Abstract
In clinical practice, a variety of medical images in addition to those obtained with CT are used in diagnosis and treatment. A new analysis model that integrates these various medical images is therefore needed. The focus of the present study thus far is pancreatic cancer, which is extremely difficult to diagnose and treat. Using the KPC mouse, we prepared time-dependent MR images and 1299 pathological images of pancreatic tumors. Using these images, 3D micro images can be reconstituted and integrated with both the MR and the serial pathological images. Manually integrated 3D images showed significant correlations between the stromal distribution and signal intensity in the MR images. The new model will be useful at the preoperative diagnosis stage and to predict the response of the tumor after chemotherapy. Furthermore, the features of normal cells and cancer cells were detected using HE images. We would like to find new markers to evaluate grade and stage of cancer at a cellular level.
