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Slice-resolved ocular dosimetry in pediatric axial CT using a validated Geant4 Monte Carlo framework.

Created on 27 Aug 2026

Authors

Nouf Abuhadi, Omrane Kadri, Kais Manai

Published in

Radiation protection dosimetry. Aug 26, 2026. Epub Aug 26, 2026.

Abstract

Accurate evaluation of eye lens exposure during pediatric computed tomography (CT) examinations is essential for radiation protection because the lens is among the most radiosensitive organs in the human body. In this study, a scanner-specific Monte Carlo framework based on Geant4 (v11.02.p2) was developed to quantify slice-resolved absorbed dose to the eye lens and selected head organs in pediatric axial CT imaging. The CT system was modeled in detail, including X-ray spectra, bowtie filtration, beam collimation, and source geometry. Beam quality was tuned using half-value layer and lateral beam profile measurements. Model validation was performed through comparison with experimental computed tomography dose index ratios, ${\text{CTDI}}_{\text{air}}/{\text{CTDI}}_{w}$, for tube voltages between 80 and 140 kVp and collimations between 10 and 40 mm, showing agreement within 2%. Simulations using 10 pediatric voxel phantoms based on International Commission on Radiological Protection-143 reference models revealed a strong dependence of ocular dose on acquisition parameters and patient anatomy. Although absolute eye-lens dose differed substantially between the two acquisition configurations, normalization relative to brain dose showed that beam collimation altered the eye-to-brain dose ratio by only about 6%. However, reducing tube voltage from 140 to 80 kVp decreased eye lens dose by $\sim $86% in newborn phantoms. The proposed framework enables detailed slice-resolved assessment of ocular exposure beyond conventional CTDI-based estimates and provides a robust tool for evaluating pediatric CT protocols and supporting optimization strategies aimed at improving radiation protection of radiosensitive tissues.

PMID:
42648871
Bibliographic data and abstract were imported from PubMed on 27 Aug 2026.

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