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Radiomics features from perihematomal edema for prediction of prognosis in the patients with basal ganglia hemorrhage
OBJECTIVE: We developed and validated a clinical-radiomics nomogram to predict the prognosis of basal ganglia hemorrhage patients. METHODS: Retrospective analyses were conducted in 197 patients with basal ganglia hemorrhage (training cohort: n = 136, test cohort: n = 61) who were admitted to The Fir...
Autores principales: | , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9680901/ https://www.ncbi.nlm.nih.gov/pubmed/36425801 http://dx.doi.org/10.3389/fneur.2022.982928 |
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author | Zhou, Peng Sun, Quanye Song, Gesheng Liu, Zexiang Qi, Jianfeng Yuan, Xuhui Wang, Xu Yan, Shaofeng Du, Jianyang Dai, Zhengjun Wang, Jianjun Hu, Shaoshan |
author_facet | Zhou, Peng Sun, Quanye Song, Gesheng Liu, Zexiang Qi, Jianfeng Yuan, Xuhui Wang, Xu Yan, Shaofeng Du, Jianyang Dai, Zhengjun Wang, Jianjun Hu, Shaoshan |
author_sort | Zhou, Peng |
collection | PubMed |
description | OBJECTIVE: We developed and validated a clinical-radiomics nomogram to predict the prognosis of basal ganglia hemorrhage patients. METHODS: Retrospective analyses were conducted in 197 patients with basal ganglia hemorrhage (training cohort: n = 136, test cohort: n = 61) who were admitted to The First Affiliated Hospital of Shandong First Medical University (Shandong Provincial Qianfoshan Hospital) and underwent computed tomography (CT) scan. According to different prognoses, patients with basal ganglia hemorrhage were divided into two groups. Independent clinical risk factors were derived with univariate and multivariate regression analysis. Radiomics signatures were obtained using least absolute shrinkage and selection operator. A radiomics score (Rad-score) was generated by 12 radiomics signatures of perihematomal edema (PHE) from CT images that were correlated with the prognosis of basal ganglia hemorrhage patients. A clinical-radiomics nomogram was conducted by combing the Rad-score and clinical risk factors using logistic regression analysis. The prediction performance of the nomogram was tested in the training cohort and verified in the test cohort. RESULTS: The clinical model conducted by four clinical risk factors and 12 radiomcis features were used to establish the Rad-score. The clinical-radiomics nomogram outperformed the clinical model in the training cohort [area under the curve (AUC), 0.92 vs. 0.85] and the test cohort (AUC, 0.91 vs 0.85). The clinical-radiomics nomogram showed good calibration and clinical benefit in both the training and test cohorts. CONCLUSION: Radiomics features of PHE in patients with basal ganglia hemorrhage could contribute to the outcome prediction. The clinical-radiomics nomogram may help first-line clinicians to make individual clinical treatment decisions for patients with basal ganglia hemorrhage. |
format | Online Article Text |
id | pubmed-9680901 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-96809012022-11-23 Radiomics features from perihematomal edema for prediction of prognosis in the patients with basal ganglia hemorrhage Zhou, Peng Sun, Quanye Song, Gesheng Liu, Zexiang Qi, Jianfeng Yuan, Xuhui Wang, Xu Yan, Shaofeng Du, Jianyang Dai, Zhengjun Wang, Jianjun Hu, Shaoshan Front Neurol Neurology OBJECTIVE: We developed and validated a clinical-radiomics nomogram to predict the prognosis of basal ganglia hemorrhage patients. METHODS: Retrospective analyses were conducted in 197 patients with basal ganglia hemorrhage (training cohort: n = 136, test cohort: n = 61) who were admitted to The First Affiliated Hospital of Shandong First Medical University (Shandong Provincial Qianfoshan Hospital) and underwent computed tomography (CT) scan. According to different prognoses, patients with basal ganglia hemorrhage were divided into two groups. Independent clinical risk factors were derived with univariate and multivariate regression analysis. Radiomics signatures were obtained using least absolute shrinkage and selection operator. A radiomics score (Rad-score) was generated by 12 radiomics signatures of perihematomal edema (PHE) from CT images that were correlated with the prognosis of basal ganglia hemorrhage patients. A clinical-radiomics nomogram was conducted by combing the Rad-score and clinical risk factors using logistic regression analysis. The prediction performance of the nomogram was tested in the training cohort and verified in the test cohort. RESULTS: The clinical model conducted by four clinical risk factors and 12 radiomcis features were used to establish the Rad-score. The clinical-radiomics nomogram outperformed the clinical model in the training cohort [area under the curve (AUC), 0.92 vs. 0.85] and the test cohort (AUC, 0.91 vs 0.85). The clinical-radiomics nomogram showed good calibration and clinical benefit in both the training and test cohorts. CONCLUSION: Radiomics features of PHE in patients with basal ganglia hemorrhage could contribute to the outcome prediction. The clinical-radiomics nomogram may help first-line clinicians to make individual clinical treatment decisions for patients with basal ganglia hemorrhage. Frontiers Media S.A. 2022-11-08 /pmc/articles/PMC9680901/ /pubmed/36425801 http://dx.doi.org/10.3389/fneur.2022.982928 Text en Copyright © 2022 Zhou, Sun, Song, Liu, Qi, Yuan, Wang, Yan, Du, Dai, Wang and Hu. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. |
spellingShingle | Neurology Zhou, Peng Sun, Quanye Song, Gesheng Liu, Zexiang Qi, Jianfeng Yuan, Xuhui Wang, Xu Yan, Shaofeng Du, Jianyang Dai, Zhengjun Wang, Jianjun Hu, Shaoshan Radiomics features from perihematomal edema for prediction of prognosis in the patients with basal ganglia hemorrhage |
title | Radiomics features from perihematomal edema for prediction of prognosis in the patients with basal ganglia hemorrhage |
title_full | Radiomics features from perihematomal edema for prediction of prognosis in the patients with basal ganglia hemorrhage |
title_fullStr | Radiomics features from perihematomal edema for prediction of prognosis in the patients with basal ganglia hemorrhage |
title_full_unstemmed | Radiomics features from perihematomal edema for prediction of prognosis in the patients with basal ganglia hemorrhage |
title_short | Radiomics features from perihematomal edema for prediction of prognosis in the patients with basal ganglia hemorrhage |
title_sort | radiomics features from perihematomal edema for prediction of prognosis in the patients with basal ganglia hemorrhage |
topic | Neurology |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9680901/ https://www.ncbi.nlm.nih.gov/pubmed/36425801 http://dx.doi.org/10.3389/fneur.2022.982928 |
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