Prediction of Chemotherapy Response of Osteosarcoma Using Baseline 18F-FDG Textural Features Machine Learning Approaches with PCA.

Su Young JeongWook KimByung Hyun ByunChang-Bae KongWon Seok SongIlhan LimSang Moo LimSang-Keun Woo

Published in: Contrast media & molecular imaging (2019)

We found that a machine learning approach based on 18F-FDG textural features could predict the chemotherapy response using baseline PET images. This early prediction of the chemotherapy response may aid in determining treatment plans for osteosarcoma patients.

Keyphrases

machine learning
pet ct
pet imaging
positron emission tomography
locally advanced
deep learning
ejection fraction
newly diagnosed
prognostic factors
rectal cancer
convolutional neural network
replacement therapy