Perfusion and diffusion MRI signatures in histologic and genetic subtypes of WHO grade II-III diffuse gliomas

Kevin Leu; Garrett A Ott; Albert Lai; Phioanh L Nghiemphu; Whitney B Pope; William H Yong; Linda M Liau; Timothy F Cloughesy; Benjamin M Ellingson

doi:10.1007/s11060-017-2506-9

Perfusion and diffusion MRI signatures in histologic and genetic subtypes of WHO grade II-III diffuse gliomas

J Neurooncol. 2017 Aug;134(1):177-188. doi: 10.1007/s11060-017-2506-9. Epub 2017 May 25.

Authors

Kevin Leu^{1

2

3}, Garrett A Ott^{1

2}, Albert Lai^{4

5}, Phioanh L Nghiemphu^{4

5}, Whitney B Pope², William H Yong⁶, Linda M Liau⁷, Timothy F Cloughesy^{4

5}, Benjamin M Ellingson^{8

9

10

11

12

13}

Affiliations

¹ UCLA Brain Tumor Imaging Laboratory (BTIL), Center for Computer Vision and Imaging Biomarkers, University of California, Los Angeles, Los Angeles, CA, USA.
² Department of Radiological Sciences, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA.
³ Department of Bioengineering, Henry Samueli School of Engineering and Applied Science, University of California, Los Angeles, Los Angeles, CA, USA.
⁴ UCLA Neuro-Oncology Program, University of California, Los Angeles, Los Angeles, CA, USA.
⁵ Department of Neurology, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA.
⁶ Department of Pathology and Laboratory Medicine, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA.
⁷ Department of Neurosurgery, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA.
⁸ UCLA Brain Tumor Imaging Laboratory (BTIL), Center for Computer Vision and Imaging Biomarkers, University of California, Los Angeles, Los Angeles, CA, USA. bellingson@mednet.ucla.edu.
⁹ Department of Radiological Sciences, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA. bellingson@mednet.ucla.edu.
¹⁰ Department of Bioengineering, Henry Samueli School of Engineering and Applied Science, University of California, Los Angeles, Los Angeles, CA, USA. bellingson@mednet.ucla.edu.
¹¹ UCLA Neuro-Oncology Program, University of California, Los Angeles, Los Angeles, CA, USA. bellingson@mednet.ucla.edu.
¹² Department of Biomedical Physics, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA. bellingson@mednet.ucla.edu.
¹³ Departments of Radiological Sciences and Psychiatry, David Geffen School of Medicine, University of California, Los Angeles, 924 Westwood Blvd, Suite 615, Los Angeles, CA, 90024, USA. bellingson@mednet.ucla.edu.

Abstract

The value of perfusion and diffusion-weighted MRI in differentiating histological subtypes according to the 2007 WHO glioma classification scheme (i.e. astrocytoma vs. oligodendroglioma) and genetic subtypes according to the 2016 WHO reclassification (e.g. 1p/19q co-deletion and IDH1 mutation status) in WHO grade II and III diffuse gliomas remains controversial. In the current study, we describe unique perfusion and diffusion MR signatures between histological and genetic glioma subtypes. Sixty-five patients with 2007 histological designations (astrocytomas and oligodendrogliomas), 1p/19q status (+ = intact/- = co-deleted), and IDH1 mutation status (MUT/WT) were included in this study. In all patients, median relative cerebral blood volume (rCBV) and apparent diffusion coefficient (ADC) were estimated within T2 hyperintense lesions. Bootstrap hypothesis testing was used to compare subpopulations of gliomas, separated by WHO grade and 2007 or 2016 glioma classification schemes. A multivariable logistic regression model was also used to differentiate between 1p19q⁺ and 1p19q^- WHO II-III gliomas. Neither rCBV nor ADC differed significantly between histological subtypes of pure astrocytomas and pure oligodendrogliomas. ADC was significantly different between molecular subtypes (p = 0.0016), particularly between IDH^WT and IDH^MUT/1p19q⁺ (p = 0.0013). IDH^MUT/1p19q⁺ grade III gliomas had higher median ADC; IDH^WT grade III gliomas had higher rCBV with lower ADC; and IDH^MUT/1p19q^- had intermediate rCBV and ADC values, similar to their grade II counterparts. A multivariable logistic regression model was able to differentiate between IDH^WT and IDH^MUT WHO II and III gliomas with an AUC of 0.84 (p < 0.0001, 74% sensitivity, 79% specificity). Within IDH^MUT WHO II-III gliomas, a separate multivariable logistic regression model was able to differentiate between 1p19q⁺ and 1p19q^- WHO II-III gliomas with an AUC of 0.80 (p = 0.0015, 64% sensitivity, 82% specificity). ADC better differentiated between genetic subtypes of gliomas according to the 2016 WHO guidelines compared to the classification scheme outlined in the 2007 WHO guidelines based on histological features of the tissue. Results suggest a combination of rCBV, ADC, T2 hyperintense volume, and presence of contrast enhancement together may aid in non-invasively identifying genetic subtypes of diffuse gliomas.

Keywords: Diffusion MRI; Glioma; IDH mutant; Perfusion MRI; WHO classification.

MeSH terms

Adult
Aged
Aged, 80 and over
Area Under Curve
Brain Neoplasms* / classification
Brain Neoplasms* / diagnostic imaging
Brain Neoplasms* / genetics
Cerebral Blood Volume / genetics
Chromosome Deletion
Chromosomes, Human, Pair 1 / genetics
Diffusion Magnetic Resonance Imaging*
Female
Glioma* / classification
Glioma* / diagnostic imaging
Glioma* / genetics
Humans
Image Processing, Computer-Assisted
Isocitrate Dehydrogenase / genetics
Magnetic Resonance Angiography*
Male
Middle Aged
Mutation / genetics
Retrospective Studies
Statistics, Nonparametric
World Health Organization
Young Adult

Substances

Isocitrate Dehydrogenase

Supplementary concepts

Chromosome 1, monosomy 1p

Grants and funding

P50 CA211015/CA/NCI NIH HHS/United States