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Fractal structure in the volumetric contrast enhancement of malignant gliomas as a marker of oxidative metabolic pathway gene expression

Publication ,  Journal Article
Miller, KJ; Berendsen, S; Seute, T; Yeom, K; Gephardt, MH; Grant, GA; Robe, PA
Published in: Translational Cancer Research
December 1, 2017

Background: Fractal structure is found throughout many processes in nature, and often arises from sets of simple rules. We examined MRI contrast enhancement patterns from glioblastoma patients for evidence of fractal structure and correlated these with gene expression patterns. Methods: For 39 glioblastoma patients, volumetric T1-post-contrast MRI scans were obtained before surgical resection. We calculated the fractal dimension of each tumor's contrast enhancement using a box-counting (cubic scaling) approach. RNA expression microarray data from resected tissue were explored by gene set enrichment analysis (GSEA), and vascular endothelial growth factor (VEGF) expression was determined by immunostaining of resected tissue. Results: We found robust evidence for fractal structure in the contrast enhancement pattern, with an average fractal dimension of 2.17±0.10, and a visually apparent split at 2.10. GSEA analysis showed a clear association between high fractal dimension (χ > 2.10) and decreased gene expression in 6 gene sets (of 4,080), all 6 of which are linked to mitochondrial respiration/ATP production pathways. On a protein level, high fractal dimension was correlated with increased VEGF. Conclusions: There is fractal structure in the volumetric enhancement pattern of glioblastomas. Variation in the fractal dimension, and therefore the complexity of contrast enhancement it reflects, is specifically associated with genetic correlates of a shift to glycolytic metabolism in tumor cells and VEGF. Drugs that restore oxidative metabolism have recently been identified as independent therapeutic agents as well as sensitizing agents for irradiation. Therefore, a radiogenomic marker of glucose metabolism, such as this fractal structure in enhancement, might help to guide individualized therapy.

Duke Scholars

Published In

Translational Cancer Research

DOI

EISSN

2219-6803

ISSN

2218-676X

Publication Date

December 1, 2017

Volume

6

Issue

6

Start / End Page

1275 / 1282

Related Subject Headings

  • 3211 Oncology and carcinogenesis
 

Citation

APA
Chicago
ICMJE
MLA
NLM
Miller, K. J., Berendsen, S., Seute, T., Yeom, K., Gephardt, M. H., Grant, G. A., & Robe, P. A. (2017). Fractal structure in the volumetric contrast enhancement of malignant gliomas as a marker of oxidative metabolic pathway gene expression. Translational Cancer Research, 6(6), 1275–1282. https://doi.org/10.21037/tcr.2017.10.15
Miller, K. J., S. Berendsen, T. Seute, K. Yeom, M. H. Gephardt, G. A. Grant, and P. A. Robe. “Fractal structure in the volumetric contrast enhancement of malignant gliomas as a marker of oxidative metabolic pathway gene expression.” Translational Cancer Research 6, no. 6 (December 1, 2017): 1275–82. https://doi.org/10.21037/tcr.2017.10.15.
Miller KJ, Berendsen S, Seute T, Yeom K, Gephardt MH, Grant GA, et al. Fractal structure in the volumetric contrast enhancement of malignant gliomas as a marker of oxidative metabolic pathway gene expression. Translational Cancer Research. 2017 Dec 1;6(6):1275–82.
Miller, K. J., et al. “Fractal structure in the volumetric contrast enhancement of malignant gliomas as a marker of oxidative metabolic pathway gene expression.” Translational Cancer Research, vol. 6, no. 6, Dec. 2017, pp. 1275–82. Scopus, doi:10.21037/tcr.2017.10.15.
Miller KJ, Berendsen S, Seute T, Yeom K, Gephardt MH, Grant GA, Robe PA. Fractal structure in the volumetric contrast enhancement of malignant gliomas as a marker of oxidative metabolic pathway gene expression. Translational Cancer Research. 2017 Dec 1;6(6):1275–1282.

Published In

Translational Cancer Research

DOI

EISSN

2219-6803

ISSN

2218-676X

Publication Date

December 1, 2017

Volume

6

Issue

6

Start / End Page

1275 / 1282

Related Subject Headings

  • 3211 Oncology and carcinogenesis