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Model-based iterative reconstruction in paediatric head computed tomography: a pilot study on dose reduction in children
PURPOSE: To evaluate the potential of model-based iterative reconstruction (MBIR) on dose reduction and image quality in children undergoing computed tomography (CT) head examinations. MATERIAL AND METHODS: This prospective study was approved by the institutional ethics committee. A total of 88 chil...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Termedia Publishing House
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8449558/ https://www.ncbi.nlm.nih.gov/pubmed/34567298 http://dx.doi.org/10.5114/pjr.2021.108884 |
Sumario: | PURPOSE: To evaluate the potential of model-based iterative reconstruction (MBIR) on dose reduction and image quality in children undergoing computed tomography (CT) head examinations. MATERIAL AND METHODS: This prospective study was approved by the institutional ethics committee. A total of 88 children (age range of 5 to 16 years) with a history of seizures underwent contrast-enhanced CT scan. Forty-one children underwent CT study according to the MBIR technique, while 47 children underwent CT of the head with the non-MBIR protocol. Images were reviewed by 2 blinded paediatric radiologists in a random order. Mean dose-length product, CT dose index (CTDI) volume, and mean effective dose were recorded for both groups. Image quality, image noise, and diagnostic acceptability of 2 image sets were also recorded. RESULTS: In the MBIR group, the mean dose-length product was reduced by 79.8%; the mean CTDI volume was reduced by 88.5%, while the mean effective dose was reduced by 81% when compared to the non-MBIR group. No significant difference was seen in diagnostic acceptability, image noise, and image quality between the 2 groups. CONCLUSIONS: MBIR technique is highly effective in reducing radiation dose in paediatric head CT examinations without any significant difference in image quality, image noise, and diagnostic acceptability. |
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