Clinical implementation of a knowledge based planning tool for prostate VMAT
Abstract Background A knowledge based planning tool has been developed and implemented for prostate VMAT radiotherapy plans providing a target average rectum dose value based on previously achievable values for similar rectum/PTV overlap. The purpose of this planning tool is to highlight sub-optimal...
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doaj-cf2a3050dfaa486ea989f2dbd7d0ad3e2020-11-24T21:46:01ZengBMCRadiation Oncology1748-717X2017-05-011211810.1186/s13014-017-0814-zClinical implementation of a knowledge based planning tool for prostate VMATRichard Powis0Andrew Bird1Matthew Brennan2Susan Hinks3Hannah Newman4Katie Reed5John Sage6Gareth Webster7Worcestershire Oncology Centre, Worcestershire Acute Hospitals NHS TrustWorcestershire Oncology Centre, Worcestershire Acute Hospitals NHS TrustWorcestershire Oncology Centre, Worcestershire Acute Hospitals NHS TrustWorcestershire Oncology Centre, Worcestershire Acute Hospitals NHS TrustWorcestershire Oncology Centre, Worcestershire Acute Hospitals NHS TrustWorcestershire Oncology Centre, Worcestershire Acute Hospitals NHS TrustWorcestershire Oncology Centre, Worcestershire Acute Hospitals NHS TrustWorcestershire Oncology Centre, Worcestershire Acute Hospitals NHS TrustAbstract Background A knowledge based planning tool has been developed and implemented for prostate VMAT radiotherapy plans providing a target average rectum dose value based on previously achievable values for similar rectum/PTV overlap. The purpose of this planning tool is to highlight sub-optimal clinical plans and to improve plan quality and consistency. Methods A historical cohort of 97 VMAT prostate plans was interrogated using a RayStation script and used to develop a local model for predicting optimum average rectum dose based on individual anatomy. A preliminary validation study was performed whereby historical plans identified as “optimal” and “sub-optimal” by the local model were replanned in a blinded study by four experienced planners and compared to the original clinical plan to assess whether any improvement in rectum dose was observed. The predictive model was then incorporated into a RayStation script and used as part of the clinical planning process. Planners were asked to use the script during planning to provide a patient specific prediction for optimum average rectum dose and to optimise the plan accordingly. Results Plans identified as “sub-optimal” in the validation study observed a statistically significant improvement in average rectum dose compared to the clinical plan when replanned whereas plans that were identified as “optimal” observed no improvement when replanned. This provided confidence that the local model can identify plans that were suboptimal in terms of rectal sparing. Clinical implementation of the knowledge based planning tool reduced the population-averaged mean rectum dose by 5.6Gy. There was a small but statistically significant increase in total MU and femoral head dose and a reduction in conformity index. These did not affect the clinical acceptability of the plans and no significant changes to other plan quality metrics were observed. Conclusions The knowledge-based planning tool has enabled substantial reductions in population-averaged mean rectum dose for prostate VMAT patients. This suggests plans are improved when planners receive quantitative feedback on plan quality against historical data.http://link.springer.com/article/10.1186/s13014-017-0814-zKnowledge-based planning (KBP)Plan optimisationOrgan at risk dose sparingScripting |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Richard Powis Andrew Bird Matthew Brennan Susan Hinks Hannah Newman Katie Reed John Sage Gareth Webster |
spellingShingle |
Richard Powis Andrew Bird Matthew Brennan Susan Hinks Hannah Newman Katie Reed John Sage Gareth Webster Clinical implementation of a knowledge based planning tool for prostate VMAT Radiation Oncology Knowledge-based planning (KBP) Plan optimisation Organ at risk dose sparing Scripting |
author_facet |
Richard Powis Andrew Bird Matthew Brennan Susan Hinks Hannah Newman Katie Reed John Sage Gareth Webster |
author_sort |
Richard Powis |
title |
Clinical implementation of a knowledge based planning tool for prostate VMAT |
title_short |
Clinical implementation of a knowledge based planning tool for prostate VMAT |
title_full |
Clinical implementation of a knowledge based planning tool for prostate VMAT |
title_fullStr |
Clinical implementation of a knowledge based planning tool for prostate VMAT |
title_full_unstemmed |
Clinical implementation of a knowledge based planning tool for prostate VMAT |
title_sort |
clinical implementation of a knowledge based planning tool for prostate vmat |
publisher |
BMC |
series |
Radiation Oncology |
issn |
1748-717X |
publishDate |
2017-05-01 |
description |
Abstract Background A knowledge based planning tool has been developed and implemented for prostate VMAT radiotherapy plans providing a target average rectum dose value based on previously achievable values for similar rectum/PTV overlap. The purpose of this planning tool is to highlight sub-optimal clinical plans and to improve plan quality and consistency. Methods A historical cohort of 97 VMAT prostate plans was interrogated using a RayStation script and used to develop a local model for predicting optimum average rectum dose based on individual anatomy. A preliminary validation study was performed whereby historical plans identified as “optimal” and “sub-optimal” by the local model were replanned in a blinded study by four experienced planners and compared to the original clinical plan to assess whether any improvement in rectum dose was observed. The predictive model was then incorporated into a RayStation script and used as part of the clinical planning process. Planners were asked to use the script during planning to provide a patient specific prediction for optimum average rectum dose and to optimise the plan accordingly. Results Plans identified as “sub-optimal” in the validation study observed a statistically significant improvement in average rectum dose compared to the clinical plan when replanned whereas plans that were identified as “optimal” observed no improvement when replanned. This provided confidence that the local model can identify plans that were suboptimal in terms of rectal sparing. Clinical implementation of the knowledge based planning tool reduced the population-averaged mean rectum dose by 5.6Gy. There was a small but statistically significant increase in total MU and femoral head dose and a reduction in conformity index. These did not affect the clinical acceptability of the plans and no significant changes to other plan quality metrics were observed. Conclusions The knowledge-based planning tool has enabled substantial reductions in population-averaged mean rectum dose for prostate VMAT patients. This suggests plans are improved when planners receive quantitative feedback on plan quality against historical data. |
topic |
Knowledge-based planning (KBP) Plan optimisation Organ at risk dose sparing Scripting |
url |
http://link.springer.com/article/10.1186/s13014-017-0814-z |
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