What All Physicians Should Know About the Potential Radiation Risk That Computed Tomography Poses for Paediatric Patients

Overview

Journal Acta Paediatr

Specialty Pediatrics

Date 2014 Mar 29

PMID 24673144

Citations 24

Authors

Kushaljit Singh Sodhi

Edward Y Lee

Affiliations

Soon will be listed here.

Abstract

Unlabelled: The repeated use of CT imaging raises a child's radiation exposure, overall radiation accrual and future cancer risks. However, our review suggests that these risks can be considerably reduced by physicians, radiologists and academic bodies, through proper justification, optimisation and dose limitation.

Conclusion: Computed tomography poses a potential risk of radiation-induced cancer in children. The physician must weigh up the overall risks and benefits of CT before referring a child for imaging.

Citing Articles

A clinical-information-free method for early diagnosis of lung cancer from the patients with pulmonary nodules based on backpropagation neural network model.

Yang X, Wu C, Liu W, Fu K, Tian Y, Wei X Comput Struct Biotechnol J. 2024; 24:404-411.

PMID: 38813092 PMC: 11134880. DOI: 10.1016/j.csbj.2024.05.010.

Three-dimensional ultrashort echo time magnetic resonance imaging in pediatric patients with pneumonia: a comparative study.

Sun Y, Chen Y, Li X, Liao Y, Chen X, Song Y BMC Med Imaging. 2023; 23(1):175.

PMID: 37919642 PMC: 10621158. DOI: 10.1186/s12880-023-01130-2.

Fast magnetic resonance imaging for diagnosing pulmonary tuberculosis in children: the sub-10-min unenhanced scan.

Pillay T, Zar H, Venkatakrishna S, Andronikou S Pediatr Radiol. 2023; 54(3):425-429.

PMID: 37212919 DOI: 10.1007/s00247-023-05683-w.

Evaluation of coronary arteries in congenital heart disease in children: diagnostic comparison of electrocardiogram-gated and non-electro-cardiogram-gated computed tomography cardiac angiography.

Sodhi K, Bhatia A, Rana P, Farook S, Saxena A, Baryah H Pol J Radiol. 2023; 87:e688-e693.

PMID: 36643008 PMC: 9834070. DOI: 10.5114/pjr.2022.123855.

Utilization of artificial intelligence approach for prediction of DLP values for abdominal CT scans: A high accuracy estimation for risk assessment.

Tekin H, Almisned F, Erguzel T, Abuzaid M, Elshami W, Ene A Front Public Health. 2022; 10:892789.

PMID: 35968466 PMC: 9366721. DOI: 10.3389/fpubh.2022.892789.