scholarly journals Tumor Control Probability Modeling for Radiation Therapy of Keratinocyte Carcinoma

2021 ◽  
Vol 11 ◽  
Author(s):  
Phillip Prior ◽  
Musaddiq J. Awan ◽  
J Frank Wilson ◽  
X. Allen Li

SummarySkin cancer patients may be treated definitively using radiation therapy (RT) with electrons, kilovoltage, or megavoltage photons depending on tumor stage and invasiveness. This study modeled tumor control probability (TCP) based on the pooled clinical outcome data of RT for primary basal and cutaneous squamous cell carcinomas (BCC and cSCC, respectively). Four TCP models were developed and found to be potentially useful in developing optimal treatment schemes based on recommended ASTRO 2020 Skin Consensus Guidelines for primary, keratinocyte carcinomas (i.e. BCC and cSCC).BackgroundRadiotherapy (RT) with electrons or photon beams is an excellent primary treatment option for keratinocyte carcinoma (KC), particularly for non-surgical candidates. Our objective is to model tumor control probability (TCP) based on the pooled clinical data of primary basal and cutaneous squamous cell carcinomas (BCC and cSCC, respectively) in order to optimize treatment schemes.MethodsPublished reports citing crude estimates of tumor control for primary KCs of the head by tumor size (diameter: ≤2 cm and >2 cm) were considered in our study. A TCP model based on a sigmoidal function of biological effective dose (BED) was proposed. Three-parameter TCP models were generated for BCCs ≤2 cm, BCCs >2cm, cSCCs ≤2 cm, and cSCCs >2 cm. Equivalent fractionation schemes were estimated based on the TCP model and appropriate parameters.ResultsTCP model parameters for both BCC and cSCC for tumor sizes ≤2 cm and >2cm were obtained. For BCC, the model parameters were found to be TD50 = 56.62 ± 6.18 × 10-3 Gy, k = 0.14 ± 2.31 × 10−2 Gy−1 and L = 0.97 ± 4.99 × 10−3 and TD50 = 55.78 ± 0.19 Gy, k = 1.53 ± 0.20 Gy−1 and L = 0.94 ± 3.72 × 10−3 for tumor sizes of ≤2 cm and >2 cm, respectively. For SCC the model parameters were found to be TD50 = 56.81 ± 19.40 × 104 Gy, k = 0.13 ± 7.92 × 104 Gy−1 and L = 0.96 ± 1.31 × 10-2 and TD50 = 58.44 ± 0.30 Gy, k = 2.30 ± 0.43 Gy−1 and L = 0.91± 1.22 × 10−2 for tumors ≤2cm and >2 cm, respectively. The TCP model with the derived parameters predicts that radiation regimens with higher doses, such as increasing the number of fractions and/or dose per fraction, lead to higher TCP, especially for KCs >2 cm in size.ConclusionFour TCP models for primary KCs were developed based on pooled clinical data that may be used to further test the recommended kV and MV x-ray and electron RT regimens from the 2020 ASTRO guidelines. Increasing both number of fractions and dose per fraction may have clinically significant effects on tumor control for tumors >2 cm in size for both BCC and cSCC.

2019 ◽  
Vol 100 (5) ◽  
pp. 263-269
Author(s):  
E. S. Sukhikh ◽  
I. N. Sheyno ◽  
L. G. Sukhikh ◽  
A. V. Taletskiy ◽  
A. V. Vertinskiy ◽  
...  

Objective. To determine the most effective irradiation regimen (total dose and dose per fraction) for hypofractionated treatment for prostate carcinomas according the TCP/NTCP radiobiological criteria.Material and methods. Using the tomographic information of five patients with low-risk prostate adenocarcinoma as an example, the authors devised dosimetric radiation therapy plans using the volumetric modulated arc therapy (VMAT) procedure. They considered the range of total doses of 33.5 to 38 Gy administered in 4 and 5 fractions. Based on the equivalent uniform dose concept proposed by A. Niemierko and on the computed differential dose volume histograms, the investigators modeled local tumor control probability (TCP) values, by taking into account the uncertainties of main radiobiological parameters, and estimated normal tissue complication probabilities (NTCP) for the anterior rectal wall as the organ most at risk of irradiation. An effective dosimetric plan was selected according to the UTCP criterion and the probability of complication-free tumor control, i.e. TCP (1 – NTCP).Results. The results of modeling the UTCP criterion show that with a higher total dose, the TCP value increases and so does the NTCP value, therefore the optimal radiation therapy plans are to irradiate with a total dose of 34 Gy over 4 fractions or with a dose of 36–37 Gy over 5 fractions. The difference between the fractionation regimens is that the UTCP value is achieved with a higher TCP value over 4 fractions and with a lower load on the rectal wall over 5 fractions.Conclusion. The choice of a specific fractionation regimen should be determined from the calculated values of differential dose volume histograms for each patient, as well as from radiobiological criteria, such as TCP, NTCP and UTCP.


1998 ◽  
Vol 84 (2) ◽  
pp. 140-143 ◽  
Author(s):  
Andrzej Niemierko

Aims To present several biological concepts and models of tissue response to fractionated radiotherapy. To describe practical implementation of these models in three-dimensional treatment planning systems. Methods Models of cell survival, Equivalent Uniform Dose (EUD) and Tumor Control Probability (TCP) are discussed. These models are based on the target-cell hypothesis which assumes that response of organs and tissues to radiation therapy can be explained and mathematically described in terms of survival of the specific target-cells. Results Several formulae for deriving and calculating EUD and TCP for a given three-dimensional dose distribution are presented and discussed. Conclusions Biological models of tissue response to radiation, when used wisely, have a potential to be useful in radiation therapy treatment planning. The models can advance our understanding of the underlying biological mechanisms, and may help in designing new and better treatment strategies. They should be particularly useful in modern conformai radiotherapy where treatment strategy for each patient can be individualized and optimized according to patient characteristics and available technology of delivering sophisticated treatment plans.


2013 ◽  
Vol 39 (12) ◽  
pp. 1940-1943
Author(s):  
Christopher M. Wolfe ◽  
Harris W. Green ◽  
Armand B. Cognetta ◽  
Kaitlyn N. Mula

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