Author: Sebastien A. Gros, Hyejoo Kang, Andrew Keeler, Luke Layman, Jason Patrick Luce, Ha Nguyen, John C. Roeske 👨🔬
Affiliation: Department of Radiation Oncology, Stritch School of Medicine, Loyola University Chicago, Stritch School of Medicine Loyola University Chicago, Cardinal Bernardin Cancer Center, Loyola University Chicago 🌍
Purpose:
This study aims to optimize virtual monoenergetic (VM) images obtained from dual-energy (DE) cone-beam computer tomography (CBCT) protocols for Image-Guided Radiation Therapy (IGRT). The objective is to develop a method to generate VM images with enhanced image quality while reducing imaging dose.
Methods:
Normalized air Kerma (Kair) per exposure was measured using an ion chamber for eight CBCT datasets with varying exposures per pulse and framerates at 80 and 140 kVp. Correlations between Kair and cone-beam dose indices (CBDI) were established to facilitate Kair-based imaging dose estimation for DE-CBCT. These estimated doses were validated through direct Kair measurements. Separately, VM images from six DE-CBCT protocols of a Catphan 604 phantom were reconstructed using the Feldkamp-Davis-Kress (FDK) algorithm within the open-source TIGRE. Image quality of these VM-CBCT at the near-optimal energy of 60 keV was evaluated using the root-mean-squared error (RMSE) of Hounsfield units (HU) and average relative contrast-noise-ratio (rCNR) over all material inserts compared to the clinical pelvis CBCT protocol.
Results:
The average difference between estimated and measured Kair across all DE-CBCT protocols was 2.2±2.1%. VM-CBCT images at 60 keV demonstrated rCNR values ranging from 0.71 to 1.36 compared to the standard clinical pelvis protocol. The estimated Kair for these VM-CBCT images ranged from 14-185 mGy, compared to 134 mGy for the clinical pelvis protocol. A VM-CBCT with Kair = 80 mGy resulted in a 19% enhancement in rCNR while maintaining an RMSE consistent with that of the clinical pelvis protocol.
Conclusion:
This pilot study demonstrated that VM-CBCT can improve rCNR while maintaining a reduced imaging dose relative to the clinical CBCT protocol. The proposed approach has the potential to optimize VM-CBCT image quality while further decreasing imaging dose. Ongoing research will focus on framerate reductions and the application of advanced reconstruction algorithms for VM-CBCT.