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Predictive Value of a Combined Model Based on Pre-Treatment and Mid-Treatment MRI-Radiomics for Disease Progression or Death in Locally Advanced Nasopharyngeal Carcinoma.

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机构: [1]Department of Radiation Oncology, Sichuan Cancer Hospital & Institute, Sichuan Cancer Center, School of Medicine, University of Electronic Science and Technology of China, Radiation Oncology Key Laboratory of Sichuan Province, Chengdu, China [2]Department of Hematology and Oncology, Anyue County People’s Hospital, Ziyang, China [3]Graduate School, Chengdu Medical College, Chengdu, China [4]Department of Transplantation Surgery, The Affiliated Hospital of Guizhou Medical University, Guiyang, China [5]University of Southern California, Viterbi School of Engineering Applied Data Science, Los Angeles, CA, United States
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关键词: radiomics nasopharyngeal carcinoma prognosis prediction model magnetic resonance imaging

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A combined model was established based on the MRI-radiomics of pre- and mid-treatment to assess the risk of disease progression or death in locally advanced nasopharyngeal carcinoma.A total of 243 patients were analyzed. We extracted 10,400 radiomics features from the primary nasopharyngeal tumors and largest metastatic lymph nodes on the axial contrast-enhanced T1 weighted and T2 weighted in pre- and mid-treatment MRI, respectively. We used the SMOTE algorithm, center and scale and box-cox, Pearson correlation coefficient, and LASSO regression to construct the pre- and mid-treatment MRI-radiomics prediction model, respectively, and the risk scores named P score and M score were calculated. Finally, univariate and multivariate analyses were used for P score, M score, and clinical data to build the combined model and grouped the patients into two risk levels, namely, high and low.A combined model of pre- and mid-treatment MRI-radiomics successfully categorized patients into high- and low-risk groups. The log-rank test showed that the high- and low-risk groups had good prognostic performance in PFS (P<0.0001, HR: 19.71, 95% CI: 12.77-30.41), which was better than TNM stage (P=0.004, HR:1.913, 95% CI:1.250-2.926), and also had an excellent predictive effect in LRFS, DMFS, and OS.Risk grouping of LA-NPC using a combined model of pre- and mid-treatment MRI-radiomics can better predict disease progression or death.Copyright © 2021 Kang, Niu, Huang, Lin, Tang, Chen, Fan, Lang, Yin and Zhang.

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出版当年[2021]版:
大类 | 3 区 医学
小类 | 3 区 肿瘤学
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大类 | 3 区 医学
小类 | 3 区 肿瘤学
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Q2 ONCOLOGY
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Q2 ONCOLOGY

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第一作者机构: [1]Department of Radiation Oncology, Sichuan Cancer Hospital & Institute, Sichuan Cancer Center, School of Medicine, University of Electronic Science and Technology of China, Radiation Oncology Key Laboratory of Sichuan Province, Chengdu, China [2]Department of Hematology and Oncology, Anyue County People’s Hospital, Ziyang, China [3]Graduate School, Chengdu Medical College, Chengdu, China
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