Prospective Longitudinal Analysis of Physiologic MRI-based Tumor Habitat Predicts Short-term Patient Outcomes in IDH-wildtype Glioblastoma

Overview

Journal Neuro Oncol

Publisher Oxford University Press

Specialties Neurology
Oncology

Date 2024 Oct 25

PMID 39450860

Authors

Hye Hyeon Moon

Ji Eun Park

Nak Young Kim

NakYoung Kim

Seo Young Park

Young-Hoon Kim

Sang Woo Song

Chang Ki Hong

Jeong Hoon Kim

Ho Sung Kim

Affiliations

Soon will be listed here.

Abstract

Background: This study validates MRI-based tumor habitats in predicting time-to-progression (TTP), overall survival (OS), and progression sites in isocitrate dehydrogenase (IDH)-wildtype glioblastoma patients.

Methods: Seventy-nine patients were prospectively enrolled between January 2020 and June 2022. MRI, including diffusion-weighted and dynamic susceptibility contrast imaging, were obtained immediately postoperation and at three serial timepoints. Voxels from cerebral blood volume and apparent diffusion coefficient maps were grouped into three habitats (hypervascular cellular, hypovascular cellular, and nonviable tissue) using k-means clustering. Predefined cutoffs for increases in hypervascular and hypovascular cellular habitat were applied to calculate the habitat risk score. Associations between spatiotemporal habitats, habitat risk score, TTP, and OS were investigated using Cox proportional hazards modeling. Habitat risk score was compared to tumor volume using time-dependent receiver operating characteristics analysis. Progression sites were matched with spatial habitats.

Results: Increases in hypervascular and hypovascular cellular habitats and habitat risk scores were associated with shorter TTP and OS (all P < .05). Hypovascular cellular habitat and habitat risk scores 1 and 2 independently predicted TTP (hazard ratio [HR], 4.14; P = .03, HR, 4.51; P = .001 and HR, 10.02; P < .001, respectively). Hypovascular cellular habitat and habitat risk score 2 independently predicted OS (HR, 4.01, P = .003; and HR, 3.27, P < .001, respectively). Habitat risk score outperformed tumor volume in predicting TTP (12-month AUC, 0.762 vs. 0.646, P = .048). Hypovascular cellular habitat predicted progression sites (mean Dice index: 0.31).

Conclusions: Multiparametric physiologic MRI-based spatiotemporal tumor habitats and habitat risk scores are useful biomarkers for early tumor progression and outcomes in IDH-wildtype glioblastoma patients.

References

Bao S, Wu Q, McLendon R, Hao Y, Shi Q, Hjelmeland A . Glioma stem cells promote radioresistance by preferential activation of the DNA damage response. Nature. 2006; 444(7120):756-60. DOI: 10.1038/nature05236. View

Sastry R, Shankar G, Gerstner E, Curry W . The impact of surgery on survival after progression of glioblastoma: A retrospective cohort analysis of a contemporary patient population. J Clin Neurosci. 2018; 53:41-47. DOI: 10.1016/j.jocn.2018.04.004. View

Hambardzumyan D, Bergers G . Glioblastoma: Defining Tumor Niches. Trends Cancer. 2016; 1(4):252-265. PMC: 4831073. DOI: 10.1016/j.trecan.2015.10.009. View

Sugahara T, Korogi Y, Kochi M, Ikushima I, Hirai T, Okuda T . Correlation of MR imaging-determined cerebral blood volume maps with histologic and angiographic determination of vascularity of gliomas. AJR Am J Roentgenol. 1998; 171(6):1479-86. DOI: 10.2214/ajr.171.6.9843274. View

Barajas Jr R, Phillips J, Parvataneni R, Molinaro A, Essock-Burns E, Bourne G . Regional variation in histopathologic features of tumor specimens from treatment-naive glioblastoma correlates with anatomic and physiologic MR Imaging. Neuro Oncol. 2012; 14(7):942-54. PMC: 3379808. DOI: 10.1093/neuonc/nos128. View

Altman D, McShane L, Sauerbrei W, Taube S . Reporting recommendations for tumor marker prognostic studies (REMARK): explanation and elaboration. BMC Med. 2012; 10:51. PMC: 3362748. DOI: 10.1186/1741-7015-10-51. View

Jung V, Romeike B, Henn W, Feiden W, Moringlane J, Zang K . Evidence of focal genetic microheterogeneity in glioblastoma multiforme by area-specific CGH on microdissected tumor cells. J Neuropathol Exp Neurol. 1999; 58(9):993-9. DOI: 10.1097/00005072-199909000-00009. View

Wen P, van den Bent M, Youssef G, Cloughesy T, Ellingson B, Weller M . RANO 2.0: Update to the Response Assessment in Neuro-Oncology Criteria for High- and Low-Grade Gliomas in Adults. J Clin Oncol. 2023; 41(33):5187-5199. PMC: 10860967. DOI: 10.1200/JCO.23.01059. View

Stupp R, Mason W, van den Bent M, Weller M, Fisher B, Taphoorn M . Radiotherapy plus concomitant and adjuvant temozolomide for glioblastoma. N Engl J Med. 2005; 352(10):987-96. DOI: 10.1056/NEJMoa043330. View

10.

Young R, Gupta A, Shah A, Graber J, Zhang Z, Shi W . Potential utility of conventional MRI signs in diagnosing pseudoprogression in glioblastoma. Neurology. 2011; 76(22):1918-24. PMC: 3115805. DOI: 10.1212/WNL.0b013e31821d74e7. View

11.

Lu V, Jue T, McDonald K, Rovin R . The Survival Effect of Repeat Surgery at Glioblastoma Recurrence and its Trend: A Systematic Review and Meta-Analysis. World Neurosurg. 2018; 115:453-459.e3. DOI: 10.1016/j.wneu.2018.04.016. View

12.

Park J, Kim H, Kim N, Park S, Kim Y, Kim J . Spatiotemporal Heterogeneity in Multiparametric Physiologic MRI Is Associated with Patient Outcomes in IDH-Wildtype Glioblastoma. Clin Cancer Res. 2020; 27(1):237-245. DOI: 10.1158/1078-0432.CCR-20-2156. View

13.

Haider A, van den Bent M, Wen P, Vogelbaum M, Chang S, Canoll P . Toward a standard pathological and molecular characterization of recurrent glioma in adults: a Response Assessment in Neuro-Oncology effort. Neuro Oncol. 2019; 22(4):450-456. PMC: 7158649. DOI: 10.1093/neuonc/noz233. View

14.

Prager B, Bhargava S, Mahadev V, Hubert C, Rich J . Glioblastoma Stem Cells: Driving Resilience through Chaos. Trends Cancer. 2020; 6(3):223-235. PMC: 8779821. DOI: 10.1016/j.trecan.2020.01.009. View

15.

Asao C, Korogi Y, Kitajima M, Hirai T, Baba Y, Makino K . Diffusion-weighted imaging of radiation-induced brain injury for differentiation from tumor recurrence. AJNR Am J Neuroradiol. 2005; 26(6):1455-60. PMC: 8149095. View

16.

Hsieh F, Lavori P . Sample-size calculations for the Cox proportional hazards regression model with nonbinary covariates. Control Clin Trials. 2001; 21(6):552-60. DOI: 10.1016/s0197-2456(00)00104-5. View

17.

Suchorska B, Weller M, Tabatabai G, Senft C, Hau P, Sabel M . Complete resection of contrast-enhancing tumor volume is associated with improved survival in recurrent glioblastoma-results from the DIRECTOR trial. Neuro Oncol. 2016; 18(4):549-56. PMC: 4799687. DOI: 10.1093/neuonc/nov326. View

18.

Shipitsin M, Campbell L, Argani P, Weremowicz S, Bloushtain-Qimron N, Yao J . Molecular definition of breast tumor heterogeneity. Cancer Cell. 2007; 11(3):259-73. DOI: 10.1016/j.ccr.2007.01.013. View

19.

Colwell N, Larion M, Giles A, Seldomridge A, Sizdahkhani S, Gilbert M . Hypoxia in the glioblastoma microenvironment: shaping the phenotype of cancer stem-like cells. Neuro Oncol. 2017; 19(7):887-896. PMC: 5570138. DOI: 10.1093/neuonc/now258. View

20.

Chaichana K, Zadnik P, Weingart J, Olivi A, Gallia G, Blakeley J . Multiple resections for patients with glioblastoma: prolonging survival. J Neurosurg. 2012; 118(4):812-20. PMC: 3700339. DOI: 10.3171/2012.9.JNS1277. View