Radiobiological modeling of interplay between accelerated repopulation and altered fractionation schedules in head and neck cancer

• Main Authors: Marcu Loredana, Bezak Eva
• Format: Article
• Language: English
• Published: Wolters Kluwer Medknow Publications 2009-01-01
• Series: Journal of Medical Physics
• Subjects: Altered fractionation; Monte Carlo; tumor repopulation
• Online Access: http://www.jmp.org.in/article.asp?issn=0971-6203;year=2009;volume=34;issue=4;spage=206;epage=211;aulast=Marcu

Head and neck cancer represents a challenge for radiation oncologists due to accelerated repopulation of cancer cells during treatment. This study aims to simulate, using Monte Carlo methods, the response of a virtual head and neck tumor to both conventional and altered fractionation schedules in radiotherapy when accelerated repopulation is considered. Although clinical trials are indispensable for evaluation of novel therapeutic techniques, they are time-consuming processes which involve many complex and variable factors for success. Models can overcome some of the limitations encountered by trials as they are able to simulate in less complex environment tumor cell kinetics and dynamics, interaction processes between cells and ionizing radiation and their outcome. Conventional, hyperfractionated and accelerated treatment schedules have been implemented in a previously developed tumor growth model which also incorporates tumor repopulation during treatment. This study focuses on the influence of three main treatment-related parameters, dose per fraction, inter fraction interval and length of treatment gap and gap timing based on RTOG trial data on head and neck cancer, on tumor control. The model has shown that conventionally fractionated radiotherapy is not able to eradicate the stem population of the tumor. Therefore, new techniques such as hyperfractionated/ accelerated radiotherapy schedules should be employed. Furthermore, the correct selection of schedule-related parameters (dose per fraction, time between fractions, treatment gap scheduling) is crucial in overcoming accelerated repopulation. Modeling of treatment regimens and their input parameters can offer better understanding of the radiobiological interactions and also treatment outcome.