DSA Quantitative Analysis and Predictive Modeling of Obliteration in Cerebral AVM following Stereotactic Radiosurgery.

Mohamed Sobhi Jabal Marwa A Mohammed Cody L Nesvick Kobeissi Hassan Christopher Salvatore Graffeo Bruce E Pollock Brinjikji W

Published in: AJNR. American journal of neuroradiology (2024)

The combination of radiomics with machine learning is a promising approach for predicting cerebral AVM obliteration status following stereotactic radiosurgery. DSA could enhance prognostication of stereotactic radiosurgery-treated AVMs due to its high spatial resolution. Model interpretation is essential for building transparent models and establishing clinically valid radiomic signatures.

Keyphrases

machine learning
subarachnoid hemorrhage
artificial intelligence
brain injury
lymph node metastasis
genome wide
big data
magnetic resonance imaging
gene expression
contrast enhanced
computed tomography
magnetic resonance
deep learning