Automated MR image processing and analysis of malignant brain tumors: Enabling technology for data mining

Glioblastoma multiforme (GBM) is a malignant brain cancer with poor patient prognosis (i.e. time to survival, time to tumor progression). A number of clinical trials are underway evaluating novel therapeutic strategies and magnetic resonance imaging is the most routinely performed procedure for accurate serial monitoring of patients. The electronic availability of the comprehensive data collected as part of the clinical trials provides an unprecedented opportunity to discover new relationships in complex diseases such as GBM. However, imaging data, which is the most accurate non-invasive assessment of GBMs, is not directly amenable for data mining. The focus of this chapter is on image analysis techniques including image spatial and intensity standardization, novel methods for robust tumor and edema segmentation, and quantification of tumor intensity, texture, and shape characteristics. The chapter concludes with an application of discovering the relationship between these quantitative image-derived features and time to survival in GBM patients; the data is part of a comprehensive large electronically accessible archive at UCLA (UCLA Neuro-oncology database).