Mohammed Z Goryawala1, Eric A Mellon2, Saumya Gurbani3, Karthik Ramesh3, Brent D Weinberg4, Lawrence Kleinberg5, Eduard Schreibmann3, Sulaiman Sheriff1, Peter B. Barker6, Shu Hui-Kuo7, Hyunsuk Shim3, and Andrew Maudsley8
1Radiology, University of Miami School of Medicine, Miami, FL, United States, 2Radiation Oncology, University of Miami School of Medicine, Miami, FL, United States, 3Emory University, Atlanta, GA, United States, 4Radiology, Emory University, Atlanta, GA, United States, 5Radiation Oncology, Johns Hopkins University, Baltimore, MD, United States, 6Radiology, Johns Hopkins University, Baltimore, MD, United States, 7Radiation Oncology, Emory University, Atlanta, GA, United States, 8Radiology, University of Miami, School of Medicine, Miami, FL, United States
Synopsis
To improve localization of tumor tissue for radiation
treatment planning a volumetric MR spectroscopic imaging acquisition was used to
identify regions of metabolic abnormality. These regions were then integrated
into the clinical treatment plan to target increased radiation dose for the
identified volume. In a 3-site clinical trial of 30 patients with newly-diagnosed
glioblastoma, the escalated dose resulted in a median overall survival of 23
months, which compares favorably with standard of care, without severe adverse
events. This study demonstrates considerable potential for incorporating
volumetric spectroscopic imaging into radiation treatment planning protocols.
Introduction
The standard of care for glioblastoma is neurosurgical
resection followed by radiation therapy (RT) and chemotherapy, with RT planning
based on contrast-enhanced T1 and T2 weighted MRI to target the resection
cavity, enhancing tumor, and surrounding edema. However, MRI alone may not
accurately predict areas at highest recurrence risk and despite aggressive
treatment the length of progression-free survival remains poor. To improve
detection of active tumor regions, this study examined supplementation of the
RT planning with volumetric high-resolution spectroscopic imaging (sMRI) to identify
actively proliferating tumor beyond areas of T1-enhancement for targeting with an
escalated dose. This was done as part of a multisite trial (NCT03137888; Emory
University, Johns Hopkins University, University of Miami).
The main goal of this study was to assess feasibility and
safety of sMRI guided dose escalation RT and to demonstrate and evaluate the
infrastructure developed to support future national level clinical trials.Methods
Previous studies have demonstrated that the choline to
N-acetylaspartate ratio (Cho/NAA) best correlates with tumor cellularity in
surgically resected tissue (ρ=0.82, p< 0.001) and that areas of metabolic
abnormalities predate disease recurrence 1. Maps of Cho/NAA were
obtained following surgical resection and prior to RT in a group of 30 patients
(median age 58, min 20 and max 72) with newly-diagnosed glioblastoma using a
whole-brain volumetric sMRI method with echo-planar readout. Parameters
included 50x50x18 k-space measurements over a FOV of 280x280x180 mm, TR 1.5s,
TE 50 ms, and inversion-recovery lipid suppression with TI=198 ms, sMRI was
reconstructed using MIDAS 2 and maps of individual metabolite
distributions were derived by spectral fitting. Voxels with a fitted linewidth
>13 Hz or outlying spectral intensities (of 4x the value of the mean+standard
deviation of all included voxels) were removed. Example Cho/NAA maps and
spectra are shown in Fig. 1.
sMRI visualization, intensity thresholding and removal of any
outlying voxels remote from the tumor volume were performed using a web-based
imaging platform, BrICS 3. Regions with significant tumor content
were identified using Cho/NAA>2.0, as illustrated in Fig. 2. The resultant sMRI
volume was then exported using DICOM-RT and incorporated into the clinical RT
planning workflow to create a RT plan as illustrated in Fig. 3, that included
an increased dose of 75 Gy in the region of metabolic abnormality and any
residual regions of contrast enhancement.Results
The volumetric sMRI sequence was successfully implemented at
three institutions, with centralized image reconstruction and analysis. Genetic
analysis revealed 7 patients with MGMT methylation and 2 with IDH mutation. No
cases of excessive or unexpected acute toxicity were observed. Late
pseudoprogression was observed in 7 patients requiring surgical assessment
(necrosis vs progressive tumor), which were found in 4 to be predominantly
necrosis.
The median dose escalation volumes for the CE T1w was 1.6 cc
(range 0 to 15.4 cc), while that from the Cho/NAA>2 (GTV3/CTV3) was 19.7 cc
(0.9 to 66.5 cc).
Interim analysis (14 patients still surviving) shows a
median overall survival (OS) of 23 months, Fig. 4, which compares favorably
with standard of care (16 months). Median follow-up of patients that were still
alive at last follow-up was 21.4 months. Our cohort included four patients with
multifocal distant recurrence and one patient with breast cancer metastases,
and a sub-analysis excluding these subjects resulted in an OS of 27.7 months. Conclusion
This study completed enrollment of 30 patients treated with
sMRI-guided dose escalated RT across three institutions. This demonstrated
successful integration of sMRI into the RT planning workflow and delivered
sMRI-guided dose escalated RT plans to glioblastoma patients without severe
adverse events. The overall survival showed considerable improvement relative
to the comparative standard of care. Based on the demonstrated feasibility and
safety it is proposed to further expand the use of sMRI-guided dose-escalated
RT to examine the impact on patient outcomes in a future national level,
randomized clinical trial.Acknowledgements
Support from National Institutes of Health grants
R01CA214557 and F30CA206291. Support for the EPSI sequence and MIDAS processing
was provided by R01EB016064.References
1. Cordova JS, et al. Whole-brain spectroscopic MRI
biomarkers identify infiltrating margins in glioblastoma patients. Neuro Oncol.
2016;18(8):1180-9.
2. http://mrir.med.miami.edu:8000/midas
3. Gurbani S et al. The brain imaging collaboration suite
(BrICS). Tomography. 2019; 5: 184-191.