Model-free dynamic contrast-enhanced MRI analysis: differentiation between active tumor and necrotic tissue in patients with glioblastoma.
Classification
DCE
Glioblastoma
MRI
Treatment response assessment
Journal
Magma (New York, N.Y.)
ISSN: 1352-8661
Titre abrégé: MAGMA
Pays: Germany
ID NLM: 9310752
Informations de publication
Date de publication:
Feb 2023
Feb 2023
Historique:
received:
05
05
2022
accepted:
13
10
2022
revised:
09
10
2022
pubmed:
27
10
2022
medline:
10
3
2023
entrez:
26
10
2022
Statut:
ppublish
Résumé
Treatment response assessment in patients with high-grade gliomas (HGG) is heavily dependent on changes in lesion size on MRI. However, in conventional MRI, treatment-related changes can appear as enhancing tissue, with similar presentation to that of active tumor tissue. We propose a model-free data-driven method for differentiation between these tissues, based on dynamic contrast-enhanced (DCE) MRI. The study included a total of 66 scans of patients with glioblastoma. Of these, 48 were acquired from 1 MRI vendor and 18 scans were acquired from a different MRI vendor and used as test data. Of the 48, 24 scans had biopsy results. Analysis included semi-automatic arterial input function (AIF) extraction, direct DCE pharmacokinetic-like feature extraction, and unsupervised clustering of the two tissue types. Validation was performed via (a) comparison to biopsy result (b) correlation to literature-based DCE curves for each tissue type, and (c) comparison to clinical outcome. Consistency between the model prediction and biopsy results was found in 20/24 cases. An average correlation of 82% for active tumor and 90% for treatment-related changes was found between the predicted component and population-based templates. An agreement between the predicted results and radiologist's assessment, based on RANO criteria, was found in 11/12 cases. The proposed method could serve as a non-invasive method for differentiation between lesion tissue and treatment-related changes.
Identifiants
pubmed: 36287282
doi: 10.1007/s10334-022-01045-z
pii: 10.1007/s10334-022-01045-z
doi:
Substances chimiques
Contrast Media
0
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Pagination
33-42Informations de copyright
© 2022. The Author(s), under exclusive licence to European Society for Magnetic Resonance in Medicine and Biology (ESMRMB).
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