Assessment of Glioma Response to Radiotherapy Using Multiple MRI Biomarkers with Manual and Semiautomated Segmentation Algorithms

Yang Yu, Dong Hoon Lee, Shin Lei Peng, Kai Zhang, Yi Zhang, Shanshan Jiang, Xuna Zhao, Hye Young Heo, Xiangyang Wang, Min Chen, Hanzhang Lu, Haiyun Li, Jinyuan Zhou

Research output: Contribution to journalArticle

8 Scopus citations

Abstract

BACKGROUND AND PURPOSE: Multimodality magnetic resonance imaging (MRI) can provide complementary information in the assessment of brain tumors. We aimed to segment tumor in amide proton transfer-weighted (APTw) images and to investigate multiparametric MRI biomarkers for the assessment of glioma response to radiotherapy. For tumor extraction, we evaluated a semiautomated segmentation method based on region of interest (ROI) results by comparing it with the manual segmentation method. METHODS: Thirteen nude rats injected with U87 tumor cells were irradiated by an 8-Gy radiation dose. All MRI scans were performed on a 4.7-T animal scanner preradiation, and at day 1, day 4, and day 8 postradiation. Two experts performed manual and semiautomated methods to extract tumor ROIs on APTw images. Multimodality MRI signals of the tumors, including structural (T2 and T1), functional (apparent diffusion coefficient and blood flow), and molecular (APTw and magnetization transfer ratio or MTR), were calculated and compared quantitatively. RESULTS: The semiautomated method provided more reliable tumor extraction results on APTw images than the manual segmentation, in less time. A considerable increase in the ADC intensities of the tumor was observed during the postradiation. A steady decrease in the blood flow values and in the APTw signal intensities were found after radiotherapy. CONCLUSIONS: The semiautomated method of tumor extraction showed greater efficiency and stability than the manual method. Apparent diffusion coefficient, blood flow, and APTw are all useful biomarkers in assessing glioma response to radiotherapy.

Original languageEnglish (US)
JournalJournal of Neuroimaging
DOIs
StateAccepted/In press - 2016

Keywords

  • APT imaging
  • Brain tumor
  • Image segmentation
  • Multiparametric MRI
  • Response assessment

ASJC Scopus subject areas

  • Radiology Nuclear Medicine and imaging
  • Clinical Neurology

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    Yu, Y., Lee, D. H., Peng, S. L., Zhang, K., Zhang, Y., Jiang, S., Zhao, X., Heo, H. Y., Wang, X., Chen, M., Lu, H., Li, H., & Zhou, J. (Accepted/In press). Assessment of Glioma Response to Radiotherapy Using Multiple MRI Biomarkers with Manual and Semiautomated Segmentation Algorithms. Journal of Neuroimaging. https://doi.org/10.1111/jon.12354