Doctor of Philosophy
Dr. Robert Bartha
Discrimination of tumor from radiation injured (RI) tissues and differentiation of tumor types using noninvasive imaging is essential for guiding surgical and radiotherapy treatments are some of the challenges that clinicians face in the course of treatment of brain tumors. The first objective in this thesis was to develop a method to discriminate between glioblastoma tumor recurrences and radiation injury using multiparametric characterization of the tissue incorporating conventional magnetic resonance imaging signal intensities and diffusion tensor imaging parameters. Our results show significant correlations in the RI that was missing in the tumor regions. These correlations may aid in differentiating between tumor recurrence and RI. The second objective of was to investigate whether texture based image analysis of routine MR images would provide quantitative information that could be used to differentiate between glioblastoma and metastasis. Our results demonstrate that first-order texture feature of standard deviation and second-order texture features of entropy, inertia, homogeneity, and energy show significant differences between the two groups. The third objective was to investigate whether quantitative measurements of tumor size and appearance on MRI scans acquired prior to helical tomotherapy (HT) type whole brain radiotherapy with simultaneous infield boost treatment could be used to differentiate responder and non-responder patient groups. Our results demonstrated that smaller size lesions may respond better to this type of radiation therapy. Measures of appearance provided limited added value over measures of size for response prediction. Quantitative measurements of rim enhancement and core necrosis performed separately did not provide additional predictive value.
Sharma, Harish A., "Multiparametric Imaging and MR Image Texture Analysis in Brain Tumors" (2014). Electronic Thesis and Dissertation Repository. 1967.