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Radiomic ADC Metrics as a Tool to Better Understand Tumor Biology.

作者信息

Reinhold Caroline, Nougaret Stephanie

机构信息

Departments of Radiology and Obstetrics and Gynecology, McGill University Health Centre, Montreal, Canada (C.R.); Augmented Intelligence Precision Laboratory, Department of Radiology, MUHC Research Institute, 1001 Decarie Blvd, Montreal, QC, Canada H4A 3J1 (C.R.); Department of Radiology, Montpellier Cancer Institute, Montpellier, France (S.N.); and IRCM, Institut de Recherche en Cancérologie de Montpellier, INSERM, U1194, Montpellier, France (S.N.).

出版信息

Radiol Imaging Cancer. 2020 May 22;2(3):e200051. doi: 10.1148/rycan.2020200051. eCollection 2020 May.

DOI:10.1148/rycan.2020200051
PMID:33779655
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC7983656/
Abstract
摘要

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本文引用的文献

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Radiol Imaging Cancer. 2020 May 22;2(3):e190085. doi: 10.1148/rycan.2020190085. eCollection 2020 May.
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The Image Biomarker Standardization Initiative: Standardized Quantitative Radiomics for High-Throughput Image-based Phenotyping.影像生物标志物标准化倡议：高通量基于影像表型的标准化定量放射组学。
Radiology. 2020 May;295(2):328-338. doi: 10.1148/radiol.2020191145. Epub 2020 Mar 10.
3
Cancer statistics, 2020.癌症统计数据，2020 年。
CA Cancer J Clin. 2020 Jan;70(1):7-30. doi: 10.3322/caac.21590. Epub 2020 Jan 8.
4
Revised FIGO staging for carcinoma of the cervix uteri.FIGO 修订版子宫颈癌分期。
Int J Gynaecol Obstet. 2019 Apr;145(1):129-135. doi: 10.1002/ijgo.12749. Epub 2019 Jan 17.
5
External validation of a combined PET and MRI radiomics model for prediction of recurrence in cervical cancer patients treated with chemoradiotherapy.基于放化疗的宫颈癌患者复发预测的 PET 和 MRI 联合放射组学模型的外部验证。
Eur J Nucl Med Mol Imaging. 2019 Apr;46(4):864-877. doi: 10.1007/s00259-018-4231-9. Epub 2018 Dec 7.
6
Separation of type and grade in cervical tumours using non-mono-exponential models of diffusion-weighted MRI.使用扩散加权磁共振成像的非单指数模型对宫颈肿瘤进行分型和分级
Eur Radiol. 2017 Feb;27(2):627-636. doi: 10.1007/s00330-016-4417-0. Epub 2016 May 24.
7
Monitoring treatment response in patients undergoing chemoradiotherapy for locally advanced uterine cervical cancer by additional diffusion-weighted imaging: A systematic review.通过额外的扩散加权成像监测局部晚期子宫颈癌患者放化疗的治疗反应：一项系统评价。
J Magn Reson Imaging. 2015 Sep;42(3):572-94. doi: 10.1002/jmri.24784. Epub 2014 Oct 24.
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9
Intra-tumour genetic heterogeneity and poor chemoradiotherapy response in cervical cancer.宫颈癌肿瘤内遗传异质性与化疗放疗反应差。
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