Article ID: | iaor2014463 |
Volume: | 65 |
Issue: | 4 |
Start Page Number: | 557 |
End Page Number: | 571 |
Publication Date: | Apr 2014 |
Journal: | Journal of the Operational Research Society |
Authors: | Saka Behlul, Rardin Ronald L, Langer Mark P |
Keywords: | radiation therapy |
Although intensity modulated radiation therapy plans are optimized as a single overall treatment plan, they are delivered over 30–50 treatment sessions (fractions) and both cumulative and per‐fraction dose constraints apply. Recent advances in imaging technology provide more insight on tumour biology that has been traditionally disregarded in planning. The current practice of delivering physical dose distributions across the tumour may potentially be improved by dose distributions guided by the biological responses of the tumour points. The biological optimization models developed and tested in this paper generate treatment plans reacting to the tumour biology prior to the treatment as well as the changing tumour biology throughout the treatment while satisfying both cumulative and fraction‐size dose limits. Complete computational testing of the proposed methods would require an array of clinical data sets with tumour biology information. Finding no open source ones in the literature, the authors sought proof of concept by testing on a simulated head‐and‐neck case adapted from a more standard one in the CERR library by blending it with available tumour biology data from a published study. The results show computed biologically optimized plans improve on tumour control obtained by traditional plans ignoring biology, and that such improvements persist under likely uncertainty in sensitivity values. Furthermore, adaptive plans using biological information improve on non‐adaptive methods.