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:: Volume 22, Issue 1 (1-2024) ::
Int J Radiat Res 2024, 22(1): 207-211 Back to browse issues page
Optically Stimulated Luminescence Nanodots experimental determination of bowtie filter shape in computed tomography
A. Khallouqi , W. Allioui , A. Halimi , O. El rhazouani , S. Didi
Hassan First University of Settat,, High Institute of Health Sciences, Laboratory of Health Sciences and Technologies, Settat, Morocco , a.khallouqi@uhp.ac.ma
Abstract:   (550 Views)
Background: Computed tomography (CT) scans have become an essential diagnostic tool, but they carry significant risks due to the exposure of patients to ionizing radiation. Therefore, healthcare professionals have a responsibility to optimize radiation dose and image quality simultaneously. One factor that significantly affects the quality of images and radiation dose is the bowtie filter used in CT systems, which homogenizes and shapes the X-ray spectrum. However, its characteristic shape, specific to each manufacturer makes it impossible to model it from only the information in the technical note alone. Materials and Methods: This study presents a novel methodology using optically stimulated luminescence (OSLD) nanodots to determine the body bowtie filter shape in a Siemens SOMATOM EMOTION 16-slice CT. The accuracy of the body bowtie filter shape generated by OSLD was validated by performing Monte Carlo simulations of CT scans. Results: The difference between simulated and measured CTDIw values for the PET/CT Siemens at 80, 110 and 130 kVp were 4.02%, 7.74%, and 4.81%, respectively. Conclusion: In this work, it has been demonstrated that the use of OSLD nanodots allows for the determination of the shape of bowtie filters in CT scans with acceptable accuracy. This work has the potential to address a significant gap in the modeling of bowtie filters, which could significantly improve the optimization of radiation dose and image quality in CT scans.
Keywords: Computed tomography (CT) dosimetry, bow-tie filter, OSL dosimeter.
Full-Text [PDF 629 kb]   (346 Downloads)    
Type of Study: Technical Note | Subject: Radiation Biology
References
1. Samei E and Pelc BJ (2020) Computed tomography. Springer, 2020. [DOI:10.1007/978-3-030-26957-9]
2. Fallah Mohammadi GR, Riyahi Alam N, Geraily G, et al. (2016) Thorax organ dose estimation in computed tomography based on patient CT data using Monte Carlo simulation. Int J Radiat Res, 14(4): 313-321. [DOI:10.18869/acadpub.ijrr.14.4.313]
3. Medicine AA of Pin (2008) The measurement, reporting, and management of radiation dose in CT. AAPM report; 2008.
4. Poirier Y, Kouznetsov A, Koger B, et al. (2014) Experimental validation of à kilovoltage X-ray source model for computing imaging dose. Medical Physics, 41(4): 041915. [DOI:10.1118/1.4869159]
5. Ahmadi N, Nasrabadi MN, Karimian A, et al. (2017) A TLD based method to estimate bowtie filter shape in PET/CT. Int J Radiat Res, 15(4): 383-390.
6. Cao Y, Ma T, de Boer SF, et al. (2020) Image artifacts caused by incorrect bowtie filters in cone‐beam CT image‐guided radiotherapy. Journal of Applied Clinical Medical Physics, 21(7): 153-159. [DOI:10.1002/acm2.12888]
7. Boone JM (2010) Method for evaluating bow tie filter angle‐dependent attenuation in CT: Theory and simulation results. Medical Physics, 37(1): 40-48. [DOI:10.1118/1.3264616]
8. Turner AC, Zhang D, Kim HJ, et al. (2009) A method to generate equivalent energy spectra and filtration models based on measurement for multidetector CT Monte Carlo dosimetry simulations. Medical Physics, 36(6Part1): 2154-2164. [DOI:10.1118/1.3117683]
9. Belinato W, Santos WS, Paschoal CMM, et al. (2015) Monte Carlo simulations in multi-detector CT (MDCT) for two PET/CT scanner models using MASH and FASH adult phantoms. Nuclear Instruments and Methods in Physics Research Section A: Accelerators, Spectrometers, Detectors and Associated Equipment. Elsevier, 784: 524-530. [DOI:10.1016/j.nima.2014.09.036]
10. Alikhani B and Büermann L (2016) Non-invasive experimental determination of a CT source model. Physica Medica, 32(1): 59-66. [DOI:10.1016/j.ejmp.2015.09.006]
11. Whiting BR, Evans JD, Dohatcu AC, et al. (2014) Measurement of bow tie profiles in CT scanners using a real‐time dosimeter. Medical Physics, 41(10): 101915. [DOI:10.1118/1.4896196]
12. Omar RS, Hashim S, Bradley DA, et al. (2022) Anthropomorphic phantom organ dose assessment using optically stimulated luminescence dosimeters unified in multi-detector computed tomography. Radiation Physics and Chemistry, 200: 110383. [DOI:10.1016/j.radphyschem.2022.110383]
13. Granville DA, Sahoo N, Sawakuchi GO (2014) Calibration of the Al2O3: C optically stimulated luminescence (OSL) signal for linear energy transfer (LET) measurements in therapeutic proton beams. Physics in Medicine & Biology, 59(15): 4295. [DOI:10.1088/0031-9155/59/15/4295]
14. Minami K, Matsubara K, Hayashi Y, et al. (2019) Influence of bowtie filter and patient positioning on in-plane dose distribution and image quality in ECG-gated CT. Nihon Hoshasen Gijutsu Gakkai Zasshi, 75(6): 536-545. [DOI:10.6009/jjrt.2019_JSRT_75.6.536]
15. Kadavigere R and Sukumar S (2022) Radiation dose optimization for computed tomography of the head in pediatric population-An experimental phantom study. Int J Radiat Res, 20(4):747-751.
16. Nakamura T, Suzuki S, Takei Y, et al. (2019) Simultaneous measurement of patient dose and distribution of indoor scattered radiation during digital breast tomosynthesis. Radiography, 25(1): 72-76. [DOI:10.1016/j.radi.2018.10.006]
17. Jan S, Benoit D, Becheva E, et al. (2011) GATE V6: a major enhancement of the GATE simulation platform enabling modelling of CT and radiotherapy. Physics in Medicine & Biology, 56(4): 881. [DOI:10.1088/0031-9155/56/4/001]
18. DeMarco JJ, Cagnon CH, Cody DD, et al. (2005) A Monte Carlo based method to estimate radiation dose from multidetector CT (MDCT): cylindrical and anthropomorphic phantoms. Physics in Medicine & Biology, 50(17): 3989. [DOI:10.1088/0031-9155/50/17/005]
19. Zhang H, Kong V, Huang K, et al. (2017) Correction of bowtie-filter normalization and crescent artifacts for a clinical CBCT system. Technology in Cancer Research & treatment, 16(1): 81-91. [DOI:10.1177/1533034615627584]
20. Hassan AI, Skalej M, Schlattl H, et al. (2018) Determination and verification of the X-ray spectrum of a CT scanner. J Med Imag, 5(01): 1. [DOI:10.1117/1.JMI.5.1.013506]
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Khallouqi A, Allioui W, Halimi A, El rhazouani O, Didi S. Optically Stimulated Luminescence Nanodots experimental determination of bowtie filter shape in computed tomography. Int J Radiat Res 2024; 22 (1) :207-211
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Volume 22, Issue 1 (1-2024) Back to browse issues page
International Journal of Radiation Research
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