Multimodality Biological Imaging of Cancer/Tumor Hypoxia

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Our long range goal is to develop non-invasive multi- modality imaging that yields biological information of human cancers in 3-dimensions (3D). The short-term objectives are to use NMR and PET for imaging tumor biology and hypoxia in rodent tumors and xenografts. In addition, pO2 levels will be directly measured in the same tumors, and tumor sections characterized to provide a biological basis for the NMR and PET images. All the 3D data sets of images and tumor sections will be spatially correlated with a stereotaxic reference system implanted around the rodent tumors and xenografts. There are three areas of investigation. First, microPET (an animal scanner) studies will be performed: (i) in vivo imaging of radiation-induced apoptosis with 124I- Annexin V, (ii) IAZG uptake as a surrogate of pO2 level, (iii) comparing 124IAZG with 18Fmiso as hypoxia markers, and (iv) assessing the effect of hypoxia on FDG uptake. Second, NMR studies will include: (i) mapping "tumor perfusion" by Gd-DTPA uptake, (ii) assessing lactate level with 1H NMR, and (iii) testing the hypothesis that 1H and 31P NMR spectral changes can predict the susceptibility of individual tumors to hypoxia- modulation. Third, biological features will be measured/analyzed in vivo and in tumor sections for the same tumors: (i) pO2 level with an oxygen probe, (ii) blood perfusion with Hoescht 33342, (iii) histochemical analysis, (iv) comparison of the TUNEL and Annexin V assays, and (v) phosphor plate autoradiography. The above will be spatially-correlated using an implantable stereotaxic marker system that identifies the image coordinates of the multiple data-sets and image registration software adapted from existing algorithms in our radiotherapy treatment planning system. Of significance is the spatial correlation of all the 3D data sets, thus relating biological attributes to image features. We believe that this is the first attempt to directly correlate invasive biological endpoints with image features from non- invasive imaging using spatially registered data-sets. Thus, this project integrates physics, chemistry, biology, engineering and computer sciences to study tumor biology and hypoxia, with considerable significance for cancer diagnosis and treatment.