Comparison of Approximate Mathematical Formulas for Optimal Organ Absorbed Dose Estimation in CT Examination of the Abdominopelvic Region

Computed tomography (CT) examinations account for a large proportion of all medical exposures. Therefore, various studies on radiation exposure have been conducted. The automatic exposure control system is commonly used in CT examinations, and its characteristics vary from equipment to equipment, which may affect the approximate formulas and coefficients of determination (R<sup>2</sup>). The purpose of this study is to compare the organ-specific absorbed dose approximate formulas for different CT equipment with the literature and to verify the optimal approximate formula. The subjects were 224 consecutive adult male patients who underwent abdominopelvic CT examinations in 2020, using an Aquilion ONE/PRISM Edition CT equipment (Canon Medical Systems, Inc., Tochigi, Japan). The vertical axis was the absorbed dose to the organs estimated by Monte Carlo simulation using Radimetrics version 3.3 (Bayer Medical Care Inc., Whippany, NJ), a dose management software (DMS). The target organs were the liver, kidney, and colon. The horizontal axis was the dose-length product (DLP) and the size-specific dose estimate (SSDE) calculated by Radimetrics. The approximate formulas analyzed were linear, power, and logarithmic. All organ-absorbed doses had the highest R<sup>2</sup> in the logarithmic approximation. By calculating the approximate formula from specimens of one's own facility, one can estimate the absorbed dose for each organ with a high degree of accuracy without using DMS.

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Journal
Cureus
Published
2025-10-27
DOI
https://doi.org/10.7759/cureus.95533
Primary Topic
Radiation Dose and Imaging
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article
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article

Comparison of Approximate Mathematical Formulas for Optimal Organ Absorbed Dose Estimation in CT Examination of the Abdominopelvic Region

Koichi Masuda, Isao Kuroda, Masaya Noguchi, Shinji Sugahara et al.
Cureus
Radiation Dose and Imaging
article

Comparison of Approximate Mathematical Formulas for Optimal Organ Absorbed Dose Estimation in CT Examination of the Abdominopelvic Region

Koichi Masuda, Isao Kuroda, Masaya Noguchi, Shinji Sugahara, Masaki Matsushita, Masato Takanashi, Masataka Hoshina
article en

Abstract

Computed tomography (CT) examinations account for a large proportion of all medical exposures. Therefore, various studies on radiation exposure have been conducted. The automatic exposure control system is commonly used in CT examinations, and its characteristics vary from equipment to equipment, which may affect the approximate formulas and coefficients of determination (R<sup>2</sup>). The purpose of this study is to compare the organ-specific absorbed dose approximate formulas for different CT equipment with the literature and to verify the optimal approximate formula. The subjects were 224 consecutive adult male patients who underwent abdominopelvic CT examinations in 2020, using an Aquilion ONE/PRISM Edition CT equipment (Canon Medical Systems, Inc., Tochigi, Japan). The vertical axis was the absorbed dose to the organs estimated by Monte Carlo simulation using Radimetrics version 3.3 (Bayer Medical Care Inc., Whippany, NJ), a dose management software (DMS). The target organs were the liver, kidney, and colon. The horizontal axis was the dose-length product (DLP) and the size-specific dose estimate (SSDE) calculated by Radimetrics. The approximate formulas analyzed were linear, power, and logarithmic. All organ-absorbed doses had the highest R<sup>2</sup> in the logarithmic approximation. By calculating the approximate formula from specimens of one's own facility, one can estimate the absorbed dose for each organ with a high degree of accuracy without using DMS.

CureusVol. 17(10)
Tokyo Medical University Ibaraki Medical Center (JP)
Openalex Percentile: Top 54%
Radiation Dose and Imaging
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Comparison of Approximate Mathematical Formulas for Optimal Organ Absorbed Dose Estimation in CT Examination of the Abdominopelvic Region — Koichi Masuda, Isao Kuroda, et al. · Cureus (2025) | TGRS Research Map | TGRS