Development of In-house Chest Phantom for Pediatric Cancer Cases

Yola Sri Wahyuni; Choirul Anam; Ilham Alkian; Ariij Naufal; Heri Sutanto

doi:10.32628/IJSRST2512129

Authors

Yola Sri Wahyuni Department of Physics, Faculty of Sciences and Mathematics, Diponegoro University, Semarang, Indonesia Author
Choirul Anam Department of Physics, Faculty of Sciences and Mathematics, Diponegoro University, Semarang, Indonesia Author
Ilham Alkian Department of Physics, Faculty of Sciences and Mathematics, Diponegoro University, Semarang, Indonesia Author
Ariij Naufal Smart Material Reseach Center (SMARC), Diponegoro University, Semarang, Indonesia Author
Heri Sutanto Smart Material Reseach Center (SMARC), Diponegoro University, Semarang, Indonesia Author

DOI:

https://doi.org/10.32628/IJSRST2512129

Keywords:

Lung Cancer, Chest Phantom, Beeswax

Abstract

This study aims to develop an in-house phantom that can more cheaply represent pediatric lung cancer cases. The materials used in this study were polymethyl methacrylate (PMMA) as a substitute for soft tissue, polyurethane (PU) foam as a substitute for lung tissue, and calcium carbonate as a replacement for rib bones. Cancer or nodules were represented using beeswax. The phantom evaluation was conducted using IndoQCT software, with parameters such as CT number, noise, signal-to-noise ratio (SNR), and contrast-to-noise ratio (CNR). The CT numbers of cancer/nodule, normal lung, soft tissue, and bone for the in-house phantom are -217 to -117, -979, 80, and 871 HU, respectively. As comparison, the CT number of cancer/nodule, normal lung, soft tissue, and bone for the real patients are -141 to -103, -906, 73, and 743 HU, respectively. These findings indicate that the CT number, noise, SNR, and CNR values for the substitute materials used in the in-house phantom closely resemble the imaging values of patients with cancer/nodules. Thus, the materials used can effectively represent human tissue substitutes.

Downloads

Download data is not yet available.

References

Bisogno G, Sarnacki S, Stachowicz-Stencel T, et al. Pleuropulmonary blastoma in children and adolescents: The EXPeRT/PARTNER diagnostic and therapeutic recommendations. Pediatr Blood Cancer. 2021;68 Suppl 4(Suppl 4):e29045. doi:10.1002/pbc.29045 DOI: https://doi.org/10.1002/pbc.29045

Wang P, Martel P, Hajjam ME, Grimaldi L, Giroux Leprieur E; ’AP-HP / Universities / Inserm COVID-19 research collaboration and AP-HP Covid CDW Initiative. Incidental diagnosis of lung cancer on chest CT scan performed for suspected or documented COVID-19 infection. Respir Med Res.

Javed, R., Abbas, T., Khan, A.H. et al. Deep learning for lung cancer detection: a review. Artif Intell Rev 57, 197 (2024). DOI: https://doi.org/10.1007/s10462-024-10807-1

Haleem A, Javaid M. Role of CT and MRI in designing and developing an orthopaedic model using additive manufacturing [published correction appears in J Clin Orthop Trauma. 2020 Nov-Dec;11(6):1169-1171.

Pengpan T, Rattanarungruangchai N, Dechjaithat J, Panthim P, Siricharuwong P, Prapan A. Optimization of Image Quality and Organ Absorbed Dose for Pediatric Chest X-Ray Examination: In-House Developed Chest Phantom Study. Radiol Res Pract. 2022;2022:3482458. Published 2022 Apr 16. doi:10.1155/2022/3482458 DOI: https://doi.org/10.1155/2022/3482458

Muhammad, N. A., Kayun, Z., Abu Hassan, H., Wong, J. H. D., Ng, K. H., & Karim, M. K. A. (2021). Evaluation of organ dose and image quality metrics of pediatric CT chest-abdomen-pelvis (CAP) examination: an anthropomorphic phantom study. Applied Sciences, 11(5), 2047. DOI: https://doi.org/10.3390/app11052047

Henriques, L. M. S., Cerqueira, R. A. D., Santos, W. S., Pereira, A. J. S., Rodrigues, T. M. A., Júnior, A. C., & Maia, A. F. (2014). Characterization of an anthropomorphic chest phantom for dose measurements in radiology beams. Radiation Physics and Chemistry, 95, 296-298. DOI: https://doi.org/10.1016/j.radphyschem.2012.12.037

Mufida, W., Utami, A. P., & Dewi, S. N. (2020). Making Radiological Phantoms Made from Local Wood as a Substitute for Human Bones. Journal of Diagnostic Imaging (JImeD), 6(1), 7-10. DOI: https://doi.org/10.31983/jimed.v6i1.5404

Mille MM, Griffin KT, Maass-Moreno R, Lee C. Fabrication of a pediatric torso phantom with multiple tissues represented using a dual nozzle thermoplastic 3D printer. J Appl Clin Med Phys. 2020;21(11):226-236. doi:10.1002/acm2.13064 DOI: https://doi.org/10.1002/acm2.13064

Jamal, Nurul HM, Inayatullah S. Sayed, and Waliullah S. Syed. "Estimation of organ absorbed dose in pediatric chest X-ray examination: A phantom study." Radiation Physics and Chemistry 166 (2020): 108472. DOI: https://doi.org/10.1016/j.radphyschem.2019.108472

Mohammed Ali A, Al-Murshedi S. Low-cost chest paediatric phantom for dose optimization: construction and validation. Radiologia (Engl Ed). 2023;65(4):327-337. doi:10.1016/j.rxeng.2022.11.001 DOI: https://doi.org/10.1016/j.rxeng.2022.11.001

Xiang, Z., & Spector, M. (2006). Biocompatibility of materials. Encyclopedia of Medical Devices and Instrumentation. DOI: https://doi.org/10.1002/0471732877.emd012

Chu PW, Yu S, Wang Y, et al. Reference phantom selection in pediatric computed tomography using large, multicenter registry data. Pediatr Radiol. 2022;52(3):445-452.doi:10.1007/s00247-021-05227-0 DOI: https://doi.org/10.1007/s00247-021-05227-0

Heryani, H., Sutanto, H., Anam, C., & Reskianto, A. D. (2020). Development of Synthetic Bones for ANSI Chest Phantom Dosimetry. European Journal of Advances in Engineering and Technology, 7(9), 12-17.

Anam, C., Amilia, R., Naufal, A., Fujibuchi, T., & Dougherty, G. (2025) A statistical-based automatic detection of a low-contrast object in the ACR CT phantom for measuring contrast-to-noise ratio of CT images. Biomed Phys Eng Express, 11(1), 017001. DOI: https://doi.org/10.1088/2057-1976/ad90e9

Anam, C., Naufal, A., Budi, W. S., Sutanto, H., Haryanto, F., & Dougherty, G., (2023) IndoQCT: a platform for automated CT image quality assessment. Med Phys Int J. 11, 328–36

Liu F, Wei Y, Zhang H, Jiang J, Zhang P, Chu Q. NTRK Fusion in Non-Small Cell Lung Cancer: Diagnosis, Therapy, and TRK Inhibitor Resistance. Front Oncol. 2022;12:864666. Published 2022 Mar 17. DOI: https://doi.org/10.3389/fonc.2022.864666

Wibowo, N. P. E., Susilo, S., & Sunarno, S. (2016). Image Proficiency Test of Digital Radiographic System Exposure Results at the Unnes Medical Physics Laboratory. Unnes Physics Journal, 5(1), 23-29.

Masuda T, Funama Y, Kiguchi M, et al. Radiation dose reduction based on CNR index with low-tube voltage scan for pediatric CT scan: an experimental study using anthropomorphic phantoms. Springerplus. 2016;5(1):2064. DOI: https://doi.org/10.1186/s40064-016-3715-y

Yücel, H., & Safi, A. (2021). Investigate the suitability of newly developed epoxy-based phantom for child's tissue equivalency in paediatric radiology. Nuclear Engineering and Technology, 53(12), 4158-4165. DOI: https://doi.org/10.1016/j.net.2021.07.002