Tumour control probability of a UK cohort of lung SABR patients

2020 ◽  
pp. 1-3
Author(s):  
J. E. Marsden
Keyword(s):  
The Other ◽  
Stereotactic Ablative Radiotherapy ◽  
Linear Quadratic ◽  
Planning Techniques ◽  
Tumour Control ◽  
Tumour Control Probability ◽  
The Uk

Abstract Aims: The aim of this work is to report on the tumour control probability (TCP) of a UK cohort of lung stereotactic ablative radiotherapy patients (n = 198) for a range of dose and fractionations common in the UK. Materials and methods: TCP values for 3 (54 Gy), 5 (55 and 60 Gy) and 8 (50 Gy) fraction (#) schemes were calculated with the linear-quadratic Marsden TCP model using the Biosuite software. Results: TCP values of 100% were computed for the 3 # and for 5 # (α/β = 10 Gy) cohorts; reduced to 99% (range 97–100) for the 5 # cohort only when an α/β of 20 Gy was used. The average TCP value for the 50 Gy in 8 # regime was 97% (range 92–99, α/β = 10 Gy) and 64% (range 48–79, α/β = 20 Gy). Statistical significant differences were observed between the α/β of 10 Gy versus 20 Gy groups and between all data grouped by fraction. Conclusion: TCPs achievable with current planning techniques in the UK have been presented. The ultra-conservative 50 Gy in 8 # scheme returns a significantly lower TCP than the other regimes.

scholarly journals Prostate cancer tumour control probability modelling for external beam radiotherapy based on multi-parametric MRI-GTV definition

2020 ◽  
Author(s):  
Ilias Sachpazidis ◽  
Panayiotis Mavroidis ◽  
Constantinos Zamboglou ◽  
Christina Marie Klein ◽  
Anca-Ligia Grosu ◽  
...  
Keyword(s):  
Prostate Cancer ◽  
Logistic Model ◽  
Radiation Treatment ◽  
Prostate Gland ◽  
Biochemical Relapse ◽  
Linear Quadratic ◽  
Tumour Control ◽  
Tumour Control Probability ◽  
Multivariate Logistic Model

Abstract 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.

scholarly journals Radiobiological Evaluation of Combined Gamma Knife Radiosurgery and Hyperthermia for Pediatric Neuro-Oncology

Cancers ◽  
2021 ◽  
Vol 13 (13) ◽  
pp. 3277
Author(s):  
Morteza Ghaderi Aram ◽  
Massimiliano Zanoli ◽  
Håkan Nordström ◽  
Iuliana Toma-Dasu ◽  
Klas Blomgren ◽  
...  
Keyword(s):  
Brain Tumour ◽  
Gamma Knife ◽  
Gamma Knife Radiosurgery ◽  
Linear Quadratic ◽  
Temperature Dependent ◽  
Malignant Brain Tumour ◽  
Tumour Control ◽  
Tumour Control Probability ◽  
Quantitative Metrics ◽  
Wide Range

Combining radiotherapy (RT) with hyperthermia (HT) has been proven effective in the treatment of a wide range of tumours, but the combination of externally delivered, focused heat and stereotactic radiosurgery has never been investigated. We explore the potential of such treatment enhancement via radiobiological modelling, specifically via the linear-quadratic (LQ) model adapted to thermoradiotherapy through modulating the radiosensitivity of temperature-dependent parameters. We extend this well-established model by incorporating oxygenation effects. To illustrate the methodology, we present a clinically relevant application in pediatric oncology, which is novel in two ways. First, it deals with medulloblastoma, the most common malignant brain tumour in children, a type of brain tumour not previously reported in the literature of thermoradiotherapy studies. Second, it makes use of the Gamma Knife for the radiotherapy part, thereby being the first of its kind in this context. Quantitative metrics like the biologically effective dose (BED) and the tumour control probability (TCP) are used to assess the efficacy of the combined plan.

scholarly journals Prostate cancer tumour control probability modelling for external beam radiotherapy based on multi-parametric MRI-GTV definition

2020 ◽  
Author(s):  
Ilias Sachpazidis ◽  
Panayiotis Mavroidis ◽  
Constantinos Zamboglou ◽  
Christina Marie Klein ◽  
Anca-Ligia Grosu ◽  
...  
Keyword(s):  
Prostate Cancer ◽  
Cancer Patients ◽  
Radiation Treatment ◽  
Prostate Gland ◽  
Multivariate Logistic Regression Model ◽  
Biochemical Relapse ◽  
Linear Quadratic ◽  
Tumour Control ◽  
Tumour Control Probability

Abstract 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.

scholarly journals Prostate cancer tumour control probability modelling for external beam radiotherapy based on multi-parametric MRI-GTV definition

2020 ◽  
Vol 15 (1) ◽  
Author(s):  
Ilias Sachpazidis ◽  
Panayiotis Mavroidis ◽  
Constantinos Zamboglou ◽  
Christina Marie Klein ◽  
Anca-Ligia Grosu ◽  
...  
Keyword(s):  
Prostate Cancer ◽  
Cancer Patients ◽  
Radiation Treatment ◽  
Prostate Gland ◽  
Multivariate Logistic Regression Model ◽  
Biochemical Relapse ◽  
Linear Quadratic ◽  
Tumour Control ◽  
Tumour Control Probability

Abstract 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 = 64.6 Gy [61.6 Gy, 67.4 Gy], γ = 3.1 [2.0, 4.4], α/β = 2.2 Gy (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 = 50.1 Gy [44.6 Gy, 56.0 Gy], γ = 0.8 [0.5, 1.2], α/β = 0.0 Gy (95% CI was undefined). For a follow-up time of 5 years and a fixed α/β = 1.6 Gy, the TCP fitting results for prostate gland were D50 = 63.9 Gy [60.8 Gy, 67.0 Gy], γ = 2.9 [1.9, 4.1], and for mpMRI-GTV D50 = 56.3 Gy [51.6 Gy, 61.1 Gy], 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 = 1.6 Gy, a fixed follow-up time for biochemical response at 5 years or Gleason score differentiation.

scholarly journals Prostate cancer tumour control probability modelling for external beam radiotherapy based on multi-parametric MRI-GTV definition

2020 ◽  
Author(s):  
Ilias Sachpazidis ◽  
Panayiotis Mavroidis ◽  
Constantinos Zamboglou ◽  
Christina Marie Klein ◽  
Anca-Ligia Grosu ◽  
...  
Keyword(s):  
Prostate Cancer ◽  
Cancer Patients ◽  
Logistic Model ◽  
External Beam Radiotherapy ◽  
Prostate Gland ◽  
Biochemical Relapse ◽  
Linear Quadratic ◽  
Tumour Control ◽  
Tumour Control Probability ◽  
Multivariate Logistic Model

Abstract 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.Results: 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 gEUD 2Gy 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 D 50 = 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, D 50 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 gEUD 2Gy 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).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.

scholarly journals Changes in radiobiological parameters in 131Cs permanent prostate implants

2013 ◽  
Vol 12 (1) ◽  
pp. 66-79
Author(s):  
Than S. Kehwar ◽  
Heather A. Jones ◽  
M. Saiful Huq ◽  
Ryan P. Smith
Keyword(s):  
Dose Reduction ◽  
Real Time ◽  
Prostate Volume ◽  
Linear Quadratic ◽  
Tumour Control ◽  
Tumour Control Probability ◽  
Permanent Implants ◽  
Prostate Implants ◽  
The Impact ◽  
Dose Reductions

AbstractIn prostate permanent implants using 131Cs seeds, the prostatic edema developed during the implantation procedure, increases the separation between the seeds. This leads to a decrease in the prostate coverage and thus causes an edema induced dose reduction, which results in an increase in tumour cell surviving fraction (SF) with a corresponding decrease in tumour control probability (TCP). To investigate the impact of edema on the SF and the TCP, the expression of the SF of the linear quadratic (LQ) model was extended to account for the effects of edema using the exponential nature of edema resolution and the dose delivered to the edematous prostate. The SF and the TCP for edematous prostate implants were calculated for 31 patients who underwent real time 131Cs permanent seed implantation. The dose delivered to the edematous prostate was calculated to compute the SF and the TCP for these patients for edema half lives (EHL) ranging from 4 days to 34 days and for edemas of magnitudes (M0) varying from 5 to 60% of the actual prostate volume.A reduction in the dose delivered to the edematous prostate was found with the increase of EHL and edema magnitude which results in an increase of the SF, and corresponding decrease in the TCP. The dose reductions in 131Cs implants varied from 1.1% (for EHL = 4 days and M0 = 5%) to 32.3% (for EHL = 34 days and M0 = 60%). These are higher than the dose reduction in 125I implants, which vary from 0.3% (for EHL = 4 days and M0 = 5%) to 17.5% (for EHL = 34 days and M0 = 60%). As edema half life increased from 4 days to 34 days and edema magnitude increased from 5 to 60% the SF increased by 4.57 log, and the TCP decreased by 0.80. Compensation of edema induced increase in the SF and decrease in the TCP in 131Cs seed implants should be carefully done by redefining seed positions with the guidance of post-needle plans. The presented model in this study can be used to estimate the SF or the TCP for pre plan or real time permanent prostate implants using day 0 post-implant CT images.

scholarly journals Derivation of the Tumour Control Probability (TCP) from a Cell Cycle Model

2006 ◽  
Vol 7 (2-3) ◽  
pp. 121-141 ◽  
Author(s):  
A. Dawson ◽  
T. Hillen
Keyword(s):  
Cell Cycle ◽  
Radiation Treatment ◽  
Malignant Cell ◽  
Time Dependent ◽  
Death Process ◽  
Linear Quadratic ◽  
Tumour Control ◽  
Tumour Control Probability ◽  
A Cell ◽  
General Time

In this paper, a model for the radiation treatment of cancer which includes the effects of the cell cycle is derived from first principles. A malignant cell population is divided into two compartments based on radiation sensitivities. The active compartment includes the four phases of the cell cycle, while the quiescent compartment consists of theG0state. Analysis of this active-quiescent radiation model confirms the classical interpretation of the linear quadratic (LQ) model, which is that a larger α/β ratio corresponds to a fast cell cycle, while a smaller ratio corresponds to a slow cell cycle. Additionally, we find that a large α/β ratio indicates the existence of a significant quiescent phase. The active-quiescent model is extended as a nonlinear birth–death process in order to derive an explicit time dependent expression for the tumour control probability (TCP). This work extends the TCP formula from Zaider and Minerbo and it enables the TCP to be calculated for general time dependent treatment schedules.

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