Skip to main page content
U.S. flag

An official website of the United States government

Dot gov

The .gov means it’s official.
Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

Https

The site is secure.
The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation
. 2013 Apr;15(4):480-9.
doi: 10.1093/neuonc/nos325. Epub 2013 Feb 7.

Using susceptibility-weighted imaging to determine response to combined anti-angiogenic, cytotoxic, and radiation therapy in patients with glioblastoma multiforme

Affiliations

Using susceptibility-weighted imaging to determine response to combined anti-angiogenic, cytotoxic, and radiation therapy in patients with glioblastoma multiforme

Janine M Lupo et al. Neuro Oncol. 2013 Apr.

Abstract

Background: The goal of this study was to investigate whether the amount of hypointense signal on susceptibility-weighted imaging within the contrast-enhancing lesion (%SWI-h) on the pretreatment scan could determine response in patients with newly diagnosed glioblastoma multiforme who received external beam radiation therapy with concomitant anti-angiogenic therapy (enzastaurin) and cytotoxic chemotherapy (temozolomide).

Methods: Twenty-five patients were imaged before therapy (postsurgical resection) and scanned serially every 2 months until progression. Standard clinical MR imaging and SWI were performed on a 3T scanner. %SWI-h was quantified for each patient's pretreatment scan. Time to progression and death were used to characterize patients into non-, immediate-, and sustained-response groups for both events. Cox proportional hazards models were used to assess the association between %SWI-h and both progression-free survival (PFS) and overall survival (OS). Classification and regression tree analysis were used to determine optimal cutoffs on which to split %SWI-h.

Results: For both death- and progression-based response categories, %SWI-h was significantly higher in sustained responders than in nonresponders. Cox model coefficients showed an association between %SWI-h and PFS and OS, both in univariate analysis (PFS: hazard ratio [HR] = 0.966, 95% confidence interval [CI] = 0.942-0.988; and OS: HR = 0.945, 95% CI = 0.915-0.976) and when adjusting for baseline KPS, age, sex, and resection extent (PFS: HR = 0.968, 95% CI = 0.940 -0.994; and OS: HR = 0.943, 95% CI = 0.908 -0.976). A cutoff value of 38.1% significantly differentiated patients into 2 groups based on censored OS and into non- and intermediate-response categories based on time to progression.

Conclusions: These early differences suggest that SWI may be able to predict which patients would benefit most from similar combination therapies and may assist clinicians in making important decisions about patient care.

PubMed Disclaimer

Figures

Fig. 1.
Fig. 1.
Methods for alignment and calculation of %SWI-h parameter.
Fig. 2.
Fig. 2.
(A) SWI with CEL contour overlay (top) and corresponding post-gad T1 images (bottom) for each response group. (B) Definition of response-based categories for time to progression and death.
Fig. 3.
Fig. 3.
PFS results. Boxplots of (A) %SWI-h for each response group and (B) when split on CART threshold for progression, including the 2 censored patients. (C) Relationship between %SWI-h and PFS. (D) CoxPH survival curves for each CART split group in B with %SWI-h < 45% in red, %SWI-h > 45% in blue, and the corresponding 95% confidence intervals indicated by dashed lines. □, + indicate have not progressed.
Fig. 4.
Fig. 4.
OS results. Boxplots of (A) %SWI-h for each response group and (B) when split on CART threshold for death, including the 3 censored patients. (C) Relationship between %SWI-h and OS. (D) CoxPH survival curves for each CART split group in B, with %SWI-h < 38% in red, %SWI-h > 38% in blue, and the corresponding 95% confidence intervals indicated by dashed lines. □, + indicate are still alive.
Fig. 5.
Fig. 5.
Relationship between automatic and manual thresholding. In (A), scatter plot of %SWI-h values for automatic versus manual thresholding. In (B), histogram of percentage difference between %SWI-h derived from automatic and manual thresholding across all patients. In (C), change in %SWI-h between manual and automatic methods as a function of change in threshold intensity between methods. Larger differences in thresholds resulted in greater changes in the %SWI-h parameter, with a maximum deviation of 20%.

Similar articles

Cited by

References

    1. Folkman J. The role of angiogenesis in tumor growth. Semin Cancer Biol. 1992;3(2):65–71. - PubMed
    1. Amoroso A, Del Porto F, Di Monaco C, Manfredini P, Afeltra A. Vascular endothelial growth factor: a key mediator of neoangiogenesis. A review. Eur Rev Med Pharmacol Sci. 1997;1(1–3):17–25. - PubMed
    1. Brat DJ, Van Meir EG. Glomeruloid microvascular proliferation orchestrated by VPF/VEGF: a new world of angiogenesis research. Am J Pathol. 2001;158(3):789–796. - PMC - PubMed
    1. Damert A, Machein M, Breier G, et al. Up-regulation of vascular endothelial growth factor expression in a rat glioma is conferred by two distinct hypoxia-driven mechanisms. Cancer Res. 1997;57(17):3860–3864. - PubMed
    1. Wesseling P, Ruiter DJ, Burger PC. Angiogenesis in brain tumors; pathobiological and clinical aspects. J Neurooncol. 1997;32(3):253–265. - PubMed

Publication types

MeSH terms