Radka Stoyanova, PhD [ View bio ](University of Miami, Miller School of Medicine)
The microenvironment in solid tumors is characterized by inadequate and heterogeneous perfusion, hyper-permeable vasculature, hypoxia, acidic extracellular pH, and nutrient deprivation. Hypoxic tumors, often associated with a more aggressive tumor phenotype, are more resistant to chemo- or radiation therapy than well-vascularized, well-oxygenated tumors. We present an approach to identify areas of tumor hypoxia using the signal-versus-time curves of Dynamic Contrast-Enhanced Magnetic Resonance Imaging (DCE-MRI) data as a surrogate marker of hypoxia. An unsupervised pattern recognition (PR) technique is applied to determine the differential signal-versus-time curves associated with different tumor microenvironment characteristics in DCE-MRI data of a preclinical cancer model. Well-perfused tumor areas are identified by rapid contrast uptake followed by rapid washout; hypoxic areas, representing regions of reduced vascularization, are identified by delayed contrast signal build-up and washout; and finally, necrotic areas exhibit slow or no contrast uptake and no discernible washout over the experimental observation.
The advantage of the proposed novel analysis approach is that it can be readily translated to the clinic, as DCE-MRI is widely available and easily implemented on any clinical magnet. Multiparametric MRI is fully integrated in contemporary radiation treatment (RT) of prostate cancer. Tumor heterogeneity, however, is a significant source of variation in biomarker expression and none of the biomarkers: Ki-67, MDM2, p16 and Cox-2, associated independently with clinical outcome of men treated primarily with RT, have gained acceptance in the clinic. We utilize MRI-guided real time ultrasound biopsies to accurately target the suspicious prostate regions. In the hypoxic areas we can assess the expression of hypoxia- and angiogenesis-related markers HIF-1a, Osteopontin (OPN) and VEGF. The goal is to develop imaging and biomarker nomograms for estimating the effects of different lengths of androgen deprivation therapy and RT doses on treatment outcomes.
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