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Advanced MRI assessment to predict benefit of anti-programmed cell death 1 protein immunotherapy response in patients with recurrent glioblastoma

  • Diagnostic Neuroradiology
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Abstract

Introduction

We describe the imaging findings encountered in GBM patients receiving immune checkpoint blockade and assess the potential of quantitative MRI biomarkers to differentiate patients who derive therapeutic benefit from those who do not.

Methods

A retrospective analysis was performed on longitudinal MRIs obtained on recurrent GBM patients enrolled on clinical trials. Among 10 patients with analyzable data, bidirectional diameters were measured on contrast enhanced T1 (pGd-T1WI) and volumes of interest (VOI) representing measurable abnormality suggestive of tumor were selected on pGdT1WI (pGdT1 VOI), FLAIR-T2WI (FLAIR VOI), and ADC maps. Intermediate ADC (IADC) VOI represented voxels within the FLAIR VOI having ADC in the range of highly cellular tumor (0.7–1.1 × 10−3 mm2/s) (IADC VOI). Therapeutic benefit was determined by tissue pathology and survival on trial. IADC VOI, pGdT1 VOI, FLAIR VOI, and RANO assessment results were correlated with patient benefit.

Results

Five patients were deemed to have received therapeutic benefit and the other five patients did not. The average time on trial for the benefit group was 194 days, as compared to 81 days for the no benefit group. IADC VOI correlated well with the presence or absence of clinical benefit in 10 patients. Furthermore, pGd VOI, FLAIR VOI, and RANO assessment correlated less well with response.

Conclusion

MRI reveals an initial increase in volumes of abnormal tissue with contrast enhancement, edema, and intermediate ADC suggesting hypercellularity within the first 0–6 months of immunotherapy. Subsequent stabilization and improvement in IADC VOI appear to better predict ultimate therapeutic benefit from these agents than conventional imaging.

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Acknowledgments

We thank Annie G. Bryant, Northeastern University, for assistance with the manuscript preparation and submission.

Conflict of interest statement

DAR reports personal fees from AbbVie, personal fees from Bristol Myers Squibb, personal fees from Cavion, grants and personal fees from Celldex, personal fees from Genentech Roche, grants and personal fees from Inovio, personal fees from Juno Pharmaceuticals, personal fees from Merck, grants and personal fees from Midatech, personal fees from Momenta Pharmaceuticals, personal fees from Novartis, personal fees from Novocure, personal fees from Oxigene, personal fees from Regeneron, personal fees from Stemline Therapeutics, and grants from Incyte, outside the submitted work

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Authors and Affiliations

  1. Department of Imaging, Dana-Farber Cancer Institute, Boston, MA, USA

    Lei Qin & Amanda Stroiney

  2. Department of Radiology, Harvard Medical School, Boston, MA, USA

    Lei Qin & Geoffrey S. Young

  3. Department of Radiology, Affiliated Cancer Hospital of Zhengzhou University, Zhengzhou, Henan, China

    Xiang Li & Jinrong Qu

  4. Department of Radiology, Brigham and Women’s Hospital, 75 Francis Street, Boston, MA, 02115, USA

    Xiang Li, Jinrong Qu & Geoffrey S. Young

  5. Department of Behavioral Neuroscience, College of Sciences, Northeastern University, Boston, MA, USA

    Amanda Stroiney

  6. Department of Pathology, Brigham and Women’s Hospital, Boston, MA, USA

    Jeffrey Helgager

  7. CenterforNeuro-Oncology, Dana-Farber Cancer Institute, 44 Binney Street, Boston, MA, 02115, USA

    David A. Reardon

  8. Department of Medicine, Harvard Medical School, Boston, MA, USA

    David A. Reardon

Authors
  1. Lei Qin
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  2. Xiang Li
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  3. Amanda Stroiney
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  4. Jinrong Qu
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  5. Jeffrey Helgager
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  6. David A. Reardon
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  7. Geoffrey S. Young
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Corresponding authors

Correspondence to David A. Reardon or Geoffrey S. Young.

Additional information

LQ and XL contributed equally to this work.

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Qin, L., Li, X., Stroiney, A. et al. Advanced MRI assessment to predict benefit of anti-programmed cell death 1 protein immunotherapy response in patients with recurrent glioblastoma. Neuroradiology 59, 135–145 (2017). https://doi.org/10.1007/s00234-016-1769-8

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  • DOI: https://doi.org/10.1007/s00234-016-1769-8

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