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Prostate cancer tumour control probability modelling for external beam radiotherapy based on multi-parametric MRI-GTV definition
Ilias Sachpazidis
Department of Radiation Oncology, Division of Medical Physics, Medical Center, University of Freiburg
Corresponding Author
ORCiD: https://orcid.org/0000-0001-5701-8947
License:
This work is licensed under a CC BY 4.0 License. Read Full License
View the published version at Radiation Oncology.
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=3.8 with 95%CI [2.6, 5.2]. 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=4.5 with 95%CI [3.0, 6.1]. 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=3.1 [2.0, 4.4], 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=0.8 [0.5, 1.2], α/β=0.0Gy (95%CI was undefined). For a follow-up time of 5 years and a fixed α/β=1.6Gy, the TCP fitting results for prostate gland were D50=63.9Gy [60.8Gy, 67.0Gy], γ=2.9 [1.9, 4.1], and for mpMRI-GTV D50=56.3Gy [51.6Gy, 61.1Gy], γ=1.3 [0.8, 1.9].
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 gEUD2Gy. 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. The failure to identify any benefit for considering mpMRI-GTV as the target responsible for the clinical response is confirmed when considering a fixed α/β=1.6Gy, a fixed follow-up time for biochemical response at 5 years or Gleason score differentiation.
Keywords
Tumour control probability (TCP), linear-quadratic Poisson model, multivariate logistic regression model, therapy response prediction, prostate cancer
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CURRENT STATUS: Published
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Posted 25 Sep, 2020
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On 20 Oct, 2020
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Editorial decision: Accept
On 05 Oct, 2020
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Received 02 Oct, 2020
Reviewer #2 agreed
On 27 Sep, 2020
Reviewer #1 agreed
On 25 Sep, 2020
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Editor invited
On 22 Sep, 2020
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Editorial decision: Minor revision
On 10 Aug, 2020
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Received 06 Aug, 2020
Review #1 received
Received 30 Jul, 2020
Editor assigned
On 28 Jul, 2020
Reviewers invited
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Reviewer #1 agreed
On 28 Jul, 2020
Reviewer #2 agreed
On 28 Jul, 2020
Submission checks complete
On 27 Jul, 2020
Editor invited
On 27 Jul, 2020
No comments provided
Editorial decision: Major revision
On 25 Jun, 2020
Review #1 received
Received 24 Jun, 2020
Review #2 received
Received 24 Jun, 2020
Reviewer #2 agreed
On 12 Jun, 2020
Reviewer #1 agreed
On 10 Jun, 2020
Reviewers invited
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This preprint is under consideration at Radiation Oncology. A preprint is a preliminary version of a manuscript that has not completed peer review at a journal. Research Square does not conduct peer review prior to posting preprints. The posting of a preprint on this server should not be interpreted as an endorsement of its validity or suitability for dissemination as established information or for guiding clinical practice.
Learn more about In Review
Research
Prostate cancer tumour control probability modelling for external beam radiotherapy based on multi-parametric MRI-GTV definition
Ilias Sachpazidis
Department of Radiation Oncology, Division of Medical Physics, Medical Center, University of Freiburg
Corresponding Author
ORCiD: https://orcid.org/0000-0001-5701-8947
Badges
Prescreen
This manuscript passed our Prescreen assessment
Complete author information
Appropriate declaration statements
Potential risks to human health
Prescreen
Peer Review Timeline
CURRENT STATUS: Published
Version 3
Posted 25 Sep, 2020
Published
On 20 Oct, 2020
No community comments so far
Editorial decision: Accept
On 05 Oct, 2020
Review #1 received
Received 02 Oct, 2020
Review #2 received
Received 02 Oct, 2020
Reviewer #2 agreed
On 27 Sep, 2020
Reviewer #1 agreed
On 25 Sep, 2020
Reviewers invited
Invitations sent on 24 Sep, 2020
Editor assigned
On 23 Sep, 2020
Submission checks complete
On 22 Sep, 2020
Editor invited
On 22 Sep, 2020
No comments provided
Editorial decision: Minor revision
On 10 Aug, 2020
Review #2 received
Received 06 Aug, 2020
Review #1 received
Received 30 Jul, 2020
Editor assigned
On 28 Jul, 2020
Reviewers invited
Invitations sent on 28 Jul, 2020
Reviewer #1 agreed
On 28 Jul, 2020
Reviewer #2 agreed
On 28 Jul, 2020
Submission checks complete
On 27 Jul, 2020
Editor invited
On 27 Jul, 2020
No comments provided
Editorial decision: Major revision
On 25 Jun, 2020
Review #1 received
Received 24 Jun, 2020
Review #2 received
Received 24 Jun, 2020
Reviewer #2 agreed
On 12 Jun, 2020
Reviewer #1 agreed
On 10 Jun, 2020
Reviewers invited
Invitations sent on 14 May, 2020
First submitted
On 13 May, 2020
Editor assigned
On 13 May, 2020
Submission checks complete
On 12 May, 2020
Editor invited
On 12 May, 2020
Metrics
Comments: 0
PDF Downloads: ...
HTML Views: ...
Subject Areas
Oncology
License:
This work is licensed under a CC BY 4.0 License. Read Full License
View the published version at Radiation Oncology.
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=3.8 with 95%CI [2.6, 5.2]. 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=4.5 with 95%CI [3.0, 6.1]. 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=3.1 [2.0, 4.4], 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=0.8 [0.5, 1.2], α/β=0.0Gy (95%CI was undefined). For a follow-up time of 5 years and a fixed α/β=1.6Gy, the TCP fitting results for prostate gland were D50=63.9Gy [60.8Gy, 67.0Gy], γ=2.9 [1.9, 4.1], and for mpMRI-GTV D50=56.3Gy [51.6Gy, 61.1Gy], γ=1.3 [0.8, 1.9].
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 gEUD2Gy. 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. The failure to identify any benefit for considering mpMRI-GTV as the target responsible for the clinical response is confirmed when considering a fixed α/β=1.6Gy, a fixed follow-up time for biochemical response at 5 years or Gleason score differentiation.
Figure 1
Figure 2
Figure 3
Figure 4
Figure 5
Figure 6
Figure 7
Due to technical limitations, full-text HTML conversion of this manuscript could not be completed. However, the manuscript can be downloaded and accessed as a PDF.