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Applying a Radiation Therapy Volume Analysis Pipeline to Determine the Utility of Spectroscopic MRI-Guided Adaptive Radiation Therapy for Glioblastoma

Authors :
Anuradha G. Trivedi
Su Hyun Kim
Karthik K. Ramesh
Alexander S. Giuffrida
Brent D. Weinberg
Eric A. Mellon
Lawrence R. Kleinberg
Peter B. Barker
Hui Han
Hui-Kuo G. Shu
Hyunsuk Shim
Eduard Schreibmann
Source :
Tomography, Vol 9, Iss 3, Pp 1052-1061 (2023)
Publication Year :
2023
Publisher :
MDPI AG, 2023.

Abstract

Accurate radiation therapy (RT) targeting is crucial for glioblastoma treatment but may be challenging using clinical imaging alone due to the infiltrative nature of glioblastomas. Precise targeting by whole-brain spectroscopic MRI, which maps tumor metabolites including choline (Cho) and N-acetylaspartate (NAA), can quantify early treatment-induced molecular changes that other traditional modalities cannot measure. We developed a pipeline to determine how spectroscopic MRI changes during early RT are associated with patient outcomes to provide insight into the utility of adaptive RT planning. Data were obtained from a study (NCT03137888) where glioblastoma patients received high-dose RT guided by the pre-RT Cho/NAA twice normal (Cho/NAA ≥ 2x) volume, and received spectroscopic MRI scans pre- and mid-RT. Overlap statistics between pre- and mid-RT scans were used to quantify metabolic activity changes after two weeks of RT. Log-rank tests were used to quantify the relationship between imaging metrics and patient overall and progression-free survival (OS/PFS). Patients with lower Jaccard/Dice coefficients had longer PFS (p = 0.045 for both), and patients with lower Jaccard/Dice coefficients had higher OS trending towards significance (p = 0.060 for both). Cho/NAA ≥ 2x volumes changed significantly during early RT, putting healthy tissue at risk of irradiation, and warranting further study into using adaptive RT planning.

Details

Language :
English
ISSN :
2379139X and 23791381
Volume :
9
Issue :
3
Database :
Directory of Open Access Journals
Journal :
Tomography
Publication Type :
Academic Journal
Accession number :
edsdoj.5e485b96372241f582bdefa0ac6356d7
Document Type :
article
Full Text :
https://doi.org/10.3390/tomography9030086