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Early pseudoprogression and progression lesions in glioblastoma patients are both metabolically heterogeneous

Ungan, G, Pons-Escoda, A, Ulinic, D, Arús, C, Ortega-Martorell, S, Olier, I, Vellido, A, Majós, C and Julià-Sapé, M (2024) Early pseudoprogression and progression lesions in glioblastoma patients are both metabolically heterogeneous. NMR in Biomedicine. pp. 1-12. ISSN 0952-3480

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The standard treatment in glioblastoma includes maximal safe resection followed by concomitant radiotherapy plus chemotherapy and adjuvant temozolomide. The first follow-up study to evaluate treatment response is performed one month after concomitant treatment, when contrast-enhancing regions may appear that can correspond to true progression or pseudoprogression.
We retrospectively evaluated 31 consecutive patients at the first follow-up after concomitant treatment to check whether the metabolic pattern assessed with multivoxel magnetic resonance spectroscopy was predictive of treatment response two months later. We extracted the underlying metabolic patterns of the contrast-enhancing regions with a blind-source separation method and mapped them over the reference images. Pattern heterogeneity was calculated using entropy and association between patterns and outcomes was measured with Cramer’s V. We identified three distinct metabolic patterns: proliferative, necrotic and responsive, which were associated with status two months later. Individually, 70% of the patients showed metabolically heterogeneous patterns in the contrast-enhancing regions. Metabolic heterogeneity was not related to the regions’ size and only stable patients were less heterogeneous than the rest. Contrast-enhancing regions are also metabolically heterogeneous one month after concomitant treatment. This could explain the reported difficulty in finding robust pseudoprogression biomarkers.

Item Type: Article
Uncontrolled Keywords: 0304 Medicinal and Biomolecular Chemistry; 0903 Biomedical Engineering; 1103 Clinical Sciences; Nuclear Medicine & Medical Imaging
Subjects: Q Science > QA Mathematics > QA75 Electronic computers. Computer science
R Medicine > RC Internal medicine > RC0254 Neoplasms. Tumors. Oncology (including Cancer)
Divisions: Computer Science & Mathematics
Publisher: Wiley
SWORD Depositor: A Symplectic
Date Deposited: 01 Dec 2023 13:06
Last Modified: 24 Jan 2024 11:00
URI: https://researchonline.ljmu.ac.uk/id/eprint/22001
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