A MONTE-CARLO SIMULATION FRAMEWORK FOR JOINT OPTIMISATION OF IMAGE QUALITY AND PATIENT DOSE IN DIGITAL PAEDIATRIC...

Area of Science:

• Medical Physics
• Radiological Sciences
• Computational Imaging

Background:

• The As Low As Reasonably Achievable (ALARA) principle mandates minimizing radiation dose in pediatric radiography.
• Optimizing imaging parameters is crucial for balancing diagnostic image quality with patient safety.
• Digital radiography necessitates advanced simulation tools for parameter evaluation.

Purpose of the Study:

• To develop and validate a Monte Carlo simulation framework for optimizing radiation dose and image quality in digital pediatric radiography.
• To apply the framework for optimizing tube voltage and pre-filtration in newborn chest radiography.
• To evaluate the impact of different imaging parameters on contrast-to-noise ratio (CNR) at a fixed radiation dose.

Main Methods:

• A high-resolution patient modeling approach with organ segmentation was employed for simultaneous dose and image quality assessment.
• Monte Carlo simulations were utilized to model the radiographic imaging process.
• The simulation accuracy was validated by comparing simulated images with acquired images of technical phantoms.
• The framework was applied to optimize tube voltage and copper pre-filtration for newborn chest X-rays.

Main Results:

• The simulation framework accurately reproduced technical phantom images, confirming its reliability.
• Optimization for newborn chest radiography identified low-kilovoltage settings combined with copper filtration as optimal.
• This combination yielded the highest Contrast-to-Noise Ratio (CNR) for a given patient dose compared to other tested parameters.

Conclusions:

• The developed Monte Carlo simulation framework is effective for dose and image quality optimization in pediatric radiography.
• Low-kV radiography with appropriate pre-filtration (e.g., copper) can enhance image quality while adhering to radiation safety principles.
• This approach offers a pathway to reduce radiation exposure in pediatric imaging without compromising diagnostic information.