Submit Manuscript  

Article Details


FDG-PET/CT Radiomics Models for The Early Prediction of Locoregional Recurrence in Head and Neck Cancer

Author(s):

Hu Cong, Wang Peng, Zhou Tian, Martin Vallières, Xu Chuanpei, Zhu Aijun* and Zhang Benxin   Pages 1 - 10 ( 10 )

Abstract:


Purpose Both CT and PET radiomics is considered as a potential prognostic biomarker in head and neck cancer. This study investigate the value of fused pre-treatment functional imaging (18F-FDG PET/CT) radiomics for modeling of local recurrence of head and neck cancers.

Material and Methods: Firstly, 298 patients is divided into a training set (n = 192) and verification set (n = 106). Secondly, PETs and CTs are fused based on wavelet transform. Thirdly, radiomics features are extracted from the 3D tumor area from PETCT fusion. The training set is used to select the features reduction and predict local recurrence, and the random forest prediction models combining radiomics and clinical variables are constructed. Finally, the ROC curve and K-M analysis are used to evaluate the prediction efficiency of the model on the validation set.

Results: Two PET / CT fusion radiomics features and three clinic parameters are extracted to construct the radiomics model. AUC value in the verification set 0.70 is better than no fused sets 0.69. The accuracy of 0.66 is not the highest value (0.67). Either consistency index CI 0.70 (from 0.67 to 0.70) or the p-value 0.025 (from 0.03 to 0.025) get the best result in all four models.

Conclusion: The radiomics model based on the fusion of PETCT is better than the model based on PET or CT alone in predicting local recurrence, the inclusion of clinical parameters may result in more accurate predictions, which has certain guiding significance for the development of personalized precise treatment scheme.

Keywords:

Local recurrence, outcome prediction, radiomics, texture analysis, FDG-PET and CT fusion, Head and Neck Cancer

Affiliation:

School of Electronic Engineering and Automation, Guilin University of Electronic Technology, Guilin, School of Electronic Engineering and Automation, Guilin University of Electronic Technology, Guilin, School of Electronic Information and Automation, Guilin University of Aerospace Technology, Guilin, Medical Physics Unit, McGill University, Montreal QC, School of Electronic Engineering and Automation, Guilin University of Electronic Technology, Guilin, School of Electronic Engineering and Automation, Guilin University of Electronic Technology, Guilin, School of Electronic Engineering and Automation, Guilin University of Electronic Technology, Guilin



Read Full-Text article