# Assessing the Organ Dose in Diagnostic Imaging with Digital Tomosynthesis System Using TLD100H Dosimeters

## TL;DR

This study evaluates radiation doses from digital tomosynthesis using TLD100H dosimeters, comparing results to traditional imaging methods.

## Contribution

The study introduces a method to improve organ dose assessment accuracy using TLD100H dosimeters in digital tomosynthesis.

## Key findings

- Lung doses during DTS were approximately 3.21 mGy for the left and 3.32 mGy for the right lung.
- RX mode resulted in significantly lower lung doses at 0.33 mGy.
- Heart dose during DTS was measured at 2.81 mGy, consistent with prior studies.

## Abstract

Background: Digital tomosynthesis (DTS) is an advanced imaging modality that enhances diagnostic accuracy by offering three-dimensional visualization from two-dimensional projections, which is particularly beneficial in breast and lung imaging. However, this increased imaging capability raises concerns about patient exposure to ionizing radiation. Methods: This study explores the energy and angular dependence of thermoluminescent dosimeters (TLDs), specifically TLD100H, to improve the accuracy of organ dose assessment during DTS. Using a comprehensive experimental approach, organ doses were measured in both DTS and traditional RX modes. Results: The results showed lung doses of approximately 3.21 mGy for the left lung and 3.32 mGy for the right lung during DTS, aligning with the existing literature. In contrast, the RX mode yielded significantly lower lung doses of 0.33 mGy. The heart dose during DTS was measured at 2.81 mGy, corroborating findings from similar studies. Conclusions: These results reinforce the reliability of TLD100H dosimetry in assessing radiation exposure and highlight the need for optimizing imaging protocols to minimize doses. Overall, this study contributes to the ongoing dialogue on enhancing patient safety in diagnostic imaging and advocates for collaboration among medical physicists, radiologists, and technologists to establish best practices.