Prediction of MGMT promotor methylation status in glioblastoma by contrast-enhanced T1-weighted intensity image

© The Author(s) 2024. Published by Oxford University Press, the Society for Neuro-Oncology and the European Association of Neuro-Oncology..

Background: The study aims to explore MRI phenotypes that predict glioblastoma's (GBM) methylation status of the promoter region of MGMT gene (pMGMT) by qualitatively assessing contrast-enhanced T1-weighted intensity images.

Methods: A total of 193 histologically and molecularly confirmed GBMs at the Kansai Network for Molecular Diagnosis of Central Nervous Tumors (KANSAI) were used as an exploratory cohort. From the Cancer Imaging Archive/Cancer Genome Atlas (TCGA) 93 patients were used as validation cohorts. "Thickened structure" was defined as the solid tumor component presenting circumferential extension or occupying >50% of the tumor volume. "Methylated contrast phenotype" was defined as indistinct enhancing circumferential border, heterogenous enhancement, or nodular enhancement. Inter-rater agreement was assessed, followed by an investigation of the relationship between radiological findings and pMGMT methylation status.

Results: Fleiss's Kappa coefficient for "Thickened structure" was 0.68 for the exploratory and 0.55 for the validation cohort, and for "Methylated contrast phenotype," 0.30 and 0.39, respectively. The imaging feature, the presence of "Thickened structure" and absence of "Methylated contrast phenotype," was significantly predictive of pMGMT unmethylation both for the exploratory (p = .015, odds ratio = 2.44) and for the validation cohort (p = .006, odds ratio = 7.83). The sensitivities and specificities of the imaging feature, the presence of "Thickened structure," and the absence of "Methylated contrast phenotype" for predicting pMGMT unmethylation were 0.29 and 0.86 for the exploratory and 0.25 and 0.96 for the validation cohort.

Conclusions: The present study showed that qualitative assessment of contrast-enhanced T1-weighted intensity images helps predict GBM's pMGMT methylation status.

Medienart:

E-Artikel

Erscheinungsjahr:

2024

Erschienen:

2024

Enthalten in:

Zur Gesamtaufnahme - volume:6

Enthalten in:

Neuro-oncology advances - 6(2024), 1 vom: 15. Jan., Seite vdae016

Sprache:

Englisch

Beteiligte Personen:

Sanada, Takahiro [VerfasserIn]
Kinoshita, Manabu [VerfasserIn]
Sasaki, Takahiro [VerfasserIn]
Yamamoto, Shota [VerfasserIn]
Fujikawa, Seiya [VerfasserIn]
Fukuyama, Shusei [VerfasserIn]
Hayashi, Nobuhide [VerfasserIn]
Fukai, Junya [VerfasserIn]
Okita, Yoshiko [VerfasserIn]
Nonaka, Masahiro [VerfasserIn]
Uda, Takehiro [VerfasserIn]
Arita, Hideyuki [VerfasserIn]
Mori, Kanji [VerfasserIn]
Ishibashi, Kenichi [VerfasserIn]
Takano, Koji [VerfasserIn]
Nishida, Namiko [VerfasserIn]
Shofuda, Tomoko [VerfasserIn]
Yoshioka, Ema [VerfasserIn]
Kanematsu, Daisuke [VerfasserIn]
Tanino, Mishie [VerfasserIn]
Kodama, Yoshinori [VerfasserIn]
Mano, Masayuki [VerfasserIn]
Kanemura, Yonehiro [VerfasserIn]

Links:

Volltext

Themen:

Glioblastoma
Journal Article
MGMT
MGMT promoter methylation
Magnetic resonance image
Radiogenomics

Anmerkungen:

Date Revised 29.02.2024

published: Electronic-eCollection

Citation Status PubMed-not-MEDLINE

doi:

10.1093/noajnl/vdae016

funding:

Förderinstitution / Projekttitel:

PPN (Katalog-ID):

NLM369000951