Herramienta económica para evaluar alineación y colimación del haz de rayos X
Low-cost tool for evaluating X-ray beam alignment and collimationContenido principal del artículo
Introducción: El control de calidad de los equipos de radiodiagnóstico requiere comprobar periódicamente la congruencia entre el campo luminoso y el campo de radiación, así como la perpendicularidad del rayo central. Sin embargo, los instrumentos comerciales pueden resultar poco accesibles para establecimientos con recursos limitados. Objetivo: Desarrollar y evaluar una herramienta económica para el control de la alineación y colimación del haz de rayos X. Materiales y métodos: Se realizó un estudio de desarrollo tecnológico con validación experimental y enfoque cuantitativo en tres equipos de radiografía computarizada, identificados como CR1, CR2 y CR3. Se fabricaron una placa de acrílico para evaluar la congruencia del campo y un dispositivo cilíndrico para verificar la perpendicularidad del rayo central. Los resultados fueron comparados con una herramienta comercial de referencia mediante análisis descriptivo. Resultados: Las desviaciones de colimación obtenidas con el prototipo oscilaron entre 1,0 y 1,5 cm, todas inferiores al límite de aceptación de 2 cm. La desviación promedio fue de 1,30 cm con el prototipo y 1,13 cm con la herramienta comercial, con una diferencia media absoluta de 0,17 cm. La alineación fue inferior a 1,5° en los tres equipos. El costo total de fabricación fue de USD 23. Conclusiones: El prototipo mostró viabilidad técnica y económica preliminar para apoyar controles básicos de constancia, aunque requiere validaciones adicionales antes de su utilización rutinaria.
Introduction: Quality control of radiodiagnostic equipment requires periodically checking the congruence between the light field and the radiation field, as well as the perpendicularity of the central ray. However, commercial instruments may be difficult to access for facilities with limited resources. Objective: To develop and evaluate a low-cost tool for controlling X-ray beam alignment and collimation. Materials and methods: A technological development study with experimental validation and a quantitative approach was conducted on three computed radiography units, identified as CR1, CR2, and CR3. An acrylic plate was manufactured to assess field congruence, and a cylindrical device was built to verify central ray perpendicularity. The results were compared with a commercial reference tool using descriptive analysis. Results: The collimation deviations obtained with the prototype ranged between 1.0 and 1.5 cm, all below the 2 cm acceptance limit. The average deviation was 1.30 cm with the prototype and 1.13 cm with the commercial tool, with a mean absolute difference of 0.17 cm. Alignment was below 1.5° in all three units. The total manufacturing cost was USD 23. Conclusions: The prototype demonstrated preliminary technical and economic feasibility to support basic constancy checks, although additional validations are required before routine use.
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International Atomic Energy Agency. Handbook of Basic Quality Control Tests for Diagnostic Radiology. IAEA Human Health Series No. 47. Vienna: IAEA; 2023. https://doi.org/10.61092/iaea.rhjo-8d0u
International Atomic Energy Agency, International Labour Office, Pan American Health Organization, World Health Organization. Radiation Protection and Safety in Medical Uses of Ionizing Radiation. IAEA Safety Standards Series No. SSG-46. Vienna: IAEA; 2018. https://www.iaea.org/publications/11102/radiation-protection-and-safety-in-medical-uses-of-ionizing-radiation
International Atomic Energy Agency. Patient Radiation Exposure Monitoring in Medical Imaging. Safety Reports Series No. 112. Vienna: IAEA; 2023. https://www.iaea.org/publications/14971/patient-radiation-exposure-monitoring-in-medical-imaging
International Atomic Energy Agency. Diagnostic Radiology Physics: A Handbook for Teachers and Students. Vienna: IAEA; 2014. https://www-pub.iaea.org/MTCD/Publications/PDF/Pub1564webNew-74666420.pdf
Vañó E, Miller DL, Martin CJ, Rehani MM, Kang K, Rosenstein M, et al. ICRP Publication 135: Diagnostic Reference Levels in Medical Imaging. Ann ICRP. 2017;46(1):1-144. https://doi.org/10.1177/0146645317717209
Jones AK, Heintz P, Geiser W, Goldman L, Jerjian K, Martin M, et al. Ongoing quality control in digital radiography: Report of AAPM Imaging Physics Committee Task Group 151. Med Phys. 2015;42(11):6658-6670. https://doi.org/10.1118/1.4932623
Shepard SJ, Wang J, Flynn M, Gingold E, Goldman L, Krugh K, et al. An exposure indicator for digital radiography: AAPM Task Group 116 executive summary. Med Phys. 2009;36(7):2898-2914. https://doi.org/10.1118/1.3121505
Dave JK, Jones AK, Fisher R, Hulme K, Rill L, Zamora D, et al. Current state of practice regarding digital radiography exposure indicators and deviation indices: Report of AAPM Imaging Physics Committee Task Group 232. Med Phys. 2018;45(11):e1146-e1160. https://doi.org/10.1002/mp.13212
Little K, Reiser I, Apgar B, Dalal P, Dave J, Fisher R, et al. AAPM Task Group Report 305: Guidance for standardization of vendor-neutral reject analysis in radiography. J Appl Clin Med Phys. 2023;24(5):e13938. https://doi.org/10.1002/acm2.13938
Ireland T, Perdomo A, Lee KL, Jones A, Barnes P, Greig T, et al. ACPSEM position paper: Recommendations for a digital general X-ray quality assurance program. Phys Eng Sci Med. 2024;47(3):789-812. https://doi.org/10.1007/s13246-024-01431-y
Tsalafoutas IA, AlKhazzam S, Tsapaki V, AlNaemi H, Kharita MH. Digital radiography image quality evaluation using various phantoms and software. J Appl Clin Med Phys. 2022;23(12):e13823. https://doi.org/10.1002/acm2.13823
Tsalafoutas IA, AlKhazzam S, Tsapaki V, AlNaemi H, Kharita MH. Automatic image quality evaluation in digital radiography using for-processing and for-presentation images. J Appl Clin Med Phys. 2024;25(4):e14285. https://doi.org/10.1002/acm2.14285
Kleefeld C, Castillo Lopez JP, Costa PR, Fitton I, Mohamed A, Pesznyak C, et al. Automated quality control solution for radiographic imaging of lung diseases. J Clin Med. 2024;13(16):4967. https://doi.org/10.3390/jcm13164967
Hamzah NA, Tan LK, Tsapaki V, Ciraj-Bjelac O, Wong JHD. Optimising the IAEA remote and automatic quality control for digital radiography: Phantom design and reproducibility investigation. Phys Eng Sci Med. 2026;49(2):905-916. https://doi.org/10.1007/s13246-026-01708-4
Dukov N, Valkova VM, Yordanova M, Tsapaki V, Bliznakova K. Design and use of a custom phantom for regular tests of radiography apparatus: A feasibility study. J Imaging. 2024;10(10):258. https://doi.org/10.3390/jimaging10100258
Maharani NLS, Tungga Dewi IZ, Darma WM, Amalia AF, Rifai R, Suparta GB. A multifunctional geometric phantom for digital radiography assessment. Radiography. 2025;31(6):103193. https://doi.org/10.1016/j.radi.2025.103193
Ogden KM, Morabito KE, Depew PK. 3D printed testing aids for radiographic quality control. J Appl Clin Med Phys. 2019;20(5):127-134. https://doi.org/10.1002/acm2.12574
Carver DE, Willis CE, Stauduhar PJ, Nishino TK, Wells JR, Samei E. Medical physics 3.0 versus 1.0: A case study in digital radiography quality control. J Appl Clin Med Phys. 2018;19(5):694-707. https://doi.org/10.1002/acm2.12425
Martinez C, de Molina C, Desco M, Abella M. Optimization of a calibration phantom for quantitative radiography. Med Phys. 2021;48(3):1039-1053. https://doi.org/10.1002/mp.14638
Funahashi M, Kashiyama K, Nakamura T, Shiraishi J. Utilization of upper and lower limits of exposure index in clinical digital radiography. Radiol Phys Technol. 2022;15(4):349-357. https://doi.org/10.1007/s12194-022-00674-2
Creeden A, Curtis M. Optimising default radiographic exposure factors using deviation index. Radiography. 2020;26(4):308-313. https://doi.org/10.1016/j.radi.2020.02.009
Bantas G, Sweeney JR, Mdletshe S. Digital radiography reject analysis: A comparison between two radiology departments in New Zealand. J Med Radiat Sci. 2023;70(2):137-144. https://doi.org/10.1002/jmrs.654
Serra D, Neep MJ, Ryan E. Multi-centre digital radiography reject analysis for different clinical room use types: The establishment of local reject reference levels for public hospital departments. J Med Radiat Sci. 2024;71(3):412-420. https://doi.org/10.1002/jmrs.796
Atkinson S, Neep MJ, Starkey D. Reject rate analysis in digital radiography: An Australian emergency imaging department case study. J Med Radiat Sci. 2020;67(1):72-79. https://doi.org/10.1002/jmrs.343
Haddad L, Saleme H, Howarth N, Tack D. Reject analysis in digital radiography and computed tomography: A Belgian imaging department case study. J Belg Soc Radiol. 2023;107(1):100. https://doi.org/10.5334/jbsr.3259
Gennaro G, Zanardo M, Ambrogi F, Sardanelli F. Phantom studies in medical imaging: A guide with recommendations and checklist. Eur Radiol Exp. 2025;9:105. https://doi.org/10.1186/s41747-025-00641-7
Filippou V, Tsoumpas C. Recent advances on the development of phantoms using 3D printing for imaging with CT, MRI, PET, SPECT and ultrasound. Med Phys. 2018;45(9):e740-e760. https://doi.org/10.1002/mp.13058
Muharam R, Lestariningsih I, Nurlely, Soejoko DS. Designing phantom in-house for quick check computed radiography and digital radiography systems. J Phys Conf Ser. 2020;1568(1):012023. https://doi.org/10.1088/1742-6596/1568/1/012023
Miranda EHA, Assunção MFM, Silva JO. Design and development of an alignment test device for clinical X-ray equipment with 3D print and low-cost materials. Braz J Radiat Sci. 2022;10(2A):1-11. https://doi.org/10.15392/bjrs.v10i2A.2024
Mora P, Pfeiffer D, Zhang G, Bosmans H, Delis H, Razi P, et al. The IAEA remote and automated quality control methodology for radiography and mammography. J Appl Clin Med Phys. 2021;22(11):126-142. https://doi.org/10.1002/acm2.13431