2208 - Phantom-Based Validation of Photon-Counting Computed Tomography Image Data for Radiation Therapy Applications

Purpose/Objective(s): Photon-Counting CT (PCCT) represents a major advancement in medical imaging, providing intrinsic spectral information that enhances image quality and material discrimination. Virtual monoenergetic image (VMI) reconstruction is a key technique in spectral CT imaging, including Dual-Energy CT (DECT) and PCCT. This study aims to validate PCCT image data for radiation therapy applications by determining the optimal VMI energy level for accurate dose calculation with existing Single-Energy calibration curves and maximizing tissue contrast for precise target delineation through rigorous phantom-based evaluations.

Materials/Methods: The Advanced Electron Density Phantom was utilized to simulate various tissue-equivalent materials. Imaging was performed on a Naeotom Alpha scanner (Siemens Healthineers, Forchheim, Germany) using a standard QuantumPlus 120 kVp protocol. Regions of interest (ROIs) were placed within the tissue-mimicking inserts to enable quantitative analysis of mean attenuation. VMI levels were varied from 40 to 190 keV in 1 keV increments. Calibration curves were derived from ROI evaluations across different VMI levels and compared to the SECT calibration curve. The impact of VMI levels on image quality was assessed for iodine inserts at concentrations ranging from 0.2 mg/ml to 15 mg/ml. Image quality was quantified using the contrast-to-noise ratio (CNR).

Results: Mean attenuation exhibited an energy-dependent decline as VMI levels increased. Calibration curve analysis revealed that the 70 keV VMI reconstruction closely resembled the SECT calibration curve, making it the most suitable choice for dose calculation while preserving the advantages of spectral imaging. CNR analysis demonstrated improvements with increasing VMI levels, peaking between 63 and 65 keV, depending on the material inserts. At these energy levels, CNR values were maximized, demonstrating superior contrast enhancement compared to SECT scans. In a comparable study on VMI optimization for brain metastases delineation in radiosurgical planning, an optimal VMI energy level of 63 keV was identified using contrast-enhanced DECT [1]. Overall, the attenuation characteristics across diverse tissue types reinforced the ability of VMI reconstructions to enhance tissue differentiation and improve target delineation, affirming the clinical potential of PCCT optimization in radiation therapy.

Conclusion: The phantom-based study highlighted multiple benefits of PCCT imaging for radiation therapy applications. PCCT facilitates the reconstruction of CT images for both dose calculation and energy-specific imaging, providing enhanced contrast and high spatial resolution for improved tissue differentiation. These findings suggest PCCT’s promising potential for refining radiation therapy planning and target delineation.