Published June 2015 | Version v1
Journal article

Using the apparent diffusion coefficient to identifying MGMT promoter methylation status early in glioblastoma: importance of analytical method

  • 1. Centre for Clinical Research, University of Queensland, Brisbane, Queensland (Australia)
  • 2. Brain Cancer Research Unit, Queensland Institute of Medical Research, Brisbane, Queensland (Australia)
  • 3. Department of Radiation Oncology, Royal Brisbane and Women's Hospital, Brisbane, Queensland (Australia)
  • 4. Discipline of Clinical Pharmacology, School of Medicine and Public Health, University of Newcastle, Newcastle, New South Wales (Australia)
  • 5. Department of Neurosurgery, Royal Brisbane and Women's Hospital, Brisbane, Queensland (Australia)
  • 6. Queensland PET Service, Royal Brisbane and Women's Hospital, Brisbane, Queensland (Australia)
  • 7. CSIRO Digital Productivity Flagship, CSIRO, Herston, Queensland (Australia)
  • 8. Centre for Medical Diagnostic Technologies in Queensland, University of Queensland, Brisbane, Queensland (Australia)
  • 9. Department of Medical Imaging, Royal Brisbane and Women's Hospital, Brisbane, Queensland (Australia)
  • 10. Discipline of Medical Imaging, University of Queensland, St Lucia, Queensland (Australia)

Description

Accurate knowledge of O6-methylguanine methyltransferase (MGMT) gene promoter subtype in patients with glioblastoma (GBM) is important for treatment. However, this test is not always available. Pre-operative diffusion MRI (dMRI) can be used to probe tumour biology using the apparent diffusion coefficient (ADC); however, its ability to act as a surrogate to predict MGMT status has shown mixed results. We investigated whether this was due to variations in the method used to analyse ADC. We undertook a retrospective study of 32 patients with GBM who had MGMT status measured. Matching pre-operative MRI data were used to calculate the ADC within contrast enhancing regions of tumour. The relationship between ADC and MGMT was examined using two published ADC methods. A strong trend between a measure of ‘minimum ADC’ and methylation status was seen. An elevated minimum ADC was more likely in the methylated compared to the unmethylated MGMT group (U = 56, P = 0.0561). In contrast, utilising a two-mixture model histogram approach, a significant reduction in mean measure of the ‘low ADC’ component within the histogram was associated with an MGMT promoter methylation subtype (P < 0.0246). This study shows that within the same patient cohort, the method selected to analyse ADC measures has a significant bearing on the use of that metric as a surrogate marker of MGMT status. Thus for dMRI data to be clinically useful, consistent methods of data analysis need to be established prior to establishing any relationship with genetic or epigenetic profiling

Availability note (English)

Available from http://dx.doi.org/10.1002/jmrs.103; Available from http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4462980

Additional details

Publishing Information

Journal Title
Journal of Medical Radiation Sciences (Print)
Journal Volume
62
Journal Issue
2
Journal Page Range
p. 92-98
ISSN
2051-3895

INIS

Country of Publication
Australia
Country of Input or Organization
International Atomic Energy Agency (IAEA)
INIS RN
46108126
Subject category
S60: APPLIED LIFE SCIENCES; S62: RADIOLOGY AND NUCLEAR MEDICINE;
Descriptors DEI
ANALOG-TO-DIGITAL CONVERTERS; DATA ANALYSIS; DIFFUSION; GENES; GLIOMAS; METHYLATION; PATIENTS; PROBES; REDUCTION; VARIATIONS
Descriptors DEC
CHEMICAL REACTIONS; DATA PROCESSING; DISEASES; ELECTRONIC EQUIPMENT; EQUIPMENT; NEOPLASMS; NERVOUS SYSTEM DISEASES; PROCESSING

Optional Information

Copyright
Copyright (c) 2015 The Authors. Journal of Medical Radiation Sciences published by Wiley Publishing Asia Pty Ltd on behalf of Australian Institute of Radiography and New Zealand Institute of Medical Radiation Technology.
Notes
PMCID: PMC4462980; PMID: 26229673; OAI: oai:pubmedcentral.nih.gov:4462980