Evaluation of barium sulfate-copper breast radiation shield for use in thoracic computed tomography examinations

Introduction: In thoracic computed tomography (CT) examinations, patients’ breasts are exposed to high radiation doses, necessitating the reduction of received dose by a radiation shield. The aim of this study is to evaluate the efficiency of a new composition of barium sulfate-copper shield with minimal impact on image quality. Materials and methods: Different breast shields were manufactured using varying weight percentages of copper and BaSO4. Thermoluminescent dosimeters (TLDs) and thorax phantoms were employed to assess the radiation shielding effectiveness. Image quality, in terms of noise and CT number accuracy, was quantitatively evaluated on a CT dose Index phantom (CTDI). Additionally, a controlled trial involving with 30 female participants was conducted to further assess CT image quality and select the best breast radiation shield. Results: The results indicated that the different shield compositions reduced the surface dose by 14.17–51.69%. The shield with a composition of 90% Cu–10% BaSO4 and 50% Cu–50% BaSO4 had the lowest noise, while the 100% bismuth shield had the highest noise. Importantly, the 50% Cu–50% BaSO4 shield did not cause artifacts in the thoracic CT images. Conclusion: By using the 50% Cu–50% BaSO4 shield, a significant dose reduction was achieved while maintaining appropriate image quality, making it suitable for clinical applications.

Publication Details

Journal
Springer Link (Chiba Institute of Technology)
Published
2024-12-13
DOI
https://doi.org/10.1051/radiopro/2024025/pdf
Primary Topic
Radiation Dose and Imaging
Type
article
Field-Weighted Citation Impact
0.00

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Evaluation of barium sulfate-copper breast radiation shield for use in thoracic computed tomography examinations

Springer Link (Chiba Institute of Technology)
Radiation Dose and Imaging
article

Evaluation of barium sulfate-copper breast radiation shield for use in thoracic computed tomography examinations

article en

Abstract

Introduction: In thoracic computed tomography (CT) examinations, patients’ breasts are exposed to high radiation doses, necessitating the reduction of received dose by a radiation shield. The aim of this study is to evaluate the efficiency of a new composition of barium sulfate-copper shield with minimal impact on image quality. Materials and methods: Different breast shields were manufactured using varying weight percentages of copper and BaSO4. Thermoluminescent dosimeters (TLDs) and thorax phantoms were employed to assess the radiation shielding effectiveness. Image quality, in terms of noise and CT number accuracy, was quantitatively evaluated on a CT dose Index phantom (CTDI). Additionally, a controlled trial involving with 30 female participants was conducted to further assess CT image quality and select the best breast radiation shield. Results: The results indicated that the different shield compositions reduced the surface dose by 14.17–51.69%. The shield with a composition of 90% Cu–10% BaSO4 and 50% Cu–50% BaSO4 had the lowest noise, while the 100% bismuth shield had the highest noise. Importantly, the 50% Cu–50% BaSO4 shield did not cause artifacts in the thoracic CT images. Conclusion: By using the 50% Cu–50% BaSO4 shield, a significant dose reduction was achieved while maintaining appropriate image quality, making it suitable for clinical applications.

Springer Link (Chiba Institute of Technology)
Semnan University
Openalex Percentile: Top 53%
Radiation Dose and Imaging
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.