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Radiomics score: a potential prognostic imaging feature for postoperative survival of solitary HCC patients

BACKGROUND: Radiomics is an emerging field in oncological research. In this study, we aimed at developing a radiomics score (rad-score) to estimate postoperative recurrence and survival in patients with solitary hepatocellular carcinoma (HCC). METHODS: A total of 319 solitary HCC patients (training...

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Autores principales: Zheng, Bo-Hao, Liu, Long-Zi, Zhang, Zhi-Zhi, Shi, Jie-Yi, Dong, Liang-Qing, Tian, Ling-Yu, Ding, Zhen-bin, Ji, Yuan, Rao, Sheng-Xiang, Zhou, Jian, Fan, Jia, Wang, Xiao-Ying, Gao, Qiang
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6249916/
https://www.ncbi.nlm.nih.gov/pubmed/30463529
http://dx.doi.org/10.1186/s12885-018-5024-z
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author Zheng, Bo-Hao
Liu, Long-Zi
Zhang, Zhi-Zhi
Shi, Jie-Yi
Dong, Liang-Qing
Tian, Ling-Yu
Ding, Zhen-bin
Ji, Yuan
Rao, Sheng-Xiang
Zhou, Jian
Fan, Jia
Wang, Xiao-Ying
Gao, Qiang
author_facet Zheng, Bo-Hao
Liu, Long-Zi
Zhang, Zhi-Zhi
Shi, Jie-Yi
Dong, Liang-Qing
Tian, Ling-Yu
Ding, Zhen-bin
Ji, Yuan
Rao, Sheng-Xiang
Zhou, Jian
Fan, Jia
Wang, Xiao-Ying
Gao, Qiang
author_sort Zheng, Bo-Hao
collection PubMed
description BACKGROUND: Radiomics is an emerging field in oncological research. In this study, we aimed at developing a radiomics score (rad-score) to estimate postoperative recurrence and survival in patients with solitary hepatocellular carcinoma (HCC). METHODS: A total of 319 solitary HCC patients (training cohort: n = 212; validation cohort: n = 107) were enrolled. Radiomics features were extracted from the artery phase of preoperatively acquired computed tomography (CT) in all patients. A rad-score was generated by using the least absolute shrinkage and selection operator (lasso) logistic model. Kaplan-Meier and Cox’s hazard regression analyses were used to evaluate the prognostic significance of the rad-score. Final nomograms predicting recurrence and survival of solitary HCC patients were established based on the rad-score and clinicopathological factors. C-index and calibration statistics were used to assess the performance of nomograms. RESULTS: Six potential radiomics features were selected out of 110 texture features to formulate the rad-score. Low rad-score positively correlated with aggressive tumor phenotypes, like larger tumor size and vascular invasion. Meanwhile, low rad-score was significantly associated with increased recurrence and reduced survival. In addition, multivariate analysis identified the rad-score as an independent prognostic factor (recurrence: Hazard ratio (HR): 2.472, 95% confident interval (CI): 1.339–4.564, p = 0.004;survival: HR: 1.558, 95%CI: 1.022–2.375, p = 0.039). Notably, the nomogram integrating rad-score had a better prognostic performance as compared with traditional staging systems. These results were further confirmed in the validation cohort. CONCLUSIONS: The preoperative CT image based rad-score was an independent prognostic factor for the postoperative outcome of solitary HCC patients. This score may be complementary to the current staging system and help to stratify individualized treatments for solitary HCC patients. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1186/s12885-018-5024-z) contains supplementary material, which is available to authorized users.
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spelling pubmed-62499162018-11-26 Radiomics score: a potential prognostic imaging feature for postoperative survival of solitary HCC patients Zheng, Bo-Hao Liu, Long-Zi Zhang, Zhi-Zhi Shi, Jie-Yi Dong, Liang-Qing Tian, Ling-Yu Ding, Zhen-bin Ji, Yuan Rao, Sheng-Xiang Zhou, Jian Fan, Jia Wang, Xiao-Ying Gao, Qiang BMC Cancer Research Article BACKGROUND: Radiomics is an emerging field in oncological research. In this study, we aimed at developing a radiomics score (rad-score) to estimate postoperative recurrence and survival in patients with solitary hepatocellular carcinoma (HCC). METHODS: A total of 319 solitary HCC patients (training cohort: n = 212; validation cohort: n = 107) were enrolled. Radiomics features were extracted from the artery phase of preoperatively acquired computed tomography (CT) in all patients. A rad-score was generated by using the least absolute shrinkage and selection operator (lasso) logistic model. Kaplan-Meier and Cox’s hazard regression analyses were used to evaluate the prognostic significance of the rad-score. Final nomograms predicting recurrence and survival of solitary HCC patients were established based on the rad-score and clinicopathological factors. C-index and calibration statistics were used to assess the performance of nomograms. RESULTS: Six potential radiomics features were selected out of 110 texture features to formulate the rad-score. Low rad-score positively correlated with aggressive tumor phenotypes, like larger tumor size and vascular invasion. Meanwhile, low rad-score was significantly associated with increased recurrence and reduced survival. In addition, multivariate analysis identified the rad-score as an independent prognostic factor (recurrence: Hazard ratio (HR): 2.472, 95% confident interval (CI): 1.339–4.564, p = 0.004;survival: HR: 1.558, 95%CI: 1.022–2.375, p = 0.039). Notably, the nomogram integrating rad-score had a better prognostic performance as compared with traditional staging systems. These results were further confirmed in the validation cohort. CONCLUSIONS: The preoperative CT image based rad-score was an independent prognostic factor for the postoperative outcome of solitary HCC patients. This score may be complementary to the current staging system and help to stratify individualized treatments for solitary HCC patients. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1186/s12885-018-5024-z) contains supplementary material, which is available to authorized users. BioMed Central 2018-11-21 /pmc/articles/PMC6249916/ /pubmed/30463529 http://dx.doi.org/10.1186/s12885-018-5024-z Text en © The Author(s). 2018 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
spellingShingle Research Article
Zheng, Bo-Hao
Liu, Long-Zi
Zhang, Zhi-Zhi
Shi, Jie-Yi
Dong, Liang-Qing
Tian, Ling-Yu
Ding, Zhen-bin
Ji, Yuan
Rao, Sheng-Xiang
Zhou, Jian
Fan, Jia
Wang, Xiao-Ying
Gao, Qiang
Radiomics score: a potential prognostic imaging feature for postoperative survival of solitary HCC patients
title Radiomics score: a potential prognostic imaging feature for postoperative survival of solitary HCC patients
title_full Radiomics score: a potential prognostic imaging feature for postoperative survival of solitary HCC patients
title_fullStr Radiomics score: a potential prognostic imaging feature for postoperative survival of solitary HCC patients
title_full_unstemmed Radiomics score: a potential prognostic imaging feature for postoperative survival of solitary HCC patients
title_short Radiomics score: a potential prognostic imaging feature for postoperative survival of solitary HCC patients
title_sort radiomics score: a potential prognostic imaging feature for postoperative survival of solitary hcc patients
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6249916/
https://www.ncbi.nlm.nih.gov/pubmed/30463529
http://dx.doi.org/10.1186/s12885-018-5024-z
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