Convolution-based estimation of organ dose in tube current modulated CT

Area of Science:

• Medical Physics
• Radiological Sciences
• Computational Imaging

Background:

• Accurate organ dose estimation in CT is crucial for patient safety.
• Modeling CT dose fields, especially with tube current modulation (TCM), presents significant challenges.
• Existing methods may lack the precision required for real-time clinical applications.

Purpose of the Study:

• To develop and validate a convolution-based method for accurate organ dose field modeling in CT exams utilizing TCM.
• To establish a framework for both prospective and retrospective real-time organ dose estimation in clinical settings.
• To improve the accuracy of patient-specific organ dose calculations.

Main Methods:

• Generated patient-specific computational phantoms from CT datasets.
• Utilized a validated Monte Carlo simulation program to model a clinical CT scanner.
• Developed a convolution-based strategy to quantify the regional dose field by convolving organ distribution with a dose profile.
• Estimated organ dose by multiplying dose coefficients with the convolved dose field.
• Validated the method by comparing results with TCM Monte Carlo simulations.

Main Results:

• The convolution-based method demonstrated good accuracy, with average percentage errors generally within 10% (normalized by CTDIvol) compared to TCM Monte Carlo simulations.
• The method accurately quantified the irradiation field under TCM scans.
• The proposed technique allows for real-time organ dose estimation, applicable both prospectively and retrospectively.

Conclusions:

• The developed convolution-based method provides an accurate and efficient approach for estimating organ dose in CT scans with TCM.
• This technique enables real-time prospective and retrospective organ dose assessments, enhancing clinical radiation safety.
• The findings support the integration of this method into clinical workflows for improved patient dosimetry.