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Tyler Seibert Lab


Dr. Seibert's research efforts focus on two fronts: imaging and genomics. The goal is to develop quantitative imaging biomarkers for cancer detection and for evaluation of treatment response. We have implemented a novel imaging approach to characterizing radiation therapy effects on normal brain regions in brain tumor patients and are studying advanced diffusion MRI in localized and metastatic prostate cancer. Our genomics efforts have been focused on the development of a model to predict the age at which men do (or do not) need screening for aggressive prostate cancer.

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THE SEIBERT LAB IS SUPPORTED IN PART BY GRANTS FROM THE NATIONAL INSTITUTE OF BIOMEDICAL IMAGING AND BIOENGINEERING, THE RMAS CENTER FOR PRECISION RADIATION MEDICINE, THE UC SAN DIEGO CENTER FOR TRANSLATIONAL IMAGING AND PRECISION MEDICINE, AND THE DEPARTMENT OF DEFENSE

Featured Articles

3D dose prediction

Measuring radiation effects on the brain

At right, regions of the cerebral cortex that are important for cognitive function and selectively vulnerable to atrophy in patients who received radiation therapy to treat their brain tumors.Seibert et abr/>l. International Journal of Radiation Oncology * Biology * Physics, 2017.

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Developing better imaging for precision radiation

Images of a man with a new diagnosis of prostate prostate cancer. (A) A conventional bone scan, which showed no metastases. (B) Whole-body advanced diffusion MRI (Restriction Spectrum Imaging, RSI), which showed a bone metastasis (blue arrow) that could be targeted with precision radiation therapy.

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Predicting cancer risk with genomics

A genetic model, called the polygenic hazard score (PHS), predicts the probability and timing of a man’s risk of developing aggressive prostate cancer. Risk-stratification with this genetic tool improves screening performance of current tests used in clinic (prostate specific antigen).
Huynh-Le et al. bioRxiv 2019. Seibert et al. BMJ 2018.

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