research profile
Dr. Sean Frigo’s Research
The best treatments are ones that model the right amount of dose in the right place at the right time and accurately predict the effects of those treatments.
Activities that advance treatment planning call for a dedicated environment that closely mimics that used for patient care, yet can tolerate being broken. My research activities are aimed at providing such a resource in order for us to develop new planning techniques and patient treatment models.
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Clinical Treatment Planning System
Our problem definition is inspired by asking what we can do better for our current patients and what we would want to do if we just had the right tools on hand. Thus, significant effort is being spent on implementing a new clinical treatment planning system for patient care. This will lay the groundwork for research in adaptive therapy and improved patient modeling.
An important effort going forward is the development of medical device management techniques to manage the clinical treatment planning system. By applying modern concepts of change and state management, we are able to demonstrate system stability and calculation accuracy as we upgrade software modules or change configurations.
Non-clinical Treatment Planning System
We are implementing a second treatment planning system that closely mimics the one we are using for patient care. Within this dedicated system, we can rapidly prototype and test new planning modules and techniques. It is important that the planning system for patient care be tightly controlled and limited changes be thoroughly tested prior to use. Thus it is important to do developmental work in a separate system that can tolerate being broken and subsequent down time, but also be subject to less rigorous controls and testing.
We intend to utilize this sandbox environment to improve how we perform adaptive planning. Through the use of CT, MR and PT imaging, we are able to build three-dimensional maps of a patient’s anatomy, identifying organs and tissues. We also can create corresponding three-dimensional maps of radiation treatment dose, showing where the radiation energy is deposited. We need to extend these capabilities to be able to do so as a patient’s anatomy changes over time, either during a single treatment course in the time-frame of weeks or during multiple courses over years. We need software and data frameworks to support this time element.
Planning unification
We employ three distinct external beam delivery technologies here at the University of Wisconsin (TrueBeam, Tomotherapy, ViewRay) in addition to brachytherapy. Each technology we use to deliver radiation dose currently has its own dedicated treatment planning system. However, each one of these systems is a data island.
Often, it is best to be able to use different delivery technologies in a single treatment course, such as boosting a prostate with HDR brachytherapy after an initial external beam treatment. It takes great manual effort to copy data between islands in order to create a plan that reflects the entire treatment course and to optimize the different plans over the treatment course. By supporting all treatment modalities within one planning environment, we can calculate and combine dose easily in order to explore the best treatment options for our patients.