Generalization of a model of tissue response to radiation based on the idea of functional subunits and binomial statistics<sup>†</sup>

Stavrev, Pavel; Stavreva, N; Niemierko, Andrzej; Goitein, Michael

doi:10.1088/0031-9155/46/5/312

Cited by 52 publications

(40 citation statements)

References 20 publications

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“…The normal tissue complication probability (NTCP) is used as a measure for the sensitivity of normal tissue for a given radiation treatment schedule. NTCP models are based on the damage probability of so called "functional subunits" (FSU) [8,18]. Of course, it is desirable to achieve a TCP close to 1, however, at the same time the NTCP must be at an acceptably low level.…”

Section: 34mentioning

confidence: 99%

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

Dawson

Hillen

2006

Computational and Mathematical Methods in Medicine

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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 the G 0 state. Analysis of this active-quiescent radiation model confirms the classical interpretation of the linear quadratic (LQ) model, which is that a larger a /b ratio corresponds to a fast cell cycle, while a smaller ratio corresponds to a slow cell cycle. Additionally, we find that a large a /b 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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Section: 34mentioning

confidence: 99%

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

Dawson

Hillen

2006

Computational and Mathematical Methods in Medicine

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“…Other methods of reducing DVHs to a single dose or volume parameter have been proposed. The work of Cozzi et al (13) suggested that most current DVH reduction schemes are somewhat error‐prone because they can lead to DVH reductions inconsistent with the expected biological effect. The KB method was found to be one of the more robust of the available DVH reduction schemes.…”

Section: Methodsmentioning

confidence: 99%

A TCP‐NTCP estimation module using DVHs and known radiobiological models and parameter sets

Warkentin

Stavrev

Stavreva

et al. 2004

J Applied Clin Med Phys

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Radiotherapy treatment plan evaluation relies on an implicit estimation of the tumor control probability (TCP) and normal tissue complication probability (NTCP) arising from a given dose distribution. A potential application of radiobiological modeling to radiotherapy is the ranking of treatment plans via a more explicit determination of TCP and NTCP values. Although the limited predictive capabilities of current radiobiological models prevent their use as a primary evaluative tool, radiobiological modeling predictions may still be a valuable complement to clinical experience. A convenient computational module has been developed for estimating the TCP and the NTCP arising from a dose distribution calculated by a treatment planning system, and characterized by differential (frequency) dose‐volume histograms (DDVHs). The radiobiological models included in the module are sigmoidal dose response and Critical Volume NTCP models, a Poisson TCP model, and a TCP model incorporating radiobiological parameters describing linear‐quadratic cell kill and repopulation. A number of sets of parameter values for the different models have been gathered in databases. The estimated parameters characterize the radiation response of several different normal tissues and tumor types. The system also allows input and storage of parameters by the user, which is particularly useful because of the rapidly increasing number of parameter estimates available in the literature. Potential applications of the system include the following: comparing radiobiological predictions of outcome for different treatment plans or types of treatment; comparing the number of observed outcomes for a cohort of patient DVHs to the predicted number of outcomes based on different models/parameter sets; and testing of the sensitivity of model predictions to uncertainties in the parameter values. The module thus helps to amalgamate and make more accessible current radiobiological modeling knowledge, and may serve as a useful aid in the prospective and retrospective analysis of radiotherapy treatment plans.PACS number: 87.53.Tf

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“…The number of clonogenic cells can be determined using some of the following relations:) (43)(44)(45) (5) (6) where D 50 is the tumor dose required to obtain a TCP of 50%. In addition, an expression for TCP may be obtained if data of clonogenic cells are not available, in terms of sigmoidal dose response parameters as (43,44,46) (sigmoidal model for TCP):…”

Section: C2 Tcpmentioning

confidence: 99%

“…In addition, an expression for TCP may be obtained if data of clonogenic cells are not available, in terms of sigmoidal dose response parameters as (43,44,46) (sigmoidal model for TCP):…”

Section: C2 Tcpmentioning

confidence: 99%

Assessment of radiobiological metrics applied to patient‐specific QA process of VMAT prostate treatments

Clemente-Gutiérrez

Perez-Vara

Clavo-Herranz

et al. 2016

J Applied Clin Med Phys

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VMAT is a powerful technique to deliver hypofractionated prostate treatments. The lack of correlations between usual 2D pretreatment QA results and the clinical impact of possible mistakes has allowed the development of 3D verification systems. Dose determination on patient anatomy has provided clinical predictive capability to patient-specific QA process. Dose-volume metrics, as evaluation criteria, should be replaced or complemented by radiobiological indices. These metrics can be incorporated into individualized QA extracting the information for response parameters (gEUD, TCP, NTCP) from DVHs. The aim of this study is to assess the role of two 3D verification systems dealing with radiobiological metrics applied to a prostate VMAT QA program. Radiobiological calculations were performed for AAPM TG-166 test cases. Maximum differences were 9.3% for gEUD, -1.3% for TCP, and 5.3% for NTCP calculations. Gamma tests and DVH-based comparisons were carried out for both systems in order to assess their performance in 3D dose determination for prostate treatments (high-, intermediate-, and low-risk, as well as prostate bed patients). Mean gamma passing rates for all structures were better than 92.0% and 99.1% for both 2%/2 mm and 3%/3 mm criteria. Maximum discrepancies were (2.4% ± 0.8%) and (6.2% ± 1.3%) for targets and normal tissues, respectively. Values for gEUD, TCP, and NTCP were extracted from TPS and compared to the results obtained with the two systems. Three models were used for TCP calculations (Poisson, sigmoidal, and Niemierko) and two models for NTCP determinations (LKB and Niemierko). The maximum mean difference for gEUD calculations was (4.7% ± 1.3%); for TCP, the maximum discrepancy was (-2.4% ± 1.1%); and NTCP comparisons led to a maximum deviation of (1.5% ± 0.5%). The potential usefulness of biological metrics in patient-specific QA has been explored. Both systems have been successfully assessed as potential tools for evaluating the clinical outcome of a radiotherapy treatment in the scope of pretreatment QA.

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Generalization of a model of tissue response to radiation based on the idea of functional subunits and binomial statistics^†

Cited by 52 publications

References 20 publications

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

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

A TCP‐NTCP estimation module using DVHs and known radiobiological models and parameter sets

Assessment of radiobiological metrics applied to patient‐specific QA process of VMAT prostate treatments

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Generalization of a model of tissue response to radiation based on the idea of functional subunits and binomial statistics†

Cited by 52 publications

References 20 publications

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

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

A TCP‐NTCP estimation module using DVHs and known radiobiological models and parameter sets

Assessment of radiobiological metrics applied to patient‐specific QA process of VMAT prostate treatments

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Product

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Generalization of a model of tissue response to radiation based on the idea of functional subunits and binomial statistics^†