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

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 1 month after concomitant treatment, when contrast‐enhancing regions may appe...

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Vydáno v:NMR in biomedicine Ročník 37; číslo 4; s. e5095 - n/a
Hlavní autoři: Ungan, Gülnur, Pons‐Escoda, Albert, Ulinic, Daniel, Arús, Carles, Ortega‐Martorell, Sandra, Olier, Ivan, Vellido, Alfredo, Majós, Carles, Julià‐Sapé, Margarida
Médium: Journal Article
Jazyk:angličtina
Vydáno: England Wiley Subscription Services, Inc 01.04.2024
Témata:
Biomarkers
Chemotherapy
convex non‐negative matrix factorization
Evaluation
Glioblastoma
Heterogeneity
Lesions
Metabolism
MRS
pseudoprogression
Radiation therapy
Temozolomide
pseudoprogression
convex non-negative matrix factorization
glioblastoma
MR
MRS
ISSN:0952-3480, 1099-1492, 1099-1492
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Shrnutí: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 1 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 MRS was predictive of treatment response 2 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 Cramér's V. We identified three distinct metabolic patterns—proliferative, necrotic, and responsive, which were associated with status 2 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 1 month after concomitant treatment. This could explain the reported difficulty in finding robust pseudoprogression biomarkers. In a retrospective study with 31 glioblastoma patients 1 month after concomitant treatment, we identified three metabolic patterns with MRS, in contrast‐enhancing regions with suspicions of progression. One pattern is proliferative, the second is necrotic, and the third has necrotic lipids and a polyunsaturated fatty acid peak. Although the patterns are associated with outcome 2 months later, they are not fully predictive due to intra‐patient heterogeneity. The heterogeneity observed is not linked either to progression or to the contrast‐enhancing regions' size.
Bibliografie:Funding information
H2020‐EU.1.3. EXCELLENT SCIENCE—Marie Skłodowska‐Curie Actions, grant number H2020‐MSCA‐ITN‐2018‐813120. Instituto de Salud Carlos III (ISCIII), Proyectos de investigación en salud 2020, grant numbers PI20/00064 and PI20/00360. Spanish Ministerio de Economía y Competitividad, SAF2014‐52332‐R. Centro de Investigación Biomédica en Red en Bioingeniería, Biomateriales y Nanomedicina (CIBER‐BBN
accessed December 29, 2023), CB06/01/0010, an initiative of the Instituto de Salud Carlos III (Spain) co‐funded by EU Fondo Europeo de Desarrollo Regional (FEDER). Spanish AEI PID2019‐104551RB‐I00 grant. Generalitat de Catalunya, Xartecsalut, 2018 XARDI 00016 and 2021 XARDI 00021.
http://www.ciber-bbn.es/en
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ISSN:0952-3480
1099-1492
1099-1492
DOI:10.1002/nbm.5095