| title | Texture analysis of apparent diffusion coefficient maps in predicting the clinical functional outcomes of acute ischemic stroke |
| title_full | Texture analysis of apparent diffusion coefficient maps in predicting the clinical functional outcomes of acute ischemic stroke |
| title_fullStr | Texture analysis of apparent diffusion coefficient maps in predicting the clinical functional outcomes of acute ischemic stroke |
| title_full_unstemmed | Texture analysis of apparent diffusion coefficient maps in predicting the clinical functional outcomes of acute ischemic stroke |
| title_short | Texture analysis of apparent diffusion coefficient maps in predicting the clinical functional outcomes of acute ischemic stroke |
| title_sort | texture analysis of apparent diffusion coefficient maps in predicting the clinical functional outcomes of acute ischemic stroke |
| topic | ischemic stroke radiology diffusion magnetic resonance imaging texture analysis prognosis |
| url | https://www.frontiersin.org/articles/10.3389/fneur.2023.1132318/full |
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