Uji Kesesuaian Pesawat Multi Slice Computed Tomography Menggunakan Water Phantom Di Instalasi Radiologi Rsud Sanjiwani
DOI:
https://doi.org/10.31004/koloni.v5i3.1264Keywords:
MSCT Scan; CT Number; Water Phantom; Uniformity; Image ArtifactAbstract
Suitability Test of an MSCT Scanner at the Radiology Installation of RSUD Sanjiwani. Multi-Slice Computed Tomography (MSCT) is a diagnostic imaging modality that utilizes X-rays and computer technology to produce detailed cross-sectional images of the body. The quality of MSCT images is influenced by scanner performance, detector response, calibration, phantom positioning, scanning parameters, and image reconstruction. Therefore, periodic quality control is required to ensure that the scanner produces consistent and acceptable diagnostic images. This study aimed to evaluate the suitability of an MSCT scanner at the Radiology Installation of RSUD Sanjiwani based on water CT number, center-to-periphery CT number uniformity, and image artifact evaluation. This study used a descriptive quantitative observational design. Data were collected for 30 days using a Siemens 64-slice MSCT scanner and a water phantom. Measurements were performed at five region of interest positions: the center, 12, 3, 6, and 9 o’clock. The scanning parameters were 120 kVp, 200 mAs, 250 mm field of view, 10 mm slice thickness, and 2.00 cm² ROI size. The mean CT number values were −0.74 HU at 12 o’clock, −0.62 HU at 3 o’clock, −0.81 HU at 6 o’clock, −0.57 HU at 9 o’clock, and −0.55 HU at the center. The center ROI value was within the acceptance range of −4 to +4 HU. The CT number values at the center and peripheral ROIs also met the center-to-periphery uniformity acceptance limit of ΔCT ≤ 2. Visual evaluation showed no streak, shading, or ring artifacts during the observation period. The MSCT scanner at the Radiology Installation of RSUD Sanjiwani met the acceptance criteria for water CT number and center-to-periphery CT number uniformity. No streak, shading, or ring artifacts were observed in the evaluated water phantom images.References
Al-Hayek, Y., Spuur, K., Davidson, R., Hayre, C., & Zheng, X. (2022a). The impacts of vertical off-centring, localiser direction, phantom positioning and tube voltage on CT number accuracy: An experimental study. Journal of Imaging, 8(7), 175. https://doi.org/10.3390/jimaging8070175
Al-Hayek, Y., Spuur, K., Davidson, R., Hayre, C., & Zheng, X. (2022b). The impacts of vertical off-centring, tube voltage, and phantom size on computed tomography numbers: An experimental study. Radiography, 28(3), 641–647. https://doi.org/10.1016/j.radi.2022.04.011
Anam, C., Amilia, R., Naufal, A., Maya, A. T., & Dwihapsari, Y. (2025). The CT number uniformity and homogeneity: Which is better for detecting the beam hardening artefacts? Jurnal Teknologi, 87(2), 253–261. https://doi.org/10.11113/jurnalteknologi.v87.21985
Badan Pengawas Tenaga Nuklir. (2018). Peraturan Badan Pengawas Tenaga Nuklir Nomor 2 Tahun 2018 tentang Uji Kesesuaian Pesawat Sinar-X Radiologi Diagnostik dan Intervensional. Jakarta, Indonesia: BAPETEN.
Badan Pengawas Tenaga Nuklir. (2022). Peraturan Badan Pengawas Tenaga Nuklir Nomor 2 Tahun 2022 tentang Perubahan atas Peraturan Badan Pengawas Tenaga Nuklir Nomor 2 Tahun 2018 tentang Uji Kesesuaian Pesawat Sinar-X Radiologi Diagnostik dan Intervensional. Jakarta, Indonesia: BAPETEN.
Barca, P., Paolicchi, F., Aringhieri, G., Palmas, F., Marfisi, D., Fantacci, M. E., Caramella, D., & Giannelli, M. (2021). A comprehensive assessment of physical image quality of five different scanners for head CT imaging as clinically used at a single hospital centre: A phantom study. PLOS ONE, 16(1), e0245374. https://doi.org/10.1371/journal.pone.0245374
Booij, R., Budde, R. P. J., Dijkshoorn, M. L., & van Straten, M. (2020). Technological developments of X-ray computed tomography over half a century: User’s influence on protocol optimization. European Journal of Radiology, 131, 109261. https://doi.org/10.1016/j.ejrad.2020.109261
Chen-Mayer, H. H., Fuld, M. K., Hoppel, B., Judy, P. F., Sieren, J. P., Guo, J., Lynch, D. A., Possolo, A., & Fain, S. B. (2017). Standardizing CT lung density measure across scanner manufacturers. Medical Physics, 44(3), 974–985. https://doi.org/10.1002/mp.12087
Gulliksrud, K., Stokke, C., & Martinsen, A. C. T. (2014). How to measure CT image quality: Variations in CT-numbers, uniformity and low contrast resolution for a CT quality assurance phantom. Physica Medica, 30(4), 521–526. https://doi.org/10.1016/j.ejmp.2014.01.006
Husby, E., Svendsen, E. D., Andersen, H. K., & Martinsen, A. C. T. (2017). 100 days with scans of the same Catphan phantom on the same CT scanner. Journal of Applied Clinical Medical Physics, 18(6), 224–231. https://doi.org/10.1002/acm2.12186
International Atomic Energy Agency. (2012). Quality assurance programme for computed tomography: Diagnostic and therapy applications (IAEA Human Health Series No. 19). Vienna, Austria: International Atomic Energy Agency.
Irsal, M., Nurbaiti, N., Mukhtar, A. N., Jauhari, A., & Winarno, G. (2020). Variation kVp and mAs on CT scan image quality using standard phantom. AIP Conference Proceedings. https://doi.org/10.1063/5.0001134
Karius, A., & Bert, C. (2022). QAMaster: A new software framework for phantom-based computed tomography quality assurance. Journal of Applied Clinical Medical Physics, 23(3), e13588. https://doi.org/10.1002/acm2.13588
Kathon, B. O., Hartoyo, P., & Samsun, S. (2022). Uji resolusi spasial dan slice thickness pada CT Scan 128 dan 16 slice dengan menggunakan phantom Quart DVT-AP. Jurnal Pembelajaran Fisika, 11(3), 123–136.
Mahmoudi, R., Jabbari, N., Aghdasi, M., & Khalkhali, H. R. (2016). Energy dependence of measured CT numbers on substituted materials used for CT number calibration of radiotherapy treatment planning systems. PLOS ONE, 11(7), e0158828. https://doi.org/10.1371/journal.pone.0158828
Nansih, L. A., & Artitin, C. (2023). The compatibility test of CT number in water on CT scan aircraft brand Philip in Radiology Installation of BMC Padang General Hospital. Jurnal Teras Kesehatan, 6(1), 16–21.
Nowik, P., Bujila, R., Poludniowski, G., & Fransson, A. (2015). Quality control of CT systems by automated monitoring of key performance indicators: A two-year study. Journal of Applied Clinical Medical Physics, 16(4), 254–265. https://doi.org/10.1120/jacmp.v16i4.5469
Ohno, Y., Fujisawa, Y., Fujii, K., Sugihara, N., Kishida, Y., Seki, S., & Yoshikawa, T. (2019). Effects of acquisition method and reconstruction algorithm for CT number measurement on standard-dose CT and reduced-dose CT: A QIBA phantom study. Japanese Journal of Radiology, 37(5), 399–411. https://doi.org/10.1007/s11604-019-00823-5
Prasetya, I. M. L., & Arthana, I. P. J. (2022). Jaminan mutu pesawat CT Scan single slice di Unit Radiologi RSU Semara Ratih. Jurnal Medika Malahayati, 6(3), 396–402.
Putra, G. P., Prasetya, I. M. L., & Wijaya, N. M. (2025). Uji kesesuaian pesawat CT Scan multislice GE Healthcare di Unit Radiologi Rumah Sakit Umum Kertha Usada. Jambura Journal of Health Science and Research, 7(1), 208–218.
Rosadi, N., Suyudi, I., & Purnamasari, D. (2022). Pengaruh perubahan arus tabung terhadap artefak gambar pada pemeriksaan CT Scan kepala. Jurnal Kesehatan, 13(2), 193–199.
Saborido-Moral, J. D., Fernández-Patón, M., Tejedor-Aguilar, N., Cristian-Marín, A., Torres-Espallardo, I., Campayo-Esteban, J. M., Pérez-Calatayud, J., Baltas, D., Martí-Bonmatí, L., & Carles, M. (2023). Free automatic software for quality assurance of computed tomography calibration, edges and radiomics metrics reproducibility. Physica Medica, 114, 103153. https://doi.org/10.1016/j.ejmp.2023.103153
Salyapongse, A. M., Rose, S. D., Pickhardt, P. J., Lubner, M. G., Toia, G. V., Bujila, R., Yin, Z., Slavic, S., & Szczykutowicz, T. P. (2023). CT number accuracy and association with object size: A phantom study comparing energy-integrating detector CT and deep silicon photon-counting detector CT. American Journal of Roentgenology, 221(4), 539–547. https://doi.org/10.2214/AJR.23.29463
Santi, D. A. N. O. (2022). Uji kesesuaian pesawat multislice computer tomography (MSCT) di Rumah Sakit Umum Daerah Sanjiwani Gianyar [Skripsi, Akademi Teknik Radiodiagnostik dan Radioterapi Bali].
Seeram, E. (2016). Computed tomography: Physical principles, clinical applications, and quality control (4th ed.). St. Louis, MO: Elsevier.
Tafti, S., Abadia, A., Fung, G., Ramirez-Giraldo, J. C., & O’Doherty, J. (2024). Comparison of Hounsfield Unit variability between two same model photon counting CT detector systems: A phantom study applied to lung CT. Physica Medica, 126, 104828. https://doi.org/10.1016/j.ejmp.2024.104828
Taqiyuddin, N. F., Anam, C., Amilia, R., Muhlisin, Z., Naufal, A., Mulatomo, T. D., Sarwidi, S., & Dougherty, G. (2025). CT number accuracies for different number of detector array and age of detector: A multi-center study. Polish Journal of Medical Physics and Engineering, 31(2), 151–157. https://doi.org/10.2478/pjmpe-2025-0017
Withers, P. J., Bouman, C., Carmignato, S., Cnudde, V., Grimaldi, D., Hagen, C. K., Maire, E., Manley, M., Du Plessis, A., & Stock, S. R. (2021). X-ray computed tomography. Nature Reviews Methods Primers, 1, 18. https://doi.org/10.1038/s43586-021-00015-4
Zhang, R., Cruz-Bastida, J. P., Gomez-Cardona, D., Hayes, J. W., Li, K., & Chen, G. H. (2018). Quantitative accuracy of CT numbers: Theoretical analyses and experimental studies. Medical Physics, 45(10), 4519–4528. https://doi.org/10.1002/mp.13119
Downloads
Published
How to Cite
Issue
Section
License
Copyright (c) 2026 Ni Wayan Lolita Dewi, I Made Lana Prasetya, Cokorda Gede Bagus Suputra
This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.
