Lei Xing Lab In the Department of Radiation Oncology

Molecular Imaging, Radiobiology Modeling and Biologically Conformal Radiation Therapy

Anatomic imaging modalities such as CT and MRI do not always provide an accurate picture of the tumor extent, especially in the zone of infiltration that may be the limiting factor in an attempt to use the radical treatment approach. Many efforts have been undertaken to apply various metabolic imaging techniques, including MR spectroscopic imaging (MRSI), SPECT and PET, to attack the problem by adding the metabolic and cellular picture to the anatomic information from conventional imaging techniques. In line with the mission of the Molecular Imaging Program at Stanford (MIPS), we are embarking on a number of efforts on applications of molecular imaging in radiation oncology. We are working to improve the current radiobiology models with consideration of  the most recent biological and molecular imaging findings. We hope to bridge the gaps between modern biology and computer modeling and clinical decision-making so that truly optimal therapeutic treatment plans can be obtained. In collaboration with Dr. D. Spielman's group, we are working on incorporating MRSI into therapeutic treatment. We are also working on a method to quantitate the MRSI abnormality data and integration of hyperpolarized 13C MSRI into radiation oncology research.

In addition to better delineating the tumor volume, biological imaging also promises to afford the spatial distribution of various biological parameters. We are establishing a new paradigm of biologically conformal radiation therapy (BCRT), which takes into account both the new tumor boundaries and the spatial biology distributions mapped by the new imaging modalities. The goal here is to customize the dose distribution according to the spatially heterogeneous tumor burden requirements to truly individualize the RT - as opposed to a spatially uniform dose distribution used in today's clinical practice. This will lay the ground for the next generation of radiation therapy, allowing us to escalate tumor dose more intelligently and effectively.

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