Optimizing exposure parameters for thorax computed radiography: An aRTist simulation study with SNR and CNR analysis

Journal of Health Engineering and Precision Medicine

Abstract

Optimization of Exposure Factors on Image Quality in Computed Radiography (CR) of a Thorax Phantom at a Military Hospital Using the aRTist Simulation Program. Thorax radiography presents particular challenges for exposure optimization due to the wide dynamic range between low-density lungs and dense mediastinal structures, requiring careful balance of technical parameters. This study aims to optimize exposure parameters affecting image quality in thoracic Computed Radiography (CR) procedures by utilizing a simulation-based approach, supporting advancements in medical imaging and radiation safety. The research employed the aRTist simulation software to model a CR system and a 3D anthropomorphic thorax phantom representing the anatomy of an adult Asian male. Five commonly used clinical exposure factor variations were simulated: 55 kV / 10 mAs, 65 kV / 8 mAs, 75 kV / 4 mAs, 85 kV / 2 mAs, and 95 kV / 1 mAs. Image quality was quantitatively assessed using Signal-to-Noise Ratio (SNR) and Contrast-to-Noise Ratio (CNR) calculated across five key Regions of Interest (ROIs) on posteroanterior (PA) thorax images. The results indicate a consistent trend: increasing tube voltage (kV) improves SNR but reduces CNR. Conversely, increasing milliampere-seconds (mAs) linearly improves both SNR and CNR up to an optimal point. The combination of 65 kV and 8 mAs yielded the most balanced image quality, achieving SNR (25.2) and CNR (3.30) values within IAEA-recommended optimal ranges (SNR 25-28, CNR 2-5), while maintaining low radiation exposure principles. Higher kV settings (85-95 kV) produced high SNR but significantly reduced CNR, compromising diagnostic contrast. The aRTist simulation program is proven effective for technically and educationally determining optimal exposure parameters for thoracic CR imaging. The 65 kV / 8 mAs combination offers the best balance between image clarity, contrast, and dose efficiency. This simulation-based methodology supports the ALARA (As Low As Reasonably Achievable) principle and enhances clinical decision-making for safe, efficient, and evidence-based radiology practices, particularly in hospital settings.

Authors 2

1. Ananda Yessica Margaretha Hutagalung
   Affiliation as printed

   Indonesian Army

2. I A S Mu’minah Aachen

   RWTH Aachen University

   Affiliation as printed

   RWTH Aachen University