Short-interval scanning of patients offers a detailed understanding of the natural progression of tumor tissue, as revealed through imaging markers such as contrast enhancement and edema, prior to therapy. Following treatment, short-interval scanning can also provide evidence of attenuation of growth rates. We present a longitudinal imaging study of a patient with glioblastoma multiforme (GBM) scanned 15 times in 104 days on a 3 T MR scanner. Images were analyzed independently by two automated algorithms capable of creating detailed maps of tumor changes as well as volumetric analysis. The algorithms, a nearest-neighbor-based tissue segmentation and a surface-modeling algorithm, tracked the patient's response to temozolomide, showing an attenuation of growth. The need for surrogate imaging end-points, of which growth rates are an example, is discussed. Further, the strengths of these algorithms, the insight gained by short-interval scanning, and the need for a better understanding of imaging markers are also described.