Multiparametric High-Resolution MRI as a Tool for Mapping of Hypoxic Level in Tumors.

In this study, we propose a simple model for prediction of hypoxic level in tumors based on multiparametric magnetic resonance imaging. The study was performed on B16F1 murine melanoma tumors ex vivo that were first magnetic resonance scanned and then analyzed for hypoxic level using hypoxia-inducable factor 1-alpha antibody staining. Each tumor was analyzed in identical sections and in identical regions of interest for pairs of hypoxic level and magnetic resonance values (apparent diffusion coefficient and T2). This was followed by correlation analysis between hypoxic level and respective magnetic resonance values. A moderate correlation was found between hypoxic level and apparent diffusion coefficient (ρ = 0.56, P < .00001) and lower between hypoxic level and T2 (ρ = 0.38, P < .00001). The data were analyzed further to obtain simple predictive models based on the multiple linear regression analysis of the measured hypoxic level (dependent variable) and apparent diffusion coefficient and T2 (independent variables). Among the hypoxic level models, the most efficient was the 3-parameter model given by relation ( HL = kADC ADC + kT2 T2 + b), where kADC = 26%/µm2/ms, kT2 = 0.8%/ms, and b = -32%. The model can be used for calculation of the predicted hypoxic level map based on magnetic resonance-measured apparent diffusion coefficient and T2 maps. Similar prediction models, based on tumor apparent diffusion coefficient and T2 maps, can be done also for other tumor types...
Source: Technology in Cancer Research and Treatment - Category: Cancer & Oncology Authors: Tags: Technol Cancer Res Treat Source Type: research