2D antiscatter grid and scatter sampling based CBCT pipeline for image guided radiation therapy

Area of Science:

• Medical Physics
• Radiological Imaging
• Radiation Oncology

Background:

• Cone-beam CT (CBCT) has limitations in tissue visualization and quantitative accuracy, hindering its use beyond target localization in radiation therapy.
• Improving CBCT image quality is crucial for quantitative treatment monitoring and adaptive radiotherapy.

Approach:

• Developed quantitative CBCT (qCBCT) by integrating a 2D antiscatter grid with a raw data processing pipeline and iterative image reconstruction.
• Implemented corrections for residual scatter, image lag, and beam hardening, specifically for offset detector geometry CBCT with a bow tie filter.
• Utilized iterative reconstruction to minimize image noise and enhance image quality.

Key Points:

• qCBCT demonstrated reduced HU degradation (10 HU for image lag, 40 HU for beam hardening) compared to standard CBCT.
• Mean HU errors in qCBCT (10 HU) were significantly lower than in clinical CBCT (27 HU) when benchmarked against MDCT.
• Inaccuracy in HU values due to phantom size changes was substantially reduced in qCBCT (22 HU) versus clinical CBCT (85 HU).
• Iterative reconstruction improved contrast-to-noise ratio by 1.25x compared to clinical CBCT protocols.

Conclusions:

• qCBCT significantly reduces artifacts and noise, narrowing the image quality gap between CBCT and MDCT.
• The enhanced quantitative accuracy of qCBCT supports its use in demanding applications like CBCT-based dose calculations and treatment response assessment in image-guided radiation therapy.