A03-1 Clinical Applications of Multidisciplinary Computational Anatomy to Surgery

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Member

  • Primary Investigator
    Makoto Hashizume (Kyusyu University, Professor)
  • Co-Investigator
    Satoshi Ieiri (Kagoshima University, Professor)
    Ryota Sozaki (Kyusyu University, Assistant Professor)
    Kenoki Ouchida (kyushu University, Assistant Professor)
    Naoki Suzuki (The Jikei University School of Medicine, Professor)
    Noriaki Ikeda (Kyusyu University, Professor)
    Yoshinao Oda (Kyusyu University, Professor)
    Kazuo Kiguchi (Kyusyu University, Professor)


Overview

In clinical practice, diagnosis and treatment are being carried out on the basis of a variety of medical images in addition to X-ray CT image. Therefore, it is necessary to develop the multidisciplinary analysis system that integrates various medical images. First, in the present study, we focused on pancreatic cancer, which is extremely difficult to diagnose and treat. Here, we used a novel mouse model of pancreatic cancer, which is called KPC mouse. We also used normal pancreas of pig to investigate the detailed structures of normal pancreas without tumors. Using micro CT/MR images and pathological images, 3D micro images would be reconstituted and integrated with MR images and serial pathological images. We also established the new mouse model, KPLC mouse, which had luminous pancreas and duodenum by luciferin administration. This new mouse model would be useful for imaging of tumor cells in in vivo or ex vivo models of pancreatic cancer. We also prepared human autopsy pancreas to investigate the normal human pancreas and the pre-neoplastic lesions of pancreas, such as PanIN and IPMN, which is a subset of pancreatic cancer. Time-dependent human pancreatic tumor would be reproduced in three dimensions using CT/MR images and the pathological images. We are aimed at establishing a novel analysis system by integrating time-dependent CT/MR images and serial pathological images. The new model enables the prediction of future CT/MR images and pathological images. This information would be useful to diagnose a malignancy grading and to predict chemotherapeutic effect and the extent of invasion of pancreatic cancer. In addition, we are developing a 4D human model where we can visualize and analyze the inner structure of a human body when a human being is in motion, and visualized changes in human growth by 4D imaging. Finally, we plan to examine whether the volume change of postmortem portal venous gas or intestinal gas might be able to estimate time since death.

Project Design

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