Diffusion MRI quality control and functional diffusion map results in ACRIN 6677/RTOG 0625: A multicenter, randomized, phase II trial of bevacizumab and chemotherapy in recurrent glioblastoma

Ellingson,Benjamin M.; Kim,Eunhee; Woodworth,Davis C.; Marques,Helga; Boxerman,Jerrold L.; Safriel,Yair; McKinstry,Robert C.; Bokstein,Felix; Jain,Rajan; Chi,T. Linda; Sorensen,A. Gregory; Gilbert,Mark R.; Barboriak,Daniel P.

doi:10.3892/ijo.2015.2891

Diffusion MRI quality control and functional diffusion map results in ACRIN 6677/RTOG 0625: A multicenter, randomized, phase II trial of bevacizumab and chemotherapy in recurrent glioblastoma

Authors:
- Benjamin M. Ellingson
- Eunhee Kim
- Davis C. Woodworth
- Helga Marques
- Jerrold L. Boxerman
- Yair Safriel
- Robert C. McKinstry
- Felix Bokstein
- Rajan Jain
- T. Linda Chi
- A. Gregory Sorensen
- Mark R. Gilbert
- Daniel P. Barboriak
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Affiliations: UCLA Neuro-Oncology Program, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, USA, Center for Statistical Sciences, Brown University, Providence, RI, USA, Department of Radiological Sciences, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, USA, Department of Diagnostic Imaging, Rhode Island Hospital and Alpert Medical School of Brown University, Providence, RI, USA, Radiology Associates of Clearwater, University of South Florida, Clearwater, FL, USA, Mallinckrodt Institute of Radiology, Washington University in St. Louis, St. Louis, MO, USA, Neuro-Oncology Service, Tel Aviv Sourasky Medical Center, Israel, Departments of Radiology and Neurosurgery, Henry Ford Hospital, Detroit, MI, USA, Department of Diagnostic Radiology, The University of Texas MD Anderson Cancer Center, Houston, TX, USA, A.A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Harvard Medical School, Charlestown, MA, USA, Department of Neuro-Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX, USA, Department of Radiology, Duke University Medical Center, Durham, NC, USA
Published online on: February 11, 2015 https://doi.org/10.3892/ijo.2015.2891
Pages: 1883-1892
Copyright: © Ellingson et al. This is an open access article distributed under the terms of Creative Commons Attribution License [CC BY_NC 3.0].

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Abstract

Functional diffusion mapping (fDM) is a cancer imaging technique that quantifies voxelwise changes in apparent diffusion coefficient (ADC). Previous studies have shown value of fDMs in bevacizumab therapy for recurrent glioblastoma multiforme (GBM). The aim of the present study was to implement explicit criteria for diffusion MRI quality control and independently evaluate fDM performance in a multicenter clinical trial (RTOG 0625/ACRIN 6677). A total of 123 patients were enrolled in the current multicenter trial and signed institutional review board-approved informed consent at their respective institutions. MRI was acquired prior to and 8 weeks following therapy. A 5-point QC scoring system was used to evaluate DWI quality. fDM performance was evaluated according to the correlation of these metrics with PFS and OS at the first follow-up time-point. Results showed ADC variability of 7.3% in NAWM and 10.5% in CSF. A total of 68% of patients had usable DWI data and 47% of patients had high quality DWI data when also excluding patients that progressed before the first follow-up. fDM performance was improved by using only the highest quality DWI. High pre-treatment contrast enhancing tumor volume was associated with shorter PFS and OS. A high volume fraction of increasing ADC after therapy was associated with shorter PFS, while a high volume fraction of decreasing ADC was associated with shorter OS. In summary, DWI in multicenter trials are currently of limited value due to image quality. Improvements in consistency of image quality in multicenter trials are necessary for further advancement of DWI biomarkers.

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1	Dolecek TA, Propp JM, Stroup NE and Kruchko C: CBTRUS statistical report: primary brain and central nervous system tumors diagnosed in the United States in 2005–2009. Neuro Oncol. 14(Suppl 5): v1–v49. 2012. View Article : Google Scholar :
2	Stupp R, Mason WP, van den Bent MJ, et al: Radiotherapy plus concomitant and adjuvant temozolomide for glioblastoma. New Engl J Med. 352:987–996. 2005. View Article : Google Scholar : PubMed/NCBI
3	Weller M, Cloughesy T, Perry JR and Wick W: Standards of care for treatment of recurrent glioblastoma - are we there yet? Neuro Oncol. 15:4–27. 2013. View Article : Google Scholar :
4	Duda DG, Batchelor TT, Willett CG and Jain RK: VEGF-targeted cancer therapy strategies: current progress hurdles and future prospects. Trends Mol Med. 13:223–230. 2007. View Article : Google Scholar : PubMed/NCBI
5	Nghiemphu PL, Liu W, Lee Y, et al: Bevacizumab and chemotherapy for recurrent glioblastoma: a single-institution experience. Neurology. 72:1217–1222. 2009. View Article : Google Scholar : PubMed/NCBI
6	Vredenburgh JJ, Desjardins A, Herndon JE, et al: Phase II trial of bevacizumab and irinotecan in recurrent malignant glioma. Clin Cancer Res. 13:1253–1259. 2007. View Article : Google Scholar : PubMed/NCBI
7	Friedman AH, Prados MD, Wen PY, et al: Bevacizumab alone and in combination with irinotecan in recurrent glioblastoma. J Clin Oncol. 27:4733–4740. 2009. View Article : Google Scholar : PubMed/NCBI
8	Macdonald DR, Cascino TL, Schold SC Jr and Cairncross JG: Response criteria for phase II studies of supratentorial malignant glioma. J Clin Oncol. 8:1277–1280. 1990.PubMed/NCBI
9	Iwamoto FM, Abrey LE, Beal K, et al: Patterns of relapse and prognosis after bevacizumab failure in recurrent glioblastoma. Neurology. 73:1200–1206. 2009. View Article : Google Scholar : PubMed/NCBI
10	Norden AD, Young GS, Setayesh K, et al: Bevacizumab for recurrent malignant gliomas: efficacy, toxicity, and patterns of recurrence. Neurology. 70:779–787. 2008. View Article : Google Scholar : PubMed/NCBI
11	Ellingson BM, Cloughesy TF, Lai A, et al: Graded functional diffusion map-defined characteristics of apparent diffusion coefficients predict overall survival in recurrent glioblastoma treated with bevacizumab. Neuro Oncol. 13:1151–1161. 2011. View Article : Google Scholar : PubMed/NCBI
12	Ellingson BM, Cloughesy TF, Zaw T, et al: Functional diffusion maps (fDMs) evaluated before and after radiochemotherapy predict progression-free and overall survival in newly diagnosed glioblastoma. Neuro Oncol. 14:333–343. 2012. View Article : Google Scholar : PubMed/NCBI
13	Ellingson BM, Malkin MG, Rand SD, et al: Validation of functional diffusion maps (fDMs) as a biomarker for human glioma cellularity. J Magn Reson Imaging. 31:538–548. 2010. View Article : Google Scholar : PubMed/NCBI
14	Wen PY, Macdonald DR, Reardon DA, et al: Updated response assessment criteria for high-grade gliomas: response assessment in neuro-oncology working group. J Clin Oncol. 28:1963–1972. 2010. View Article : Google Scholar : PubMed/NCBI
15	Chenevert TL, Galban CJ, Ivancevic MK, et al: Diffusion coefficient measurement using a temperature-controlled fluid for quality control in multicenter studies. J Magn Reson Imaging. 34:983–987. 2011. View Article : Google Scholar : PubMed/NCBI
16	Hamstra DA, Chenevert TL, Moffat BA, et al: Evaluation of the functional diffusion map as an early biomarker of time-to-progression and overall survival in high-grade glioma. Proc Natl Acad Sci USA. 102:16759–16764. 2005. View Article : Google Scholar : PubMed/NCBI
17	Moffat BA, Chenevert TL, Lawrence TS, et al: Functional diffusion map: a noninvasive MRI biomarker for early stratification of clinical brain tumor response. Proc Natl Acad Sci USA. 102:5524–5529. 2005. View Article : Google Scholar : PubMed/NCBI
18	Ellingson BM, Kim HJ, Woodworth DC, et al: Recurrent glioblastoma treated with bevacizumab: contrast-enhanced T1-weighted subtraction maps improve tumor delineation and aid prediction of survival in a multicenter clinical trial. Radiology. 271:200–210. 2014. View Article : Google Scholar : PubMed/NCBI
19	Padhani AR, Liu G, Koh DM, et al: Diffusion-weighted magnetic resonance imaging as a cancer biomarker: consensus and recommendations. Neoplasia. 11:102–125. 2009.PubMed/NCBI
20	Woodworth DC, Pope WB, Liau LM, et al: Nonlinear distortion correction of diffusion MR images improves quantitative DTI measurements in glioblastoma. J Neurooncol. 116:551–558. 2014. View Article : Google Scholar :
21	Ellingson BM, Cloughesy TF, Lai A, Nghiemphu PL and Pope WB: Nonlinear registration of diffusion-weighted images improves clinical sensitivity of functional diffusion maps in recurrent glioblastoma treated with bevacizumab. Magn Reson Med. 67:237–245. 2012. View Article : Google Scholar