A novel analytical population tumor control probability model includes cell density and volume variations: application to canine brain tumor
| Autor: | Uwe Schneider, Stephan Radonic, Valeria Meier, Jürgen Besserer, Carla Rohrer Bley |
|---|---|
| Přispěvatelé: | University of Zurich, Radonic, Stephan |
| Rok vydání: | 2021 |
| Předmět: |
Cancer Research
Exponential distribution 10253 Department of Small Animals Cell Survival Population Cell Count Poisson distribution Logistic regression 030218 nuclear medicine & medical imaging 03 medical and health sciences symbols.namesake Dogs 0302 clinical medicine Cell density Animals Medicine Applied mathematics 2741 Radiology Nuclear Medicine and Imaging Radiology Nuclear Medicine and imaging 1306 Cancer Research Dog Diseases Poisson Distribution education education.field_of_study Models Statistical Radiation 630 Agriculture Brain Neoplasms business.industry Radiobiology Tumor control Tumor Burden 3108 Radiation Distribution (mathematics) Volume (thermodynamics) Oncology Radiology Nuclear Medicine and imaging 030220 oncology & carcinogenesis Linear Models symbols 570 Life sciences biology Radiation Dose Hypofractionation 2730 Oncology business |
| DOI: | 10.5167/uzh-209922 |
| Popis: | Purpose Tumor control probability (TCP) models based on Poisson statistics characterize the distribution of surviving clonogens. Thus enabling the calculation of TCP for individuals. To mathematically describe clinically observed survival data of patient cohorts it is necessary to extend the Poisson TCP model. This is typically done by either incorporating variations of model parameters or by using an empirical logistic model. The purpose of this work is the development of an analytical population TCP model by mechanistic extension of the Possion model. Methods and Materials The frequency distribution of gross tumor volumes was used to incorporate tumor volume variations into the TCP model. Additionally the tumor cell density variation was incorporated. Both versions of the population TCP model were fitted to clinical data and compared to existing literature. Results It was shown that clinically observed brain tumor volumes of dogs undergoing radiotherapy are distributed according to an exponential distribution. The average gross tumor volume size was 3.37 cm3. Fitting the population TCP model including the volume variation using linear-quadratic and track-event model yielded α = 0.36 G y − 1 a , β = 0.045 G y − 2 , a = 0.9 y r − 1 , T D = 5.0 d , and p = . 36 G y − 1 , q = 0.48 G y − 1 , a = 0.80 y r − 1 , T D = 3.0 d , respectively. Fitting the population TCP model including both the volume and cell density variation yielded α = 0.43 G y − 1 , β = 0.0537 G y − 2 , a = 2.0 y r − 1 , T D = 3.0 d , σ = 2.5 , and p = . 43 G y − 1 , q = 0.55 G y − 1 , a = 2.0 y r − 1 , T D = 2.0 d , σ = 3.0 , respectively. Conclusions Two sets of radiobiological parameters were obtained which can be used for quantifying the TCP for radiation therapy of brain tumors in dogs. We established a mechanistic link between the poisson statistics based individual TCP model and the logistic TCP model. This link can be used to determine the radiobiological parameters of patient specific TCP models from published fits of logistic models to cohorts of patients. |
| Databáze: | OpenAIRE |
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