COLLOQUIUM: Physics Insights Applied to Breathing Motion Management for Radiation Therapy

Speaker:  Dr. Daniel Low, Ph.D. – Professor and Vice Chair of Medical Physics at UCLA. 

Topic:  “Physics Insights Applied to Breathing Motion Management for Radiation Therapy” 

Time:  2:00 PM, Friday, March 20, 2015 (refreshments served at 1:45 PM) 

Place:  P 148 (refreshments will be served at 1:45 in P-145A)



Breathing motion causes challenges for radiation therapy treatments of lung cancer and upper abdominal cancers.  The treatment planning process involves a characterization of the breathing motion so that an appropriate motion mitigation strategy can be planned. Mitigation strategies include designing radiation beams that encompass the tumor with its motion and gating the linear accelerator so that the tumor is effectively static or nearly static.  CT manufacturers understood that radiation oncology needed a feature to capture the tumor’s breathing-induced motion and they had developed extensive methods for measuring and characterizing cardiac motion.  Because it was relatively straightforward to slightly modify the software from cardiac to pulmonary gating, they did so, replacing EKG or EEG signals with surrogates that monitored the breathing cycle.  Unfortunately, unlike most cardiac cycles, breathing is irregular, so the same algorithms worked poorer for pulmonary gating, especially with irregularly breathing patients.    About 12 years ago, our group decided to develop a better method for measuring and characterizing breathing motion.  As physicists, we started with basic physics principles rather than a simple observational approach. This enabled us to describe breathing motion using a relatively simple equation, which through first order approximations, allows us to characterize the complex breathing motion that most lung tissues exhibit.  We also used mass conservation to predict observables (which we observed), used fundamental biomechanics to regenerate our model (putting it on a more substantial footing), and developed an effective CT technique to acquire the CT data necessary to feed the model. We also developed a technique to measure the model and process accuracy for each patient, something that no other technique provided.  We are in the process of clinically implementing the technique.  This talk will discuss the technique and the impact that having an understanding of physics had on its development.


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