Pediatric Computed Tomography Dose Optimization Strategies: A Literature Review

Mahrooqi, Khalid Mohammed Salim Al; Ng, Curtise; Sun, Zhonghua

doi:10.1016/j.jmir.2015.03.003

Cited by 22 publications

(16 citation statements)

References 80 publications

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“…Thus, it might undermine achievement of potential dose optimisation. However, it is established that on-the-job continuous medical education (CME) in radiation protection was effective and substantially improved radiographers' performance, radiation protection knowledge and skills [29,[34][35][36]. On the other hand, slightly above 50% of the participants were aware that scan protocols are relevant for dose optimisation.…”

Section: Awareness About General Radiation Protection and Dose Optimimentioning

confidence: 99%

Assessment of diagnostic reference levels awareness and knowledge amongst CT radiographers

Abdulkadir

Piersson

Musa

et al. 2021

Egypt J Radiol Nucl Med

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Background Reports indicated that numerous factors, including inadequate personnel knowledge, contributes to insufficient patient data for setting up diagnostic reference levels (DRLs) in developing countries. This study aims to evaluate the knowledge of DRLs as an optimisation tool amongst computed tomography (CT) radiographers in northern Nigeria. This is a quantitative cross-sectional study. A structured questionnaire was devised and distributed on site to sixty-two CT radiographers in northern Nigeria. A total of fifteen questions were included in the questionnaire focusing on DRLs, dose optimisation and dose descriptors generating quantitative data concerning overall CT radiographers’ perceived knowledge and awareness about DRLs. Results A response rate of 77.4% (48/62) was achieved. About 83.3% of the participants declare DRLs awareness, and 37.5% carried out a local dose survey. The percentage correctly perceived knowledge of concepts; DRLs was 45.8%, dose optimisation (42%) and CT dose descriptor (39%). Radiographers with work experience ranging from 4-10 years had the highest score. Conclusion In this survey, deficiencies were noted in radiographers’ knowledge about DRLs with precise knowledge gap in the implementation of local dose survey for DRLs and optimisation. There is a need for continuous radiographers’ training with greater emphasis on dose optimisation and institutional based dose evaluation.

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Section: Awareness About General Radiation Protection and Dose Optimimentioning

confidence: 99%

Assessment of diagnostic reference levels awareness and knowledge amongst CT radiographers

Abdulkadir

Piersson

Musa

et al. 2021

Egypt J Radiol Nucl Med

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“…The dose optimization is particularly important for pediatric patients because they have longer life and more rapid cell proliferation, leading to two to three times more susceptibility to the potential harmful effects of ionizing radiation than the adult counterpart [ 17 , 33 , 36 , 40 ]. Nonetheless, dose optimization in pediatric radiology is challenging, as there is a greater variation of body size and composition within and across age groups [ 4 , 33 ].…”

Section: Introductionmentioning

confidence: 99%

Artificial Intelligence for Radiation Dose Optimization in Pediatric Radiology: A Systematic Review

2022

Children

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Radiation dose optimization is particularly important in pediatric radiology, as children are more susceptible to potential harmful effects of ionizing radiation. However, only one narrative review about artificial intelligence (AI) for dose optimization in pediatric computed tomography (CT) has been published yet. The purpose of this systematic review is to answer the question “What are the AI techniques and architectures introduced in pediatric radiology for dose optimization, their specific application areas, and performances?” Literature search with use of electronic databases was conducted on 3 June 2022. Sixteen articles that met selection criteria were included. The included studies showed deep convolutional neural network (CNN) was the most common AI technique and architecture used for dose optimization in pediatric radiology. All but three included studies evaluated AI performance in dose optimization of abdomen, chest, head, neck, and pelvis CT; CT angiography; and dual-energy CT through deep learning image reconstruction. Most studies demonstrated that AI could reduce radiation dose by 36–70% without losing diagnostic information. Despite the dominance of commercially available AI models based on deep CNN with promising outcomes, homegrown models could provide comparable performances. Future exploration of AI value for dose optimization in pediatric radiology is necessary due to small sample sizes and narrow scopes (only three modalities, CT, positron emission tomography/magnetic resonance imaging and mobile radiography, and not all examination types covered) of existing studies.

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“…Therefore, if possible, the CT should be optimized to reduce the radiation dose to young children, with the dose depending on the age and size of the body. 14) MRI and PET-CT imaging of pilomatricoma have also been reported. 3,8) However, both MRI and PET-CT seem to offer little advantage over other tests because of their high cost, long test time, and the requirement for sedation or anesthesia.…”

Section: Discussionmentioning

confidence: 99%

Evaluation of Ultrasonography and CT for Imaging of Head and Neck Pilomatricoma in Children and Adolescents

Won¹,

Cho²,

Ryu³

et al. 2021

Korean J Otorhinolaryngol-Head Neck Surg

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Background and Objectives Pilomatricoma is a frequently diagnosed skin lesion of the head and neck that may often be misdiagnosed as other skin lesions. This study evaluated whether ultrasonography (USG) or computed tomography (CT) is the most helpful imaging modality for the accurate preoperative diagnosis of pilomatricoma in head and neck regions of children and adolescents.Subjects and Method A retrospective review was conducted for 59 patients with pilomatricoma under the age of 19 years. All cases were pathologically confirmed with pilomatricoma in the head or neck.Results Preoperative imaging examinations were performed with USG in six cases and with CT in nine cases. The accuracy of preoperative diagnosis was compared between three groups: 1) with clinical findings only, 2) with USG, and 3) with CT. The correct preoperative diagnosis was made in 18 (30.5%) of the total of 59 cases. Using only clinical findings, 10 (22.7%) out of 44 patients were diagnosed as pilomatricoma. With the addition of USG, pilomatricoma was diagnosed in 1 (16.7%) out of six cases, whereas with the addition of CT, 7 (77.8%) out of 9 cases (77.8%) were diagnosed correctly. Preoperative diagnosis of pilomatricoma with CT imaging was more accurate than clinical findings only (vs. CT; odds ratio [OR]=11.900, 95% confidence interval [CI] 2.126-66.615; p=0.001) or USG (vs. CT; OR=17.500, 95% CI 1.223-250.357; p=0.020).Conclusion In the preoperative diagnosis of pilomatricoma, imaging modalities such as CT and USG are helpful, with CT offering higher diagnostic accuracy and USG procedural benefits in younger children.

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Pediatric Computed Tomography Dose Optimization Strategies: A Literature Review

Cited by 22 publications

References 80 publications

Assessment of diagnostic reference levels awareness and knowledge amongst CT radiographers

Assessment of diagnostic reference levels awareness and knowledge amongst CT radiographers

Artificial Intelligence for Radiation Dose Optimization in Pediatric Radiology: A Systematic Review

Evaluation of Ultrasonography and CT for Imaging of Head and Neck Pilomatricoma in Children and Adolescents

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