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Radiomics diagnosed histopathological growth pattern in prediction of response and 1-year progression free survival for colorectal liver metastases patients treated with bevacizumab containing chemotherapy.

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机构: [1]Department of Radiology, Peking University People’s Hospital, 11 Xizhimen South St., Beijing 100044, China [2]School of Life Science and Technology, Xidian University, 266 Xinglong Section of Xifeng Road, Xi’an, Shanxi 710126, China [3]Department of Radiology, West China Hospital of Sichuan University, 37 Guoxue Xiang Street, Chengdu, Sichuan Provence 610041, China [4]Department of Radiology, The Sixth Affiliated Hospital of Sun Yat-sen University, Guangzhou 510655, China [5]Key Laboratory of Molecular Imaging, Institute of Automation, Chinese Academy of Sciences, 95 Zhongguancun East Road, Beijing 100190, China [6]Beijing Key Laboratory of Molecular Imaging, Beijing 100190, China [7]Department of Medical Oncology, The Sixth Affiliated Hospital of Sun Yat-sen University, Guangzhou 510655, China [8]Department of Gastrointestinal Surgery, Peking University People’s Hospital, 11 Xizhimen South St., Beijing 100044, China [9]Department of Medical Oncology, Cancer Center, West China Hospital of Sichuan University, 37 Guoxue Xiang Street, Chengdu, Sichuan Provence 610041, China [10]Beijing Advanced Innovation Centre for Big Data-Based Precision Medicine, School of Medicine, Beihang University, Beijing 100191, China [11]Engineering Research Centre of Molecular and Neuro Imaging of Ministry of Education, School of Life Science and Technology, Xidian University, Xi’an 710126, China
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关键词: Histopathologic growth pattern Colorectal liver metastases Unresectable Radiomics Bevacizumab

摘要:
To investigate the capability of a radiomics model, which was designed to identify histopathologic growth pattern (HGP) of colorectal liver metastases (CRLMs) based on contrast-enhanced multidetector computed tomography (ceMDCT), to predict early response and 1-year progression free survival (PFS) in patients treated with bevacizumab-containing chemotherapy.Patients with unresectable CRLMs who were treated with bevacizumab-containing chemotherapy were included in this multicenter retrospective study. For each target lesion, the radiomics-diagnosed HGP (RAD_HGP) of desmoplastic (D) pattern or replacement (R) pattern was determined. Logistic regression and receiver operating characteristic (ROC) curves were used to assess lesion- and patient-based responses according to morphologic response criteria. One-year PFS was calculated using Kaplan-Meier curves. Hazard ratios for 1-year PFS were obtained through Cox proportional hazard regression analysis.Among 119 study patients, 206 D pattern and 140 R pattern lesions were identified. In patients with multiple lesions, 52 had D pattern, 31 had R pattern, and 36 had mixed (D + R) pattern. The area under the curve value for RAD_HGP in predicting early response was 0.707 for lesion-based analysis and 0.720 for patient-based analysis. Patients with D pattern had a significantly longer PFS than patients with R pattern or mixed pattern (P < 0.001). RAD_HGP was the only independent predictor of 1-year PFS.HGP diagnosed using a radiomics model could be used as an effective predictor of PFS for patients with CRLMs treated with bevacizumab-containing chemotherapy.Copyright © 2021 Elsevier B.V. All rights reserved.

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出版当年[2021]版:
大类 | 2 区 医学
小类 | 3 区 核医学
最新[2023]版:
大类 | 3 区 医学
小类 | 3 区 核医学
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出版当年[2021]版:
Q2 RADIOLOGY, NUCLEAR MEDICINE & MEDICAL IMAGING
最新[2023]版:
Q1 RADIOLOGY, NUCLEAR MEDICINE & MEDICAL IMAGING

影响因子: 最新[2023版] 最新五年平均 出版当年[2021版] 出版当年五年平均 出版前一年[2020版] 出版后一年[2022版]

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第一作者机构: [1]Department of Radiology, Peking University People’s Hospital, 11 Xizhimen South St., Beijing 100044, China
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通讯机构: [5]Key Laboratory of Molecular Imaging, Institute of Automation, Chinese Academy of Sciences, 95 Zhongguancun East Road, Beijing 100190, China [6]Beijing Key Laboratory of Molecular Imaging, Beijing 100190, China [10]Beijing Advanced Innovation Centre for Big Data-Based Precision Medicine, School of Medicine, Beihang University, Beijing 100191, China [11]Engineering Research Centre of Molecular and Neuro Imaging of Ministry of Education, School of Life Science and Technology, Xidian University, Xi’an 710126, China
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