open access

Vol 53, No 3 (2019)
Research paper
Published online: 2019-03-11
Submitted: 2018-11-06
Accepted: 2018-11-06
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Quantitative volumetric analysis of primary glioblastoma multiforme on MRI and 11C-methionine PET: initial study on five patients

Jingwang Zhao, Zhijuan Chen, Li Cai, Shaoya Yin, Weidong Yang, Zengguang Wang
DOI: 10.5603/PJNNS.a2019.0009
·
Pubmed: 30855705
·
Neurol Neurochir Pol 2019;53(3):199-204.

open access

Vol 53, No 3 (2019)
Research paper
Published online: 2019-03-11
Submitted: 2018-11-06
Accepted: 2018-11-06

Abstract

To investigate the discrepancy between 11C-methionine (MET) positron emission tomography (PET) and MRI results in primary glioblastoma multiforme (GBM) through three-dimensional (3D) volumetric analysis, we retrospectively analysed patients with primary GBM who underwent preoperative 3D MRI and MET PET and were operated between June 2016 and January 2017. Tumour delineation and volumetric analysis were conducted using MRIcron software. Tumour volumes defined by MRI (VMRI) were manually drawn slice by slice in axial and sagittal or coronal images of enhanced T1 sequence, while metabolic tumour volumes were automatically segmented in MET PET (VMET) based on three (frontal, occipital and temporal) 3D reference volumes of interest (VOI). Discrepancies were evaluated in terms of both absolute volume and percentage on the combined images. MET PET contours contained and extended beyond MRI contours in all five patients; in a subset of cases, MET PET contours extended to the contralateral hemisphere. The discrepancy between MET uptake and MRI results was 27.67 cm3 (4.20–51.20 cm3), i.e. approximately 39.0% (17.4–64.3%) of the metabolic tumour volume was located outside the volumes of the Gd-enhanced area. Metabolic tumour volume is substantially underestimated by Gd-enhanced area in patients with primary GBM. Quantitative volumetric information derived from MET uptake is useful in defining tumour targets and designing individualised therapy strategies in primary GBM.

Abstract

To investigate the discrepancy between 11C-methionine (MET) positron emission tomography (PET) and MRI results in primary glioblastoma multiforme (GBM) through three-dimensional (3D) volumetric analysis, we retrospectively analysed patients with primary GBM who underwent preoperative 3D MRI and MET PET and were operated between June 2016 and January 2017. Tumour delineation and volumetric analysis were conducted using MRIcron software. Tumour volumes defined by MRI (VMRI) were manually drawn slice by slice in axial and sagittal or coronal images of enhanced T1 sequence, while metabolic tumour volumes were automatically segmented in MET PET (VMET) based on three (frontal, occipital and temporal) 3D reference volumes of interest (VOI). Discrepancies were evaluated in terms of both absolute volume and percentage on the combined images. MET PET contours contained and extended beyond MRI contours in all five patients; in a subset of cases, MET PET contours extended to the contralateral hemisphere. The discrepancy between MET uptake and MRI results was 27.67 cm3 (4.20–51.20 cm3), i.e. approximately 39.0% (17.4–64.3%) of the metabolic tumour volume was located outside the volumes of the Gd-enhanced area. Metabolic tumour volume is substantially underestimated by Gd-enhanced area in patients with primary GBM. Quantitative volumetric information derived from MET uptake is useful in defining tumour targets and designing individualised therapy strategies in primary GBM.

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Keywords

Volumetric analysis, glioblastoma multiforme, MRI, 11C-methionine

About this article
Title

Quantitative volumetric analysis of primary glioblastoma multiforme on MRI and 11C-methionine PET: initial study on five patients

Journal

Neurologia i Neurochirurgia Polska

Issue

Vol 53, No 3 (2019)

Pages

199-204

Published online

2019-03-11

DOI

10.5603/PJNNS.a2019.0009

Pubmed

30855705

Bibliographic record

Neurol Neurochir Pol 2019;53(3):199-204.

Keywords

Volumetric analysis
glioblastoma multiforme
MRI
11C-methionine

Authors

Jingwang Zhao
Zhijuan Chen
Li Cai
Shaoya Yin
Weidong Yang
Zengguang Wang

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