Radiomics Analysis for Evaluation of Pathological Complete Response to Neoadjuvant Chemoradiotherapy in Locally Advanced Rectal Cancer
Zhenyu Liu,Xiao-Yan Zhang,Yan-Jie Shi,Lin Wang,Hai-Tao Zhu,Zhenchao Tang,Shuo Wang,Xiao-Ting Li,Jie Tian,Ying-Shi Sun +9 more
TLDR
Using pre- and posttreatment MRI data, a radiomics model with excellent performance for individualized, noninvasive prediction of pCR is developed and may be used to identify LARC patients who can omit surgery after chemoradiotherapy.Abstract:
Purpose: To develop and validate a radiomics model for evaluating pathologic complete response (pCR) to neoadjuvant chemoradiotherapy in patients with locally advanced rectal cancer (LARC).Experimental Design: We enrolled 222 patients (152 in the primary cohort and 70 in the validation cohort) with clinicopathologically confirmed LARC who received chemoradiotherapy before surgery. All patients underwent T2-weighted and diffusion-weighted imaging before and after chemoradiotherapy; 2,252 radiomic features were extracted from each patient before and after treatment imaging. The two-sample t test and the least absolute shrinkage and selection operator regression were used for feature selection, whereupon a radiomics signature was built with support vector machines. Multivariable logistic regression analysis was then used to develop a radiomics model incorporating the radiomics signature and independent clinicopathologic risk factors. The performance of the radiomics model was assessed by its calibration, discrimination, and clinical usefulness with independent validation.Results: The radiomics signature comprised 30 selected features and showed good discrimination performance in both the primary and validation cohorts. The individualized radiomics model, which incorporated the radiomics signature and tumor length, also showed good discrimination, with an area under the receiver operating characteristic curve of 0.9756 (95% confidence interval, 0.9185-0.9711) in the validation cohort, and good calibration. Decision curve analysis confirmed the clinical utility of the radiomics model.Conclusions: Using pre- and posttreatment MRI data, we developed a radiomics model with excellent performance for individualized, noninvasive prediction of pCR. This model may be used to identify LARC patients who can omit surgery after chemoradiotherapy. Clin Cancer Res; 23(23); 7253-62. ©2017 AACR.read more
Citations
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Journal ArticleDOI
The Applications of Radiomics in Precision Diagnosis and Treatment of Oncology: Opportunities and Challenges.
Zhenyu Liu,Shuo Wang,Di Dong,Jingwei Wei,Cheng Fang,Xuezhi Zhou,Kai Sun,Longfei Li,Bo Li,Meiyun Wang,Jie Tian,Jie Tian +11 more
TL;DR: The recent methodological developments in radiomics are reviewed, including data acquisition, tumor segmentation, feature extraction, and modelling, as well as the rapidly developing deep learning technology.
Journal ArticleDOI
Radiomics of Multiparametric MRI for Pretreatment Prediction of Pathologic Complete Response to Neoadjuvant Chemotherapy in Breast Cancer: A Multicenter Study.
Zhenyu Liu,Zhuolin Li,Jinrong Qu,Renzhi Zhang,Xuezhi Zhou,Longfei Li,Kai Sun,Zhenchao Tang,Hui Jiang,Hailiang Li,Qianqian Xiong,Yingying Ding,Xinming Zhao,Kun Wang,Zaiyi Liu,Jie Tian +15 more
TL;DR: There is a possibility that RMM provided a potential tool to develop a model for predicting pCR to NAC in breast cancer, and was significantly higher than that of clinical model in two of the three external validation cohorts.
Journal ArticleDOI
Development and validation of an individualized nomogram to identify occult peritoneal metastasis in patients with advanced gastric cancer.
Di Dong,Lei Tang,Zhemin Li,Mengjie Fang,Jianbo Gao,X H Shan,Xiangji Ying,Yi Sun,Jia Fu,X X Wang,L M Li,Zhenhui Li,D F Zhang,Yan Zhang,Z M Li,Fei Shan,Zhaode Bu,Jie Tian,Jie Tian,Jiafu Ji +19 more
TL;DR: CT phenotypes of both primary tumor and nearby peritoneum are significantly associated with occult PM status, and a nomogram of these CT phenotypes and Lauren type has an excellent prediction ability of occult PM, and may have significant clinical implications on early detection of occultPM for AGC.
Journal ArticleDOI
MR Imaging of Rectal Cancer: Radiomics Analysis to Assess Treatment Response after Neoadjuvant Therapy.
Natally Horvat,Harini Veeraraghavan,Monika Khan,Ivana Blazic,Junting Zheng,Marinela Capanu,Evis Sala,Julio Garcia-Aguilar,Marc J. Gollub,Iva Petkovska +9 more
TL;DR: T2- Weighted-based radiomics showed better classification performance compared with qualitative assessment at T2-weighted and DW imaging for diagnosing pCR in patients with locally advanced rectal cancer after CRT.
Journal ArticleDOI
MRI of Rectal Cancer: Tumor Staging, Imaging Techniques, and Management.
TL;DR: In restaging after neoadjuvant CRT, in addition to reassessing the features noted during primary staging, rectal MRI can help in the assessment of treatment response, especially with the emergence of nonsurgical approaches such as "watch and wait."
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