ORIGINAL_ARTICLE
Modification of Source Strength in Low-Dose-Rate Lung Brachytherapy with 125I and 103Pd seeds
Background: A new treatment approach for most patients who have undergone early stage non-small-cell lung carcinoma (NSCLC) is wedge resection plus permanent implant brachytherapy. However, the specification of dose to medium at low energies especially in heterogeneous lung is unclear yet. Objective: The present study aims to modify source strength for different configurations of 125I and 103Pd seeds used in lung permanent implant brachytherapy.Methods: Different arrays of 125I and 103Pd seeds were simulated by MCNPX code in protocol-based water vs. actual 3D lung environments. Absorbed dose was, then, scored in both mediums. Dose differences between both environments were calculated and source strength was modified for the prescription point. In addition, lung-to-water absorbed dose ratio was obtained and presented by precise equations.Results: Due to significant differences in prescription dose, source strength was modified 16%-19% and 37%-43% for different configurations of 125I and 103Pd seeds, respectively. In addition, depth-dependent dose differences were observed between the actual lung and protocol-based water mediums (dose difference as a function of depth). Conclusion: Modification of source strength is essential for different arrangements of 125I and 103Pd seeds in lung implantation. Modified source strength and presented equations are recommended to be considered in future studies based on lung brachytherapy.
https://jbpe.sums.ac.ir/article_43265_6809bc41cf90cb7c30ec8a129cb0bd12.pdf
2017-09-01
191
204
125I seed
103Pd seed
lung permanent implant brachytherapy
Monte Carlo Method
H
Rezaei
hrezaei.m.ph@gmail.com
1
Department of Radiology, School of Paramedical Sciences, Shiraz University of Medical Sciences, Shiraz, Iran
AUTHOR
H
Mostaghimi
mostaghimi@sums.ac.ir
2
Department of Biomedical Physics and Engineering, School of Medicine, Shiraz University of Medical Sciences, Shiraz, Iran
LEAD_AUTHOR
A R
Mehdizadeh
3
Department of Biomedical Physics and Engineering, School of Medicine, Shiraz University of Medical Sciences, Shiraz, Iran
AUTHOR
Jemal A, Siegel R, Ward E, Murray T, Xu J, Thun MJ. Cancer statistics, 2007. CA Cancer J Clin. 2007;57:43-66. doi.org/10.3322/canjclin.57.1.43. PubMed PMID: 17237035.
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Lal R, Enting D, Kristeleit H. Systemic treatment of non-small-cell lung cancer. European Journal of Cancer. 2011;47:S375-S7. doi.org/10.1016/S0959-8049(11)70209-X.
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Devlin PM. Brachytherapy: applications and techniques: Springer Publishing Company; 2015.
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Voynov G, Heron DE, Lin CJ, Burton S, Chen A, Quinn A, et al. Intraoperative (125)I Vicryl mesh brachytherapy after sublobar resection for high-risk stage I non-small cell lung cancer. Brachytherapy. 2005;4:278-85. doi.org/10.1016/j.brachy.2005.03.007. PubMed PMID: 16344258.
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Sutherland JG, Furutani KM, Thomson RM. Monte Carlo calculated doses to treatment volumes and organs at risk for permanent implant lung brachytherapy. Phys Med Biol. 2013;58:7061-80. doi.org/10.1088/0031-9155/58/20/7061. PubMed PMID: 24051987.
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Sutherland J, Furutani K, Garces YI, Thomson R. Model-based dose calculations for 125I lung brachytherapy. Med Phys. 2012;39:4365-77. doi.org/10.1118/1.4729737. PubMed PMID: 24387504.
6
S Sutherland JG, Miksys N, Furutani KM, Thomson RM. Metallic artifact mitigation and organ-constrained tissue assignment for Monte Carlo calculations of permanent implant lung brachytherapy. Med Phys. 2014;41:011712. doi.org/10.1118/1.4851555. PubMed PMID: 24387504.
7
Johnson M, Colonias A, Parda D, Trombetta M, Gayou O, Reitz B, et al. Dosimetric and technical aspects of intraoperative I-125 brachytherapy for stage I non-small cell lung cancer. Phys Med Biol. 2007;52:1237-45. doi.org/10.1088/0031-9155/52/5/002. PubMed PMID: 17301451.
8
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Santos R, Colonias A, Parda D, Trombetta M, Maley RH, Macherey R, et al. Comparison between sublobar resection and 125Iodine brachytherapy after sublobar resection in high-risk patients with Stage I non-small-cell lung cancer. Surgery. 2003;134:691-7; discussion 7. doi.org/10.1016/S0039-6060(03)00327-1. PubMed PMID: 14605631.
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Rivard MJ, Coursey BM, DeWerd LA, Hanson WF, Huq MS, Ibbott GS, et al. Update of AAPM Task Group No. 43 Report: A revised AAPM protocol for brachytherapy dose calculations. Med Phys. 2004;31:633-74. doi.org/10.1118/1.1646040. PubMed PMID: 15070264.
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Mostaghimi H, Mehdizadeh AR, Darvish L, Akbari S, Rezaei H. Mathematical formulation of 125 I seed dosimetry parameters and heterogeneity correction in lung permanent implant brachytherapy. Journal of Cancer Research and Therapeutics. 2017. [in Press]
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Rivard MJ. Monte Carlo radiation dose simulations and dosimetric comparison of the model 6711 and 9011 I125 brachytherapy sources. Medical physics. 2009;36:486-91. doi.org/10.1118/1.3056463.
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24
ORIGINAL_ARTICLE
Impact of Prolonged Fraction Delivery Time Modelling Stereotactic Body Radiation Therapy with High Dose Hypofractionation on the Killing of Cultured ACHN Renal Cell Carcinoma Cell Line
Introduction: Stereotactic body radiotherapy delivers hypofractionated irradiation with high dose per fraction through complex treatment techniques. The increased complexity leads to longer dose delivery times for each fraction. The purpose of this study is to investigate the impact of prolonged fraction delivery time with high-dose hypofractionation on the killing of cultured ACHN cells.Methods and Materials: The radiobiological characteristics and repair half-time of human ACHN renal cell carcinoma cell line were studied with clonogenic assays. A total dose of 20 Gy was administered in 1, 2 or 3 fractions over 15, 30 or 45 min to investigate the biological effectiveness of radiation delivery time and hypofractionation. Cell cycle and apoptosis analysis was performed after 3-fraction irradiation over 30 and 45 min.Results: The α/β and repair half-time were 5.2 Gy and 19 min, respectively. The surviving fractions increased with increase in the fraction delivery time and decreased more pronouncedly with increase in the fraction number over a treatment period of 30 to 45 min. With increase in the total radiation time to 30 and 45 min, it was found that with the same total dose, 2- and 3-fraction irradiation led to more cell killing than 1-fraction irradiation. 3-fraction radiation induced G2/M arrest, and the percentage of apoptotic cells decreased when the fraction delivery time increased from 30 min to 45 min.Conclusion: Our findings revealed that sublethal damage repair and redistribution of the cell cycle were predominant factors affecting cell response in the prolonged and hypofractionated irradiation regimes, respectively.
https://jbpe.sums.ac.ir/article_43266_5112c2fe1862ea4d0ef20033c255f277.pdf
2017-09-01
205
216
Hypofractionation
Prolonged Fraction Delivery Time
Renal cell carcinoma
Stereotactic Body Radiotherapy
Sublethal Damage Repair
M
Khorramizadeh
1
Department of Medical Physics, Faculty of Medicine, Dezful University of Medical Sciences, Dezful, Iran
AUTHOR
A
Saberi
ahsaberi70@hotmail.com
2
Department of Medical Genetics, School of Medicine, Ahvaz Jundishapur University of Medical Sciences, Ahvaz, Iran
LEAD_AUTHOR
M
Tahmasebi–birgani
3
Department of Medical Physics, Faculty of Medicine, Dezful University of Medical Sciences, Dezful, Iran
AUTHOR
P
Shokrani
shokrani@med.mui.ac.ir
4
Department of Medical Physics and Medical Engineering, School of Medicine, Isfahan University of Medical Sciences, Isfahan, Iran
AUTHOR
A
Amouhedari
amouheidari@yahoo.com
5
Department of Radiation Oncology, Milad Hospital, Isfahan, Iran
AUTHOR
Protzel C, Maruschke M, Hakenberg OW. Epidemiology, aetiology, and pathogenesis of renal cell carcinoma. European Urology Supplements. 2012;11:52-9. doi.org/10.1016/j.eursup.2012.05.002.
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2
Yu H, Lin X, Wang F, Zhang B, Wang W, Shi H, et al. Proliferation inhibition and the underlying molecular mechanisms of microRNA-30d in renal carcinoma cells. Oncol Lett. 2014;7:799-804. PubMed PMID: 24520297. PubMed PMCID: 3919943.
3
Mena AC, Pulido EG, Guillen-Ponce C. Understanding the molecular-based mechanism of action of the tyrosine kinase inhibitor: sunitinib. Anticancer Drugs. 2010;21:S3-11. doi.org/10.1097/01.cad.0000361534.44052.c5. PubMed PMID: 20110785.
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Stinauer MA, Kavanagh BD, Schefter TE, Gonzalez R, Flaig T, Lewis K, et al. Stereotactic body radiation therapy for melanoma and renal cell carcinoma: impact of single fraction equivalent dose on local control. Radiat Oncol. 2011;6:34. doi.org/10.1186/1748-717X-6-34. PubMed PMID: 21477295. PubMed PMCID: 3094365.
6
Lo SS, Fakiris AJ, Chang EL, Mayr NA, Wang JZ, Papiez L, et al. Stereotactic body radiation therapy: a novel treatment modality. Nat Rev Clin Oncol. 2010;7:44-54. doi.org/10.1038/nrclinonc.2009.188. PubMed PMID: 19997074.
7
Wersall PJ, Blomgren H, Lax I, Kalkner KM, Linder C, Lundell G, et al. Extracranial stereotactic radiotherapy for primary and metastatic renal cell carcinoma. Radiother Oncol. 2005;77:88-95. doi.org/10.1016/j.radonc.2005.03.022. PubMed PMID: 15972239.
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Svedman C, Sandstrom P, Pisa P, Blomgren H, Lax I, Kalkner KM, et al. A prospective Phase II trial of using extracranial stereotactic radiotherapy in primary and metastatic renal cell carcinoma. Acta Oncol. 2006;45:870-5. doi.org/10.1080/02841860600954875. PubMed PMID: 16982552.
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Svedman C, Karlsson K, Rutkowska E, Sandstrom P, Blomgren H, Lax I, et al. Stereotactic body radiotherapy of primary and metastatic renal lesions for patients with only one functioning kidney. Acta Oncol. 2008;47:1578-83. doi.org/10.1080/02841860802123196. PubMed PMID: 18607859.
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Teh BS, Ishiyama H, Mathews T, Xu B, Butler EB, Mayr NA, et al. Stereotactic body radiation therapy (SBRT) for genitourinary malignancies. Discov Med. 2010;10:255-62. PubMed PMID: 20875347.
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Wang X, Xiong XP, Lu J, Zhu GP, He SQ, Hu CS, et al. The in vivo study on the radiobiologic effect of prolonged delivery time to tumor control in C57BL mice implanted with Lewis lung cancer. Radiat Oncol. 2011;6:4. doi.org/10.1186/1748-717X-6-4. PubMed PMID: 21226899. PubMed PMCID: 3024935.
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Benedict SH, Lin PS, Zwicker RD, Huang DT, Schmidt-Ullrich RK. The biological effectiveness of intermittent irradiation as a function of overall treatment time: development of correction factors for linac-based stereotactic radiotherapy. Int J Radiat Oncol Biol Phys. 1997;37:765-9. doi.org/10.1016/S0360-3016(97)00023-0. PubMed PMID: 9128949.
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Zheng XK, Chen LH, Wang WJ, Ye F, Liu JB, Li QS, et al. Impact of prolonged fraction delivery times simulating IMRT on cultured nasopharyngeal carcinoma cell killing. Int J Radiat Oncol Biol Phys. 2010;78:1541-7. doi.org/10.1016/j.ijrobp.2010.07.005. PubMed PMID: 21092834.
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Wang JZ, Li XA, D’Souza WD, Stewart RD. Impact of prolonged fraction delivery times on tumor control: a note of caution for intensity-modulated radiation therapy (IMRT). Int J Radiat Oncol Biol Phys. 2003;57:543-52. doi.org/10.1016/S0360-3016(03)00499-1. PubMed PMID: 12957268.
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Sterzing F, Munter MW, Schafer M, Haering P, Rhein B, Thilmann C, et al. Radiobiological investigation of dose-rate effects in intensity-modulated radiation therapy. Strahlenther Onkol. 2005;181:42-8. doi.org/10.1007/s00066-005-1290-1. PubMed PMID: 15660192.
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Mu X, Lofroth PO, Karlsson M, Zackrisson B. The effect of fraction time in intensity modulated radiotherapy: theoretical and experimental evaluation of an optimisation problem. Radiother Oncol. 2003;68:181-7. doi.org/10.1016/S0167-8140(03)00165-8. PubMed PMID: 12972314.
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Kothari G, Foroudi F, Gill S, Corcoran NM, Siva S. Outcomes of stereotactic radiotherapy for cranial and extracranial metastatic renal cell carcinoma: a systematic review. Acta Oncol. 2015;54:148-57. doi.org/10.3109/0284186X.2014.939298. PubMed PMID: 25140860.
24
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Ning S, Trisler K, Wessels BW, Knox SJ. Radiobiologic studies of radioimmunotherapy and external beam radiotherapy in vitro and in vivo in human renal cell carcinoma xenografts. Cancer. 1997;80:2519-28. doi.org/10.1002/(SICI)1097-0142(19971215)80:12+3.0.CO;2-E. PubMed PMID: 9406705.
27
Park HJ, Griffin RJ, Hui S, Levitt SH, Song CW. Radiation-induced vascular damage in tumors: implications of vascular damage in ablative hypofractionated radiotherapy (SBRT and SRS). Radiat Res. 2012;177:311-27. doi.org/10.1667/RR2773.1. PubMed PMID: 22229487.
28
Dewan MZ, Galloway AE, Kawashima N, Dewyngaert JK, Babb JS, Formenti SC, et al. Fractionated but not single-dose radiotherapy induces an immune-mediated abscopal effect when combined with anti-CTLA-4 antibody. Clin Cancer Res. 2009;15:5379-88. doi.org/10.1158/1078-0432.CCR-09-0265. PubMed PMID: 19706802. PubMed PMCID: 2746048.
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30
Withers HR. Cell cycle redistribution as a factor in multifraction irradiation. Radiology. 1975;114:199-202. doi.org/10.1148/114.1.199. PubMed PMID: 1208860.
31
Yao Q, Zheng R, Xie G, Liao G, Du S, Ren C, et al. Late-responding normal tissue cells benefit from high-precision radiotherapy with prolonged fraction delivery times via enhanced autophagy. Sci Rep. 2015;5:9119. doi.org/10.1038/srep09119. PubMed PMID: 25766900. PubMed PMCID: 4357857.
32
ORIGINAL_ARTICLE
Reducing radiation doses in female breast and lung during CT examinations of thorax: A new technique in two scanners
Background: Chest CT is a commonly used examination for the diagnosis of lung diseases, but a breast within the scanned field is nearly never the organ of interest.Objective: The purpose of this study is to compare the female breast and lung doses using split and standard protocols in chest CT scanning.Materials and Methods: The sliced chest and breast female phantoms were used. CT exams were performed using a single-slice (SS)- and a 16 multi-slice (MS)- CT scanner at 100 kVp and 120 kVp. Two different protocols, including standard and split protocols, were selected for scanning. The breast and lung doses were measured using thermo-luminescence dosimeters which were inserted into different layers of the chest and breast phantoms. The differences in breast and lung radiation doses in two protocols were studied in two scanners, analyzed by SPSS software and compared by t-test.Results: Breast dose by split scanning technique reduced 11% and 31% in SS- and MS- CT. Also, the radiation dose of lung tissue in this method decreased 18% and 54% in SS- and MS- CT, respectively. Moreover, there was a significant difference (p< 0.0001) in the breast and lung radiation doses between standard and split scanning protocols.Conclusion: The application of a split scan technique instead of standard protocol has a considerable potential to reduce breast and lung doses in SS- and MS- CT scanners. If split scanning protocol is associated with an optimum kV and MSCT, the maximum dose decline will be provided.
https://jbpe.sums.ac.ir/article_43267_a3b6d57f1d06dcf076e76b451e621228.pdf
2017-09-01
217
224
Breast Dose
Lung Dose
Split Protocol
Chest CT
P
Mehnati
parinazmehnati8@gmail.com
1
Department of Medical Physics, School of Medicine, Tabriz University of Medical Sciences, Tabriz, Iran
LEAD_AUTHOR
M
Ghavami
mostafa.ghavami@yahoo.com
2
Department of Radiology, School of Medicine, Tabriz University of Medical Sciences, Tabriz, Iran
AUTHOR
H
Heidari
hhp26@yahoo.com
3
Department of Medical Physics, School of Medicine, Tabriz University of Medical Sciences, Tabriz, Iran
AUTHOR
Janbabanezhad-Toori A, Shabestani-Monfared A, Deevband M, Abdi R, Nabahati M. Dose Assessment in Computed Tomography Examination and Establishment of Local Diagnostic Reference Levels in Mazandaran, Iran. Journal of Biomedical Physics and Engineering. 2015.
1
Angel E, Yaghmai N, Jude CM, DeMarco JJ, Cagnon CH, Goldin JG, et al. Dose to radiosensitive organs during routine chest CT: effects of tube current modulation. AJR Am J Roentgenol. 2009;193:1340-5. doi.org/10.2214/AJR.09.2886. PubMed PMID: 19843751. PubMed PMCID: 2954276.
2
Goo HW. CT radiation dose optimization and estimation: an update for radiologists. Korean J Radiol. 2012;13:1-11. doi.org/10.3348/kjr.2012.13.1.1. PubMed PMID: 22247630. PubMed PMCID: 3253393.
3
Pantos I, Thalassinou S, Argentos S, Kelekis NL, Panayiotakis G, Efstathopoulos EP. Adult patient radiation doses from non-cardiac CT examinations: a review of published results. Br J Radiol. 2011;84:293-303. doi.org/10.1259/bjr/69070614. PubMed PMID: 21266399. PubMed PMCID: 3473464.
4
Kim YK, Sung YM, Choi JH, Kim EY, Kim HS. Reduced radiation exposure of the female breast during low-dose chest CT using organ-based tube current modulation and a bismuth shield: comparison of image quality and radiation dose. AJR Am J Roentgenol. 2013;200:537-44. doi.org/10.2214/AJR.12.9237. PubMed PMID: 23436842.
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Zhu X, Yu J, Huang Z. Low-dose chest CT: optimizing radiation protection for patients. AJR Am J Roentgenol. 2004;183:809-16. doi.org/10.2214/ajr.183.3.1830809. PubMed PMID: 15333374.
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Tappouni R, Mathers B. Scan Quality and Entrance Skin Dose in Thoracic CT: A Comparison between Bismuth Breast Shield and Posteriorly Centered Partial CT Scans. ISRN Radiol. 2013;2013:457396. doi.org/10.5402/2013/457396. PubMed PMID: 24967274. PubMed PMCID: 4045517.
7
Angel E, Yaghmai N, Jude CM, DeMarco JJ, Cagnon CH, Goldin JG, et al. Dose to radiosensitive organs during routine chest CT: effects of tube current modulation. AJR Am J Roentgenol. 2009;193:1340-5. doi.org/10.2214/AJR.09.2886. PubMed PMID: 19843751. PubMed PMCID: 2954276.
8
Linet MS, Slovis TL, Miller DL, Kleinerman R, Lee C, Rajaraman P, et al. Cancer risks associated with external radiation from diagnostic imaging procedures. CA Cancer J Clin. 2012;62:75-100. doi.org/10.3322/caac.21132. PubMed PMID: 22307864. PubMed PMCID: 3548988.
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Kubo T, Lin PJ, Stiller W, Takahashi M, Kauczor HU, Ohno Y, et al. Radiation dose reduction in chest CT: a review. AJR Am J Roentgenol. 2008;190:335-43. doi.org/10.2214/AJR.07.2556. PubMed PMID: 18212218.
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McCollough CH, Wang J, Berland LL. Bismuth shields for CT dose reduction: do they help or hurt? J Am Coll Radiol. 2011;8:878-9. doi.org/10.1016/j.jacr.2011.09.001. PubMed PMID: 22137008.
22
Hohl C, Wildberger JE, Suss C, Thomas C, Muhlenbruch G, Schmidt T, et al. Radiation dose reduction to breast and thyroid during MDCT: effectiveness of an in-plane bismuth shield. Acta Radiol. 2006;47:562-7. doi.org/10.1080/02841850600702150. PubMed PMID: 16875333.
23
ORIGINAL_ARTICLE
An Analytical-empirical Calculation of Linear Attenuation Coefficient of Megavoltage Photon Beams
Background: In this study, a method for linear attenuation coefficient calculation was introduced.Methods: Linear attenuation coefficient was calculated with a new method that base on the physics of interaction of photon with matter, mathematical calculation and x-ray spectrum consideration. The calculation was done for Cerrobend as a common radiotherapy modifier and Mercury.Results: The values of calculated linear attenuation coefficient with this new method are in acceptable range. Also, the linear attenuation coefficient decreases slightly as the thickness of attenuating filter (Cerrobend or mercury) increased, so the procedure of linear attenuation coefficient variation is in agreement with other documents. The results showed that the attenuation ability of mercury was about 1.44 times more than Cerrobend. Conclusion: The method that was introduced in this study for linear attenuation coefficient calculation is general enough to treat beam modifiers with any shape or material by using the same formalism; however, calculating was made only for mercury and Cerrobend attenuator. On the other hand, it seems that this method is suitable for high energy shields or protector designing.
https://jbpe.sums.ac.ir/article_43268_5730fa971b1179d7def09c38ec225634.pdf
2017-09-01
225
232
F
Seif
sahar_s59@yahoo.com
1
Assistant professor, Department of Medical Physics and Radiotherapy, Arak University of Medical Sciences, Arak, Iran
AUTHOR
M J
Tahmasebi-Birgani
s.medphy@gmail.com
2
Professor, Department of Medical Physics and Radiotherapy, Ahvaz Jundishapur University of Medical Sciences, Ahvaz, Iran
AUTHOR
M R
Bayatiani
mr_kbi@yahoo.com
3
Assistant professor, Department of Medical Physics and Radiotherapy, Arak University of Medical Sciences, Arak, Iran
LEAD_AUTHOR
Chang SX, Cullip TJ, Deschesne KM. Intensity modulation delivery techniques: “step & shoot” MLC auto-sequence versus the use of a modulator. Med Phys. 2000;27:948-59. doi.org/10.1118/1.598989. PubMed PMID: 10841397.
1
Meyer J, Mills JA, Haas OC, Parvin EM, Burnham KJ. Some limitations in the practical delivery of intensity modulated radiation therapy. Br J Radiol. 2000;73:854-63. doi.org/10.1259/bjr.73.872.11026861. PubMed PMID: 11026861.
2
du Plessis FC, Willemse CA. Monte Carlo calculation of effective attenuation coefficients for various compensator materials. Med Phys. 2003;30:2537-44. doi.org/10.1118/1.1591432. PubMed PMID: 14528976.
3
Midgley SM. Materials analysis using x-ray linear attenuation coefficient measurements at four photon energies. Phys Med Biol. 2005;50:4139-57. doi.org/10.1088/0031-9155/50/17/016. PubMed PMID: 16177536.
4
Lin JP, Chu TC, Liu MT. Dose compensation of the total body irradiation therapy. Appl Radiat Isot. 2001;55:623-30. doi.org/10.1016/S0969-8043(01)00129-4. PubMed PMID: 11573795.
5
Tahmasebi-Birgani MJ, Seif F, Bayatiani MR. Dosimetric characteristics of mercury and cerrobend blocks in megavoltage radiation therapy. Journal of Radioanalytical and Nuclear Chemistry. 2015;303:1843-50.
6
Huang PH, Chin LM, Bjarngard BE. Scattered photons produced by beam-modifying filters. Med Phys. 1986;13:57-63. doi.org/10.1118/1.595923. PubMed PMID: 3951410.
7
Mejaddem Y, Hyodynmaa S, Brahme A. Photon scatter in intensity modulating filters evaluated by first Compton scatter and Monte Carlo calculations and experiments in broad beams. Phys Med Biol. 2000;45:2747-60. doi.org/10.1088/0031-9155/45/10/302. PubMed PMID: 11049169.
8
Dimitriadis D, Fallone B. Compensators for intensity-modulated beams. Medical Dosimetry. 2002;27:215-20. doi.org/10.1016/S0958-3947(02)00139-5. PubMed PMID: 17592450.
9
Sasaki K, Obata Y. Dosimetric characteristics of a cubic-block-piled compensator for intensity-modulated radiation therapy in the Pinnacle radiotherapy treatment planning system. J Appl Clin Med Phys. 2007;8:85-100. PubMed PMID: 17592450.
10
Midgley SM. A parameterization scheme for the x-ray linear attenuation coefficient and energy absorption coefficient. Phys Med Biol. 2004;49:307-25. doi.org/10.1088/0031-9155/49/2/009. PubMed PMID: 15083673.
11
Alles J, Mudde RF. Beam hardening: analytical considerations of the effective attenuation coefficient of X-ray tomography. Med Phys. 2007;34:2882-9. doi.org/10.1118/1.2742501. PubMed PMID: 17821996.
12
Ali ES, Rogers DW. Functional forms for photon spectra of clinical linacs. Phys Med Biol. 2012;57:31-50. doi.org/10.1088/0031-9155/57/1/31. PubMed PMID: 22126713.
13
Birgani MJT, Seif F, Chegeni N, Bayatiani MR. Determination of the effective atomic and mass numbers for mixture and compound materials in high energy photon interactions. Journal of Radioanalytical and Nuclear Chemistry. 2012;292:1367-70. doi.org/10.1007/s10967-012-1677-2.
14
Chen Z, Wang X, Bortfeld T, Mohan R, Reinstein L. The influence of scatter on the design of optimized intensity modulations. Med Phys. 1995;22:1727-33. doi.org/10.1118/1.597536. PubMed PMID: 8587525.
15
IAEA. Absorbed Dose Determination in Electron Beam Radiotherapy: An International Code of Practice for Dosimetry Based on Standards of Absorbed Dose to Water IAEA Technical Report Series, IAEA TRS-398; 2001.
16
Johns HE. Physics of radiology: Charles River Media; 1983.
17
Gürler O, Yalçın S. A practical method for calculation of mass-attenuation coefficients of β particles. Annals of Nuclear Energy. 2005;32:1918-25. doi.org/10.1016/j.anucene.2005.05.007.
18
ORIGINAL_ARTICLE
Modelling Tumor-induced Angiogenesis: Combination of Stochastic Sprout Spacing and Sprout Progression
Background: Angiogenesis initiated by cancerous cells is the process by which new blood vessels are formed to enhance oxygenation and growth of tumor. Objective: In this paper, we present a new multiscale mathematical model for the formation of a vascular network in tumor angiogenesis process. Methods: Our model couples an improved sprout spacing model as a stochastic mathematical model of sprouting along an existing parent blood vessel, with a mathematical model of sprout progression in the extracellular matrix (ECM) in response to some tumor angiogenic factors (TAFs). We perform simulations of the siting of capillary sprouts on an existing blood vessel using finite difference approximation of the dynamic equations of some angiogenesis activators and inhibitors. Angiogenesis activators are chemicals secreted by hypoxic tumor cells for initiating angiogenesis, and inhibitors of the angiogenesis are chemicals that are produced around every new sprout during tumor angiogenesis to inhibit the formation of further sprouts as a feedback of sprouting in angiogenesis. Moreover, for modelling sprout progression in ECM, we use three equations for the motility of endothelial cells at the tip of the activated sprouts, the consumption of TAF and the production and uptake of Fibronectin by endothelial cells. Results: Coupling these two basic models not only does provide a better time estimation of angiogenesis process, but also it is more compatible with reality. Conclusion: This model can be used to provide basic information for angiogenesis in the related studies. Related simulations can estimate the position and number of sprouts along parent blood vessel during the initial steps of angiogenesis and models the process of sprout progression in ECM until they vascularize a tumor.
https://jbpe.sums.ac.ir/article_43269_dfb077420161a8a5382b156017ab6e6c.pdf
2017-09-01
233
256
Capillary network
Feedback Inhibition
Extracellular Matrix
Tumor Angiogenic Factors
Finite Difference Method
F
Hosseini
farideh_hosseini68@yahoo.com
1
Department of Electrical Engineering, Faculty of Engineering, Ferdowsi University of Mashhad, Mashhad, Iran
AUTHOR
N
Naghavi
n.naghavi@um.ac.ir
2
Department of Electrical Engineering, Faculty of Engineering, Ferdowsi University of Mashhad, Mashhad, Iran
LEAD_AUTHOR
Cieślak T, Morales-Rodrigo C. Long-time behavior of an angiogenesis model with flux at the tumor boundary. Zeitschrift für angewandte Mathematik und Physik. 2013;64:1625-41. doi.org/10.1007/s00033-013-0302-8.
1
Conway EM, Collen D, Carmeliet P. Molecular mechanisms of blood vessel growth. Cardiovasc Res. 2001;49:507-21. doi.org/10.1016/S0008-6363(00)00281-9. PubMed PMID: 11166264.
2
Kurz H, Burri PH, Djonov VG. Angiogenesis and vascular remodeling by intussusception: from form to function. News Physiol Sci. 2003;18:65-70. doi.org/10.1152/nips.01417.2002. PubMed PMID: 12644622.
3
Vilanova G, Colominas I, Gomez H. Capillary networks in tumor angiogenesis: from discrete endothelial cells to phase-field averaged descriptions via isogeometric analysis. Int J Numer Method Biomed Eng. 2013;29:1015-37. doi.org/10.1002/cnm.2552. PubMed PMID: 23653256.
4
Figg W, Folkman J. Angiogenesis: an integrative approach from science to medicine: Springer Science & Business Media; 2008.
5
Qutub A, Gabhann FM, Karagiannis ED, Vempati P, Popel AS. Multiscale models of angiogenesis. Engineering in Medicine and Biology Magazine, IEEE. 2009;28(2):14-31. doi.org/10.1109/MEMB.2009.931791.
6
Billy F, Ribba B, Saut O, Morre-Trouilhet H, Colin T, Bresch D, et al. A pharmacologically based multiscale mathematical model of angiogenesis and its use in investigating the efficacy of a new cancer treatment strategy. J Theor Biol. 2009;260:545-62. doi.org/10.1016/j.jtbi.2009.06.026. PubMed PMID: 19615383.
7
Mantzaris NV, Webb S, Othmer HG. Mathematical modeling of tumor-induced angiogenesis. Journal of mathematical biology. 2004;49:111-87. doi.org/10.1007/s00285-003-0262-2.
8
Hanahan D, Weinberg RA. The hallmarks of cancer. Cell. 2000;100:57-70. doi.org/10.1016/S0092-8674(00)81683-9.
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Hanahan D, Weinberg RA. Hallmarks of cancer: the next generation. Cell. 2011;144:646-74. doi.org/10.1016/j.cell.2011.02.013. PubMed PMID: 21376230.
10
Araujo RP, McElwain DL. A history of the study of solid tumour growth: the contribution of mathematical modelling. Bull Math Biol. 2004;66:1039-91. doi.org/10.1016/j.bulm.2003.11.002. PubMed PMID: 15294418.
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Addison-Smith B, McElwain DL, Maini PK. A simple mechanistic model of sprout spacing in tumour-associated angiogenesis. J Theor Biol. 2008;250:1-15. doi.org/10.1016/j.jtbi.2007.08.030. PubMed PMID: 18028960.
12
Folkman J, Klagsbrun M. Angiogenic factors. Science. 1987;235:442-7. doi.org/10.1126/science.2432664. PubMed PMID: 2432664.
13
Anderson AR, Chaplain MA. Continuous and discrete mathematical models of tumor-induced angiogenesis. Bull Math Biol. 1998;60:857-99. doi.org/10.1006/bulm.1998.0042. PubMed PMID: 9739618.
14
Anderson A, Chaplain M, Garcia-Reimbert C, Vargas C. A gradient-driven mathematical model of antiangiogenesis. Mathematical and computer modelling. 2000;32:1141-52. doi.org/10.1016/S0895-7177(00)00196-5.
15
Folkman J. Angiogenesis in cancer, vascular, rheumatoid and other disease. Nat Med. 1995;1:27-31. doi.org/10.1038/nm0195-27. PubMed PMID: 7584949.
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Anderson A, Chaplain M, Newman E, Steele R, Thompson A. Mathematical modelling of tumour invasion and metastasis. Computational and Mathematical Methods in Medicine. 2000;2:129-54. doi.org/10.1080/10273660008833042.
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Thorgeirsson UP, Lindsay CK, Cottam DW, Gomez DE. Tumor invasion, proteolysis, and angiogenesis. Journal of Neuro-oncology. 1993;18:89-103. doi.org/10.1007/BF01050415.
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Saarela J, Rehn M, Oikarinen A, Autio-Harmainen H, Pihlajaniemi T. The short and long forms of type XVIII collagen show clear tissue specificities in their expression and location in basement membrane zones in humans. Am J Pathol. 1998;153:611-26. doi.org/10.1016/S0002-9440(10)65603-9. PubMed PMID: 9708820. PubMed PMCID: 1852992.
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Heljasvaara R, Nyberg P, Luostarinen J, Parikka M, Heikkila P, Rehn M, et al. Generation of biologically active endostatin fragments from human collagen XVIII by distinct matrix metalloproteases. Exp Cell Res. 2005;307:292-304. doi.org/10.1016/j.yexcr.2005.03.021. PubMed PMID: 15950618.
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Karihaloo A, Karumanchi SA, Barasch J, Jha V, Nickel CH, Yang J, et al. Endostatin regulates branching morphogenesis of renal epithelial cells and ureteric bud. Proc Natl Acad Sci U S A. 2001;98:12509-14. doi.org/10.1073/pnas.221205198. PubMed PMID: 11606725. PubMed PMCID: 60084.
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Jurasz P, Alonso D, Castro-Blanco S, Murad F, Radomski MW. Generation and role of angiostatin in human platelets. Blood. 2003;102:3217-23. doi.org/10.1182/blood-2003-02-0378. PubMed PMID: 12855585.
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Dvorak HF. How tumors make bad blood vessels and stroma. The American journal of pathology. 2003;162:1747-57. doi.org/10.1016/S0002-9440(10)64309-X.
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Stokes CL, Lauffenburger DA. Analysis of the roles of microvessel endothelial cell random motility and chemotaxis in angiogenesis. J Theor Biol. 1991;152:377-403. doi.org/10.1016/S0022-5193(05)80201-2. PubMed PMID: 1721100.
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Hosseini F, Naghavi N. Two dimensional mathematical model of tumor angiogenesis: coupling of avascular growth and vascularization. Iranian J Med Phys. 2015;12(3):146-66.
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Orme ME, Chaplain MA. A mathematical model of the first steps of tumour-related angiogenesis: capillary sprout formation and secondary branching. IMA J Math Appl Med Biol. 1996;13:73-98. doi.org/10.1093/imammb/13.2.73. PubMed PMID: 8671581.
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Stéphanou A, McDougall SR, Anderson AR, Chaplain MA. Mathematical modelling of the influence of blood rheological properties upon adaptative tumour-induced angiogenesis. Mathematical and Computer Modelling. 2006;44:96-123. doi.org/10.1016/j.mcm.2004.07.021.
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McDougall SR, Anderson AR, Chaplain MA. Mathematical modelling of dynamic adaptive tumour-induced angiogenesis: clinical implications and therapeutic targeting strategies. J Theor Biol. 2006;241:564-89. doi.org/10.1016/j.jtbi.2005.12.022. PubMed PMID: 16487543.
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Paku S, Paweletz N. First steps of tumor-related angiogenesis. Lab Invest. 1991;65:334-46. PubMed PMID: 1716330.
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Serini G, Ambrosi D, Giraudo E, Gamba A, Preziosi L, Bussolino F. Modeling the early stages of vascular network assembly. EMBO J. 2003;22:1771-9. doi.org/10.1093/emboj/cdg176. PubMed PMID: 12682010. PubMed PMCID: 154468.
53
ORIGINAL_ARTICLE
Synergistic Effects of NDRG2 Overexpression and Radiotherapy on Cell Death of Human Prostate LNCaP Cells
Background: Radiation therapy is among the most conventional cancer therapeutic modalities with effective local tumor control. However, due to the development of radio-resistance, tumor recurrence and metastasis often occur following radiation therapy. In recent years, combination of radiotherapy and gene therapy has been suggested to overcome this problem. The aim of the current study was to explore the potential synergistic effects of N-Myc Downstream-Regulated Gene 2 (NDRG2) overexpression, a newly identified candidate tumor suppressor gene, with radiotherapy against proliferation of prostate LNCaP cell line.Materials and Methods: In this study, LNCaP cells were exposed to X-ray radiation in the presence or absence of NDRG2 overexpression using plasmid PSES- pAdenoVator-PSA-NDRG2-IRES-GFP. The effects of NDRG2 overexpression, X-ray radiation or combination of both on the cell proliferation and apoptosis of LNCaP cells were then analyzed using MTT assay and flow cytometery, respectively.Results: Results of MTT assay showed that NDRG2 overexpression and X-ray radiation had a synergistic effect against proliferation of LNCaP cells. Moreover, NDRG2 overexpression increased apoptotic effect of X-ray radiation in LNCaP cells synergistically.Conclusion: Our findings suggested that NDRG2 overexpression in combination with radiotherapy may be an effective therapeutic option against prostate cancer.
https://jbpe.sums.ac.ir/article_43270_b4e72a444f66fc1f43065c97b8ef9b18.pdf
2017-09-01
257
264
Gene Therapy
Radiation Therapy
Prostate Cancer
N-Myc Downstream-Regulated Gene 2
M
Alizadeh Zarei
marziyehalizadeh91@yahoo.com
1
Diagnostic Laboratory Sciences and Technology Research Center, Shiraz University of Medical Sciences, Shiraz, Iran
AUTHOR
M A
Takhshid
2
Diagnostic Laboratory Sciences and Technology Research Center, Shiraz University of Medical Sciences, Shiraz, Iran
LEAD_AUTHOR
A
Behzad Behbahani
behzadba@gmail.com
3
Diagnostic Laboratory Sciences and Technology Research Center, Shiraz University of Medical Sciences, Shiraz, Iran
AUTHOR
S Y
Hosseini
hosseinisy22@yahoo.com
4
Bacteriology and Virology Department, Shiraz University of Medical Sciences, Shiraz, Iran
AUTHOR
M A
Okhovat
okhovat.clinicallab@gmail.com
5
Diagnostic Laboratory Sciences and Technology Research Center, Shiraz University of Medical Sciences, Shiraz, Iran
AUTHOR
Gh R
Rafiee Dehbidi
aliraf60@gmail.com
6
Diagnostic Laboratory Sciences and Technology Research Center, Shiraz University of Medical Sciences, Shiraz, Iran
AUTHOR
M A
Mosleh Shirazi
mosleh_amin@hotmail.com
7
Ionizing and Nonionizing Radiation Protection Research Center, Shiraz University of Medical Sciences, Shiraz, Iran
AUTHOR
Center MM, Jemal A, Lortet-Tieulent J, Ward E, Ferlay J, Brawley O, et al. International variation in prostate cancer incidence and mortality rates. Eur Urol. 2012;61:1079-92. doi.org/10.1016/j.eururo.2012.02.054. PubMed PMID: 22424666.
1
Jain S, Saxena S, Kumar A. Epidemiology of prostate cancer in India. Meta Gene. 2014;2:596-605. doi.org/10.1016/j.mgene.2014.07.007. PubMed PMID: 25606442. PubMed PMCID: 4287887.
2
Hosseini M, SeyedAlinaghi S, Mahmoudi M, McFarland W. A case-control study of risk factors for prostate cancer in Iran. Acta Med Iran. 2010;48:61-6. PubMed PMID: 21137672.
3
Mousavi SM, Gouya MM, Ramazani R, Davanlou M, Hajsadeghi N, Seddighi Z. Cancer incidence and mortality in Iran. Ann Oncol. 2009;20:556-63. doi.org/10.1093/annonc/mdn642. PubMed PMID: 19073863.
4
Akbari ME, Hosseini SJ, Rezaee A, Hosseini MM, Rezaee I, Sheikhvatan M. Incidence of genitourinary cancers in the Islamic Republic of Iran: a survey in 2005. Asian Pac J Cancer Prev. 2008;9:549-52. PubMed PMID: 19256736.
5
Fujita T, Satoh T, Timme TL, Hirayama T, Zhu JX, Kusaka N, et al. Combined therapeutic effects of adenoviral vector-mediated GLIPR1 gene therapy and radiotherapy in prostate and bladder cancer models. Urologic Oncology: Seminars and Original Investigations: Elsevier; 2014.
6
Pollack A, Zagars GK. External beam radiotherapy dose response of prostate cancer. International Journal of Radiation Oncology* Biology* Physics. 1997;39:1011-8. doi.org/10.1016/S0360-3016(97)00508-7.
7
Zelefsky MJ, Cowen D, Fuks Z, Shike M, Burman C, Jackson A, et al. Long term tolerance of high dose three-dimensional conformal radiotherapy in patients with localized prostate carcinoma. Cancer. 1999;85:2460-8. doi.org/10.1002/(SICI)1097-0142(19990601)85:113.0.CO;2-N. PubMed PMID: 10357419.
8
Teh BS, Aguilar-Cordova E, Vlachaki MT, Aguilar L, Mai WY, Caillouet J, et al. Combining radiotherapy with gene therapy (from the bench to the bedside): a novel treatment strategy for prostate cancer. Oncologist. 2002;7:458-66. doi.org/10.1634/theoncologist.7-5-458. PubMed PMID: 12401909.
9
Kaliberov SA, Buchsbaum DJ. Chapter seven--Cancer treatment with gene therapy and radiation therapy. Adv Cancer Res. 2012;115:221-63. doi.org/10.1016/B978-0-12-398342-8.00007-0. PubMed PMID: 23021246. PubMed PMCID: 3664947.
10
Yao L, Zhang J, Liu X. NDRG2: a Myc-repressed gene involved in cancer and cell stress. Acta Biochim Biophys Sin (Shanghai). 2008;40:625-35. doi.org/10.1111/j.1745-7270.2008.00434.x. PubMed PMID: 18604454.
11
Tepel M, Roerig P, Wolter M, Gutmann DH, Perry A, Reifenberger G, et al. Frequent promoter hypermethylation and transcriptional downregulation of the NDRG2 gene at 14q11.2 in primary glioblastoma. Int J Cancer. 2008;123:2080-6. doi.org/10.1002/ijc.23705. PubMed PMID: 18709645.
12
Liu N, Wang L, Liu X, Yang Q, Zhang J, Zhang W, et al. Promoter methylation, mutation, and genomic deletion are involved in the decreased NDRG2 expression levels in several cancer cell lines. Biochem Biophys Res Commun. 2007;358:164-9. doi.org/10.1016/j.bbrc.2007.04.089. PubMed PMID: 17470364.
13
Lorentzen A, Vogel LK, Lewinsky RH, Saebo M, Skjelbred CF, Godiksen S, et al. Expression of NDRG2 is down-regulated in high-risk adenomas and colorectal carcinoma. BMC Cancer. 2007;7:192. doi.org/10.1186/1471-2407-7-192. PubMed PMID: 17935612. PubMed PMCID: 2099434.
14
Shi H, Jin H, Chu D, Wang W, Zhang J, Chen C, et al. Suppression of N-myc downstream-regulated gene 2 is associated with induction of Myc in colorectal cancer and correlates closely with differentiation. Biol Pharm Bull. 2009;32:968-75. doi.org/10.1248/bpb.32.968. PubMed PMID: 19483300.
15
Golestan AM, Mojtahedi ZP, Ghalamfarsa GP, Hamidinia MM, Takhshid MAP. The Effects of NDRG2 Overexpression on Cell Proliferation and Invasiveness of SW48 Colorectal Cancer Cell Line. Iran J Med Sci. 2015;40:430-9. PubMed PMID: 26379350. PubMed PMCID: 4567603.
16
Li SJ, Wang WY, Li B, Chen B, Zhang B, Wang X, et al. Expression of NDRG2 in human lung cancer and its correlation with prognosis. Med Oncol. 2013;30:421. doi.org/10.1007/s12032-012-0421-7. PubMed PMID: 23307246. PubMed PMCID: 3586402.
17
Faraji SN, Mojtahedi Z, Ghalamfarsa G, Takhshid MA. N-myc downstream regulated gene 2 overexpression reduces matrix metalloproteinase-2 and -9 activities and cell invasion of A549 lung cancer cell line in vitro. Iran J Basic Med Sci. 2015;18:773-9. PubMed PMID: 26557966. PubMed PMCID: 4633460.
18
Hu XL, Liu XP, Lin SX, Deng YC, Liu N, Li X, et al. NDRG2 expression and mutation in human liver and pancreatic cancers. World J Gastroenterol. 2004;10:3518-21. doi.org/10.3748/wjg.v10.i23.3518. PubMed PMID: 15526377. PubMed PMCID: 4576239.
19
Gao L, Wu GJ, Liu XW, Zhang R, Yu L, Zhang G, et al. Suppression of invasion and metastasis of prostate cancer cells by overexpression of NDRG2 gene. Cancer Lett. 2011;310:94-100. doi.org/10.1016/j.canlet.2011.06.015. PubMed PMID: 21741166.
20
Ren GF, Tang L, Yang AQ, Jiang WW, Huang YM. Prognostic impact of NDRG2 and NDRG3 in prostate cancer patients undergoing radical prostatectomy. Histol Histopathol. 2014;29:535-42. PubMed PMID: 24222185.
21
Li R, Yu C, Jiang F, Gao L, Li J, Wang Y, et al. Overexpression of N-Myc downstream-regulated gene 2 (NDRG2) regulates the proliferation and invasion of bladder cancer cells in vitro and in vivo. PLoS One. 2013;8:e76689. doi.org/10.1371/journal.pone.0076689. PubMed PMID: 24146910. PubMed PMCID: 3797857.
22
Horwitz EM, Hanks GE. External beam radiation therapy for prostate cancer. CA Cancer J Clin. 2000;50:349-75; quiz 76-9. doi.org/10.3322/canjclin.50.6.349. PubMed PMID: 11146903.
23
Mosleh-Shirazi, M.A., S. Rahimi, and S. Karbasi, Medium-Term Stability of the Photon Beam Energy of An Elekta CompactTM Linear Accelerator Based on Daily Measurements of Beam Quality Factor. Iranian Journal of Medical Physics. 2016;12(4):230-234. doi 10.22038/ijmp.2016.6835
24
Zeng M, Cerniglia GJ, Eck SL, Stevens CW. High-efficiency stable gene transfer of adenovirus into mammalian cells using ionizing radiation. Hum Gene Ther. 1997;8:1025-32. doi.org/10.1089/hum.1997.8.9-1025. PubMed PMID: 9189760.
25
Yaowen Z, Yongzhen C, Jin L, Qin W. Gene therapy and radiotherapy in malignant tumor. International Journal of Radiation Medicine and Nuclear Medicine. 2008;32:247-50.
26
Simons JW, Marshall FF. The future of gene therapy in the treatment of urologic malignancies. Urol Clin North Am. 1998;25:23-38. doi.org/10.1016/S0094-0143(05)70430-4. PubMed PMID: 9529534.
27
Najafi M, Fardid R, Takhshid MA, Mosleh-Shirazi MA, Rezaeyan AH, Salajegheh A. Radiation-induced oxidative stress at out-of-field lung tissues after pelvis irradiation in rats. Cell J. 2016; 18(3): 340-345.
28
Chhikara M, Huang H, Vlachaki MT, Zhu X, Teh B, Chiu KJ, et al. Enhanced therapeutic effect of HSV-tk+GCV gene therapy and ionizing radiation for prostate cancer. Mol Ther. 2001;3:536-42. doi.org/10.1006/mthe.2001.0298. PubMed PMID: 11319915.
29
Lohr F, Hu K, Haroon Z, Samulski TV, Huang Q, Beaty J, et al. Combination treatment of murine tumors by adenovirus-mediated local B7/IL12 immunotherapy and radiotherapy. Mol Ther. 2000;2:195-203. doi.org/10.1006/mthe.2000.0114. PubMed PMID: 10985949.
30
Kaliberov SA, Kaliberova LN, Buchsbaum DJ. Combined ionizing radiation and sKDR gene delivery for treatment of prostate carcinomas. Gene Ther. 2005;12:407-17. doi.org/10.1038/sj.gt.3302432. PubMed PMID: 15616600.
31
ORIGINAL_ARTICLE
The Optimization of Magnetic Resonance Imaging Pulse Sequences in Order to Better Detection of Multiple Sclerosis Plaques
Background and objective: Magnetic resonance imaging (MRI) is the most sensitive technique to detect multiple sclerosis (MS) plaques in central nervous system. In some cases, the patients who were suspected to MS, Whereas MRI images are normal, but whether patients don’t have MS plaques or MRI images are not enough optimized enough in order to show MS plaques? The aim of the current study is evaluating the efficiency of different MRI sequences in order to better detection of MS plaques.Materials and methods: In this cross-sectional study which was performed at Shohada-E Tajrish in Tehran - Iran hospital between October, 2011 to April, 2012, included 20 patients who suspected to MS disease were selected by the method of random sampling and underwent routine brain Pulse sequences (Axial T2w, Axial T1w, Coronal T2w, Sagittal T1w, Axial FLAIR) by Siemens, Avanto, 1.5 Tesla system. If any lesion which is suspected to the MS disease was observed, additional sequences such as: Sagittal FLAIR Fat Sat, Sagittal PDw-fat Sat, Sagittal PDw-water sat was also performed.Results: This study was performed in about 52 lesions and the results in more than 19 lesions showed that, for the Subcortical and Infratentorial areas, PDWw sequence with fat suppression is the best choice, And in nearly 33 plaques located in Periventricular area, FLAIR Fat Sat was the most effective sequence than both PDw fat and water suppression pulse sequences.Conclusion: Although large plaques may visible in all images, but important problem in patients with suspected MS is screening the tiny MS plaques. This study showed that for revealing the MS plaques located in the Subcortical and Infratentorial areas, PDw-fat sat is the most effective sequence, and for MS plaques in the periventricular area, FLAIR fat Sat is the best choice.
https://jbpe.sums.ac.ir/article_43271_83f6da3fd0a7216f7052ec3e9d87ad7e.pdf
2017-09-01
265
270
Multiple Sclerosis
MRI
PDW fat suppression
PDW water suppression
FLAIR
Z
Farshidfar
abdolmohammadi.jamil@gmail.com
1
MSc of Medical Imaging Technology (MRI), Radiology Department of Paramedical School, Shiraz University of Medical Sciences, Shiraz, Iran
AUTHOR
F
Faeghi
2
Ph.D. in Medical Physics, Radiology Technology Department, School of Allied Medical Sciences, Shahid Beheshti University of Medical Sciences, Tehran, Iran
AUTHOR
H R
Haghighatkhah
3
MD, Department of Radiology, Shohada Tajrish Hospital, Shahid Beheshti University of medical sciences, Tehran, Iran
AUTHOR
J
Abdolmohammadi
4
MSc. of Medical Imaging Technology (MRI), Department of Radiology, Faculty of Paramedical Sciences, Kurdistan University of Medical Sciences, Sanandaj, Iran
LEAD_AUTHOR
Lucchinetti CF, Popescu BF, Bunyan RF, Moll NM, Roemer SF, Lassmann H, et al. Inflammatory cortical demyelination in early multiple sclerosis. N Engl J Med. 2011;365:2188-97. doi.org/10.1056/NEJMoa1100648. PubMed PMID: 22150037. PubMed PMCID: 3282172.
1
Filippi M, Rocca MA, Barkhof F, Bruck W, Chen JT, Comi G, et al. Association between pathological and MRI findings in multiple sclerosis. Lancet Neurol. 2012;11:349-60. doi.org/10.1016/S1474-4422(12)70003-0. PubMed PMID: 22441196.
2
Antel J, Antel S, Caramanos Z, Arnold DL, Kuhlmann T. Primary progressive multiple sclerosis: part of the MS disease spectrum or separate disease entity? Acta Neuropathol. 2012;123:627-38. doi.org/10.1007/s00401-012-0953-0. PubMed PMID: 22327362.
3
Vrethem M, Malmgren K, Lindh J. A patient with both narcolepsy and multiple sclerosis in association with Pandemrix vaccination. J Neurol Sci. 2012;321:89-91. doi.org/10.1016/j.jns.2012.07.025. PubMed PMID: 22841884.
4
Skoog B, Runmarker B, Winblad S, Ekholm S, Andersen O. A representative cohort of patients with non-progressive multiple sclerosis at the age of normal life expectancy. Brain. 2012;135:900-11. doi.org/10.1093/brain/awr336. PubMed PMID: 22366800.
5
Milo R, Kahana E. Multiple sclerosis: geoepidemiology, genetics and the environment. Autoimmunity reviews. 2010;9(5):A387-A94.
6
Alport AR, Sander HW. Clinical approach to peripheral neuropathy: anatomic localization and diagnostic testing. Continuum (Minneap Minn). 2012;18:13-38. doi.org/10.1212/01.CON.0000411546.13207.b1. PubMed PMID: 22810068.
7
Reimer P, Parizel PM, Meaney JF, Stichnoth FA. Clinical MR imaging: Springer; 2010.
8
Minneboo A. Magnetic Resonance Imaging Predictors for Disability in Multiple Sclerosis: Amsterdam: Vrije Universiteit; 2008.
9
Poser CM, Brinar VV. Diagnostic criteria for multiple sclerosis: an historical review. Clin Neurol Neurosurg. 2004;106:147-58. doi.org/10.1016/j.clineuro.2004.02.004. PubMed PMID: 15177763.
10
McDonald WI, Compston A, Edan G, Goodkin D, Hartung HP, Lublin FD, et al. Recommended diagnostic criteria for multiple sclerosis: guidelines from the International Panel on the diagnosis of multiple sclerosis. Ann Neurol. 2001;50:121-7. doi.org/10.1002/ana.1032. PubMed PMID: 11456302.
11
Polman CH, Reingold SC, Edan G, Filippi M, Hartung HP, Kappos L, et al. Diagnostic criteria for multiple sclerosis: 2005 revisions to the “McDonald Criteria”. Ann Neurol. 2005;58:840-6. doi.org/10.1002/ana.20703. PubMed PMID: 16283615.
12
Loizou CP, Murray V, Pattichis MS, Seimenis I, Pantziaris M, Pattichis CS. Multiscale amplitude-modulation frequency-modulation (AM-FM) texture analysis of multiple sclerosis in brain MRI images. IEEE Trans Inf Technol Biomed. 2011;15:119-29. doi.org/10.1109/TITB.2010.2091279. PubMed PMID: 21062681.
13
Polman CH, Reingold SC, Banwell B, Clanet M, Cohen JA, Filippi M, et al. Diagnostic criteria for multiple sclerosis: 2010 revisions to the McDonald criteria. Ann Neurol. 2011;69:292-302. doi.org/10.1002/ana.22366. PubMed PMID: 21387374. PubMed PMCID: 3084507.
14
Montalban X, Tintore M, Swanton J, Barkhof F, Fazekas F, Filippi M, et al. MRI criteria for MS in patients with clinically isolated syndromes. Neurology. 2010;74:427-34. doi.org/10.1212/WNL.0b013e3181cec45c. PubMed PMID: 20054006.
15
Traboulsee A, Li DK, Zhao G, Paty DW. Conventional MRI techniques in multiple sclerosis. MR Imaging in White Matter Diseases of the Brain and Spinal Cord: Springer; 2005. p. 211-23.
16
Miller DH, Albert PS, Barkhof F, Francis G, Frank JA, Hodgkinson S, et al. Guidelines for the use of magnetic resonance techniques in monitoring the treatment of multiple sclerosis. US National MS Society Task Force. Ann Neurol. 1996;39:6-16. doi.org/10.1002/ana.410390104. PubMed PMID: 8572668.
17
Gawne-Cain ML, Silver NC, Moseley IF, Miller DH. Fast FLAIR of the brain: the range of appearances in normal subjects and its application to quantification of white-matter disease. Neuroradiology. 1997;39:243-9. doi.org/10.1007/s002340050402. PubMed PMID: 9144670.
18
Kepes JJ. Large focal tumor-like demyelinating lesions of the brain: intermediate entity between multiple sclerosis and acute disseminated encephalomyelitis? A study of 31 patients. Ann Neurol. 1993;33:18-27. doi.org/10.1002/ana.410330105. PubMed PMID: 8494332.
19
Brück W, Bitsch A, Kolenda H, Brück Y, Stiefel M, Lassmann H. Inflammatory central nervous system demyelination: correlation of magnetic resonance imaging findings with lesion pathology. Annals of Neurology. 1997;42(5):783-93.
20
Nijeholt GJ, van Walderveen MA, Castelijns JA, van Waesberghe JH, Polman C, Scheltens P, et al. Brain and spinal cord abnormalities in multiple sclerosis. Correlation between MRI parameters, clinical subtypes and symptoms. Brain. 1998;121:687-97. doi.org/10.1093/brain/121.4.687. PubMed PMID: 9577394.
21
Herskovits EH, Itoh R, Melhem ER. Accuracy for detection of simulated lesions: comparison of fluid-attenuated inversion-recovery, proton density--weighted, and T2-weighted synthetic brain MR imaging. AJR Am J Roentgenol. 2001;176:1313-8. doi.org/10.2214/ajr.176.5.1761313. PubMed PMID: 11312201.
22
Kamson DO, Illes Z, Aradi M, Orsi G, Perlaki G, Leel-Ossy E, et al. Volumetric comparisons of supratentorial white matter hyperintensities on FLAIR MRI in patients with migraine and multiple sclerosis. J Clin Neurosci. 2012;19:696-701. doi.org/10.1016/j.jocn.2011.07.044. PubMed PMID: 22440862.
23
Prosperini L, Kouleridou A, Petsas N, Leonardi L, Tona F, Pantano P, et al. The relationship between infratentorial lesions, balance deficit and accidental falls in multiple sclerosis. J Neurol Sci. 2011;304:55-60. doi.org/10.1016/j.jns.2011.02.014. PubMed PMID: 21402386.
24
Lazeron RH, Langdon DW, Filippi M, van Waesberghe JH, Stevenson VL, Boringa JB, et al. Neuropsychological impairment in multiple sclerosis patients: the role of (juxta)cortical lesion on FLAIR. Mult Scler. 2000;6:280-5. doi.org/10.1177/135245850000600410. PubMed PMID: 10962549.
25
Castillo MS, Davis FG, Surawicz T, Bruner JM, Bigner S, Coons S, et al. Consistency of primary brain tumor diagnoses and codes in cancer surveillance systems. Neuroepidemiology. 2004;23:85-93. doi.org/10.1159/000073980. PubMed PMID: 14739573.
26
Gawne-Cain ML, O’Riordan JI, Thompson AJ, Moseley IF, Miller DH. Multiple sclerosis lesion detection in the brain: a comparison of fast fluid-attenuated inversion recovery and conventional T2-weighted dual spin echo. Neurology. 1997;49:364-70. doi.org/10.1212/WNL.49.2.364. PubMed PMID: 9270563.
27
Bakshi R, Czarnecki D, Shaikh ZA, Priore RL, Janardhan V, Kaliszky Z, et al. Brain MRI lesions and atrophy are related to depression in multiple sclerosis. Neuroreport. 2000;11:1153-8. doi.org/10.1097/00001756-200004270-00003. PubMed PMID: 10817583.
28
Seewann A, Kooi EJ, Roosendaal SD, Pouwels PJ, Wattjes MP, van der Valk P, et al. Postmortem verification of MS cortical lesion detection with 3D DIR. Neurology. 2012;78:302-8. doi.org/10.1212/WNL.0b013e31824528a0. PubMed PMID: 22218278.
29
Roosendaal SD, Moraal B, Pouwels PJ, Vrenken H, Castelijns JA, Barkhof F, et al. Accumulation of cortical lesions in MS: relation with cognitive impairment. Mult Scler. 2009;15:708-14. doi.org/10.1177/1352458509102907. PubMed PMID: 19435749.
30
ORIGINAL_ARTICLE
Evaluation of Radiation Exposure Pattern and Radiation Absorbed Dose Resulting from Occupational Exposure of Anesthesiologists to Ionizing Radiation
Introduction: Little information is available concerning the radiation exposure of anesthesiologists, and no such data have previously been collected in Iran. This prospective study was performed to determine the amount of radiation exposure of anesthesiologists for the purpose of assessing whether or not dangerous levels of radiation exposures were being reached, and to identify factors that correlate with excessive risk.Participants and Methods: The radiation exposure of all anesthesiology residents and the attending of Shiraz University of Medical Sciences during a 3-month period (from June to August 2016) was measured using a film badge with monthly readings. Physicians were divided into two groups: group 1 (the ones assigned to ORs with radiation exposure), and group 2 (the ones assigned to ORs with no or minimal radiation exposure).Results: A total number of 10744 procedures were performed in 3 major university hospitals including 353 cases of pediatric angiography, 251 cases of percutaneous nephrolithotomy, 43 cases of chronic pain palliation and 672 cases of orthopedic surgeries with C-arm application. In all 3 months, there were statistically significant differences in the amount of radiation exposure between the two groups.Conclusion: Anesthesiologists working in the cardiac catheterization laboratory, pain treatment service, orthopedic and urologic ORs are exposed to statistically significantly higher radiation levels compared to their colleagues in other ORs. The radiation exposure to anesthesiologists can rise to high levels; therefore, they should get proper teaching, shielding and periodic evaluations.
https://jbpe.sums.ac.ir/article_43272_90fdf749adcc5eab52769e221bc99a63.pdf
2017-09-01
271
278
Anesthesiologist
Radiation
Exposure
Ionizing
B
Maghsoudi
pvatankhah@yahoo.com
1
Anesthesiology and critical care research center, Shiraz University of Medical Sciences, Shiraz, Iran
AUTHOR
S M J
Mortazavi
mortazavismj@gmail.com
2
The Ionizing and Non-ionizing Radiation Protection Research Center (INIRPRC) & Medical Physics & Medical Engineering Department, Shiraz University of Medical Sciences, School of Medicine, Shiraz, Iran
AUTHOR
S
Khademi
sarakhademi22@yahoo.com
3
Anesthesiology and critical care research center, Shiraz University of Medical Sciences, Shiraz, Iran
AUTHOR
P
Vatankhah
4
Anesthesiology and critical care research center, Shiraz University of Medical Sciences, Shiraz, Iran
LEAD_AUTHOR
Chodick G, Bekiroglu N, Hauptmann M, Alexander BH, Freedman DM, Doody MM, et al. Risk of cataract after exposure to low doses of ionizing radiation: a 20-year prospective cohort study among US radiologic technologists. Am J Epidemiol. 2008;168:620-31. doi.org/10.1093/aje/kwn171. PubMed PMID: 18664497. PubMed PMCID: 2727195.
1
Gilbert ES. Ionising radiation and cancer risks: what have we learned from epidemiology? Int J Radiat Biol. 2009;85:467-82. doi.org/10.1080/09553000902883836. PubMed PMID: 19401906. PubMed PMCID: 2859619.
2
Richardson DB, Cardis E, Daniels RD, Gillies M, O’Hagan JA, Hamra GB, et al. Risk of cancer from occupational exposure to ionising radiation: retrospective cohort study of workers in France, the United Kingdom, and the United States (INWORKS). BMJ. 2015;351:h5359. doi.org/10.1136/bmj.h5359. PubMed PMID: 26487649. PubMed PMCID: 4612459.
3
Sont WN, Zielinski JM, Ashmore JP, Jiang H, Krewski D, Fair ME, et al. First analysis of cancer incidence and occupational radiation exposure based on the National Dose Registry of Canada. Am J Epidemiol. 2001;153:309-18. doi.org/10.1093/aje/153.4.309. PubMed PMID: 11207146.
4
The United Nation Scientific Committee on the Effects of Atomic Radiation. Radiation UNSCotEoA. Sources and effects of ionizing radiation: sources: United Nations Publications; 2000.
5
Durack DP, Gardner AI, Trang A. Radiation exposure during anaesthetic practice. Anaesth Intensive Care. 2006;34:216-7. PubMed PMID: 16617643.
6
Beir V. Health effects of exposure to low levels of ionizing radiation. Washington, DC: National Academy of Sciences; 1990.
7
Ainsbury EA, Bouffler SD, Dorr W, Graw J, Muirhead CR, Edwards AA, et al. Radiation cataractogenesis: a review of recent studies. Radiat Res. 2009;172:1-9. doi.org/10.1667/RR1688.1. PubMed PMID: 19580502.
8
Katz JD. Radiation exposure to anesthesia personnel: the impact of an electrophysiology laboratory. Anesth Analg. 2005;101:1725-6. doi.org/10.1213/01.ANE.0000184039.00652.B8. PubMed PMID: 16301249.
9
Ismail S, Khan FA, Sultan N, Naqvi M. Radiation exposure of trainee anaesthetists. Anaesthesia. 2006;61:9-14. doi.org/10.1111/j.1365-2044.2005.04419.x. PubMed PMID: 16409335.
10
McGowan C, Heaton B, Stephenson RN. Occupational x-ray exposure of anaesthetists. Br J Anaesth. 1996;76:868-9. doi.org/10.1093/bja/76.6.868. PubMed PMID: 8679364.
11
Valentin J. Avoidance of radiation injuries from medical interventional procedures. Ann ICRP. 2000;30:7-67. doi.org/10.1016/S0146-6453(01)00004-5. PubMed PMID: 11459599.
12
Sinclair WK. Radiation protection recommendations on dose limits: the role of the NCRP and the ICRP and future developments. Int J Radiat Oncol Biol Phys. 1995;31:387-92. doi.org/10.1016/0360-3016(94)00275-P. PubMed PMID: 7836093.
13
Shook DC, Gross W. Offsite anesthesiology in the cardiac catheterization lab. Curr Opin Anaesthesiol. 2007;20:352-8. doi.org/10.1097/ACO.0b013e32827ab47b. PubMed PMID: 17620845.
14
Mehlman CT, DiPasquale TG. Radiation exposure to the orthopaedic surgical team during fluoroscopy: “how far away is far enough?”. J Orthop Trauma. 1997;11:392-8. doi.org/10.1097/00005131-199708000-00002. PubMed PMID: 9314144.
15
Henderson KH, Lu JK, Strauss KJ, Treves ST, Rockoff MA. Radiation exposure of anesthesiologists. J Clin Anesth. 1994;6:37-41. doi.org/10.1016/0952-8180(94)90116-3. PubMed PMID: 8142097.
16
Kincaid OW. The problem of repeated exposure to radiation by anesthesiologists. Anesth Analg. 1958;37:361-70. doi.org/10.1213/00000539-195811000-00017. PubMed PMID: 13606411.
17
Otto LK, Davidson S. Radiation exposure of Certified Registered Nurse Anesthetists during ureteroscopic procedures using fluoroscopy. AANA J. 1999;67:53-8. PubMed PMID: 10488277.
18
Lowe FC, Auster M, Beck TJ, Chang R, Marshall FF. Monitoring radiation exposure to medical personnel during percutaneous nephrolithotomy. Urology. 1986;28:221-6. doi.org/10.1016/0090-4295(86)90047-6. PubMed PMID: 3750603.
19
Keenan W, Woodward A, Price D, Eckloff K, Richards J, Powell J, et al. Manipulation under anaesthetic of children’s fractures: use of the image intensifier reduces radiation exposure to patients and theatre personnel. Journal of Pediatric Orthopaedics. 1996;16:183-6. doi.org/10.1097/01241398-199603000-00009.
20
ORIGINAL_ARTICLE
An Update of Couch Effect on the Attenuation of Megavoltage Radiotherapy Beam and the Variation of Absorbed Dose in the Build-up Region
Purpose: Fiber carbon is the most common material used in treating couch as it causes less beam attenuation than other materials. Beam attenuation replaces build-up region, reduces skin-sparing effect and causes target volume under dosage. In this study, we aimed to evaluate beam attenuation and variation of build-up region in 550 TxT radiotherapy couch. Materials and Methods: In this study, we utilized cylindrical PMMA Farmer chamber, DOSE-1 electrometer and set PMMA phantom in isocenter of gantry and the Farmer chamber on the phantom. Afterwards, the gantry rotated 10°, and attenuation was assessed. To measure build-up region, we used Markus chamber, Solid water phantom and DOSE-1 electrometer. Doing so, we set Solid water phantom on isocenter of gantry and placed Markus chamber in it, then we quantified the build-up region at 0° and 180° gantry angels and compared the obtained values.Results: Notable attenuation and build-up region variation were observed in 550 TxT treatment table. The maximum rate of attenuation was 5.95% for 6 MV photon beam, at 5×5 cm2 field size and 130° gantry angle, while the maximum variation was 7 mm for 6 MV photon beam at 10×10 cm2 field size.Conclusion: Fiber carbon caused beam attenuation and variation in the build-up region. Therefore, the application of fiber carbon is recommended for planning radiotherapy to prevent skin side effects and to decrease the risk of cancer recurrence.
https://jbpe.sums.ac.ir/article_43273_fcb7214c8b747bac79df621b355614ec.pdf
2017-09-01
279
288
Beam Attenuation
Carbon Fiber
Couch Insert
Surface Dose
Megavoltage Radiotherapy
T
Sedaghatian
taherehsedaghatian@yahoo.com
1
Department of Medical Physics, Faculty of Medicine, Tabriz University of Medical Science, Tabriz, Iran
AUTHOR
M
Momennezhad
momennezhadm@mums.ac.ir
2
Department of Medical Physics, Faculty of Medicine, Mashhad University of Medical Sciences, Iran
AUTHOR
S H
Rasta
s.h.rasta@abdn.ac.uk
3
Immunology Research Center, Tabriz University of Medical Sciences, Tabriz, Iran
LEAD_AUTHOR
Y
Makhdoomi
makhdoumi@gmail.com
4
Radiotherapy and Oncology Reza Center, Mashhad, Iran
AUTHOR
S
Abdollahian
mph586@gmail.com
5
Radiotherapy and Oncology Reza Center, Mashhad, Iran
AUTHOR
Hoppe BS, Laser B, Kowalski AV, Fontenla SC, Pena-Greenberg E, Yorke ED, et al. Acute skin toxicity following stereotactic body radiation therapy for stage I non-small-cell lung cancer: who’s at risk? Int J Radiat Oncol Biol Phys. 2008;72:1283-6. doi.org/10.1016/j.ijrobp.2008.08.036. PubMed PMID: 19028267.
1
De Ost B, Vanregemorter J, Schaeken B, Van den Weyngaert D. The effect of carbon fibre inserts on the build-up and attenuation of high energy photon beams. Radiother Oncol. 1997;45:275-7. doi.org/10.1016/S0167-8140(97)00118-7. PubMed PMID: 9426122.
2
Higgins DM, Whitehurst P, Morgan AM. The effect of carbon fiber couch inserts on surface dose with beam size variation. Med Dosim. 2001;26:251-4. doi.org/10.1016/S0958-3947(01)00071-1. PubMed PMID: 11704460.
3
McCormack S, Diffey J, Morgan A. The effect of gantry angle on megavoltage photon beam attenuation by a carbon fiber couch insert. Med Phys. 2005;32:483-7. doi.org/10.1118/1.1852792. PubMed PMID: 15789595.
4
Poppe B, Chofor N, Ruhmann A, Kunth W, Djouguela A, Kollhoff R, et al. The effect of a carbon-fiber couch on the depth-dose curves and transmission properties for megavoltage photon beams. Strahlenther Onkol. 2007;183:43-8. doi.org/10.1007/s00066-007-1582-8. PubMed PMID: 17225945.
5
Mihaylov IB, Corry P, Yan Y, Ratanatharathorn V, Moros EG. Modeling of carbon fiber couch attenuation properties with a commercial treatment planning system. Med Phys. 2008;35:4982-8. doi.org/10.1118/1.2982135. PubMed PMID: 19070232.
6
Njeh CF, Raines TW, Saunders MW. Determination of the photon beam attenuation by the Brainlab imaging couch: angular and field size dependence. J Appl Clin Med Phys. 2009;10:2979. doi.org/10.1120/jacmp.v10i3.2979. PubMed PMID: 19692980.
7
Gerig LH, Niedbala M, Nyiri BJ. Dose perturbations by two carbon fiber treatment couches and the ability of a commercial treatment planning system to predict these effects. Med Phys. 2010;37:322-8. doi.org/10.1118/1.3271364. PubMed PMID: 20175495.
8
Seppala JK, Kulmala JA. Increased beam attenuation and surface dose by different couch inserts of treatment tables used in megavoltage radiotherapy. J Appl Clin Med Phys. 2011;12:3554. doi.org/10.1120/jacmp.v12i4.3554. PubMed PMID: 22089010.
9
Myint WK, Niedbala M, Wilkins D, Gerig LH. Investigating treatment dose error due to beam attenuation by a carbon fiber tabletop. J Appl Clin Med Phys. 2006;7:21-7. doi.org/10.1120/jacmp.v7i3.2247. PubMed PMID: 17533341.
10
Khan FM, Gibbons JP. Khan’s the physics of radiation therapy. 5th edition. Philadelphia: Lippincott Williams & Wilkins; 2014.
11
Lee KW, Wu JK, Jeng SC, Hsueh Liu YW, Cheng JC. Skin dose impact from vacuum immobilization device and carbon fiber couch in intensity modulated radiation therapy for prostate cancer. Med Dosim. 2009;34:228-32. doi.org/10.1016/j.meddos.2008.10.001. PubMed PMID: 19647634.
12
Vanetti E, Nicolini G, Clivio A, Fogliata A, Cozzi L. The impact of treatment couch modelling on RapidArc. Phys Med Biol. 2009;54:N157-66. doi.org/10.1088/0031-9155/54/9/N03. PubMed PMID: 19351984.
13
Butson MJ, Cheung T, Yu PK. Megavoltage x-ray skin dose variation with an angle using grid carbon fibre couch tops. Phys Med Biol. 2007;52:N485-92. doi.org/10.1088/0031-9155/52/20/N03. PubMed PMID: 17921572.
14
Almond P, Andreo P, Mattsson O, Nahum A, Roos M. The use of plane-parallel ionization chambers in high-energy electron and photon beams. An international Code of Practice for dosimetry. IAEA Technical Reports Series no. 381. 1997.
15
Nuutinen J, Lahtinen T, Turunen M, Alanen E, Tenhunen M, Usenius T, et al. A dielectric method for measuring early and late reactions in irradiated human skin. Radiother Oncol. 1998;47:249-54. doi.org/10.1016/S0167-8140(97)00234-X. PubMed PMID: 9681887.
16
Nuutinen J, Vaananen A, Lahtinen T, Turunen M, Remes S, Alanen E. Radiobiological depth of subcutaneous induration. Radiother Oncol. 2000;55:187-90. doi.org/10.1016/S0167-8140(99)00147-4. PubMed PMID: 10799731.
17
Spezi E, Ferri A. Dosimetric characteristics of the Siemens IGRT carbon fiber tabletop. Med Dosim. 2007;32:295-8. doi.org/10.1016/j.meddos.2006.11.006. PubMed PMID: 17980831.
18
ORIGINAL_ARTICLE
In vitro Evaluation of the Relationship between Gray Scales in Digital Intraoral Radiographs and Hounsfield Units in CT Scans
Background: Jaw bone quality plays an essential role in treatment planning and prognosis of dental implants. Regarding several available methods for bone density measurements, they are not routinely used before implant surgery due to hard accessibility.Objective: An in vitro investigation of correlation between average gray scale in direct digital radiographs and Hounsfield units in CT-Scan provides a feasible method for evaluating alveolar bone quality prior to implant surgery.Methods: 26 sheep’s mandibles in which a square shape ROI marked by gutta percha, were prepared. Three direct digital radiographs (CCD sensor) from every specimen were taken using 80, 100 and 200 milli-seconds. Then, the average gray levels for ROIs were calculated using a costume-made software. Next, the specimens were scanned using a 16-slice spiral CT and the Hounsfield Unit of each ROI was calculated. Pearson analysis measured the correlation between Hounsfield units and average gray levels.Results: There was a positive correlation between Hounsfield unit and average gray level in the radiographs and the correlation was better in higher exposure times. Conclusion: It is possible to estimate Hounsfield unit and bone density in the jaw bones using average gray scale in a digital radiograph. This approach is easy, simple and available and also results in lower patient exposure comparing other bone densitometric analysis methods.
https://jbpe.sums.ac.ir/article_43274_1f134a105ab480d35449a01ae309bf7c.pdf
2017-09-01
289
298
Hounsfield Units
Gray Level
Bone Density
Implant
L
Khojastepour
1
Professor of Oral and Maxillofacial Radiology (M.Sc.), Department of Radiology, School of Dentistry, Shiraz University of Medical Sciences, Shiraz, Iran
AUTHOR
S
Mohammadzadeh
2
Specialist in Periodontology (M.Sc.), Department of Periodontics, School of Dentistry, Bushehr University of Medical Sciences, Bushehr, Iran
AUTHOR
M
Jazayeri
jazayerm@yahoo.com
3
Specialist in Oral and Maxillofacial Radiology (M.Sc.), Private Clinic of Oral and Maxillofacial Radiology, Khoramabad, Iran
AUTHOR
M
Omidi
mahsaomidi@yahoo.com
4
Assistant Professor of Oral and Maxillofacial Radiology (M.Sc), Department of Radiology, School of Dentistry, Shiraz University of Medical Sciences, International Branch, Shiraz, Iran
LEAD_AUTHOR
Compston J. Bone quality: what is it and how is it measured? Arquivos Brasileiros de Endocrinologia & Metabologia. 2006;50:579-85. doi.org/10.1590/S0004-27302006000400003.
1
Fyhrie DP. Summary--Measuring “bone quality”. J Musculoskelet Neuronal Interact. 2005;5:318-20. PubMed PMID: 16340121.
2
Licata A. Bone density vs bone quality: what’s a clinician to do? Cleve Clin J Med. 2009;76:331-6. doi.org/10.3949/ccjm.76a.08041. PubMed PMID: 19487553.
3
Sievanen H, Kannus P, Jarvinen TL. Bone quality: an empty term. PLoS Med. 2007;4:e27. doi.org/10.1371/journal.pmed.0040027. PubMed PMID: 17341126.
4
Minkin C, Marinho VC. Role of the osteoclast at the bone-implant interface. Adv Dent Res. 1999;13:49-56. doi.org/10.1177/08959374990130011401. PubMed PMID: 11276746.
5
Sakka S, Coulthard P. Bone quality: a reality for the process of osseointegration. Implant Dent. 2009;18(6):480-5. doi: 10.1097/ID.0b013e3181bb840d. Review. PubMed PMID: 20009601.
6
Santiago RC, de Paula FO, Fraga MR, Picorelli Assis NM, Vitral RW. Correlation between miniscrew stability and bone mineral density in orthodontic patients. Am J Orthod Dentofacial Orthop. 2009;136:243-50. doi.org/10.1016/j.ajodo.2007.08.031. PubMed PMID: 19651355.
7
Misch CE. Bone density: a key determinant for treatment planning. Contemporary implant dentistry. 3rd ed. St Louis: Mosby; 2007. p. 130-146.
8
Johansson P, Strid K. Assessment of bone quality from cutting resistance during implant surgery. International Journal of Oral and Maxillofacial Implants. 1994;9:279-88.
9
Scarfe WC, Farman AG, Sukovic P. Clinical applications of cone-beam computed tomography in dental practice. J Can Dent Assoc. 2006;72:75-80. PubMed PMID: 16480609.
10
Nackaerts O, Maes F, Yan H, Couto Souza P, Pauwels R, Jacobs R. Analysis of intensity variability in multislice and cone beam computed tomography. Clin Oral Implants Res. 2011;22:873-9. doi.org/10.1111/j.1600-0501.2010.02076.x. PubMed PMID: 21244502.
11
Naitoh M, Aimiya H, Hirukawa A, Ariji E. Morphometric analysis of mandibular trabecular bone using cone beam computed tomography: an in vitro study. Int J Oral Maxillofac Implants. 2010;25:1093-8. PubMed PMID: 21197484.
12
Merheb J, Van Assche N, Coucke W, Jacobs R, Naert I, Quirynen M. Relationship between cortical bone thickness or computerized tomography-derived bone density values and implant stability. Clin Oral Implants Res. 2010;21:612-7. doi.org/10.1111/j.1600-0501.2009.01880.x. PubMed PMID: 20666788.
13
Gomes PP, Guimaraes Filho R, Mazzonetto R. Evaluation of the bending strength of rigid internal fixation with absorbable and metallic screws in mandibular ramus sagittal split osteotomy: in vitro study. Pesqui Odontol Bras. 2003;17:267-72. doi.org/10.1590/S1517-74912003000300012. PubMed PMID: 14762506.
14
Trisi P, Todisco M, Consolo U, Travaglini D. High versus low implant insertion torque: a histologic, histomorphometric, and biomechanical study in the sheep mandible. Int J Oral Maxillofac Implants. 2011;26:837-49. PubMed PMID: 21841994.
15
Kayipmaz S, Sezgin OS, Saricaoglu ST, Can G. An in vitro comparison of diagnostic abilities of conventional radiography, storage phosphor, and cone beam computed tomography to determine occlusal and approximal caries. Eur J Radiol. 2011;80:478-82. doi.org/10.1016/j.ejrad.2010.09.011. PubMed PMID: 20934291.
16
Ulusu T, Bodur H, Odabas ME. In vitro comparison of digital and conventional bitewing radiographs for the detection of approximal caries in primary teeth exposed and viewed by a new wireless handheld unit. Dentomaxillofac Radiol. 2010;39:91-4. doi.org/10.1259/dmfr/15182314. PubMed PMID: 20100920. PubMed PMCID: 3520193.
17
Kamburoglu K, Senel B, Yuksel SP, Ozen T. A comparison of the diagnostic accuracy of in vivo and in vitro photostimulable phosphor digital images in the detection of occlusal caries lesions. Dentomaxillofac Radiol. 2010;39:17-22. doi.org/10.1259/dmfr/91657756. PubMed PMID: 20089739. PubMed PMCID: 3520404.
18
Senel B, Kamburoglu K, Ucok O, Yuksel SP, Ozen T, Avsever H. Diagnostic accuracy of different imaging modalities in detection of proximal caries. Dentomaxillofac Radiol. 2010;39:501-11. doi.org/10.1259/dmfr/28628723. PubMed PMID: 21062944. PubMed PMCID: 3520212.
19
Schropp L, Alyass NS, Wenzel A, Stavropoulos A. Validity of wax and acrylic as soft-tissue simulation materials used in in vitro radiographic studies. Dentomaxillofac Radiol. 2012;41:686-90. doi.org/10.1259/dmfr/33467269. PubMed PMID: 22933536. PubMed PMCID: 3528195.
20
Turkyilmaz I, McGlumphy EA. Influence of bone density on implant stability parameters and implant success: a retrospective clinical study. BMC Oral Health. 2008;8:32. doi.org/10.1186/1472-6831-8-32. PubMed PMID: 19025637. PubMed PMCID: 2614413.
21
Morea C, Dominguez GC, Coutinho A, Chilvarquer I. Quantitative analysis of bone density in direct digital radiographs evaluated by means of computerized analysis of digital images. Dentomaxillofac Radiol. 2010;39:356-61. doi.org/10.1259/dmfr/13093703. PubMed PMID: 20729185. PubMed PMCID: 3520242.
22
Gu L, Yu LY, Zhou Y, Xie C. Application of the bone quality of pre-implanted mandible through optical density measurement. Shanghai Kou Qiang Yi Xue. 2008;17:479-82. PubMed PMID: 18989587.
23
Norton MR, Gamble C. Bone classification: an objective scale of bone density using the computerized tomography scan. Clin Oral Implants Res. 2001;12:79-84. doi.org/10.1034/j.1600-0501.2001.012001079.x. PubMed PMID: 11168274.
24
Shapurian T, Damoulis PD, Reiser GM, Griffin TJ, Rand WM. Quantitative evaluation of bone density using the Hounsfield index. Int J Oral Maxillofac Implants. 2006;21:290-7. PubMed PMID: 16634501.
25
Mah P, Reeves TE, McDavid WD. Deriving Hounsfield units using grey levels in cone beam computed tomography. Dentomaxillofac Radiol. 2010;39:323-35. doi.org/10.1259/dmfr/19603304. PubMed PMID: 20729181. PubMed PMCID: 3520236.
26
Nomura Y, Watanabe H, Honda E, Kurabayashi T. Reliability of voxel values from cone-beam computed tomography for dental use in evaluating bone mineral density. Clin Oral Implants Res. 2010;21:558-62. doi.org/10.1111/j.1600-0501.2009.01896.x. PubMed PMID: 20443807.
27
Miles DA, Danforth RA. A clinician’s guide to understanding cone beam volumetric imaging (CBVI). Peer-Reviwed Publication-Academy of Dental Therapeutics and Stomatology 2008. 2007.
28
Nackaerts O, Jacobs R, Horner K, Zhao F, Lindh C, Karayianni K, et al. Bone density measurements in intra-oral radiographs. Clin Oral Investig. 2007;11:225-9. doi.org/10.1007/s00784-007-0107-2. PubMed PMID: 17668257.
29
Sakakura CE, Giro G, Goncalves D, Pereira RM, Orrico SR, Marcantonio E, Jr. Radiographic assessment of bone density around integrated titanium implants after ovariectomy in rats. Clin Oral Implants Res. 2006;17:134-8. doi.org/10.1111/j.1600-0501.2005.01224.x. PubMed PMID: 16584408.
30
ORIGINAL_ARTICLE
Uncertainty Analysis in MRI-based Polymer Gel Dosimetry
Background: Polymer gel dosimeters combined with magnetic resonance imaging (MRI) can be used for dose verification of advanced radiation therapy techniques. However, the uncertainty of dose map measured by gel dosimeter should be known. The purpose of this study is to investigate the uncertainty related to calibration curve and MRI protocol for MAGIC (Methacrylic and Ascorbic acid in Gelatin Initiated by Copper) gel and finally ways of optimization MRI protocol is introduced.Materials and Methods: MAGIC gel was prepared by the Fong et al. instruction. The gels were poured into calibration vials and irradiated by 18 MV photons. 1.5 Tesla MRI was used for reading out information. Finally, uncertainty of measured dose was calculated.Results: Results show that for MAGIC polymer gel dosimeter, at low doses, the estimated uncertainty is high (≈ 18.96% for 1 Gy) but it reduces to approximately 4.17% for 10 Gy. Also, with increasing dose, the uncertainty for the measured dose decreases non-linearly. For low doses, the most significant uncertainties are σR0 (uncertainty of intercept) and σa (uncertainty of slope) for high doses. MRI protocol parameters influence signal-to-noise ratio (SNR).Conclusion: The most important source of uncertainty is uncertainty of R2. Hence, MRI protocol and parameters therein should be optimized. At low doses, the estimated uncertainty is high and reduces by increasing dose. It is suggested that in relative dosimetry, gels are irradiated by high doses in linear range of given gel dosimeter and then scaled down to the desired dose range.
https://jbpe.sums.ac.ir/article_43275_524dd4185896a7a4536d7bb8d307f28b.pdf
2017-09-01
299
304
MRI
Gel Dosimetry
Uncertainty Analysis
Radiation Therapy
M
Keshtkar
keshtkar.dmohammad@yahoo.com
1
Department of Medical Physics and Radiology, Faculty of Medicine, Gonabad University of Medical Sciences, Gonabad, Iran
LEAD_AUTHOR
A
Takavar
2
Department of Medical Physics and Radiology, Faculty of Medicine, Gonabad University of Medical Sciences, Gonabad, Iran
AUTHOR
M H
Zahmatkesh
3
Novin Institute of Medical Radiation, Shahid Beheshti University of Medical Sciences, Tehran, Iran
AUTHOR
A R
Montazerabadi
4
Department of Medical Physics and Radiology, Faculty of Medicine, Gonabad University of Medical Sciences, Gonabad, Iran
AUTHOR
Baldock C, De Deene Y, Doran S, Ibbott G, Jirasek A, Lepage M, et al. Polymer gel dosimetry. Physics in medicine and biology. 2010;55:R1. doi.org/10.1088/0031-9155/55/5/R01.
1
Keshtkar M, Takavar A, Zahmatkesh MH, Nedaie HA, Vaezzadeh A, Naderi M. Three-dimensional gel dosimetry for dose volume histogram verification in compensator-based IMRT. Int J Radiat Res. 2014;12(1):13-20.
2
Keshtkar M, Takavar A, Zahmatkesh M, Vaezzadeh A, Gholami M, Ghasemian Z. Application of Polymer Gel dosimetry in Dose Verification of IMRT. Frontiers in Biomedical Technologies. 2015;1(4):279-83.
3
Watanabe Y, Kubo H. A variable echo-number method for estimating R2 in MRI-based polymer gel dosimetry. Med Phys. 2011;38:975-82. doi.org/10.1118/1.3544659. PubMed PMID: 21452734. PubMed PMCID: 3041809.
4
De Deene Y, editor. Review of quantitative MRI principles for gel dosimetry. Journal of Physics: Conference Series; 2009: IOP Publishing.
5
B Baldock C, Murry P, Kron T. Uncertainty analysis in polymer gel dosimetry. Phys Med Biol. 1999;44:N243-6. doi.org/10.1088/0031-9155/44/11/402. PubMed PMID: 10588291.
6
Baldoc C, Lepage M, Back SA, Murry PJ, Jayasekera PM, Porter D, et al. Dose resolution in radiotherapy polymer gel dosimetry: effect of echo spacing in MRI pulse sequence. Phys Med Biol. 2001;46:449-60. doi.org/10.1088/0031-9155/46/2/312. PubMed PMID: 11229725.
7
Fong PM, Keil DC, Does MD, Gore JC. Polymer gels for magnetic resonance imaging of radiation dose distributions at normal room atmosphere. Phys Med Biol. 2001;46:3105-13. doi.org/10.1088/0031-9155/46/12/303. PubMed PMID: 11768494.
8
Watanabe Y, Gopishankar N. Three-dimensional dosimetry of TomoTherapy by MRI-based polymer gel technique. J Appl Clin Med Phys. 2011;12:3273. PubMed PMID: 21330972. PubMed PMCID: 3378327.
9
Oldham M, Baustert I, Lord C, Smith TA, McJury M, Warrington AP, et al. An investigation into the dosimetry of a nine-field tomotherapy irradiation using BANG-gel dosimetry. Phys Med Biol. 1998;43:1113-32. doi.org/10.1088/0031-9155/43/5/005. PubMed PMID: 9623644.
10
Gustavsson H, Karlsson A, Back SA, Olsson LE, Haraldsson P, Engstrom P, et al. MAGIC-type polymer gel for three-dimensional dosimetry: intensity-modulated radiation therapy verification. Med Phys. 2003;30:1264-71. doi.org/10.1118/1.1576392. PubMed PMID: 12852552.
11
Watanabe Y. Variable transformation of calibration equations for radiation dosimetry. Phys Med Biol. 2005;50:1221-34. doi.org/10.1088/0031-9155/50/6/012. PubMed PMID: 15798318.
12
De Deene Y, Baldock C. Optimization of multiple spin-echo sequences for 3D polymer gel dosimetry. Phys Med Biol. 2002;47:3117-41. doi.org/10.1088/0031-9155/47/17/306. PubMed PMID: 12361214.
13
De Deene Y, Van de Walle R, Achten E, De Wagter C. Mathematical analysis and experimental investigation of noise in quantitative magnetic resonance imaging applied in polymer gel dosimetry. Signal Processing. 1998;70:85-101. doi.org/10.1016/S0165-1684(98)00115-7.
14
ORIGINAL_ARTICLE
Online Estimation of Elbow Joint Angle Using Upper Arm Acceleration: A Movement Partitioning Approach
Estimating the elbow angle using shoulder data is very important and valuable in Functional Electrical Stimulation (FES) systems which can be useful in assisting C5/C6 SCI patients. Much research has been conducted based on the elbow-shoulder synergies.The aim of this study was the online estimation of elbow flexion/extension angle from the upper arm acceleration signals during ADLs. For this, a three-level hierarchical structure was proposed based on a new approach, i.e. ‘the movement phases’. These levels include Clustering, Recognition using HMMs and Angle estimation using neural networks. ADLs were partitioned to the movement phases in order to obtain a structured and efficient method. It was an online structure that was very useful in the FES control systems. Different initial locations for the objects were considered in recording the data to increase the richness of the database and to improve the neural networks generalization.The cross correlation coefficient (K) and Normalized Root Mean Squared Error (NRMSE) between the estimated and actual angles, were obtained at 90.25% and 13.64%, respectively. A post-processing method was proposed to modify the discontinuity intervals of the estimated angles. Using the post-processing, K and NRMSE were obtained at 91.19% and 12.83%, respectively.
https://jbpe.sums.ac.ir/article_43264_b699cf834db47f9f580d04cee9ca9ecd.pdf
2017-09-01
305
314
Angle Estimation
Activities of Daily Living (ADL)
Movement Phases
Hierarchical Structure
M
Farokhzadi
mona.farokhzadi@ut.ac.ir
1
Biomedical Engineering Faculty, Amirkabir University of Technology, Tehran, Iran
LEAD_AUTHOR
A
Maleki
ali_maleki@aut.ac.ir
2
Biomedical Engineering Faculty, Amirkabir University of Technology, Tehran, Iran
AUTHOR
A
Fallah
afallah@aut.ac.ir
3
Biomedical Engineering Faculty, Amirkabir University of Technology, Tehran, Iran
AUTHOR
S
Rashidi
rashidi.saeid@gmail.com
4
Biomedical Engineering Faculty, Amirkabir University of Technology, Tehran, Iran
AUTHOR
bin Abdullah MFA, Negara AFP, Sayeed MS, Choi D-J, Muthu KS. Classification algorithms in human activity recognition using smartphones. International Journal of Computer and Information Engineering. 2012;6:77-84.
1
He Z, Jin L, editors. Activity recognition from acceleration data based on discrete consine transform and SVM. Systems, Man and Cybernetics, 2009. SMC 2009. IEEE International Conference on; 2009: IEEE.
2
Kao T-P, Lin C-W, Wang J-S, editors. Development of a portable activity detector for daily activity recognition. 2009 IEEE International Symposium on Industrial Electronics; 2009: IEEE.
3
Zhang Y, Markovic S, Sapir I, Wagenaar RC, Little TD, editors. Continuous functional activity monitoring based on wearable tri-axial accelerometer and gyroscope. 2011 5th International Conference on Pervasive Computing Technologies for Healthcare (PervasiveHealth) and Workshops; 2011: IEEE.
4
Ravi N, Dandekar N, Mysore P, Littman ML, editors. Activity recognition from accelerometer data. AAAI; 2005.
5
Mannini A, Sabatini AM. Machine learning methods for classifying human physical activity from on-body accelerometers. Sensors (Basel). 2010;10:1154-75. doi.org/10.3390/s100201154. PubMed PMID: 22205862. PubMed PMCID: 3244008.
6
Zhu C, Sheng W. Wearable sensor-based hand gesture and daily activity recognition for robot-assisted living. IEEE Transactions on Systems, Man, and Cybernetics-Part A: Systems and Humans. 2011;41:569-73. doi.org/10.1109/TSMCA.2010.2093883.
7
Yang J-Y, Wang J-S, Chen Y-P. Using acceleration measurements for activity recognition: An effective learning algorithm for constructing neural classifiers. Pattern recognition letters. 2008;29:2213-20. doi.org/10.1016/j.patrec.2008.08.002.
8
Kabir MH, Hoque MR, Thapa K, Yang S-H. Two-layer hidden Markov model for human activity recognition in home environments. International Journal of Distributed Sensor Networks. 2016;2016:15. doi.org/10.1155/2016/4560365.
9
Zheng Y. Human activity recognition based on the hierarchical feature selection and classification framework. Journal of Electrical and Computer Engineering. 2015;2015:34. doi.org/10.1155/2015/140820.
10
Krassnig G, Tantinger D, Hofmann C, Wittenberg T, Struck M, editors. User-friendly system for recognition of activities with an accelerometer. 2010 4th International Conference on Pervasive Computing Technologies for Healthcare; 2010: IEEE.
11
Lee MW, Khan AM, Kim JH, Cho YS, Kim TS. A single tri-axial accelerometer-based real-time personal life log system capable of activity classification and exercise information generation. Conf Proc IEEE Eng Med Biol Soc. 2010;2010:1390-3. PubMed PMID: 21096339.
12
Popovic M, Popovic D. A new approach to reaching control for tetraplegic subjects. J Electromyogr Kinesiol. 1994;4:242-53. doi.org/10.1016/1050-6411(94)90011-6. PubMed PMID: 20870563.
13
Maleki A, Fallah A. Using synergy to control reaching movement neuroprosthesis: muscle synergy or kinematic synergy. Iran J Biomed Eng. 2008;2:131:40. [in Persian]
14
Hesam Shariati N, Maleki A, Fallah A. Genetic Feedforward-Feedback Controller for Functional Electrical Stimulation Control of Elbow Joint Angle. Journal of Biomedical Physics and Engineering. 2012;2(1 Mar).
15
Raj R, Sivanandan K. Estimation of elbow joint angle from time domain features of SEMG signals using fuzzy logic for prosthetic control. Int journal of current engineering and technology. 2015;5:2078-81.
16
Kaliki RR, Davoodi R, Loeb GE. The effects of training set on prediction of elbow trajectory from shoulder trajectory during reaching to targets. Conf Proc IEEE Eng Med Biol Soc. 2006;1:5483-6. doi.org/10.1109/iembs.2006.260058. PubMed PMID: 17946704.
17
Toosi MA, Maleki A, Fallah A, editors. Estimation and anticipation of elbow joint angle from shoulder data during planar movements. Control, Instrumentation and Automation (ICCIA), 2011 2nd International Conference on; 2011: IEEE.
18
Kwon S, Kim J, editors. Real-time upper limb motion prediction from noninvasive biosignals for physical human-machine interactions. Systems, Man and Cybernetics, 2009. SMC 2009. IEEE International Conference on; 2009: IEEE.
19
Mijovic B, Popovic MB, Popovic DB. Synergistic control of forearm based on accelerometer data and artificial neural networks. Braz J Med Biol Res. 2008;41:389-97. doi.org/10.1590/S0100-879X2008005000019. PubMed PMID: 18516468.
20
Popovic M, Popovic D. Cloning biological synergies improves control of elbow neuroprosthesis. IEEE Eng Med Biol Mag. 2001;20:74-81. doi.org/10.1109/51.897830. PubMed PMID: 11211663.
21
Popović MB, Popović DB, Tomović R. Control of arm movement: reaching synergies for neuroprosthesis with life-like control. Journal of Automatic Control. 2002;12:9-15. doi.org/10.2298/JAC0201009P.
22
Yoshikawa M, Mikawa M, Tanaka K, editors. A myoelectric interface for robotic hand control using support vector machine. 2007 IEEE/RSJ International Conference on Intelligent Robots and Systems; 2007: IEEE.
23
Micera S, Carpaneto J, Dario P, Popovic M, editors. Statistical and soft-computing techniques for the prediction of upper arm articular synergies. Neural Network Applications in Electrical Engineering, 2002. NEUREL’02. 2002 6th Seminar on; 2002: IEEE.
24
Maleki A, Farokhzadi M. The user-friendly system for recording kinematic information of the limb motion using sensors based on the accelerometer. 17th Iranian Conference on Biomedical Engineering, Isfahan, Iran, 2010. http://www.civilica.com/Paper-ICBME17-ICBME17_141.html.
25
Bishop C. Pattern recognition and machine learning. Springer Science; 2006 p. 166-9.
26