After the embargo period via non-commercial hosting platforms such as their institutional repository  via commercial sites with which Elsevier has an agreement In all cases accepted manuscripts should: link to the formal publication via its DOI  bear a CC-BY-NC-ND license -this is easy to do, click here to find out how  if aggregated with other manuscripts, for example in a repository or other site, be shared in alignment with our hosting policy  not be added to or enhanced in any way to appear more like, or to substitute for, the published journal article AbstractPurpose: Radiotherapy plan evaluation is currently performed by assessing physical parameters, which has many limitations. Biological modelling can potentially allow plan evaluation that is more reflective of clinical outcomes, however further research is required into this field before it can be used clinically.Methods: A simple program, RADBIOMOD, has been developed using Visual Basic for Applications (VBA) for Microsoft Excel that incorporates multiple different biological models for radiotherapy plan evaluation, including modified Poisson tumour control probability (TCP), modified Zaider-Minerbo TCP, Lyman-Kutcher-Burman normal tissue complication probability (NTCP), equivalent uniform dose (EUD), EUD-based TCP, EUDbased NTCP, and uncomplicated tumour control probability (UTCP). RADBIOMOD was compared to existing biological modelling calculators for 15 sample cases.Results: Comparing RADBIOMOD to the existing biological modelling calculators, all models tested had mean absolute errors and root mean square errors less than 1%.Conclusions: RADBIOMOD produces results that are non-significantly different from existing biological modelling calculators for the models tested. It is hoped that this freely available, user-friendly program will aid future research into biological modelling.

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The aim of this study was to compare IMRT optimization in the CMS XiO radiotherapy treatment planning system, with and without segment weight optimization. Twenty‐one prostate cancer patients were selected for this study. All patients were initially planned with step‐and‐shoot IMRT (S‐IMRT). A new plan was then created for each patient by applying the segment weight optimization tool (SWO‐IMRT). Analysis was performed on the (SWO‐IMRT) and (S‐IMRT) plans by comparing the total number of segments, monitor units, rectal and bladder dose. The study showed a statistically significant reduction in the total number of segments (mean: 25.3%; range: 16.8%–31.1%) with SWO‐IMRT as compared to S‐IMRT (p<0.0001). Similarly, a mean reduction of 3.8% (range: 0.4%–7.7%) in the total MU was observed with SWO‐IMRT (p<0.0001). The study showed an average rectal dose decrease of 13.7% (range: 7.9%–21.4%) with SWO‐IMRT (p<0.0001). We also observed a statistically significant reduction of 26.7% (range: 16.0%–41.4%; p < 0.0001) in the mean dose to the posterior one‐third rectum and an overall reduction in mean bladder dose of 2.2% (range: 0.1%–6.1%) for SWO‐IMRT (p<0.0001). This study shows that the segment weight optimization method significantly reduces the total number of segments and the dose to the rectum for IMRT prostate cancer. It also resulted in fewer monitor units for most of the prostate cases observed in this study.PACS numbers: 85.55.ne; 87.55.de; 87.55.kd

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