Cone-beam x-ray luminescence computed tomography based on x-ray absorption dosage

Area of Science:

• Medical Imaging
• Biomedical Engineering
• Nanotechnology

Background:

• X-ray luminescence computed tomography (XLCT) is a promising hybrid imaging modality using x-ray excitable nanophosphors.
• Cone-beam XLCT (CB-XLCT) offers fast in vivo imaging capabilities.
• Existing XLCT models often overlook the precise x-ray excitation process, assuming light emission based solely on x-ray intensity distribution.

Purpose of the Study:

• To develop an improved imaging model for CB-XLCT that accurately reflects nanophosphor excitation based on x-ray absorption dose.
• To enhance the image quality of CB-XLCT by addressing limitations in current imaging models.
• To improve the reconstruction algorithm for CB-XLCT using a novel imaging model.

Main Methods:

• Proposed a new imaging model for CB-XLCT based on x-ray absorption dose, rather than x-ray intensity.
• Implemented a reconstruction algorithm combining adaptive Tikhonov regularization with the proposed dose-based imaging model.
• Validated the model through numerical simulations and phantom experiments.

Main Results:

• The dose-based model significantly improved CB-XLCT image quality compared to traditional intensity-based models.
• Improvements were observed in target shape, localization accuracy, and image contrast.
• The new model demonstrated enhanced performance in distinguishing closely spaced targets, indicating improved spatial resolution.

Conclusions:

• The proposed dose-based imaging model represents a significant advancement for CB-XLCT.
• This approach enhances critical imaging metrics, offering better diagnostic potential for in vivo applications.
• The findings suggest a more accurate and effective method for CB-XLCT reconstruction and image analysis.