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Simulating the Effect of Spectroscopic MRI As a Metric for Radiation Therapy Planning in Patients with Glioblastoma

Overview
Journal Tomography
Publisher MDPI
Specialty Radiology
Date 2017 Jan 21
PMID 28105468
Citations 19
Authors
Affiliations
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Abstract

Due to glioblastoma's infiltrative nature, an optimal radiation therapy (RT) plan requires targeting infiltration not identified by anatomical magnetic resonance imaging (MRI). Here, high-resolution, whole-brain spectroscopic MRI (sMRI) is used to describe tumor infiltration alongside anatomical MRI and simulate the degree to which it modifies RT target planning. In 11 patients with glioblastoma, data from preRT sMRI scans were processed to give high-resolution, whole-brain metabolite maps normalized by contralateral white matter. Maps depicting choline to N-Acetylaspartate (Cho/NAA) ratios were registered to contrast-enhanced T1-weighted RT planning MRI for each patient. Volumes depicting metabolic abnormalities (1.5-, 1.-, and 2.0-fold increases in Cho/NAA ratios) were compared with conventional target volumes and contrast-enhancing tumor at recurrence. sMRI-modified RT plans were generated to evaluate target volume coverage and organ-at-risk dose constraints. Conventional clinical target volumes and Cho/NAA abnormalities identified significantly different regions of microscopic infiltration with substantial Cho/NAA abnormalities falling outside of the conventional 60 Gy isodose line (41.1, 22.2, and 12.7 cm, respectively). Clinical target volumes using Cho/NAA thresholds exhibited significantly higher coverage of contrast enhancement at recurrence on average (92.4%, 90.5%, and 88.6%, respectively) than conventional plans (82.5%). sMRI-based plans targeting tumor infiltration met planning objectives in all cases with no significant change in target coverage. In 2 cases, the sMRI-modified plan exhibited better coverage of contrast-enhancing tumor at recurrence than the original plan. Integration of the high-resolution, whole-brain sMRI into RT planning is feasible, resulting in RT target volumes that can effectively target tumor infiltration while adhering to conventional constraints.

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References
1.
Farace P, Giri M, Meliado G, Amelio D, Widesott L, Ricciardi G . Clinical target volume delineation in glioblastomas: pre-operative versus post-operative/pre-radiotherapy MRI. Br J Radiol. 2010; 84(999):271-8. PMC: 3473876. DOI: 10.1259/bjr/10315979. View

2.
Guo J, Yao C, Chen H, Zhuang D, Tang W, Ren G . The relationship between Cho/NAA and glioma metabolism: implementation for margin delineation of cerebral gliomas. Acta Neurochir (Wien). 2012; 154(8):1361-70. PMC: 3407558. DOI: 10.1007/s00701-012-1418-x. View

3.
Law M . MR spectroscopy of brain tumors. Top Magn Reson Imaging. 2005; 15(5):291-313. DOI: 10.1097/00002142-200410000-00003. View

4.
di Costanzo A, Scarabino T, Trojsi F, Giannatempo G, Popolizio T, Catapano D . Multiparametric 3T MR approach to the assessment of cerebral gliomas: tumor extent and malignancy. Neuroradiology. 2006; 48(9):622-31. DOI: 10.1007/s00234-006-0102-3. View

5.
Stockmann J, Witzel T, Keil B, Polimeni J, Mareyam A, LaPierre C . A 32-channel combined RF and B0 shim array for 3T brain imaging. Magn Reson Med. 2015; 75(1):441-51. PMC: 4771493. DOI: 10.1002/mrm.25587. View