Author:
Ding Linda,D. Bradford Carla,Ulin Kenneth,Smith Koren,Kuo I-Lin,Fan Yankhua,Khalifeh Abdulnasser,Liu Fenghong,Lu Suhong,Bushe Harry,Larosa Salvatore,Bunaciu Camelia,Saleeby Jonathan,Higgins Shannon,Trifone Julie,Britton Maureen,Taylor Joshua,Croos Marious,Figura Katie,Quinn Thomas,O’Connor Linda,Briggs Kathleen,Suhl Sherri,Quigley Jean,Reifler Heather,Kirby Shawn,Prior Fred,Saltz Joel,Bishop-Jodoin Maryann,J. FitzGerald Thomas
Abstract
Technology and computational analytics are moving forward at an extraordinary rate with changes in patient care and department workflows. This rapid pace of change often requires initiating and maintaining the educational support at multiple levels to introduce technology to radiation oncology staff members. Modern physics quality assurance and dosimetry treatment planning now require expertise beyond traditional skill based in computational algorithms and image management including quality assurance of the process of image acquisition and fusion of image datasets. Expertise in volumetric anatomy and normal tissue contouring are skills now performed by physics/dosimetry in collaboration with physicians and these skills are required in modern physics dosimetry training programs. In this chapter, challenges of modern radiation planning are reviewed for each disease site. Skills including future applications of image integration into planning objects and the future utility of artificial intelligence in modern radiation therapy treatment planning are reviewed as these issues will need to be added to modern training programs.