Voxelwise Prediction of Recurrent High-Grade Glioma via Proximity Estimation-Coupled Multidimensional Support Vector Machine.
Journal
International journal of radiation oncology, biology, physics
ISSN: 1879-355X
Titre abrégé: Int J Radiat Oncol Biol Phys
Pays: United States
ID NLM: 7603616
Informations de publication
Date de publication:
01 04 2022
01 04 2022
Historique:
received:
16
05
2021
revised:
09
12
2021
accepted:
16
12
2021
pubmed:
30
12
2021
medline:
26
4
2022
entrez:
29
12
2021
Statut:
ppublish
Résumé
To provide early and localized glioblastoma (GBM) recurrence prediction, we introduce a novel postsurgery multiparametric magnetic resonance-based support vector machine (SVM) method coupling with stem cell niche (SCN) proximity estimation. This study used postsurgery magnetic resonance imaging (MRI) scans from 50 patients with recurrent GBM, obtained approximately 2 months before clinically diagnosed recurrence. The main prediction pipeline consisted of a proximity-based estimator to identify regions with high risk of recurrence (HRRs) and an SVM classifier to provide voxelwise prediction in HRRs. The HRRs were estimated using the weighted sum of inverse distances to 2 possible origins of recurrence-the SCN and the tumor cavity. Subsequently, multiparametric voxels (from T1, T1 contrast-enhanced, fluid-attenuated inversion recovery, T2, and apparent diffusion coefficient) within the HRR were grouped into recurrent (warped from the clinical diagnosis) and nonrecurrent subregions and fed into the proximity estimation-coupled SVM classifier (SVM On 2-month prerecurrence MRI scans from 30 test cohort patients, the SVM We demonstrated a novel voxelwise early prediction method, SVM
Identifiants
pubmed: 34963559
pii: S0360-3016(21)03425-8
doi: 10.1016/j.ijrobp.2021.12.153
pmc: PMC8923952
mid: NIHMS1773843
pii:
doi:
Types de publication
Journal Article
Research Support, Non-U.S. Gov't
Langues
eng
Sous-ensembles de citation
IM
Pagination
1279-1287Subventions
Organisme : NCATS NIH HHS
ID : KL2 TR001854
Pays : United States
Organisme : NCI NIH HHS
ID : R01 CA188300
Pays : United States
Organisme : NCI NIH HHS
ID : R01 CA259008
Pays : United States
Informations de copyright
Copyright © 2022 Elsevier Inc. All rights reserved.
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