Prostate cancer tumour control probability modelling for external beam radiotherapy based on multi-parametric MRI-GTV definition
Authors: Sachpazidis Ilias , Mavroidis Panayiotis , Zamboglou Constantinos , Klein Christina Marie , Grosu Anca-Ligia , Baltas Dimos 
Published: August 2020

Purpose: To evaluate the applicability and estimate the radiobiological parameters of linear-quadratic Poisson tumour control probability (TCP) model for primary prostate cancer patients for two relevant target structures (prostate gland and GTV). The TCP describes the dose–response of prostate after definitive radiotherapy (RT). Also, to analyse and identify possible significant correlations between clinical and treatment factors such as planned dose to prostate gland, dose to GTV, volume of prostate and mpMRI-GTV based on multivariate logistic regression model.Methods: The study included 129 intermediate and high-risk prostate cancer patients (cN0 and cM0), who were treated with image-guided intensity modulated radiotherapy (IMRT) +/- androgen deprivation therapy with a median follow-up period of 81.4 months (range: 42.0 - 149.0) months. Tumour control was defined as biochemical relapse free survival according to the Phoenix definition (BRFS). MpMRI-GTV was delineated retrospectively based on a pre-treatment multi-parametric MR imaging (mpMRI), which was co-registered to the planning CT. The clinical treatment planning procedure was based on prostate gland, delineated on CT imaging modality. Furthermore, we also fitted the clinical data to TCP model for the two considered targets for the 5-year follow-up after radiation treatment, where our cohort was composed of a total number of 108 patients, of which 19 were biochemical relapse (BR) patients. Results: For the median follow-up period of 81.4 months (range: 42.0 - 149.0) months, our results indicated an appropriate α/β = 1.3 Gy for prostate gland and α/β = 2.9 Gy for mpMRI-GTV. Only for prostate gland, EQD2 and gEUD2Gy were significantly lower in the biochemical relapse (BR) group compared to the biochemical control (BC) group. Fitting results to the linear-quadratic Poisson TCP model for prostate gland and α/β = 1.3 Gy were D50 = 66.8 Gy with 95%CI [64.6 Gy, 69.0 Gy], and γ = 3.81 with 95%CI [2.58, 5.20]. For mpMRI-GTV and α/β = 2.9 Gy, D50 was 68.1 Gy with 95%CI [66.1 Gy, 70.0 Gy], and γ = 4.45 with 95%CI [3.00, 6.12]. The fitness of the model was better for prostate gland. For the multivariate logistic model, the gEUD2Gy for prostate gland showed a very high significant predictive value (p = 0.001), whereas regarding mpMRI-GTV only its volume showed a significance (p = 0.01). Finally, for the 5-year follow-up after the radiation treatment, our results for the prostate gland were: D50=64.6Gy [61.6Gy, 67.4Gy], γ=3.08 [2.03, 4.35], α/β=2.2Gy (95%CI was undefined). For the mpMRI-GTV, the optimizer was unable to deliver any reasonable results for the expected clinical D50 and α/β. The results for the mpMRI-GTV were: D50=50.1Gy [44.6Gy, 56.0Gy], γ=0.84 [0.53, 1.21], α/β=0.0Gy (95%CI was undefined). Conclusion: The linear-quadratic Poisson TCP model was better fit when the prostate gland was considered as responsible target than with mpMRI-GTV. This is compatible with the results of the comparison of the dose distributions among BR and BC groups and with the results achieved with the multivariate logistic model regarding gEUD 2Gy . Probably limitations of mpMRI in defining the GTV explain these results. Another explanation could be the relatively homogeneous dose prescription and the relatively low number of recurrences.