Background and Objective: Nowadays, Computer Tomography is one of the best radiological imaging technics which can give right diagnostic information, among the detection of multiphasic adenomas, the detection of cardiac, cerebral and vascular abnormalities. Although these good qualities, this technic is too radiant for the patient. In this paper, we based on the irradiation doses delivered from the current protocols to find a practical method of their optimization during the pediatric cranial scan. Materials and Methods: This work relies on a collection of data from patients in the hospitals, so that analyze them, give the conclusions and, propose an optimal practical method to decrease the irradiation doses. To collect data, we performed a prospective study of seventeen months (from December 2017 to May 2019) carried out simultaneously in three hospitals of the city: The Centre Medical la Cathédrale (H1), the Yaoundé Central Hospital (H2) and the Yaoundé Gyneaco-Obstetric and pediatric hospital (H3). This study included a total of 192 cases of cerebral trauma, of which 11 cases excluded for incomplete information. The dosimetry quality control (CTDIvol) using the PMMA phantoms of 16 cm and 32 cm fulfilled. The scanographic parameters of the patient acquisition protocol were recorded and analyzed. Some of those parameters were modified and entered the CT with the help of a biomedical engineer to reduce the delivered dose. The relationship between CTDIvol and kV is statistically significant (p < 0.05) to identify significant differences in obtained results before and after the optimization of protocols. Results: Among patients, 172 are boys, and the remaining 9 are girls all were in the 0 to 15 age group. CTDIvol values varied from 34.2 mGy to 107.8 mGy and PDLs from 107.8 mGy.cm to 2214.5 mGy.cm in H1. In H2, CTDIvol varied from 5.8 mGy to 44 mGy and PDLs from 91.4 mGy.cm to 665.5 mGy.cm. CTDIvol varied between 9.34 mGy to 92.81 mGy and PDLs from 162.38 mGy.cm to 2713.67 mGy.cm in H3. All values are taken at 75th percentile, with or without contrast injection. Conclusion: The implementation of the optimization of protocols requires the display of the CT parameters to use and to respect during the traumatic brain tests. With displaying and respecting protocol, the CTDIvol decreased by almost 50 per cent.
References
[1]
Journy, N. (2014) Analyse de la relation entre l’exposition aux rayonnements ionisants lors d’examens de scanographie et la survenue de pathologie tumorale, au sein de la cohorte. Enfant Scanner. Santé publique et épidémiologie. Université Paris Sud-Paris XI, 235 p.
[2]
Morel, J.B., Aurélien, B., Lévy, P., et al. (2016) Optimization of the Pediatric Head Computed Tomography Scan Image Quality: Reducing Dose with an Automatic Tube Potential Selection in Infants. Journal of Neuroradiology, 43, 398-403. https://doi.org/10.1016/j.neurad.2016.03.005
[3]
De Gonzalez, B., Curtis, R.E., Kry, S.F., et al. (2011) Proportion of Second Cancers Attributable to Radiotherapy Treatment in Adults: Prospective Cohort Study in the US SEER Cancer Registries. The Lancet Oncology, 12, 353-360. https://doi.org/10.1016/S1470-2045(11)70061-4
[4]
Brisse, H. and Aubert, B. (2009) Niveaux d’exposition en tomodensitométrie mul-ticoupes pédiatriques: Résultat de l’enquête dosimétrique SFIPP/IRSN2007/2008. Journal de Radiologie, 90, 207-215. https://doi.org/10.1016/S0221-0363(09)72471-0
[5]
Baysson, H., Journy, N., Roué, T., et al. (2016) Exposition à la scanographie dans l’enfance et risque de cancer à long terme Une synthèse des études épidémiologiques récentes. Bulletin du Cancer, 103, 190-198. https://doi.org/10.1016/j.bulcan.2015.11.003
[6]
Nelson, T. (2014) Practical Strategies to Reduce Pediatric CT Radiation Dose. Journal of the American College of Radiology, 11, 292-299. https://doi.org/10.1016/j.jacr.2013.10.011
[7]
Kofler, J.M., Cody, D. and Morin, R.L. (2014) CT Protocol Review and Optimization. Journal of the American College of Radiology, 11, 267-270. https://doi.org/10.1016/j.jacr.2013.10.013
[8]
Robinson, A. and Dellagrammaticas, H.D. (1983) Radiation Doses to Neonates during Requiring Intensive Care. The British Journal of Radiology, 56, 397. https://doi.org/10.1259/0007-1285-56-666-397
[9]
Brisse, H., Sirimelli, D., Adamsbaume, C., et al. (2004) Irradiation Medicale de l’enfant. Journal de Radiologie, 85, 1671-1672. https://doi.org/10.1016/S0221-0363(04)97730-X
[10]
https://www.sciencesetavenir.fr/
[11]
Biwele, S., Menouna, N., Zogo, O., et al. (2015) Apport de la tomodensitométrie dans le diagnostic de la pathologie pancréatique au Cameroun. Journal Africain d’Hépato-Gastroentérologie, 10, 53-57.
[12]
Guegang, G.E., Zeh, O.F., Moifo, B., Ndam, I.A., et al. (2014) Evaluation des doses d’irradiation délivrée aux patients au cours de l’uroscanner réalisé pour le bilan de la lithiase des voies urinaires hautes. African Journal of Medical Imaging, 6, 31-37.
[13]
Moifo, B., Nguefack, S., Zeh, O.F., et al. (2013) Computer Tomography Findings in Cerebral Palsy in Yaoundé Cameroon. African Journal of Medical Imaging, 5, 134-142.
[14]
Zogo, O., Mokubangele, M., Moifo, B., et al. (2012) Evaluation de la dose patiente en scanographie pédiatrique dans deux hôpitaux universitaires à Yaoundé Cameroun. Radioprotection, 47, 533-542. https://doi.org/10.1051/radiopro/2012016
[15]
Lambers, J., John, D., Mackenzie, M.D., et al. (2014) Techniques and Tactics for Optimizing CT Dose in Adults and Children: State of the Art and Future Advances. Journal of the American College of Radiology, 11, 262-266. https://doi.org/10.1016/j.jacr.2013.10.012
[16]
Thibault, J.B., Bouman, S. and Hsich, J.A. (2007) Three-Dimensional Statistical Approach to Improved Image Quality for Multislice Helical CT. Medical Physics, 34, 4526-4544. https://doi.org/10.1118/1.2789499
[17]
Pickhardt, P.J., Lubner, M.G., Kim, D.H., et al. (2012) Abdominal CT with Model-Based Iterative Reconstruction (MBIR): Initial Result of Prospective Trial Comparing Ultralow-Dose Imaging. American Journal of Roentgenology, 199, 1266-1260. https://doi.org/10.2214/AJR.12.9382
[18]
Solomon, J.B., Li, X. and Samei, E. (2013) Relating Noise to Image Quality Indication in CT Examination with Tube Current Modulation. American Journal of Roentgenology, 200, 592-600. https://doi.org/10.2214/AJR.12.8580
[19]
American College of Radiology (ACR) (2018) Dose Index Registry. http://www.acr.org/quality-safety_National_Radiology-data_registry/doseindex
[20]
https://www.populationpyramid.net/cameroon/
[21]
International Commission on Radiological Protection (ICRP) (1991) 1990 Recommendations of the International Commission on Radiological Protection. ICRP Publication 60, Pergamon Press, Oxford, 1-88.
[22]
Shrimpton, P.C., Jansen, J.T.M. and Harrison, J.D. (2016) Updated Estimates of Typical Effective Doses for Common CT Examination in the UK Following the 2011 National Review. The British Journal of Radiology;, 89, 20150346. https://doi.org/10.1259/bjr.20150346
[23]
Kalra, M.K., Mayer, M.M., Toth, T.L., et al. (2004) Strategies for CT Radiation Dose Optimization. Radiology, 230, 619-628. https://doi.org/10.1148/radiol.2303021726
[24]
Greffier, J. (2016) Reconstruction itérative en Scanographie: Optimisation de la qualité d’image et dose pour une prise en charge personnalisée. Médecine humaine et pathologie. Université de Montpellier, Français. https://tel.archives-ouvertes.fr/tel-01499577
[25]
Shrimpton, P.C., Hillier, M.C., Lewis, M.A. and Dunn, M. (2005) Doses from Computed Tomography (CT) Examinations in the UK-2003 Review. National Radiological Protection Board, Chilton, 107 p.
[26]
Deak, P.D., Small, Y. and Kalender, W.A. (2010) Multisection CT Protocols: Sex- and Age-Specific Conversion Factors Used to Determine Effective Dose from Dose-Length Product. Radiology, 257, 158-166. https://doi.org/10.1148/radiol.10100047
[27]
Nor ETSP1129093A (2012) Arrété du 24 octobre 2011 relatif aux niveaux de référence diagnostiques en radiologie et en medecine nucléaire. Journal officiel de la république francaise, texte No. 22, sur 147, 5117.
[28]
Tchagna Kouanou, A., Tchiotsop, D., Kengne, R., et al. (2018) An Optimal Big Data Workflow for Biomedical Image Analysis. Informatics in Medicine Unlocked, 11, 68-74. https://doi.org/10.1016/j.imu.2018.05.001
