Seminar: Evolution of Treatment Planning in Radiation Therapy

Nilendu Gupta, PhD, The Ohio State University Wexner Medical Center

All dates for this event occur in the past.

E141 Scott Laboratory
E141 Scott Laboratory
201 W. 19th Ave.
Columbus, OH 43210
United States

Abstract
The delivery of radiation therapy for cancer patients requires the computation of patient specific treatment plans with detailed dose distributions and computation of dose volume statistics for the treatment target and normal tissues, and organs at risk (OAR’s). Radiotherapy treatment techniques have become increasingly complex, requiring faster, but more accurate dose calculations for the complex modulated beam arrangements and patient geometries. Intensity modulated treatment plans require iterative optimization of the beam fluence modulation to meet target and normal tissue/OAR dose constraints through an inverse planning process. In this lecture, the evolution of dose calculation algorithms for photon beam planning systems will be reviewed and state of the art discussed. The advent of machine learning has resulted in several machine learning algorithms being commercially introduced into the radiotherapy planning process. Machine learning based approaches to improve patient plan quality and throughput such as knowledge based segmentation, knowledge based planning and multi-criteria optimization that are recently becoming available will be reviewed.

 

About the speaker
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Hosted by Professor Vaibhav Sinha.