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Multi-Parametric MRI and Texture Analysis to Visualize Spatial Histologic Heterogeneity and Tumor Extent in Glioblastoma

Author

Listed:
  • Leland S Hu
  • Shuluo Ning
  • Jennifer M Eschbacher
  • Nathan Gaw
  • Amylou C Dueck
  • Kris A Smith
  • Peter Nakaji
  • Jonathan Plasencia
  • Sara Ranjbar
  • Stephen J Price
  • Nhan Tran
  • Joseph Loftus
  • Robert Jenkins
  • Brian P O’Neill
  • William Elmquist
  • Leslie C Baxter
  • Fei Gao
  • David Frakes
  • John P Karis
  • Christine Zwart
  • Kristin R Swanson
  • Jann Sarkaria
  • Teresa Wu
  • J Ross Mitchell
  • Jing Li

Abstract

Background: Genetic profiling represents the future of neuro-oncology but suffers from inadequate biopsies in heterogeneous tumors like Glioblastoma (GBM). Contrast-enhanced MRI (CE-MRI) targets enhancing core (ENH) but yields adequate tumor in only ~60% of cases. Further, CE-MRI poorly localizes infiltrative tumor within surrounding non-enhancing parenchyma, or brain-around-tumor (BAT), despite the importance of characterizing this tumor segment, which universally recurs. In this study, we use multiple texture analysis and machine learning (ML) algorithms to analyze multi-parametric MRI, and produce new images indicating tumor-rich targets in GBM. Methods: We recruited primary GBM patients undergoing image-guided biopsies and acquired pre-operative MRI: CE-MRI, Dynamic-Susceptibility-weighted-Contrast-enhanced-MRI, and Diffusion Tensor Imaging. Following image coregistration and region of interest placement at biopsy locations, we compared MRI metrics and regional texture with histologic diagnoses of high- vs low-tumor content (≥80% vs

Suggested Citation

  • Leland S Hu & Shuluo Ning & Jennifer M Eschbacher & Nathan Gaw & Amylou C Dueck & Kris A Smith & Peter Nakaji & Jonathan Plasencia & Sara Ranjbar & Stephen J Price & Nhan Tran & Joseph Loftus & Robert, 2015. "Multi-Parametric MRI and Texture Analysis to Visualize Spatial Histologic Heterogeneity and Tumor Extent in Glioblastoma," PLOS ONE, Public Library of Science, vol. 10(11), pages 1-14, November.
    • Handle: RePEc:plo:pone00:0141506
    DOI: 10.1371/journal.pone.0141506
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