Patient’s Radiation Risk in Perspective: Insight from Brain Computed Tomography Scan Examination using a 64 Slice CT Machine

Background: Computed Tomography (CT) uses Ionizing radiation which can cause damage. The study evaluated patient’s radiation risk with an insight to brain CT scan using 64 slice CT machine. Method: The study was an empirical study conducted at the Rivers State University Teaching Hospital with patients referred for brain CT scan using a 64 Slice GE Optima Helical CT system, from June 2022 to December 2022. Participants were counseled, informed consent and ethical approval obtained before the study. The examination was performed in accordance with standard protocols for brain CT scan. Radiation dose was measured with a coded themoluminiscent dosimeter chip. The effective doses were estimated by multiplying the absorbed dose by the weighting factor. The cancer and hereditary risk per procedure were estimated by multiplying the effective dose with the cancer and hereditary risk factor coefficients of 5.5x10−2 Sv−1 and 0.2X10−2 Sv−1 respectively. Statistical Package for the Social Sciences (SPSS) windows version 22.30 statistical software (SPSS Inc, Chicago, Illinois, USA) was used to analyse the data and the results presented in tables, charts and graphs. Result: Males undertake CT brain in younger age; however, the absorbed radiation dose with its consequent effective dose was higher in females and low radiation dose could inadvertently necessitate cancer. Conclusion: The prevalence of obesity was found to be high. Therefore, there is a need for proper health education and promotion to reduce it and its possible attending consequences.

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Publication Details

Journal
Afrischolar Discovery
Published
2024-08-19
DOI
https://doi.org/10.60787/tnhj.v24i3.892
Primary Topic
Radiation Dose and Imaging
Type
article
Field-Weighted Citation Impact
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article

Patient’s Radiation Risk in Perspective: Insight from Brain Computed Tomography Scan Examination using a 64 Slice CT Machine

Afrischolar Discovery
Radiation Dose and Imaging
article

Patient’s Radiation Risk in Perspective: Insight from Brain Computed Tomography Scan Examination using a 64 Slice CT Machine

article en

Abstract

Background: Computed Tomography (CT) uses Ionizing radiation which can cause damage. The study evaluated patient’s radiation risk with an insight to brain CT scan using 64 slice CT machine. Method: The study was an empirical study conducted at the Rivers State University Teaching Hospital with patients referred for brain CT scan using a 64 Slice GE Optima Helical CT system, from June 2022 to December 2022. Participants were counseled, informed consent and ethical approval obtained before the study. The examination was performed in accordance with standard protocols for brain CT scan. Radiation dose was measured with a coded themoluminiscent dosimeter chip. The effective doses were estimated by multiplying the absorbed dose by the weighting factor. The cancer and hereditary risk per procedure were estimated by multiplying the effective dose with the cancer and hereditary risk factor coefficients of 5.5x10−2 Sv−1 and 0.2X10−2 Sv−1 respectively. Statistical Package for the Social Sciences (SPSS) windows version 22.30 statistical software (SPSS Inc, Chicago, Illinois, USA) was used to analyse the data and the results presented in tables, charts and graphs. Result: Males undertake CT brain in younger age; however, the absorbed radiation dose with its consequent effective dose was higher in females and low radiation dose could inadvertently necessitate cancer. Conclusion: The prevalence of obesity was found to be high. Therefore, there is a need for proper health education and promotion to reduce it and its possible attending consequences.

Afrischolar Discovery
University of Port Harcourt (NG), Rivers State University (NG)
Quality Education
Openalex Percentile: Top 45%
Radiation Dose and Imaging
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Patient’s Radiation Risk in Perspective: Insight from Brain Computed Tomography Scan Examination using a 64 Slice CT Machine · Afrischolar Discovery (2024) | TGRS Research Map | TGRS