Journal articles on the topic 'Radiobiological'

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1

Belmans, Niels, Anne Caroline Oenning, Benjamin Salmon, Bjorn Baselet, Kevin Tabury, Stéphane Lucas, Ivo Lambrichts, Marjan Moreels, Reinhilde Jacobs, and Sarah Baatout. "Radiobiological risks following dentomaxillofacial imaging: should we be concerned?" Dentomaxillofacial Radiology 50, no. 6 (September 1, 2021): 20210153. http://dx.doi.org/10.1259/dmfr.20210153.

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Objectives: This review aimed to present studies that prospectively investigated biological effects in patients following diagnostic dentomaxillofacial radiology (DMFR). Methods: Literature was systematically searched to retrieve all studies assessing radiobiological effects of using X-ray imaging in the dentomaxillofacial area, with reference to radiobiological outcomes for other imaging modalities and fields. Results: There is a lot of variability in the reported radiobiological assessment methods and radiation dose measures, making comparisons of radiobiological studies challenging. Most radiological DMFR studies are focusing on genotoxicity and cytotoxicity, data for 2D dentomaxillofacial radiographs, albeit with some methodological weakness biasing the results. For CBCT, available evidence is limited and few studies include comparative data on both adults and children. Conclusions In the future, one will have to strive towards patient-specific measures by considering age, gender and other individual radiation sensitivity-related factors. Ultimately, future radioprotection strategies should build further on the concept of personalized medicine, with patient-specific optimization of the imaging protocol, based on radiobiological variables.
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2

Namdar, Aysan Mohammad, Mohammad Mohammadzadeh, Murat Okutan, and Asghar Mesbahi. "A review on the dosimetrical and radiobiological prediction of radiation-induced hypothyroidism in radiation therapy of head-and-neck cancer, breast cancer, and Hodgkin’s lymphoma survivors." Polish Journal of Medical Physics and Engineering 24, no. 4 (December 1, 2018): 137–48. http://dx.doi.org/10.2478/pjmpe-2018-0020.

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Abstract A review on the radiobiological modeling of radiation-induced hypothyroidism after radiation therapy of head-and-neck cancers, breast cancer, and Hodgkin’s lymphoma is presented. The current review is based on data relating to dose-volume constrains and normal tissue complication probability (NTCP) as a function of either radiobiological or (pre)treatment-clinical parameters. Also, these data were explored in order to provide more helpful criteria for radiobiological optimization of treatment plans involving thyroid gland as a critical normal organ.
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3

Knaup, Courtney, Panayiotis Mavroidis, Gregory Swanson, Sotirios Stathakis, Dimos Baltas, and Niko Papanikolaou. "Inclusion of radiobiological factors in prostate brachytherapy treatment planning." Journal of Radiotherapy in Practice 12, no. 2 (June 28, 2012): 163–72. http://dx.doi.org/10.1017/s1460396912000209.

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AbstractPurpose: Comparison of prostate seed implant treatment plans is currently based on evaluation of dose-volume histograms and doses to the tumour and normal structures. However, these do not account for effects of varying dose-rate, tumour repopulation and other biological effects. In this work, incorporation of the radiobiological response is used to obtain a more inclusive and clinically relevant treatment plan evaluation tool.Materials and Methods: Ten patients were evaluated. For each patient, six different treatment plans were created on the Prowess system. Plans with iodine-125 used a prescription dose of 145 Gy while plans with palladium-103 used 115 Gy. The biologically effective dose was used together with the tumour control probability and the normal tissue complication probabilities of urethra, bladder, rectum and surrounding tissue to evaluate the effectiveness of each treatment plan. Results from the radiobiological evaluation were compared to standard dose quantifiers.Results: The use of response probabilities is seen to provide a simpler means of treatment evaluation compared to standard dose quantifiers. This allows for different treatment plans to be quickly compared. Additionally, the use of radiobiologically-based plan evaluation allows for optimisation of seed type and initial seed strengths to find the ideal balance of TCP and NTCP.Conclusion: The goal of this work was to incorporate the biological response to obtain a more complete and clinically relevant treatment plan evaluation tool. This resulted in a simpler means of plan evaluation that may be used to compare and optimise prostate seed implant treatment plans.
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4

Santacroce, Antonio, Marcel A. Kamp, Wilfried Budach, and Daniel Hänggi. "Radiobiology of Radiosurgery for the Central Nervous System." BioMed Research International 2013 (2013): 1–9. http://dx.doi.org/10.1155/2013/362761.

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According to Leksell radiosurgery is defined as “the delivery of a single, high dose of irradiation to a small and critically located intracranial volume through the intact skull.” Before its birth in the early 60s and its introduction in clinical therapeutic protocols in late the 80s dose application in radiation therapy of the brain for benign and malignant lesions was based on the administration of cumulative dose into a variable number of fractions. The rationale of dose fractionation is to lessen the risk of injury of normal tissue surrounding the target volume. Radiobiological studies of cell culture lines of malignant tumors and clinical experience with patients treated with conventional fractionated radiotherapy helped establishing this radiobiological principle. Radiosurgery provides a single high dose of radiation which translates into a specific toxic radiobiological response. Radiobiological investigations to study the effect of high dose focused radiation on the central nervous system began in late the 50s. It is well known currently that radiobiological principles applied for dose fractionation are not reproducible when single high dose of ionizing radiation is delivered. A review of the literature about radiobiology of radiosurgery for the central nervous system is presented.
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5

Birschwilks, M., M. Gruenberger, C. Adelmann, S. Tapio, G. Gerber, P. N. Schofield, and B. Grosche. "The European Radiobiological Archives: Online Access to Data from Radiobiological Experiments." Radiation Research 175, no. 4 (April 2011): 526–31. http://dx.doi.org/10.1667/rr2471.1.

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6

Knaup, Courtney, Panayiotis Mavroidis, Carlos Esquivel, Sotirios Stathakis, Gregory Swanson, Dimos Baltas, and Nikos Papanikolaou. "Radiobiological comparison of single and dual-isotope prostate seed implants." Journal of Radiotherapy in Practice 12, no. 2 (August 2, 2012): 154–62. http://dx.doi.org/10.1017/s1460396912000076.

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AbstractPurpose: Several isotopes are available for low dose-rate prostate brachytherapy. Currently most implants use a single isotope. However, the use of dual-isotope implants may yield an advantageous combination of characteristics such as half-life and relative biological effectiveness. However, the use of dual-isotope implants complicates treatment planning and quality assurance. Do the benefits of dual-isotope implants outweigh the added difficulty? The goal of this work was to use a linear-quadratic model to compare single and dual-isotope implants.Materials & Methods: Ten patients were evaluated. For each patient, six treatment plans were created with single or dual-isotope combinations of 125I, 103Pd and 131Cs. For each plan the prostate, urethra, rectum and bladder were contoured by a physician. The biologically effective dose was used to determine the tumor control probability and normal tissue complication probabilities for each plan. Each plan was evaluated using favorable, intermediate and unfavorable radiobiological parameters. The results of the radiobiological analysis were used to compare the single and dual-isotope treatment plans.Results: Iodine-125 only implants were seen to be most affected by changes in tumor parameters. Significant differences in organ response probabilities were seen at common dose levels. However, after adjusting the initial seed strength the differences between isotope combinations were minimal.Conclusions: The objective of this work was to perform a radiobiologically based comparison of single and dual-isotope prostate seed implant plans. For all isotope combinations, the plans were improved by varying the initial seed strength. For the optimized treatment plans, no substantial differences in predicted treatment outcomes were seen among the different isotope combinations.
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7

Birschwilks, M., P. N. Schofield, and B. Grosche. "The European Radiobiological Archives." Health Physics 102, no. 2 (February 2012): 220. http://dx.doi.org/10.1097/hp.0b013e3182216d02.

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8

Nahum, A. E. "243 Radiobiological treatment planning." Radiotherapy and Oncology 76 (September 2005): S117. http://dx.doi.org/10.1016/s0167-8140(05)81220-4.

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9

Goldman, M. "Chernobyl: a radiobiological perspective." Science 238, no. 4827 (October 30, 1987): 622–23. http://dx.doi.org/10.1126/science.3672115.

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10

Schimmerling, Walter. "Radiobiological problems in space." Radiation and Environmental Biophysics 31, no. 3 (September 1992): 197–203. http://dx.doi.org/10.1007/bf01214827.

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11

Jelgersma, Claudius, Carolin Senger, Anne Kathrin Kluge, Anastasia Janas, Melina Nieminen-Kelhä, Irina Kremenetskaia, Susanne Mueller, et al. "Establishment and Validation of CyberKnife Irradiation in a Syngeneic Glioblastoma Mouse Model." Cancers 13, no. 14 (July 8, 2021): 3416. http://dx.doi.org/10.3390/cancers13143416.

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CyberKnife stereotactic radiosurgery (CK-SRS) precisely delivers radiation to intracranial tumors. However, the underlying radiobiological mechanisms at high single doses are not yet fully understood. Here, we established and evaluated the early radiobiological effects of CK-SRS treatment at a single dose of 20 Gy after 15 days of tumor growth in a syngeneic glioblastoma-mouse model. Exact positioning was ensured using a custom-made, non-invasive, and trackable frame. One superimposed target volume for the CK-SRS planning was created from the fused tumor volumes obtained from MRIs prior to irradiation. Dose calculation and delivery were planned using a single-reference CT scan. Six days after irradiation, tumor volumes were measured using MRI scans, and radiobiological effects were assessed using immunofluorescence staining. We found that CK-SRS treatment reduced tumor volume by approximately 75%, impaired cell proliferation, diminished tumor vasculature, and increased immune response. The accuracy of the delivered dose was demonstrated by staining of DNA double-strand breaks in accordance with the planned dose distribution. Overall, we confirmed that our proposed setup enables the precise irradiation of intracranial tumors in mice using only one reference CT and superimposed MRI volumes. Thus, our proposed mouse model for reproducible CK-SRS can be used to investigate radiobiological effects and develop novel therapeutic approaches.
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12

Drexler, Guido A., and Miguel J. Ruiz-Gómez. "Microirradiation techniques in radiobiological research." Journal of Biosciences 40, no. 3 (June 27, 2015): 629–43. http://dx.doi.org/10.1007/s12038-015-9535-3.

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13

Hall, Eric J., Richard C. Miller, and David J. Brenner. "Radiobiological principles in intravascular irradiation." Cardiovascular Radiation Medicine 1, no. 1 (January 1999): 42–47. http://dx.doi.org/10.1016/s1522-1865(98)00004-3.

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14

Hopewell, J. W., and G. J. M. J. van den Aardweg. "Radiobiological studies with pig skin." International Journal of Radiation Oncology*Biology*Physics 14, no. 5 (May 1988): 1047–50. http://dx.doi.org/10.1016/0360-3016(88)90031-4.

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15

Shirazi, Alireza, Seied Rabie Mahdavi, and Klaus Rudiger Trott. "Radiation myelopathy: a radiobiological review." Reports of Practical Oncology & Radiotherapy 9, no. 4 (2004): 119–27. http://dx.doi.org/10.1016/s1507-1367(04)71019-6.

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16

Koumeir, Charbel, Viviana De Nadal, Roberto Cherubini, Michel Cherel, Eric Garrido, Sébastien Gouard, Arnaud Guertin, et al. "THE RADIOBIOLOGICAL PLATFORM AT ARRONAX." Radiation Protection Dosimetry 183, no. 1-2 (January 21, 2019): 270–73. http://dx.doi.org/10.1093/rpd/ncy301.

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17

AKIYAMA, MITOSHI, and NORI NAKAMURA. "Future Perspective of Radiobiological Studies." Journal of Radiation Research 32, SUPPLEMENT (1991): 394. http://dx.doi.org/10.1269/jrr.32.supplement_394.

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18

Burlakova, E. B. "Low Intensity Radiation: Radiobiological Aspects." Radiation Protection Dosimetry 62, no. 1-2 (October 1, 1995): 13–18. http://dx.doi.org/10.1093/rpd/62.1-2.13.

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19

Nuutinen, Jouni, Anssi Väänänen, Tapani Lahtinen, Marita Turunen, Saara Remes, and Esko Alanen. "Radiobiological depth of subcutaneous induration." Radiotherapy and Oncology 55, no. 2 (May 2000): 187–90. http://dx.doi.org/10.1016/s0167-8140(99)00147-4.

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20

Mohan, Radhe, Christopher R. Peeler, Fada Guan, Lawrence Bronk, Wenhua Cao, and David R. Grosshans. "Radiobiological issues in proton therapy." Acta Oncologica 56, no. 11 (August 22, 2017): 1367–73. http://dx.doi.org/10.1080/0284186x.2017.1348621.

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21

Burlakova, E. B. "Low Intensity Radiation: Radiobiological Aspects." Radiation Protection Dosimetry 62, no. 1-2 (October 1, 1995): 13–18. http://dx.doi.org/10.1093/oxfordjournals.rpd.a082810.

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22

Warkentin, Brad. "Radiobiological Modelling in Radiation Oncology." Medical Physics 35, no. 4 (March 27, 2008): 1621. http://dx.doi.org/10.1118/1.2890975.

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23

Jones, Bleddyn, and Roger G. Dale. "Radiobiological modeling and clinical trials." International Journal of Radiation Oncology*Biology*Physics 48, no. 1 (August 2000): 259–65. http://dx.doi.org/10.1016/s0360-3016(00)00542-3.

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24

Krasavin, Evgenii A. "Radiobiological research at JINR's accelerators." Uspekhi Fizicheskih Nauk 186, no. 4 (2016): 435–43. http://dx.doi.org/10.3367/ufnr.0186.201604e.0435.

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25

Krasavin, E. A. "Radiobiological research at JINR's accelerators." Physics-Uspekhi 59, no. 4 (April 30, 2016): 411–18. http://dx.doi.org/10.3367/ufne.0186.201604e.0435.

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26

Zaider, Marco. "Radiobiological Modelling in Radiation Oncology." International Journal of Radiation Biology 84, no. 4 (January 2008): 351. http://dx.doi.org/10.1080/09553000801986680.

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27

Balonov, M. I., K. N. Muksinova, and G. S. Mushkacheva. "Tritium Radiobiological Effects in Mammals." Health Physics 65, no. 6 (December 1993): 713–26. http://dx.doi.org/10.1097/00004032-199312000-00009.

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28

Kellerer, A. M. "Radiobiological Challenges Posed by Microdosimetry." Health Physics 70, no. 6 (June 1996): 832–36. http://dx.doi.org/10.1097/00004032-199606000-00008.

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29

Guerrero, Mariana. "Radiobiological Modelling in Radiation Oncology." International Journal of Radiation Oncology*Biology*Physics 70, no. 5 (April 2008): 1613. http://dx.doi.org/10.1016/j.ijrobp.2007.11.051.

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30

Datesman, A. "Shot noise in radiobiological systems." Journal of Environmental Radioactivity 164 (November 2016): 365–68. http://dx.doi.org/10.1016/j.jenvrad.2016.06.017.

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31

Her, Emily Jungmin, Annette Haworth, Pejman Rowshanfarzad, and Martin A. Ebert. "Progress towards Patient-Specific, Spatially-Continuous Radiobiological Dose Prescription and Planning in Prostate Cancer IMRT: An Overview." Cancers 12, no. 4 (April 1, 2020): 854. http://dx.doi.org/10.3390/cancers12040854.

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Advances in imaging have enabled the identification of prostate cancer foci with an initial application to focal dose escalation, with subvolumes created with image intensity thresholds. Through quantitative imaging techniques, correlations between image parameters and tumour characteristics have been identified. Mathematical functions are typically used to relate image parameters to prescription dose to improve the clinical relevance of the resulting dose distribution. However, these relationships have remained speculative or invalidated. In contrast, the use of radiobiological models during treatment planning optimisation, termed biological optimisation, has the advantage of directly considering the biological effect of the resulting dose distribution. This has led to an increased interest in the accurate derivation of radiobiological parameters from quantitative imaging to inform the models. This article reviews the progress in treatment planning using image-informed tumour biology, from focal dose escalation to the current trend of individualised biological treatment planning using image-derived radiobiological parameters, with the focus on prostate intensity-modulated radiotherapy (IMRT).
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32

Akimoto, Tetsuo. "Radiobiological basis for hyperfractionated radiation therapy." Toukeibu Gan 33, no. 3 (2007): 276–79. http://dx.doi.org/10.5981/jjhnc.33.276.

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33

Van der Kogel, A. "SP-0331: Radiobiological basis of retreatment." Radiotherapy and Oncology 115 (April 2015): S164. http://dx.doi.org/10.1016/s0167-8140(15)40329-9.

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34

Zwicker, R. D., A. Meigooni, and M. Mohiuddin. "Radiobiological advantage of megavoltage grid therapy." International Journal of Radiation Oncology*Biology*Physics 51, no. 3 (November 2001): 401. http://dx.doi.org/10.1016/s0360-3016(01)02562-7.

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35

Shirazi, A., S. R. Mahdavi, and K. R. Trott. "333. Radiation myelopathy: A radiobiological review." Reports of Practical Oncology & Radiotherapy 8 (2003): S359. http://dx.doi.org/10.1016/s1507-1367(03)70816-5.

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36

Trott, Klaus-Rüdiger, and Friedrich Kamprad. "Radiobiological mechanisms of anti-inflammatory radiotherapy." Radiotherapy and Oncology 51, no. 3 (June 1999): 197–203. http://dx.doi.org/10.1016/s0167-8140(99)00066-3.

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37

Sgouros, George, Eric Frey, Richard Wahl, Bin He, Andrew Prideaux, and Robert Hobbs. "Three-Dimensional Imaging-Based Radiobiological Dosimetry." Seminars in Nuclear Medicine 38, no. 5 (September 2008): 321–34. http://dx.doi.org/10.1053/j.semnuclmed.2008.05.008.

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38

Dale, R. G. "247 Radiobiological modelling & clinical trials." Radiotherapy and Oncology 76 (September 2005): S118. http://dx.doi.org/10.1016/s0167-8140(05)81224-1.

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39

Ngo, F. Q. H., C. B. Schroy, X. L. Jia, I. Kalvakolanu, W. K. Roberts, J. W. Blue, A. R. Antunez, P. D. Higgins, and M. Tefft. "Basic Radiobiological Investigations of Fast Neutrons." Radiation Research 128, no. 1 (October 1991): S94. http://dx.doi.org/10.2307/3578009.

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40

Stolbovoy, A. V., and I. F. Zalyalov. "Radiobiological models and clinical radiation oncology." Onkologiya. Zhurnal imeni P.A.Gertsena 5, no. 6 (2016): 88. http://dx.doi.org/10.17116/onkolog20165688-96.

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41

Schaue, Dörthe, Evelyn L. Kachikwu, and William H. McBride. "Cytokines in Radiobiological Responses: A Review." Radiation Research 178, no. 6 (December 2012): 505–23. http://dx.doi.org/10.1667/rr3031.1.

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42

Kuna, Pavel. "Haemopoietic stem cells in radiobiological experiment." Kontakt 9, no. 2 (December 21, 2007): 378–86. http://dx.doi.org/10.32725/kont.2007.058.

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43

Nikezic, Dragoslav, and Kwan Ngok Yu. "Alpha-particle fluence in radiobiological experiments." Journal of Radiation Research 58, no. 2 (November 3, 2016): 195–200. http://dx.doi.org/10.1093/jrr/rrw106.

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Abstract Two methods were proposed for determining alpha-particle fluence for radiobiological experiments. The first involved calculating the probabilities of hitting the target for alpha particles emitted from a source through Monte Carlo simulations, which when multiplied by the activity of the source gave the fluence at the target. The second relied on the number of chemically etched alpha-particle tracks developed on a solid-state nuclear track detector (SSNTD) that was irradiated by an alpha-particle source. The etching efficiencies (defined as percentages of latent tracks created by alpha particles from the source that could develop to become visible tracks upon chemical etching) were computed through Monte Carlo simulations, which when multiplied by the experimentally counted number of visible tracks would also give the fluence at the target. We studied alpha particles with an energy of 5.486 MeV emitted from an 241Am source, and considered the alpha-particle tracks developed on polyallyldiglycol carbonate film, which is a common SSNTD. Our results showed that the etching efficiencies were equal to one for source–film distances of from 0.6 to 3.5 cm for a circular film of radius of 1 cm, and for source–film distances of from 1 to 3 cm for circular film of radius of 2 cm. For circular film with a radius of 3 cm, the etching efficiencies never reached 1. On the other hand, the hit probability decreased monotonically with increase in the source–target distance, and fell to zero when the source–target distance was larger than the particle range in air.
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44

Wigg, David R. "A radiobiological basis for bioeffect planning." Medical Physics 27, no. 11 (November 2000): 2637. http://dx.doi.org/10.1118/1.1320061.

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45

Horneck, Gerda. "Radiobiological experiments in space: A review." International Journal of Radiation Applications and Instrumentation. Part D. Nuclear Tracks and Radiation Measurements 20, no. 1 (January 1992): 185–205. http://dx.doi.org/10.1016/1359-0189(92)90099-h.

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46

Wang, H., and I. J. Das. "Radiobiological Assessment of IMRT Treatment Plans." International Journal of Radiation Oncology*Biology*Physics 99, no. 2 (October 2017): E735—E736. http://dx.doi.org/10.1016/j.ijrobp.2017.06.2370.

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47

Rossi, Harald H. "Strategy and tactics in radiobiological research." Radiation and Environmental Biophysics 32, no. 4 (December 1993): 273–76. http://dx.doi.org/10.1007/bf01225914.

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48

Prudyvus, I. S., and N. I. Okeanova. "Radiobiological planning of contact radiation therapy." Biomedical Engineering 26, no. 6 (November 1992): 314–15. http://dx.doi.org/10.1007/bf00557090.

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49

Song, Chang W., Mi-Sook Kim, L. Chinsoo Cho, Kathryn Dusenbery, and Paul W. Sperduto. "Radiobiological basis of SBRT and SRS." International Journal of Clinical Oncology 19, no. 4 (July 5, 2014): 570–78. http://dx.doi.org/10.1007/s10147-014-0717-z.

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50

Holloway, Lois. "Of what use is radiobiological modelling?" Australasian Physics & Engineering Sciences in Medicine 32, no. 2 (June 2009): xi—xiv. http://dx.doi.org/10.1007/bf03178628.

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