@inproceedings{7a7abcf568dd49bbae397fb78893a9d7,
title = "Radiomics-based malignancy prediction of parotid gland tumor",
abstract = "We have investigated an approach for prediction of parotid gland tumor (PGT) malignancy on preoperative magnetic resonance (MR) images. The PGT regions were segmented on the MR images of 42 patients. A total of 972 radiomic features were extracted from tumor regions in T1- and T2-weighted MR images. Five features were selected as a radiomic biomarker from the 972 features by using a least absolute shrinkage and selection operator (LASSO). Malignancies of PGTs (high grade versus intermediate and low grades) were predicted by using random forest (RF) and k-nearest neighbors (k-NN) with the radiomic biomarker. The proposed approach was evaluated using the accuracy and the mean area under the receiver operating characteristic curve (AUC) based on a leave-one-out cross validation test. The accuracy and AUC of the malignancy prediction of PGTs were 73.8% and 0.88 for the RF and 88.1% and 0.95 for the k-NN, respectively. Our results suggested that the radiomics-based k-NN approach using preoperative MR images could be feasible to predict the malignancy of PGT.",
author = "H. Kamezawa and H. Arimura and R. Yasumatsu and K. Ninomiya and S. Haseai",
note = "Funding Information: This research was supported by JSPS KAKENHI Grant Number JP 17K15808 and “Program for Supporting Educations and Researches on Mathematics and Data Science in Kyushu University”. The authors express their gratitude to all members of the Arimura Laboratory (http://www.shs.kyushu-u.ac.jp/~arimura) for valuable comments and helpful discussions.; International Forum on Medical Imaging in Asia 2019 ; Conference date: 07-01-2019 Through 09-01-2019",
year = "2019",
doi = "10.1117/12.2521362",
language = "English",
series = "Proceedings of SPIE - The International Society for Optical Engineering",
publisher = "SPIE",
editor = "Hiroshi Fujita and Kim, {Jong Hyo} and Feng Lin",
booktitle = "International Forum on Medical Imaging in Asia 2019",
address = "United States",
}