DSA Quantitative Analysis and Predictive Modeling of Obliteration in Cerebral AVM following Stereotactic Radiosurgery.
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.
Authors
- Marwa A. Mohammed (ORCID: https://orcid.org/0000-0001-5524-369X)
- Mohamed Sobhi Jabal (ORCID: https://orcid.org/0000-0003-2891-8633)
- Bruce E. Pollock (ORCID: https://orcid.org/0000-0002-6148-9079)
- Hassan Kobeissi (ORCID: https://orcid.org/0000-0001-7446-624X)
- Cody L. Nesvick (ORCID: https://orcid.org/0000-0002-2249-5054)
- Waleed Brinjikji (ORCID: https://orcid.org/0000-0001-5271-5524)
- Christopher S. Graffeo (ORCID: https://orcid.org/0000-0001-5314-1067)
Institutions
- Mayo Clinic (US)
- Mayo Clinic in Arizona (US)
- Mayo Clinic in Florida (US)
- University of Pennsylvania (US)
Publication Details
- Journal
- PubMed
- Published
- 2024-10-03
- DOI
- https://doi.org/10.3174/ajnr.a8351
- Citations
- 2
- Primary Topic
- Vascular Malformations Diagnosis and Treatment
- Type
- article
- Field-Weighted Citation Impact
- 0.74