Relevant bibliographies by topics / Tumour control probability

Academic literature on the topic 'Tumour control probability'

Author: Grafiati
Published: 4 June 2021
Last updated: 29 January 2023

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Journal articles on the topic "Tumour control probability"

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Bassler, Niels, Jakob Toftegaard, Armin Lühr, Brita Singers Sørensen, Emanuele Scifoni, Michael Krämer, Oliver Jäkel, Lise Saksø Mortensen, Jens Overgaard, and Jørgen B. Petersen. "LET-painting increases tumour control probability in hypoxic tumours." Acta Oncologica 53, no. 1 (September 10, 2013): 25–32. http://dx.doi.org/10.3109/0284186x.2013.832835.

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Ebert, M. A., and P. W. Hoban. "Some characteristics of tumour control probability for heterogeneous tumours." Physics in Medicine and Biology 41, no. 10 (October 1, 1996): 2125–33. http://dx.doi.org/10.1088/0031-9155/41/10/019.

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Tarnawski, Rafal, Krzysztof Skladowski, and Andrzej Swierniak. "How Treatment Gaps Effect Tumour Control Probability." IFAC Proceedings Volumes 33, no. 3 (March 2000): 161–65. http://dx.doi.org/10.1016/s1474-6670(17)35507-6.

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Dhawan, Andrew, Mohammad Kohandel, Richard Hill, and Sivabal Sivaloganathan. "Tumour Control Probability in Cancer Stem Cells Hypothesis." PLoS ONE 9, no. 5 (May 8, 2014): e96093. http://dx.doi.org/10.1371/journal.pone.0096093.

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Maler, A., and F. Lutscher. "Cell-cycle times and the tumour control probability." Mathematical Medicine and Biology 27, no. 4 (December 6, 2009): 313–42. http://dx.doi.org/10.1093/imammb/dqp024.

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Gong, J., M. M. Dos Santos, C. Finlay, and T. Hillen. "Are more complicated tumour control probability models better?" Mathematical Medicine and Biology 30, no. 1 (October 17, 2011): 1–19. http://dx.doi.org/10.1093/imammb/dqr023.

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Malinen, E. "SP-0207: Image-based radiobiological tumour control probability modelling." Radiotherapy and Oncology 119 (April 2016): S94. http://dx.doi.org/10.1016/s0167-8140(16)31456-6.

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Levin-Plotnik, D., and R. J. Hamilton. "Optimization of tumour control probability for heterogeneous tumours in fractionated radiotherapy treatment protocols." Physics in Medicine and Biology 49, no. 3 (January 16, 2004): 407–24. http://dx.doi.org/10.1088/0031-9155/49/3/005.

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Wiklund, Kristin, Iuliana Toma-Dasu, and Bengt K. Lind. "Impact of Dose and Sensitivity Heterogeneity on TCP." Computational and Mathematical Methods in Medicine 2014 (2014): 1–7. http://dx.doi.org/10.1155/2014/182935.

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This present paper presents an analytical description and numerical simulations of the influence of macroscopic intercell dose variations and intercell sensitivity variations on the probability of controlling the tumour. Computer simulations of tumour control probability accounting for heterogeneity in dose and radiation sensitivity were performed. An analytical expression for tumor control probability accounting for heterogeneity in sensitivity was also proposed and validated against simulations. The results show good agreement between numerical simulations and the calculated TCP using the proposed analytical expression for the case of a heterogeneous dose and sensitivity distributions. When the intratumour variations of dose and sensitivity are taken into account, the total dose required for achieving the same level of control as for the case of homogeneous distribution is only slightly higher, the influence of the variations in the two factors taken into account being additive. The results of this study show that the interplay between cell or tumour variation in the sensitivity to radiation and the inherent heterogeneity in dose distribution is highly complex and therefore should be taken into account when predicting the outcome of a given treatment in terms of tumor control probability.
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Cho, G. A., M. A. Ebert, L. Holloway, Z. Kuncic, C. Baldock, and D. I. Thwaites. "Radiation treatment dose optimisation using Poisson tumour control probability parameters." Journal of Physics: Conference Series 489 (March 24, 2014): 012047. http://dx.doi.org/10.1088/1742-6596/489/1/012047.

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Dissertations / Theses on the topic "Tumour control probability"

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Buffa, Francesca Meteora. "Significance of hypoxia for tumour response to radiation : mathematical modelling and analysis of local control and clonogenic assay data." Thesis, Institute of Cancer Research (University Of London), 2001. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.272410.

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Kalyankuppam, Selvaraj Jothybasu. "Modelling the effect of geometric uncertainties, clonogen distribution and IMRT interplay effect on tumour control probability." Thesis, University of Liverpool, 2013. http://livrepository.liverpool.ac.uk/17533/.

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Geometric uncertainties are inevitable in radiotherapy. These uncertainties in tumour position are classified as systematic (Ε) and random (δ) errors. To account for these uncertainties, a margin is added to the clinical target volume (CTV) to create the planning target volume (PTV). The size of the PTV is critical for obtaining an optimal treatment plan. Dose-based (i.e., physical) margin recipes as a function of systematic and random errors based on coverage probability of a certain level of dose (90% or 95% of the prescription dose) have been published and widely used. However, with a TCP-based margin it is possible to consider fractionation and the radiobiological characteristics, especially the dose-response slope (50) of the tumour. Studies have shown that the density of the clonogens decrease from the boundary of the gross tumour volume (GTV). In such a scenario, dose that is lower than in the GTV should be sufficient to eradicate these clonogens. Thus a smaller PTV margin with a gradual dose fall off can be used if the clonogen density in the GTV-CTV region is found to be lower than in GTV. Studies have reported tiny tumour islets outside the CTV region. These tiny tumour islets can be eradicated in some cases by the incidental dose outside the PTV due to the nature of the photon beam irradiation, but if they are not in the beam path the treatment outcome is compromised. In this thesis, a Monte Carlo approach is used to simulate the effect of geometric uncertainties, number of fractions and dose-response slope (gamma50) using the 'enhanced Marsden' TCP model on the treatment outcome. Systematic and random errors were drawn from a pseudo-random number generator. The dose variations caused by tumour displacements due to geometric uncertainties in the CTV are accumulated each fraction on a voxel-by-voxel basis. Required margins for ≤ 1% mean population TCP (TCPpop) for four-field (4F) brick and a highly conformal spherical dose distribution for varying number of fractions, different γ50 and different combinations of Ε and δ are investigated. It is found that TCP-based margins are considerably smaller than dose-based recipes in most cases except for tumours with a steep dose-response slope (high γ50) and a small number of fractions for both 4F and spherical dose distributions. For smaller geometric uncertainties (Ε = δ = 1 mm) margins can be close to zero for the 4F technique due to high incidental dose outside the PTV. It is evident from the analyses that margins depend on the number of fractions, γ50, the degree of dose conformality in addition to Ε and δ. Ideally margins should be anisotropic and individualized, taking into account γ50, number of fractions, and the dose distribution, as well as estimates of Ε and γ. No single 'recipe' can adequately account for all these variables. Using an exponential clonogen distribution in the GTV-CTV region, possible PTV margin reduction is demonstrated. Moreover, the effect of extra-CTV tumour islets is studied using a prostate IMRT plan. The islets were randomly distributed around the CTV with in a radius of 3 cm to represent different patients. The doses were rescaled up to 102 Gy to obtain the dose-response curve (DRC). Interestingly, the obtained DRC showed a biphasic response where 100% TCP could not be achieved just by escalating the dose. Another potential problem encountered in intensity-modulated radiotherapy (IMRT) is the problems caused by the 'interplay' effect between the respiration-induced tumour motion and the multileaf collimator (MLC) leaves movement during treatment. Several dosimetric studies in the literature have shown that 'interplay' effects blur the dose distribution by producing 'hot' and 'cold' dose inside the tumour. Most of these studies were done in a phantom with ion chambers or films, which provide only 1D or 2D dose information. If 3D dose information is available, a TCP based analysis would provide a direct estimate of interplay on the clinical outcome. In this thesis, an in-house developed dose model enabled us to calculate the 3D time-resolved dose contribution to each voxel in the target volume considering the change in segment shapes and position of the target volume. Using the model, delivered dose is accumulated in a voxel-by-voxel basis inclusive of tumour motion over the course of treatment. The effect of interplay on dose and TCP is studied for conventionally and hypofractionated treatments using DICOM datasets. Moreover, the effect of dose rate on interplay is also studied for single-fraction treatments. Simulations were repeated several times to obtain mean population TCP (TCPpop) for each plan. The average variation observed in mean dose to the target volumes were -0.76 ± 0.36% for the 20 fraction treatment and -0.26 ± 0.68%, -1.05 ± 0.98% for the 3- and single-fraction treatments respectively. For the 20-fraction treatment, the drop in TCPpop was -1.05 ± 0.39%, whereas for the 3 and single fraction treatments it was -2.8 ± 1.68% and -4.0 ± 2.84% respectively. By reducing the dose rate from 600 to 300 MU/min for the single-fraction treatments, the drop in TCPpop was reduced by ~ 1:5%. In summary, the effect of interplay on treatment outcome is negligible for conventionally fractionated treatments, whereas a considerable drop in TCP is observed for the 3- and single-fraction treatments. Where no motion management techniques such as tracking or gating are available for hypo-fractionated treatments, reduced dose rate could be used to reduce the interplay effect.
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Hornby, Colin, and n/a. "Tumour Control and Normal Tissue Complication Probabilities: Can they be correlated with the measured clinical outcomes of prostate cancer radiotherapy?" RMIT University. Medical Sciences, 2006. http://adt.lib.rmit.edu.au/adt/public/adt-VIT20080702.123739.

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The chief aim in developing radiation treatment plans is to maximise tumour cell kill while minimising the killing of normal cells. The acceptance by a radiation oncologist of a radiation therapy treatment plan devised by the radiation therapist, at present is largely based on the oncologists' previous clinical experience with reference to established patterns of treatment and their clinical interpretation of the dose volume histogram. Some versions of radiotherapy planning computer software now incorporate a function that permits biologically based predictions about the probability of tumour control (TCP) and/or normal tissue complications (NTCP). The biological models used for these probabilities are founded upon statistical and mathematical principles as well as radiobiology concepts. TCP and NTCP potentially offer the capability of being able to better optimise treatments for an individual patient's tumour and normal anatomy. There have been few attempts in the past to correlate NTCPs to actual treatment complications, and the reported complications have generally not shown any significant correlation. Thus determining whether either or both NTCPs and TCPs could be correlated with the observed clinical outcomes of prostate radiotherapy is the central topic of this thesis. In this research, TCPs and NTCPs were prospectively calculated for prostate cancer patients receiving radiation therapy, and subsequently assessed against the clinical results of the delivered treatments. This research was conducted using two different types of NTCP models, which were correlated against observed treatment-induced complications in the rectum and bladder. The two NTCP models were also compared to determine their relative efficacy in predicting the recorded toxicities. As part of this research the refinement of some of the published bladder parameters required for NTCP calculations was undertaken to provide a better fit between predicted and observed complication rates for the bladder wall which was used in this research. TCPs were also calculated for each patient using the best available estimate of the radiosensitivity of the prostate gland from recent research. The TCP/NTCP data was analysed to determine if any correlations existed between the calculated probabilities and the observed clinical data. The results of the analyses showed that a correlation between the NTCP and a limited number of toxicities did occur. Additionally the NTCP predictions were compared to existing parameters and methods for radiotherapy plan evaluation - most notably DVHs. It is shown that NTCPs can provide superior discriminatory power when utilised for prospective plan evaluation. While the TCP could not be correlated with clinical outcomes due to insufficient follow-up data, it is shown that there was a correlation between the TCP and the treatment technique used.
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Lindblom, Emely. "The impact of hypoxia on tumour control probability in the high-dose range used in stereotactic body radiation therapy." Thesis, Stockholms universitet, Fysikum, 2012. http://urn.kb.se/resolve?urn=urn:nbn:se:su:diva-84518.

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The use of stereotactic body radiation therapy employing few large fractions of radiation dose for the treatment of non-small cell lung cancer has been proven very successful, high values of tumour control probability (TCP) being clinically achieved. In spite of the success of the fractionation schedules currently used, there is a tendency towards reducing the number of fractions for economical and practical reasons, and also for maximizing the comfort of the patients. It is therefore the main aim of this thesis to investigate the impact of a severely reduced number of fractions on the tumour control probability for tumours that contain hypoxic areas. The impact on TCP of other factors such as hypoxic fraction, distribution of the oxygen partial pressure and location of the hypoxic volume within the tumour were also investigated. The effect of tumour motion due to breathing was included and evaluated using Cone Beam Computed Tomography (CBCT) data from patients imaged with internal markers in the liver and pancreas. The results clearly showed that in the presence of hypoxia, TCP is seriously compromised if there is not enough time for reoxygenation between fractions. A reduction in the number of fractions of just one fraction may require an increase of several Gy per fraction to obtain a similar TCP. The diaphragmatic tumour motion range showed little influence on TCP provided that the PTV encompassed all tumour positions. The dose delivered to the PTV margin was found not to be the only factor that is significant for local control, the average dose correlated better with TCP. The agreement of the results of this work with clinical results also serve as a strong indicator that inter-fraction reoxygenation is an important process in real-life patients treated with stereotactic body radiotherapy.
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Herwiningsih, Sri. "Dosimetric verification of stereotactic body radiotherapy treatment plans for early stage non-small cell lung cancer using Monte Carlo simulation." Thesis, Queensland University of Technology, 2017. https://eprints.qut.edu.au/109755/1/Sri_Herwiningsih_Thesis.pdf.

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This thesis is an evaluation of the dosimetric accuracy of the dose calculation algorithm used for planning of lung stereotactic body radiotherapy treatments. It specifically investigates the accuracy of the collapsed cone convolution algorithm employed in the Pinnacle3 Radiotherapy Treatment Planning System by using Monte Carlo techniques as an independent verification tool. The thesis also investigates the impact of dose calculation uncertainties on treatment outcome estimation through the use of radiobiological modelling.
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Bloch, Jonatas Carrero. "Avaliação de técnicas radioterápicas conformacionais utilizando critérios físicos e biológicos." Universidade de São Paulo, 2012. http://www.teses.usp.br/teses/disponiveis/59/59135/tde-26062012-160955/.

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No combate às neoplasias, diferentes técnicas radioterápicas têm surgido, apoiadas em avanços tecnológicos, com o objetivo de otimizar a eliminação das células tumorais produzindo o menor dano a tecidos sadios dos pacientes. Os planejamentos de tratamentos radioterápicos visam o estabelecimento de parâmetros técnicos de irradiação de forma que as doses prescritas nos volumes de tratamento sejam atingidas. Enquanto que a prescrição das doses se baseiam em considerações biológicas de radiosensibilidade dos tecidos, os cálculos físicos do planejamento levam em conta parâmetros dosimétricos associados aos feixes de radiação e às características físicas dos tecidos irradiados. A incorporação de informações de sensibilidade de tecidos aos cálculos radioterápicos pode auxiliar na particularização de tratamentos e no estabelecimento de critérios de comparação e escolha de técnicas radioterápicas, contribuindo para o controle tumoral e sucesso do tratamento. Para tanto, modelos biológicos de resposta celular à radiação ionizante devem ser bem estabelecidos. Este trabalho visou estudar a aplicabilidade do uso de modelos biológicos em cálculos de planejamento radioterápico com objetivo de auxiliar na avaliação de técnicas radioterápicas. A probabilidade de controle tumoral (TCP) foi estudada para duas formulações do modelo linear-quadrático, com e sem consideração de repopulação celular, em função de parâmetros de planejamento, como dose por fração, e de parâmetros radiobiológicos, como a razão ?/?. Além disso, o uso de critérios biológicos para comparação de técnicas radioterápicas foi testado através da simulação de um planejamento de próstata utilizando simulação Monte Carlo com o código PENELOPE. Posteriormente, planejamentos radioterápicos de tumores de próstata de cinco pacientes do Hospital das Clínicas da Faculdade de Medicina de Ribeirão Preto, USP, utilizando-se três técnicas de irradiação diferentes, foram comparados através do critério de probabilidade de controle tumoral. Para tanto, matrizes de dose obtidas do sistema de planejamento radioterápico XiO foram utilizadas para obter as distribuições de TCP e histogramas TCP-volume. Os estudos realizados permitiram concluir que variações em parâmetros radiobiológicos podem influenciar significativamente cálculos de controle tumoral e que a análise de histogramas TCP-volume pode fornecer informações importantes para avaliação de tratamentos radioterápicos. Entretanto, o estabelecimento de fatores quantitativos de comparação através de critérios radiobiológicos passa pelo estabelecimento de protocolos de prescrição clínica baseados nesses critérios. Além disto, valores radiobiológicos sofreram grandes alterações na literatura recentemente e, portanto, a inclusão destes parâmetros nos cálculos de planejamentos requer grandes cuidados.
In the fight against cancer, different irradiation techniques have been developed based on technological advances and aiming to optimize the elimination of tumor cells with the lowest damage to healthy tissues. The radiotherapy planning goal is to establish irradiation technical parameters in order to achieve the prescribed dose distribution over the treatment volumes. While dose prescription is based on radiosensitivity of the irradiated tissues, the physical calculations on treatment planning take into account dosimetric parameters related to the radiation beam and the physical characteristics of the irradiated tissues. To incorporate tissue\'s radiosensitivity into radiotherapy planning calculations can help particularize treatments and establish criteria to compare and elect radiation techniques, contributing to the tumor control and the success of the treatment. Accordingly, biological models of cellular response to radiation have to be well established. This work aimed to study the applicability of using biological models in radiotherapy planning calculations to aid evaluating radiotherapy techniques. Tumor control probability (TCP) was studied for two formulations of the linear-quadratic model, with and without repopulation, as a function of planning parameters, as dose per fraction, and of radiobiological parameters, as the ?/? ratio. Besides, the usage of biological criteria to compare radiotherapy techniques was tested using a prostate planning simulated with Monte Carlo code PENELOPE. Afterwards, prostate plannings for five patients from the Hospital das Clínicas da Faculdadede Medicina de Ribeirão Preto, USP, using three different techniques were compared using the tumor control probability. In that order, dose matrices from the XiO treatment planning system were converted to TCP distributions and TCP-volume histograms. The studies performed allow the conclusions that radiobiological parameters can significantly influence tumor control calculations and that the TCP-volume histograms can provide important information for treatment techniques evaluation. However, the establishment of quantitative comparison parameters using radiobiological criteria demands the establishment of prescription protocols based on these same parameters. Also, the literature recently showed large variations in radiobiological parameters, meaning that the inclusion of those in treatment planning calculations should require a careful endeavor.
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Prescott, Kimberly B. "Studies of tumor control probability modeling in glioblastoma multiforme and optimization techniques in mammosite breast brachytherapy." Oklahoma City : [s.n.], 2008.

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胡寶文 and Po-man Wu. "The application of the tumor control probability model of nasopharyngeal carcinoma in three dimensional conformal treatment planevaluation." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 2000. http://hub.hku.hk/bib/B31241232.

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Wu, Po-man. "The application of the tumor control probability model of nasopharyngeal carcinoma in three dimensional conformal treatment plan evaluation /." Hong Kong : University of Hong Kong, 2000. http://sunzi.lib.hku.hk/hkuto/record.jsp?B22079063.

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Wiklund, Kristin. "Modeling of dose and sensitivity heterogeneities in radiation therapy." Doctoral thesis, Stockholms universitet, Fysikum, 2012. http://urn.kb.se/resolve?urn=urn:nbn:se:su:diva-74719.

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The increased interest in the use of light ion therapy is due to the high dose conformity to the target and the dense energy deposition along the tracks resulting in increased relative biological effectiveness compared to conventional radiation therapy. In spite of the good clinical experience, fundamental research on the characteristics of the ion beams is still needed in order to be able to fully explore their use. Therefore, a Monte Carlo track structure code, KITrack, simulating the transport of electrons in liquid water, has been developed and used for calculation of parameters of interest for beam characterization. The influence of the choice of the cross sections for the physical processes on the electron tracks has also been explored. As an alternative to Monte Carlo calculations a semi-analytical approach to calculate the radial dose distribution from ions, has been derived and validated. In advanced radiation therapy, accurate characterization of the beams has to be complemented by comprehensive radiobiological models, which relate the dose deposition into the cells to the outcome of the treatment. The second part of the study has therefore explored the influence of heterogeneity in the dose deposition into the cells as well as the heterogeneity in the cells sensitivity to radiation on the probability of controlling the tumor. Analytical expressions for tumor control probability including heterogeneous dose depositions or variation of radiation sensitivity of cells and tumors have been derived and validated with numerical simulations. The more realistic case of a combination of these effects has also been explored through numerical simulations. The MC code KITrack has evolved into an extremely useful tool for beam characterization. The tumor control probability, given by the analytical derived expression, can help improve radiation therapy. A novel anisotropy index has been proposed. It is a measure of the absence of isotropy and provides deeper understanding of the relationship between beam quality and biological effects.

At the time of the doctoral defense, the following paper was unpublished and had a status as follows: Paper 4: Manuscript.

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Books on the topic "Tumour control probability"

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Uusijärvi, Helena. Dosimetry and tumour control probability in radionuclide therapy: Influence of radionuclide properties and activity distribution. Göteborg: Göteborg University, 2007.

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Book chapters on the topic "Tumour control probability"

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Ureba, Ana, Jakob Ödén, Iuliana Toma-Dasu, and Marta Lazzeroni. "Photon and Proton Dose Painting Based on Oxygen Distribution – Feasibility Study and Tumour Control Probability Assessment." In Advances in Experimental Medicine and Biology, 223–28. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-031-14190-4_37.

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Lindblom, Emely, Iuliana Toma-Dasu, and Alexandru Dasu. "Accounting for Two Forms of Hypoxia for Predicting Tumour Control Probability in Radiotherapy: An In Silico Study." In Advances in Experimental Medicine and Biology, 183–87. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-91287-5_29.

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Ureba, Ana, Emely Kjellsson Lindblom, Iuliana Toma-Dasu, Alexandru Dasu, and Marta Lazzeroni. "Assessment of the Probability of Tumour Control for Prescribed Doses Based on Imaging of Oxygen Partial Pressure." In Advances in Experimental Medicine and Biology, 185–90. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-48238-1_29.

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Speer, Tod W., Rene Rubin, Iris Rusu, Iris Rusu, Yan Yu, Laura Doyle, Cheng B. Saw, et al. "Tumor Control Probability (TCP)." In Encyclopedia of Radiation Oncology, 921–22. Berlin, Heidelberg: Springer Berlin Heidelberg, 2013. http://dx.doi.org/10.1007/978-3-540-85516-3_666.

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El Naqa, Issam. "Modeling of Tumor Control Probability (TCP)." In Machine Learning in Radiation Oncology, 311–23. Cham: Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-18305-3_18.

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Nagano, H., S. Nakayama, H. Asada, T. Syutou, K. Tanahata, and S. Inomori. "Tumor Control Probability Predicts the Fate of Multiple Metastatic Brain Tumors." In Radiosurgery, 66–76. Basel: KARGER, 2004. http://dx.doi.org/10.1159/000078138.

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Toma-Dasu, I., M. Hedman, and A. Dasu. "The value of individual measurements for tumor control probability predictions in head and neck patients." In IFMBE Proceedings, 1675–78. Cham: Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-19387-8_407.

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"Tumor Control Probability." In Handbook of Disease Burdens and Quality of Life Measures, 4341. New York, NY: Springer New York, 2010. http://dx.doi.org/10.1007/978-0-387-78665-0_6829.

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"Uncomplicated Tumor Control Probability (P+)." In Handbook of Disease Burdens and Quality of Life Measures, 4342. New York, NY: Springer New York, 2010. http://dx.doi.org/10.1007/978-0-387-78665-0_6842.

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"Tumor Control and Normal Tissue Complication Probability Models in Radiation Therapy." In Tutorials in Radiotherapy Physics, 235–96. Boca Raton, FL : CRC Press, Taylor & Francis Group, 2016. |: CRC Press, 2016. http://dx.doi.org/10.1201/9781315381961-13.

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Conference papers on the topic "Tumour control probability"

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Sukhikh, Evgeniia S., Andrey V. Vertinskiy, Leonid G. Sukhikh, Alexandr V. Taletsky, and Mariya A. Tatarchenko. "INFLUENCE OF THE DISTANCE BETWEEN IMPLANTED SOURCES ON THE TUMOUR CONTROL PROBABILITY." In RAP Conference. Sievert Association, 2020. http://dx.doi.org/10.37392/rapproc.2019.36.

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Hyka, Niko, and Dafina Xhako. "New method to calculate the tumor control probability for PPIR." In TURKISH PHYSICAL SOCIETY 35TH INTERNATIONAL PHYSICS CONGRESS (TPS35). AIP Publishing, 2019. http://dx.doi.org/10.1063/1.5135450.

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Dinapoli, Nicola, Anna Rita Alitto, Mauro Vallati, Rosa Autorino, Roberto Gatta, Luca Boldrini, Andrea Damiani, Giovanna Mantini, and Vincenzo Valentini. "RadioBio data: A Moddicom Module to Predict Tumor Control Probability and Normal Tissue Complication Probability in Radiotherapy." In 9th International Conference on Health Informatics. SCITEPRESS - Science and and Technology Publications, 2016. http://dx.doi.org/10.5220/0005693502770281.

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Latha, C., and K. Perumal. "Improved probability based fuzzy C-means and active contour using brain tumor images." In 2017 IEEE International Conference on Power, Control, Signals and Instrumentation Engineering (ICPCSI). IEEE, 2017. http://dx.doi.org/10.1109/icpcsi.2017.8391839.

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Gupta, Vijay K., and Charles D. Eggleton. "A 3-D Computational Model of L-Selectin-PSGL-1 Dependent Homotypic Leukocyte Binding and Rupture in Shear Flow." In ASME 2012 Summer Bioengineering Conference. American Society of Mechanical Engineers, 2012. http://dx.doi.org/10.1115/sbc2012-80862.

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Abstract:
Cell adhesion plays a pivotal role in diverse biological processes, including inflammation, tumor metastasis, arteriosclerosis, and thrombosis. Changes in cell adhesion can be the defining event in a wide range of diseases, including cancer, atherosclerosis, osteoporosis, and arthritis. Cells are exposed constantly to hemodynamic/hydrodynamic forces and the balance between the dispersive hydrodynamic forces and the adhesive forces generated by the interactions of membrane-bound receptors and their ligands determines cell adhesion. Therefore to develop novel tissue engineering based approaches for therapeutic interventions in thrombotic disorders, inflammatory, and a wide range of other diseases, it is crucial to understand the complex interplay among blood flow, cell adhesion, and vascular biology at the molecular level. In response to tissue injury or infection, polymorphonuclear (PMN) leukocytes are recruited from the bloodstream to the site of inflammation through interactions between cell surface receptors and complementary ligands expressed on the surface of the endothelium [1]. PMN-PMN interactions also contribute to the process of recruitment. It has been shown that PMNs rolling on activated endothelium cells can mediate secondary capture of PMNs flowing in the free blood stream through homotypic interactions [2]. This is mediated by L-selectin (ligand) binding to PSGL-1 (receptor) between a free-stream PMN and one already adherent to the endothelium cells [3]. Both PSGL-1 and L-selectin adhesion molecules are concentrated on tips of PMN microvilli [4]. Homotypic PMN aggregation in vivo or in vitro is supported by multiple L-selectin–PSGL-1 bondings between pairs of microvilli. The ultimate objective of our work is to develop software that can simulate the adhesion of cells colliding under hydrodynamic forces that can be used to investigate the complex interplay among the physical mechanisms and scales involved in the adhesion process. However, cell-cell adhesion is a complex phenomenon involving the interplay of bond kinetics and hydrodynamics. Hence, as a first step we recently developed a 3-D computational model based on the Immersed Boundary Method to simulate adhesion-detachment of two PMN cells in quiescent conditions and the exposing the cells to external pulling forces and shear flow in order to investigate the behavior of the nano-scale molecular bonds to forces applied at the cellular scale [5]. Our simulations predicted that the total number of bonds formed is dependent on the number of available receptors (PSGL-1) when ligands (L-selectin) are in excess, while the excess amount of ligands controls the rate of bond formation [5]. Increasing equilibrium bond length causes an increased intercellular contact area hence results in a higher number of receptor-ligand bonds [5]. Off-rates control the average number of bonds by modulating bond lifetimes while On-rate constants determine the rate of bond formation [5]. An applied external pulling force leads to time-dependent on- and off-rates and causes bond rupture [5]. It was shown that the time required for bond rupture in response to an applied external force is inversely proportional to the applied external force and decreases with increasing offrate [5]. Fig. 1 shows the time evolution of the total number of bonds formed for various values of NRmv (number of receptor) and NLmv (number of ligand). As expected, the total number of bonds formed at equilibrium is dependent on NRmv when NLmv is in excess. In this particular case study since two pairs (or four) microvilli each with NRmv are involved in adhesion hence the equilibrium bond number is approximately 4NRmv. It is noticed that for NRmv = 50, as we vary NLmv the mean value of the total number of bonds at equilibrium does not change appreciably. However, it can be noticed from Fig. 1 that for NRmv = 50, as the excess number of ligands (NLmv) increases there is a slight increase in the rate of bond formation due to the increase in probability of bond formation. Having developed confidence in the ability of the numerical method to simulate the adhesion of two cells that can form up to 200 bonds, we apply the method to study the effect of shear rate on the detachment of two cells. In particular, we first would like to establish the minimum shear rate needed for the two cells to detach for a given number of bonds between them. Fig. 2 shows the variation of force per bond at no rupture with number of bonds for various shear rates indicated. It is seen that at a given shear rate as the number of bonds increases the force per bond at no rupture decreases. This is attributed to the fact that force caused by shear flow is shared equally among the existing bonds. Further, it is seen that a given number of bonds as the shear rate increases the force per bond at no rupture increases. This is due to the fact that at a given number of bonds between the cells as we increase the shear rate the force caused by the flow increases hence the force per bond increases. We further notice that at shear rate = 3000 s−1 cells attached either by a single bond or by two bonds detach while they don’t for higher (> 2) number of bonds. This clearly demonstrate that there is a minimum shear rate needed to detach cells adhered by a given number of bonds. The higher the number of bonds, the higher the minimum shear rate for complete detachment of cells. For example, from Fig. 2 is it clear that for the cells adhered by two and five bonds the minimum shear rate needed for complete detachment of these two cells are 3000 s−1 and 6000 s−1, respectively.
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