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Pretreatment MRI-Derived Radiomics May Evaluate the Response of Different Induction Chemotherapy Regimens in Locally advanced Nasopharyngeal Carcinoma. | LitMetric

Pretreatment MRI-Derived Radiomics May Evaluate the Response of Different Induction Chemotherapy Regimens in Locally advanced Nasopharyngeal Carcinoma.

Acad Radiol

Institute of Cancer Research and Basic Medical Sciences of Chinese Academy of Sciences, China; Department of Radiology, Zhejiang Cancer Hospital, Hangzhou, Zhejiang, China; Department of Radiology, Cancer Hospital of the University of Chinese Academy of Sciences, China. Electronic address:

Published: December 2020

AI Article Synopsis

  • The study evaluates how well radiomics can predict the response to two different chemotherapy regimens in patients with advanced nasopharyngeal carcinoma.
  • A total of 265 patients were analyzed, comparing those treated with gemcitabine plus cisplatin (GP) and docetaxel plus cisplatin (TP), using MRI data to extract relevant features.
  • Results showed that the GP regimen had a higher accuracy in predicting treatment response compared to the TP regimen, suggesting that MRI-based radiomics could improve chemotherapy management.

Article Abstract

Rationale And Objectives: To evaluate and compare the performance of radiomics in predicting induction chemotherapy response treated with two different regimens in patients with advanced nasopharyngeal carcinoma.

Materials And Methods: A total of 265 patients with pathologically confirmed locally advanced nasopharyngeal carcinoma (stage II-IV), including 115 treated with gemcitabine plus cisplatin (GP group) and 150 treated with docetaxel plus cisplatin (TP group) were retrospectively enrolled. Radiomics features were extracted from the volume of interest delineated in multi-MR sequences on a 3T scanner. After random stratified grouping (training and validation cohorts) and logistic regression based on selected features, the association between the radiomics signature and the early response to induction chemotherapy were established for GP and TP regiments, respectively.

Results: Clinical factors showed no significant difference between the response and non-response groups for the GP and TP regiments (all p > 0.05). The accuracy of the radiomics signature consisting of selected features from the joint T1, T2, and T1C in the GP group (0.852 in the training cohort vs. 0.853 in the validation cohort) was significantly higher than that in the TP group (0.774 vs 0.727). The overall performance of the GP model was steady, with efficiency to distinguish responders from nonresponders with an AUC reaching 0.907 (95% confidence interval [CI] [0.843-0.970]) in the training cohort and 0.886 (95% CI [0.772-0.998]) in the validation cohort, while leveling at 0.800 (95% CI [0.712-0.888]) in the training cohort and 0.863 (95% CI [0.758-0.967]) in the validation cohort in the TP group.

Conclusion: Pretreatment MR radiomics signature can better predict the early response to IC in the GP regimen than the TP regimen, which may be helpful to guide IC management.

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Source
http://dx.doi.org/10.1016/j.acra.2020.09.002DOI Listing

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