Dose-calculation algorithms in the context of inhomogeneity corrections for high energy photon beams.
Radiation therapy has witnessed a plethora of innovations and developments in the past 15 years. Since the introduction of computed tomography for treatment planning there has been a steady introduction of new methods to refine treatment delivery. Imaging continues to be an integral part of the planning, but also the delivery, of modern radiotherapy. However, all the efforts of image guided radiotherapy, intensity-modulated planning and delivery, adaptive radiotherapy, and everything else that we pride ourselves in having in the armamentarium can fall short, unless there is an accurate dose-calculation algorithm. The agreement between the calculated and delivered doses is of great significance in radiation therapy since the accuracy of the absorbed dose as prescribed determines the clinical outcome. Dose-calculation algorithms have evolved greatly over the years in an effort to be more inclusive of the effects that govern the true radiation transport through the human body. In this Vision 20/20 paper, we look back to see how it all started and where things are now in terms of dose algorithms for photon beams and the inclusion of tissue heterogeneities. Convolution-superposition algorithms have dominated the treatment planning industry for the past few years. Monte Carlo techniques have an inherent accuracy that is superior to any other algorithm and as such will continue to be the gold standard, along with measurements, and maybe one day will be the algorithm of choice for all particle treatment planning in radiation therapy.
Papanikolaou
Niko
N
Department of Radiation Oncology, Cancer Therapy and Research Center at University of Texas Health Sciences Center, San Antonio, Texas 78229, USA.
Stathakis
Sotirios
S
D000465:Algorithms; D016477:Artifacts; D003198:Computer Simulation; D008954:Models, Biological; D017785:Photons / Q000627:therapeutic use*; D011874:Radiometry / Q000379:methods*; D011879:Radiotherapy Dosage; D011880:Radiotherapy Planning, Computer-Assisted / Q000379:methods*; D011882:Radiotherapy, High-Energy / Q000379:methods*; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity