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Journal articles on the topic 'Distributions de dose'

Author: Grafiati

Published: 7 July 2024

Last updated: 31 July 2025

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1

Beckett, Craig, and Peter Dickof. "Mapping dose distributions." Medical Physics 25, no. 10 (1998): 1944–53. http://dx.doi.org/10.1118/1.598384.

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2

Dutreix, Andree. "3D Dose Distributions." Journal of Medical Physics 11, no. 3 (1986): 166. http://dx.doi.org/10.4103/0971-6203.50340.

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3

Pike, G. Bruce, Ervin B. Podgorsak, Terence M. Peters, Conrado Pla, André Olivier, and Luis Souhami. "Dose distributions in radiosurgery." Medical Physics 17, no. 2 (1990): 296–304. http://dx.doi.org/10.1118/1.596508.

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4

Placidi, Lorenzo, Eliana Gioscio, Cristina Garibaldi, et al. "A Multicentre Evaluation of Dosiomics Features Reproducibility, Stability and Sensitivity." Cancers 13, no. 15 (2021): 3835. http://dx.doi.org/10.3390/cancers13153835.

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Dosiomics is a texture analysis method to produce dose features that encode the spatial 3D distribution of radiotherapy dose. Dosiomic studies, in a multicentre setting, require assessing the features’ stability to dose calculation settings and the features’ capability in distinguishing different dose distributions. Dose distributions were generated by eight Italian centres on a shared image dataset acquired on a dedicated phantom. Treatment planning protocols, in terms of planning target volume coverage and dose–volume constraints to the organs at risk, were shared among the centres to produc

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5

Low, Daniel A., Delphine Morele, Philip Chow, Tai H. Dou та Tao Ju. "Does the γ dose distribution comparison technique default to the distance to agreement test in clinical dose distributions?" Medical Physics 40, № 7 (2013): 071722. http://dx.doi.org/10.1118/1.4811141.

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6

Bak, Jino, Jin Hwa Choi, Jae-Sung Kim, and Suk Won Park. "Modified dose difference method for comparing dose distributions." Journal of Applied Clinical Medical Physics 13, no. 2 (2012): 73–80. http://dx.doi.org/10.1120/jacmp.v13i2.3616.

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7

Vaas, L. H., R. O. Blaauboer, and H. P. Leenhouts. "Radiation Sources, Doses and Dose Distributions in the Netherlands." Radiation Protection Dosimetry 36, no. 2-4 (1991): 89–92. http://dx.doi.org/10.1093/oxfordjournals.rpd.a080974.

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8

Vaas, L. H., R. O. Blaauboer, and H. P. Leenhouts. "Radiation Sources, Doses and Dose Distributions in the Netherlands." Radiation Protection Dosimetry 36, no. 2-4 (1991): 89–92. http://dx.doi.org/10.1093/rpd/36.2-4.89.

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9

Keall, P., S. Zavgorodni, L. Schmidt, and D. Haskard. "Improving wedged field dose distributions." Physics in Medicine and Biology 42, no. 11 (1997): 2183–92. http://dx.doi.org/10.1088/0031-9155/42/11/013.

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10

Cross, W. G., J. Böhm, M. Charles, E. Piesch, and S. M. Seltzer. "6. Calculation of Dose Distributions." Journal of the International Commission on Radiation Units and Measurements os29, no. 1 (1997): 18–32. http://dx.doi.org/10.1093/jicru/os29.1.18.

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11

Cross, W. G., J. Böhm, M. Charles, E. Piesch, and S. M. Seltzer. "6. Calculation of Dose Distributions." Reports of the International Commission on Radiation Units and Measurements os-29, no. 1 (1997): 18–32. http://dx.doi.org/10.1093/jicru_os29.1.18.

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12

Pla, Conrado, Michael D. C. Evans, and Ervin B. Podgorsak. "Dose distributions around selectron applicators." International Journal of Radiation Oncology*Biology*Physics 13, no. 11 (1987): 1761–66. http://dx.doi.org/10.1016/0360-3016(87)90175-1.

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13

Pla, Conrado, Michael D. C. Evans, and Ervin B. Podgorsak. "Dose Distributions Around Selectron Applicators." Medical Dosimetry 13, no. 2 (1988): 102. http://dx.doi.org/10.1016/0958-3947(88)90045-3.

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14

Al Hakim, Reza Azizul Nasa, Sigit Arrohman, Eko Saputra, et al. "The Contact Simulation Comparison of UHMWPE to the Crosslink Intensity Effect." E3S Web of Conferences 73 (2018): 12014. http://dx.doi.org/10.1051/e3sconf/20187312014.

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Ultra High Molecular Weight Polyethylene called UHMWPE is a unique polymer material that has excellent physical and mechanical properties. UHMWPE material is frequently used in prosthesis. One example of UHMWPE uses in prosthesis is acetabular liner which is one component for Total Hip Joint Replacement (THR) and can also be found for bearing surfaces on the knee, ankle, shoulder, and connective tissue of the joint. UHMWPE material is made by compression molding process. However, UHMWPE wear often causes the failure of artificial hip joints. Therefore, a treatment to reduce the crosslink metho

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15

Yamada, Takahiro, Seishin Takao, Hidenori Koyano, et al. "Validation of dose distribution for liver tumors treated with real-time-image gated spot-scanning proton therapy by log data based dose reconstruction." Journal of Radiation Research 62, no. 4 (2021): 626–33. http://dx.doi.org/10.1093/jrr/rrab024.

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Abstract In spot scanning proton therapy (SSPT), the spot position relative to the target may fluctuate through tumor motion even when gating the radiation by utilizing a fiducial marker. We have established a procedure that evaluates the delivered dose distribution by utilizing log data on tumor motion and spot information. The purpose of this study is to show the reliability of the dose distributions for liver tumors treated with real-time-image gated SSPT (RGPT). In the evaluation procedure, the delivered spot information and the marker position are synchronized on the basis of log data on

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16

Komemushi, Atsushi, Noboru Tanigawa, Shuji Kariya, et al. "Does Vertebroplasty Affect Radiation Dose Distribution?: Comparison of Spatial Dose Distributions in a Cement-Injected Vertebra as Calculated by Treatment Planning System and Actual Spatial Dose Distribution." Radiology Research and Practice 2012 (2012): 1–6. http://dx.doi.org/10.1155/2012/571571.

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Purpose. To assess differences in dose distribution of a vertebral body injected with bone cement as calculated by radiation treatment planning system (RTPS) and actual dose distribution.Methods. We prepared two water-equivalent phantoms with cement, and the other two phantoms without cement. The bulk density of the bone cement was imported into RTPS to reduce error from high CT values. A dose distribution map for the phantoms with and without cement was calculated using RTPS with clinical setting and with the bulk density importing. Actual dose distribution was measured by the film density. D

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17

Fenwick, John D., Wolfgang A. Tomé, Michael W. Kissick, and T. Rock Mackie. "Modelling simple helically delivered dose distributions." Physics in Medicine and Biology 50, no. 7 (2005): 1505–17. http://dx.doi.org/10.1088/0031-9155/50/7/013.

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18

Pike, Bruce, Ervin B. Podgorsak, Terence M. Peters, and Conrado Pla. "Dose distributions in dynamic stereotactic radiosurgery." Medical Physics 14, no. 5 (1987): 780–89. http://dx.doi.org/10.1118/1.596003.

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19

Ayadi, M., D. Sarrut, and C. Ginestet. "SU-FF-T-154: Cumulating Static Dose Distributions to Simulate Dynamic Dose Distributions: An Experimental Study." Medical Physics 33, no. 6Part9 (2006): 2084. http://dx.doi.org/10.1118/1.2241078.

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20

Van de Kamer, Jeroen B., Astrid A. C. De Leeuw, Marinus A. Moerland, Arjan Bel, and Ina M. Jurgenliemk-Schulz. "Adding MRI-based 3D brachytherapy dose distributions to 3D IMRT dose distributions in cervical cancer patients." Brachytherapy 7, no. 2 (2008): 123–24. http://dx.doi.org/10.1016/j.brachy.2008.02.097.

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21

van Dijk, Robert H. W., Nick Staut, Cecile J. A. Wolfs, and Frank Verhaegen. "A novel multichannel deep learning model for fast denoising of Monte Carlo dose calculations: preclinical applications." Physics in Medicine & Biology 67, no. 16 (2022): 164001. http://dx.doi.org/10.1088/1361-6560/ac8390.

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Abstract Objective. In preclinical radiotherapy with kilovolt (kV) x-ray beams, accurate treatment planning is needed to improve the translation potential to clinical trials. Monte Carlo based radiation transport simulations are the gold standard to calculate the absorbed dose distribution in external beam radiotherapy. However, these simulations are notorious for their long computation time, causing a bottleneck in the workflow. Previous studies have used deep learning models to speed up these simulations for clinical megavolt (MV) beams. For kV beams, dose distributions are more affected by

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22

Radojcic, Đeni Smilovic, David Rajlic, Bozidar Casar, et al. "Evaluation of two-dimensional dose distributions for pre-treatment patient-specific IMRT dosimetry." Radiology and Oncology 52, no. 3 (2018): 346–52. http://dx.doi.org/10.2478/raon-2018-0019.

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Abstract Background The accuracy of dose calculation is crucial for success of the radiotherapy treatment. One of the methods that represent the current standard for patient-specific dosimetry is the evaluation of dose distributions measured with an ionization chamber array inside a homogeneous phantom using gamma method. Nevertheless, this method does not replicate the realistic conditions present when a patient is undergoing therapy. Therefore, to more accurately evaluate the treatment planning system (TPS) capabilities, gamma passing rates were examined for beams of different complexity pas

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23

Zapp, E. Neal, Chester R. Ramsey, Lawrence W. Townsend, and Gautam D. Badhwar. "Solar particle event dose distributions: Parameterization of dose-time profiles." Acta Astronautica 43, no. 3-6 (1998): 249–59. http://dx.doi.org/10.1016/s0094-5765(98)00158-1.

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24

Knisely, Jonathan P., James E. Bond, Ning J. Yue, Colin Studholme, and Alain C. J. de Lotbinière. "Image registration and calculation of a biologically effective dose for multisession radiosurgical treatments." Journal of Neurosurgery 93, supplement_3 (2000): 208–18. http://dx.doi.org/10.3171/jns.2000.93.supplement_3.0208.

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✓ The purpose of this study was to develop techniques for registering image sets associated with staged or multifraction radiosurgical treatments of large targets with the Leksell gamma knife to transform shot coordinates between treatment sessions and produce cumulative dose distributions and to investigate the theoretical biological effects of such protracted treatments by means of such concepts as the linear—quadratic model and biologically effective dose. An image registration technique based on normalized mutual information was adapted to produce one fused-image study from an imaging seri

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25

Adekunle Job. "Simulation of ITV and GTV doses in SBRT treatment of lung cancer." World Journal of Advanced Research and Reviews 26, no. 1 (2025): 3601–12. https://doi.org/10.30574/wjarr.2025.26.1.1345.

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Background: Stereo-tactic body radiation therapy (SBRT) has emerged as a highly effective treatment for early-stage non-small cell lung cancer (NSCLC) and metastatic lung tumors. Its ability to deliver high doses of radiation precisely to the tumor while sparing surrounding healthy tissue makes it a preferred option for inoperable cases. Accurate dose distribution assessment is critical for optimizing treatment plans and minimizing toxicity risks. Objective: This study aims to analyze the dose distribution of SBRT in lung cancer treatment using Monte Carlo simulations and experimental verifica

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26

Berns, Ch, P. Fritz, F. W. Hensley, and M. Wannenmacher. "54 PDR optimized dose distributions versus non-optimized CLDR dose distributions on the basis of clinical examples." Radiotherapy and Oncology 31 (April 1994): S35. http://dx.doi.org/10.1016/0167-8140(94)91152-5.

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27

Gore, Elizabeth, Michael T. Gillin, Katherine Albano, and Beth Erickson. "Comparison of high dose-rate and low dose-rate dose distributions for vaginal cylinders." International Journal of Radiation Oncology*Biology*Physics 31, no. 1 (1995): 165–70. http://dx.doi.org/10.1016/0360-3016(94)00326-g.

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28

Kajikawa, Tomohiro, Noriyuki Kadoya, Kengo Ito, et al. "A convolutional neural network approach for IMRT dose distribution prediction in prostate cancer patients." Journal of Radiation Research 60, no. 5 (2019): 685–93. http://dx.doi.org/10.1093/jrr/rrz051.

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Abstract The purpose of the study was to compare a 3D convolutional neural network (CNN) with the conventional machine learning method for predicting intensity-modulated radiation therapy (IMRT) dose distribution using only contours in prostate cancer. In this study, which included 95 IMRT-treated prostate cancer patients with available dose distributions and contours for planning target volume (PTVs) and organs at risk (OARs), a supervised-learning approach was used for training, where the dose for a voxel set in the dataset was defined as the label. The adaptive moment estimation algorithm w

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29

Thieke, Christian, Thomas Bortfeld, and Karl-Heinz Küfer. "Characterization of Dose Distributions Through the Max and Mean Dose Concept." Acta Oncologica 41, no. 2 (2002): 158–61. http://dx.doi.org/10.1080/028418602753669535.

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30

Niemierko, Andrzej. "Reporting and analyzing dose distributions: A concept of equivalent uniform dose." Medical Physics 24, no. 1 (1997): 103–10. http://dx.doi.org/10.1118/1.598063.

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31

Reda, Sonia, Eman Massoud, Ibrahem Bashter, and Esmat Amin. "Comparison between the calculated and measured dose distributions for four beams of 6 MeV linac in a human-equivalent phantom." Nuclear Technology and Radiation Protection 21, no. 2 (2006): 67–72. http://dx.doi.org/10.2298/ntrp0602067r.

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Radiation dose distributions in various parts of the body are of importance in radiotherapy. Also, the percent depth dose at different body depths is an important parameter in radiation therapy applications. Monte Carlo simulation techniques are the most accurate methods for such purposes. Monte Carlo computer calculations of photon spectra and the dose ratios at surfaces and in some internal organs of a human equivalent phantom were performed. In the present paper, dose distributions in different organs during bladder radiotherapy by 6 MeV X-rays were measured using thermoluminescence dosimet

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32

Piatkevich, M. N., H. I. Brynkevich, and E. V. Titovich. "Establishment of criteria for gamma-analysis of individual dose distributions during verification of radiotherapy high-tech treatment plans for cancer patients." Proceedings of the National Academy of Sciences of Belarus, Physical-Technical Series 67, no. 1 (2022): 119–28. http://dx.doi.org/10.29235/1561-8358-2022-67-1-119-128.

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A typical process for verification of treatment plans in intensity-modulated radiation therapy is described. The main errors and uncertainties that arise in the course of planning dose distribution and in the process of dose delivery are listed. Methods for comparing dose distributions are considered: the distance to agreement (DTA) and the test for the algebraic dose difference. Formulas for calculating the shift of points of dose distributions, as well as the minimum value of the shift of points, are provided. The influences of global and local normalization and spatial resolution on the int

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33

Arsalan, M. Z., M. B. Kakakhel, M. Shamshad, and T. A. Afridi. "Patient-Specific Pre-Treatment VMAT Plan Verification Using Gamma Passing Rates." Atom Indonesia 1, no. 1 (2023): 53–59. http://dx.doi.org/10.55981/aij.2023.1261.

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Continuous gantry motion, continuous beam modulation, and variable dose rate are used in volumetric modulated arc therapy (VMAT) to obtain highly conformal radiation therapy dose distributions. Several errors during daily radiation therapy treatment can be sources of uncertainties in dose delivery. These errors include monitor unit calculation errors and other human mistakes. Due to the uncertainties in the excessively modulated VMAT plan, the intended dose distribution is not delivered perfectly, leading to a mismatch between the measured and planned dose distributions. This necessitates an e

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34

Климанов, В., V. Klimanov, Ж. Галяутдинова, et al. "Reconstruction of Bremsstrahlung Spectrum of Medical Electron Linear Accelerators from Deep Dose Distributions in Water Phantom." Medical Radiology and radiation safety 62, no. 5 (2017): 47–51. http://dx.doi.org/10.12737/article_59f300494670a7.65219672.

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Purpose: Development of the bremsstrahlung spectrum reconstruction method of medical electron linear accelerators (ELA) with different field sizes on the base of the deep dose distributions in a water phantom and determination of photon spectra for Varian Trilogy accelerator 6 MV.  Material and methods: The proposed methodology is based on the use of dose kernels algorithm of point monoenergetic monodirectional source (pencil beam (PB)) for the deep dose distribution calculation, created different cross-section beams of in a water phantom, and experimental measurements of these distribut

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35

Shortt, K. R., C. K. Ross, A. F. Bielajew, and D. W. O. Rogers. "Electron beam dose distributions near standard inhomogeneities." Physics in Medicine and Biology 31, no. 3 (1986): 235–49. http://dx.doi.org/10.1088/0031-9155/31/3/003.

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36

Sont, W. N. "Statistical Modelling of Annual Occupational Dose Distributions." Radiation Protection Dosimetry 36, no. 2-4 (1991): 279–83. http://dx.doi.org/10.1093/oxfordjournals.rpd.a081013.

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37

Sont, W. N. "Statistical Modelling of Annual Occupational Dose Distributions." Radiation Protection Dosimetry 36, no. 2-4 (1991): 279–83. http://dx.doi.org/10.1093/rpd/36.2-4.279.

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38

Cross, W. G., J. Böhm, M. Charles, E. Piesch, and S. M. Seltzer. "Appendix C: Absorbed Dose Distributions; Conversion Factors." Journal of the International Commission on Radiation Units and Measurements os29, no. 1 (1997): 92–106. http://dx.doi.org/10.1093/jicru/os29.1.92.

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39

Cross, W. G., J. Böhm, M. Charles, E. Piesch, and S. M. Seltzer. "Appendix C: Absorbed Dose Distributions; Conversion Factors." Reports of the International Commission on Radiation Units and Measurements os-29, no. 1 (1997): 92–106. http://dx.doi.org/10.1093/jicru_os29.1.92.

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40

Mohan, R. "139: Robust Optimization of IMPT Dose Distributions." Radiotherapy and Oncology 110 (February 2014): S68—S69. http://dx.doi.org/10.1016/s0167-8140(15)34160-8.

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41

Goitein, Michael. "Comparison of proton and photon dose distributions." Radiotherapy and Oncology 37 (October 1995): S43. http://dx.doi.org/10.1016/0167-8140(96)80598-6.

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42

Scarlat, F., Nicoleta Baboi, and V. Manu. "An analytical approximation of depth-dose distributions." Radiotherapy and Oncology 37 (October 1995): S54. http://dx.doi.org/10.1016/0167-8140(96)80641-4.

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43

Peppa, Vasiliki, Eleftherios P. Pappas, Pantelis Karaiskos, and Panagiotis Papagiannis. "Time resolved dose rate distributions in brachytherapy." Physica Medica 41 (September 2017): 13–19. http://dx.doi.org/10.1016/j.ejmp.2017.04.013.

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44

Mackeprang, P.-H., W. Volken, D. Terribilini, et al. "Assessing dose rate distributions in VMAT plans." Physics in Medicine and Biology 61, no. 8 (2016): 3208–21. http://dx.doi.org/10.1088/0031-9155/61/8/3208.

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45

Faddegon, B. A., and I. Blevis. "Electron spectra derived from depth dose distributions." Medical Physics 27, no. 3 (2000): 514–26. http://dx.doi.org/10.1118/1.598919.

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46

Yaparpalvi, R., K. J. Mehta, S. C. Desai, H. C. Kuo, W. A. Tome, and S. Kalnicki. "Are Inversely Planned Dose Distributions Superior to Manually Optimized Dose Distributions in Cervix T&O HDR Brachytherapy?" International Journal of Radiation Oncology*Biology*Physics 96, no. 2 (2016): E307. http://dx.doi.org/10.1016/j.ijrobp.2016.06.1397.

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47

Buliński, Krzysztof, Tomasz Kuszewski, Katarzyna Wnuk, Janusz Braziewicz, and Krzysztof Ślosarek. "Uncertainties in the measurement of relative doses in radiotherapy." Polish Journal of Medical Physics and Engineering 27, no. 1 (2021): 1–9. http://dx.doi.org/10.2478/pjmpe-2021-0001.

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Abstract Both the measurement of the dose and the measurement of its distribution, like any other measurements, are subject to measurement uncertainties. These uncertainties affect all dose calculations and dose distributions in a patient’s body during treatment planning in radiotherapy. Measurement uncertainty is not a medical physicist’s error, but an inevitable element of their work. Planning the dose distribution in a patient’s body, we often try to reduce it in the volume of critical organs (OaR - Organ at Risk) or increase the minimum dose in the PTV region by a few percent. It is believ

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48

Northum, Jeremy D., and Stephen B. Guetersloh. "The Application of Microdosimetric Principles to Radiation Hardness Testing." Science and Technology of Nuclear Installations 2014 (2014): 1–5. http://dx.doi.org/10.1155/2014/828921.

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Chord length distributions for rectangular parallelepipeds of various relative dimensions were studied in relation to radiation hardness testing. For each geometry, a differential chord length distribution was generated using a Monte Carlo method to simulate exposure to an isotropic radiation source. The frequency and dose distributions of chord length crossings for each geometry, as well as the means of these distributions, are presented. In every case, the dose mean chord length was greater than the frequency mean chord length with a 34.5% increase found for the least extreme case of a cube.

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49

Cengiz, Mustafa, Fatma Colak, Demet Yildiz, et al. "The effect of leg position on the dose distribution of intracavitary brachytherapy for cervical cancer: 3D computerised tomography plan evaluation and in vivo dosimetric study." Journal of Radiotherapy in Practice 15, no. 4 (2016): 341–45. http://dx.doi.org/10.1017/s146039691600025x.

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AbstractPurposeTo evaluate the impact of leg position on the dose distribution during intracavitary brachytherapy for cervical cancer.Patients and methodsThis prospective study was performed on 11 women with cervical cancer who underwent intracavitary brachytherapy. After insertion of the brachytherapy applicator, two sets of computed tomography slices were taken including pelvis, one with straight leg and one with leg flexion position with knee support. The dose (7 Gy) was prescribed to point A. The radiotherapy plan was run on the Plato Planning Software System V14·1 to get the dose distribu

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50

Musselman, R. C., A. J. Huerta, P. M. McCool, and R. J. Oshima. "Response of Beans to Simulated Ambient and Uniform Ozone Distributions with Equal Peak Concentration." Journal of the American Society for Horticultural Science 111, no. 3 (1986): 470–73. http://dx.doi.org/10.21273/jashs.111.3.470.

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Abstract Response of Phaseolus vulgaris L. cv. California Dark Red Kidney to 2 different ozone concentration distributions was examined at 2 dose levels in controlled fumigations. When peak ozone concentrations were equal and total doses equivalent, there was no difference in injury, growth, or yield between a simulated ambient distribution with normal diurnal ozone fluctuations and a uniform distribution typical of laboratory fumigation at constant concentration. Plants fumigated with either ambient or uniform ozone distribution had oxidant stipple leaf necrosis and reduced growth and yield.

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