PURPOSE: A method of prostate implant dose distribution assessment using a bioeffect model that incorporates a distribution of tumor cell densities is demonstrated. This method provides both a quantitative method of describing implant quality and spatial information related to the location of underdosed regions of the prostate. This model, unlike any other, takes into account the likelihood of finding cancer cells in the underdosed region. METHODS AND MATERIAL: The prostate volumes of 5 patients were divided into multiple subsections and a unique cell density was assigned to each subsection. The assigned cell density was a function of probability of finding tumor foci in that subsection. The tumor control probability (TCP) for each subsection was then calculated to identify the location of any significantly underdosed part of the prostate. In addition, a single TCP value for the entire prostate was calculated to score the overall quality of the implant. RESULTS: Adequately dosed subsections scored TCP values greater than 0.80. The TCP for underdosed regions fell dramatically particularly in subsections at higher risk of containing tumor cells. CONCLUSIONS: Despite uncertainties in radiobiological parameters used to calculate the TCP and the distribution of cancer foci through the prostate, the bioeffect model was found to be useful in identifying regions of underdosed prostate that may be at risk of local recurrence due to inadequate dose. Unlike the isodose distribution, the model has the potential to demonstrate that small volumes of tissue underdosed in regions most likely to contain higher numbers of tumor cells may be more significant than larger volumes irradiated to a lower dose but with a lower probability of containing cancer cells.
PURPOSE: A method of prostate implant dose distribution assessment using a bioeffect model that incorporates a distribution of tumor cell densities is demonstrated. This method provides both a quantitative method of describing implant quality and spatial information related to the location of underdosed regions of the prostate. This model, unlike any other, takes into account the likelihood of finding cancer cells in the underdosed region. METHODS AND MATERIAL: The prostate volumes of 5 patients were divided into multiple subsections and a unique cell density was assigned to each subsection. The assigned cell density was a function of probability of finding tumor foci in that subsection. The tumor control probability (TCP) for each subsection was then calculated to identify the location of any significantly underdosed part of the prostate. In addition, a single TCP value for the entire prostate was calculated to score the overall quality of the implant. RESULTS: Adequately dosed subsections scored TCP values greater than 0.80. The TCP for underdosed regions fell dramatically particularly in subsections at higher risk of containing tumor cells. CONCLUSIONS: Despite uncertainties in radiobiological parameters used to calculate the TCP and the distribution of cancer foci through the prostate, the bioeffect model was found to be useful in identifying regions of underdosed prostate that may be at risk of local recurrence due to inadequate dose. Unlike the isodose distribution, the model has the potential to demonstrate that small volumes of tissue underdosed in regions most likely to contain higher numbers of tumor cells may be more significant than larger volumes irradiated to a lower dose but with a lower probability of containing cancer cells.
Authors: Ravinder Nath; William S Bice; Wayne M Butler; Zhe Chen; Ali S Meigooni; Vrinda Narayana; Mark J Rivard; Yan Yu Journal: Med Phys Date: 2009-11 Impact factor: 4.071
Authors: E J Her; A Haworth; H M Reynolds; Y Sun; A Kennedy; V Panettieri; M Bangert; S Williams; M A Ebert Journal: Radiat Oncol Date: 2020-07-13 Impact factor: 3.481
Authors: Robert N Finnegan; Hayley M Reynolds; Martin A Ebert; Yu Sun; Lois Holloway; Jonathan R Sykes; Jason Dowling; Catherine Mitchell; Scott G Williams; Declan G Murphy; Annette Haworth Journal: Phys Imaging Radiat Oncol Date: 2022-03-06