A general method to derive tissue parameters for Monte Carlo dose calculation with multi-energy CT

Area of Science:

• Medical Physics
• Radiotherapy Physics
• Medical Imaging

Background:

• Accurate human tissue characterization is crucial for precise radiotherapy dose calculations.
• Current methods for tissue characterization using CT have limitations in elemental composition determination.
• Dual- and multi-energy CT offer potential for improved tissue analysis.

Purpose of the Study:

• To develop and evaluate a general method for human tissue characterization using dual- and multi-energy CT.
• To assess the method's performance in determining elemental compositions relevant to radiotherapy.
• To enable accurate Monte Carlo dose calculations through improved tissue data.

Main Methods:

• Applied principal component analysis to literature data for ideal human tissue material identification.
• Adapted CT data analysis theory to elemental composition for tissue information extraction.
• Integrated a novel stoichiometric calibration for clinical applicability.
• Compared performance against existing techniques using simulated CT data.

Main Results:

• The developed method demonstrated systematic superiority over water-lipid-protein decomposition for elemental weights using dual-energy CT.
• Performance was comparable to parameterization techniques for elemental weight determination.
• Achieved better accuracy and unbiased results for proton stopping powers and energy absorption coefficients.
• Simulations with multi-energy CT data showed potential for extracting more detailed information.

Conclusions:

• The proposed method effectively determines elemental compositions from dual-energy CT data.
• It provides accurate physical quantities essential for radiotherapy dose calculation.
• The technique is well-suited for Monte Carlo simulations and shows promise for multi-energy CT applications in tissue characterization.