Radiomic Phenotypes Distinguish Atypical Teratoid/Rhabdoid Tumors from Medulloblastoma.

Michael Zhang Samuel W Wong S Lummus Michelle Han Alireza Radmanesh Saman Seyed Ahmadian Laura M Prolo Hollie A Lai A Eghbal Ozgur Oztekin Samuel H Cheshier Paul Graham Fisher Chang Y Ho Hannes Vogel Nicholas A Vitanza Robert M Lober Gerald A Grant Alok I Jaju Kristen W Yeom

Published in: AJNR. American journal of neuroradiology (2021)

Six quantitative signatures of image intensity, texture, and morphology distinguish atypical teratoid/rhabdoid tumors from medulloblastomas with high prediction performance across different machine learning strategies. Use of this technique for preoperative diagnosis of atypical teratoid/rhabdoid tumors could significantly inform therapeutic strategies and patient care discussions.

Keyphrases

machine learning
deep learning
patients undergoing
high resolution
magnetic resonance imaging
gene expression
big data
contrast enhanced
mass spectrometry