Advanced Magnetic Resonance Imaging in the Evaluation of Treated Glioblastoma: A Pictorial Essay

Overview

Journal Cancers (Basel)

Publisher MDPI

Specialty Oncology

Date 2023 Aug 12

PMID 37568606

Authors

Matia Martucci

Rosellina Russo

Carolina Giordano

Chiara Schiarelli

Gabriella DApolito

Laura Tuzza

Francesca Lisi

Giuseppe Ferrara

Francesco Schimperna

Stefania Vassalli

Rosalinda Calandrelli

Simona Gaudino

Affiliations

Soon will be listed here.

Abstract

MRI plays a key role in the evaluation of post-treatment changes, both in the immediate post-operative period and during follow-up. There are many different treatment's lines and many different neuroradiological findings according to the treatment chosen and the clinical timepoint at which MRI is performed. Structural MRI is often insufficient to correctly interpret and define treatment-related changes. For that, advanced MRI modalities, including perfusion and permeability imaging, diffusion tensor imaging, and magnetic resonance spectroscopy, are increasingly utilized in clinical practice to characterize treatment effects more comprehensively. This article aims to provide an overview of the role of advanced MRI modalities in the evaluation of treated glioblastomas. For a didactic purpose, we choose to divide the treatment history in three main timepoints: post-surgery, during Stupp (first-line treatment) and at recurrence (second-line treatment). For each, a brief introduction, a temporal subdivision (when useful) or a specific drug-related paragraph were provided. Finally, the current trends and application of radiomics and artificial intelligence (AI) in the evaluation of treated GB have been outlined.

Citing Articles

Radiogenomic Landscape of Metastatic Endocrine-Positive Breast Cancer Resistant to Aromatase Inhibitors.

Khanyile R, Chipiti T, Hull R, Dlamini Z Cancers (Basel). 2025; 17(5).

PMID: 40075655 PMC: 11899325. DOI: 10.3390/cancers17050808.

Enhancing Glioblastoma Resection with NIR Fluorescence Imaging: A Systematic Review.

Mansour H, Shah S, Aguilar T, Abdul-Muqsith M, Gonzales-Portillo G, Mehta A Cancers (Basel). 2024; 16(23).

PMID: 39682171 PMC: 11639985. DOI: 10.3390/cancers16233984.

Complex Diagnostic Challenges in Glioblastoma: The Role of F-FDOPA PET Imaging.

Sipos D, Debreczeni-Mate Z, Ritter Z, Freihat O, Simon M, Kovacs A Pharmaceuticals (Basel). 2024; 17(9).

PMID: 39338377 PMC: 11434841. DOI: 10.3390/ph17091215.

A Comprehensive Review on the Role of MRI in the Assessment of Supratentorial Neoplasms: Comparative Insights Into Adult and Pediatric Cases.

Bhangale P, Kashikar S, Kasat P, Shrivastava P, Kumari A Cureus. 2024; 16(8):e67553.

PMID: 39310617 PMC: 11416707. DOI: 10.7759/cureus.67553.

Deep Learning for MRI Segmentation and Molecular Subtyping in Glioblastoma: Critical Aspects from an Emerging Field.

Bonada M, Rossi L, Carone G, Panico F, Cofano F, Fiaschi P Biomedicines. 2024; 12(8).

PMID: 39200342 PMC: 11352020. DOI: 10.3390/biomedicines12081878.

References

Patel P, Baradaran H, Delgado D, Askin G, Christos P, Tsiouris A . MR perfusion-weighted imaging in the evaluation of high-grade gliomas after treatment: a systematic review and meta-analysis. Neuro Oncol. 2016; 19(1):118-127. PMC: 5193025. DOI: 10.1093/neuonc/now148. View

Lai P, Chung H, Chang H, Fu J, Wang P, Hsu S . Susceptibility-weighted imaging provides complementary value to diffusion-weighted imaging in the differentiation between pyogenic brain abscesses, necrotic glioblastomas, and necrotic metastatic brain tumors. Eur J Radiol. 2019; 117:56-61. DOI: 10.1016/j.ejrad.2019.05.021. View

Ekinci G, Akpinar I, Baltacioglu F, Erzen C, Kilic T, Elmaci I . Early-postoperative magnetic resonance imaging in glial tumors: prediction of tumor regrowth and recurrence. Eur J Radiol. 2003; 45(2):99-107. DOI: 10.1016/s0720-048x(02)00027-x. View

Zikou A, Sioka C, Alexiou G, Fotopoulos A, Voulgaris S, Argyropoulou M . Radiation Necrosis, Pseudoprogression, Pseudoresponse, and Tumor Recurrence: Imaging Challenges for the Evaluation of Treated Gliomas. Contrast Media Mol Imaging. 2019; 2018:6828396. PMC: 6305027. DOI: 10.1155/2018/6828396. View

Brandsma D, Stalpers L, Taal W, Sminia P, van den Bent M . Clinical features, mechanisms, and management of pseudoprogression in malignant gliomas. Lancet Oncol. 2008; 9(5):453-61. DOI: 10.1016/S1470-2045(08)70125-6. View

Bloch O, Han S, Cha S, Sun M, Aghi M, McDermott M . Impact of extent of resection for recurrent glioblastoma on overall survival: clinical article. J Neurosurg. 2012; 117(6):1032-8. DOI: 10.3171/2012.9.JNS12504. View

Garcia-Ruiz A, Naval-Baudin P, Ligero M, Pons-Escoda A, Bruna J, Plans G . Precise enhancement quantification in post-operative MRI as an indicator of residual tumor impact is associated with survival in patients with glioblastoma. Sci Rep. 2021; 11(1):695. PMC: 7804103. DOI: 10.1038/s41598-020-79829-3. View

Pope W . Predictive imaging marker of bevacizumab efficacy: perfusion MRI. Neuro Oncol. 2015; 17(8):1046-7. PMC: 4490878. DOI: 10.1093/neuonc/nov067. View

Park J, Kim H, Park S, Jung S, Kim J, Heo H . Identification of Early Response to Anti-Angiogenic Therapy in Recurrent Glioblastoma: Amide Proton Transfer-weighted and Perfusion-weighted MRI compared with Diffusion-weighted MRI. Radiology. 2020; 295(2):397-406. DOI: 10.1148/radiol.2020191376. View

10.

Lescher S, Schniewindt S, Jurcoane A, Senft C, Hattingen E . Time window for postoperative reactive enhancement after resection of brain tumors: less than 72 hours. Neurosurg Focus. 2014; 37(6):E3. DOI: 10.3171/2014.9.FOCUS14479. View

11.

Friedman H, Prados M, Wen P, Mikkelsen T, Schiff D, Abrey L . Bevacizumab alone and in combination with irinotecan in recurrent glioblastoma. J Clin Oncol. 2009; 27(28):4733-40. DOI: 10.1200/JCO.2008.19.8721. View

12.

Cui Y, Zeng W, Jiang H, Ren X, Lin S, Fan Y . Higher Cho/NAA Ratio in Postoperative Peritumoral Edema Zone Is Associated With Earlier Recurrence of Glioblastoma. Front Neurol. 2020; 11:592155. PMC: 7747764. DOI: 10.3389/fneur.2020.592155. View

13.

Rudie J, Rauschecker A, Bryan R, Davatzikos C, Mohan S . Emerging Applications of Artificial Intelligence in Neuro-Oncology. Radiology. 2019; 290(3):607-618. PMC: 6389268. DOI: 10.1148/radiol.2018181928. View

14.

Afonso M, Brito M . Therapeutic Options in Neuro-Oncology. Int J Mol Sci. 2022; 23(10). PMC: 9140894. DOI: 10.3390/ijms23105351. View

15.

Ellingson B, Bendszus M, Boxerman J, Barboriak D, Erickson B, Smits M . Consensus recommendations for a standardized Brain Tumor Imaging Protocol in clinical trials. Neuro Oncol. 2015; 17(9):1188-98. PMC: 4588759. DOI: 10.1093/neuonc/nov095. View

16.

Negroni D, Bono R, Soligo E, Longo V, Cossandi C, Carriero A . T1-Weighted Contrast Enhancement, Apparent Diffusion Coefficient, and Cerebral-Blood-Volume Changes after Glioblastoma Resection: MRI within 48 Hours vs. beyond 48 Hours. Tomography. 2023; 9(1):342-351. PMC: 9967426. DOI: 10.3390/tomography9010027. View

17.

Razek A, El-Serougy L, Abdelsalam M, Gaballa G, Talaat M . Differentiation of residual/recurrent gliomas from postradiation necrosis with arterial spin labeling and diffusion tensor magnetic resonance imaging-derived metrics. Neuroradiology. 2017; 60(2):169-177. DOI: 10.1007/s00234-017-1955-3. View

18.

Lau D, Magill S, Aghi M . Molecularly targeted therapies for recurrent glioblastoma: current and future targets. Neurosurg Focus. 2014; 37(6):E15. PMC: 5058366. DOI: 10.3171/2014.9.FOCUS14519. View

19.

Ozsunar Y, Mullins M, Kwong K, Hochberg F, Ament C, Schaefer P . Glioma recurrence versus radiation necrosis? A pilot comparison of arterial spin-labeled, dynamic susceptibility contrast enhanced MRI, and FDG-PET imaging. Acad Radiol. 2010; 17(3):282-90. DOI: 10.1016/j.acra.2009.10.024. View

20.

Rieger J, Bahr O, Muller K, Franz K, Steinbach J, Hattingen E . Bevacizumab-induced diffusion-restricted lesions in malignant glioma patients. J Neurooncol. 2009; 99(1):49-56. DOI: 10.1007/s11060-009-0098-8. View