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

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−, 1.75−, 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 cm3, 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.

The Use of Quantitative Imaging in Radiation Oncology: A Quantitative Imaging Network (QIN) Perspective

“…This group reported abnormal pretreatment sMRI volumes predicted for the sites of eventual glioblastoma recurrence, and the retrospective integration of these abnormal volumes (defined at Cho/NAA thresholds of 1.5, 1.75 and 2.0 greater than contralateral white matter) into the original treatment plans would have improved coverage of the recurrent disease (92.4%, 90.5%, and 88.6%, respectively) compared to the original treatment (82.5%) while maintaining dosimetric constraints. [177] An example is shown demonstrating regions of disease recurrence were previously identified by pre-treatment Cho/NAA maps despite not being apparent on the initial T1 post-contrast and/or FLAIR sequences (Fig. 3B).…”

Magnetic resonance spectroscopic imaging in gliomas: clinical diagnosis and radiotherapy planning

“… 57 The metabolic information from MRSI can be added to the information from conventional anatomical MRI, leading to a higher coverage of recurrent contrast-enhancing tumor and a more precise estimation of disease extent. 58 Cordova et al showed that MRSI-based target volume identified significantly different regions of microscopic tumor infiltration than conventional clinical target volumes and exhibited better coverage of contrast-enhancing tumor at recurrence in two out of seven patients. 11 In a multisite pilot study which aimed at establishing feasibility and safety of dose-escalated RT based on metabolic abnormalities in patients with GBM, Gurbani et al developed the Brain Imaging Collaboration Suite which is a cloud platform that combines whole-brain MRSI and MRI data and allows members from different institutions to define RT targets.…”

“… 58 Cordova et al showed that MRSI-based target volume identified significantly different regions of microscopic tumor infiltration than conventional clinical target volumes and exhibited better coverage of contrast-enhancing tumor at recurrence in two out of seven patients. 11 In a multisite pilot study which aimed at establishing feasibility and safety of dose-escalated RT based on metabolic abnormalities in patients with GBM, Gurbani et al developed the Brain Imaging Collaboration Suite which is a cloud platform that combines whole-brain MRSI and MRI data and allows members from different institutions to define RT targets. In their series, they did not detect any severe toxicity in 18 patients treated using targets created in Brain Imaging Collaboration Suite.…”

“…RT target volumes are determined based on MRI. Contrast-enhanced T 1 weighted (CE- T 1 W) sequences are helpful to define the resection cavity 11 whereas the T 2 weighted fluid-attenuated inversion recovery (FLAIR) sequence is helpful to indicate areas of brain alteration from edema or tumor infiltration. However, conventional MRI is limited in certain aspects.…”

The Brain Imaging Collaboration Suite (BrICS): A Cloud Platform for Integrating Whole-Brain Spectroscopic MRI into the Radiation Therapy Planning Workflow

“…However, the use of sMRI in clinical practice has been hampered by data processing requirements and limited integration into the RT planning workflow. In previous studies, several time-intensive manual processing steps were required to import metabolite volumes into clinical imaging software so that they could be used in the operating room or for RT planning (17, 18). To enable integration of sMRI into clinical practice, we have developed a software platform designed specifically for the integration of sMRI into the RT planning workflow.…”