Validation of dual-energy CT-based composition analysis using fresh animal tissues and composition-optimized tissue...

Area of Science:

• Medical Physics
• Radiotherapy Technology
• Biomedical Imaging

Background:

• Proton therapy offers precise dose delivery but is sensitive to range uncertainties.
• In-vivo monitoring of proton range requires accurate patient tissue composition data.
• Current methods for elemental composition assessment are being explored for integration with proton therapy.

Purpose of the Study:

• To validate a dual-energy computed tomography (DECT)-based algorithm for extracting elemental tissue composition.
• To compare DECT-derived compositions with reference methods like chemical combustion analysis (CCA) and prompt gamma-ray (PG) measurements.
• To assess the potential of DECT for improving in-vivo dose verification in proton therapy.

Main Methods:

• DECT imaging of phantoms with known tissue compositions at two energy levels.
• Validation against reference compositions from CCA and multi-layer ionization chamber measurements of stopping-power ratio (SPR).
• Monte Carlo simulations for PG signal analysis to estimate carbon and oxygen content.

Main Results:

• DECT-based estimation of soft tissue carbon and oxygen content showed good agreement with CCA and PG results.
• Accurate prediction of phosphorous and calcium content within 0.4 wt% and 1.1 wt% of CCA results, respectively.
• DECT demonstrated comparable or superior agreement with ground truth compared to single-energy CT (SECT).

Conclusions:

• DECT-based elemental composition estimation is a viable method for proton therapy applications.
• This approach can enhance the accuracy of in-vivo range monitoring and dose verification.
• DECT offers a promising tool for improving the safety and efficacy of proton beam radiation therapy.