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

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.

Figure 1

Mean ADC estimates for cerebrospinal fluid (CSF) and normal-appearing white matter (NAWM) across different sites, scanner manufacturers, and field strengths. Kruskal-Wallis non-parametric comparisons of CSF and NAWM in sites with 3 or more patients suggested ADC varied significantly by site (P<0.0001), with some sites showing systematically higher or lower ADC values in normal tissues.

Figure 2

Example images for QC scores resulting from varying degrees of geometric distortion in ADC maps. QC score = 5 (great) reflects high-quality diffusion MRI data with no distortions. QC score = 4 (good) reflects mild geometric distortion that does not affect the tumor. QC score = 3 (usable) reflects moderate geometric distortion not affecting the tumor. QC score = 2 (unusable) involves images with moderate distortion that is affecting measurement of the tumor. QC score = 1 (unusable) involves severe distortion that is affecting measurement of the tumor.

Figure 3

Examples of anatomical imaging and fDM response to bevacizumab and irinotecan or temozolomide. (A) This patient demonstrates a small change in enhancing tumor volume, but a relatively large proportion of the tumor with decreasing ADC (blue voxels). (B) This patient shows a similar change in enhancing tumor to the patient in (A), but shows very little change in ADC. (C) A patient with a dramatic change in contrast enhancement following therapy that is not accompanied by a substantial change in ADC. (D) A patient with a decrease in contrast enhancement that involves a large proportion of the tumor with increasing ADC (red voxels). Red voxels = ΔADC >+0.4 μm²/ms; blue voxels = ΔADC <−0.4 μm²/ms; green voxels = −0.4 μm²/ms ≤ΔADC ≤+0.4 μm²/ms.

Figure 4

Pre-treatment contrast enhancing tumor volume and fDM response correlation of progression-free survival (PFS) for usable (QC ≥3) and high quality (QC=5) DWI data. (A) Stratification of PFS based on pre-treatment contrast enhancing volume (T1+C) in patients with usable DWI data (log-rank, P=0.0026). (B) Stratification of PFS based on the volume fraction of enhancing tumor with an increase in ADC [%ADC(+)] in patients with usable DWI data (log-rank, P=0.103). (C) Stratification of PFS based on the volume fraction of enhancing tumor with a decrease in ADC [%ADC(−)] in patients with usable DWI data (log-rank, P=0.166). (D) Stratification of PFS based on T1+C in patients with high quality DWI data (log-rank, P=0.0106). (E) Stratification of PFS based on %ADC(+) evaluated in patients with high quality DWI data (log-rank, P=0.0421). (F) Stratification of PFS based on %ADC(−) evaluated in patients with high quality DWI data (log-rank, P=0.121).

Figure 5

Pre-treatment contrast enhancing tumor volume and fDM response correlation with overall survival (OS) for usable (QC ≥3) and high quality (QC=5) DWI data. (A) Stratification of OS based on pre-treatment contrast enhancing volume (T1+C) in patients with usable DWI data (log-rank, P=0.125). (B) Stratification of OS based on volume fraction of enhancing tumor with an increase in ADC [%ADC(+)] in patients with usable DWI data (log-rank, P=0.158). (C) Stratification of OS based on volume fraction of enhancing tumor with a decrease in ADC [%ADC(−)] in patients with usable DWI data (log-rank, P=0.219). (D) Stratification of OS based on T1+C evaluated for patients with high quality DWI data (log-rank, P=0.099). (E) Stratification of OS based on %ADC(+) in patients with high quality DWI data (log-rank, P=0.668). (F) Stratification of OS based on %ADC(−) evaluated in patients with high quality DWI data (log-rank, P=0.0346).