Simultaneous motion estimation and image reconstruction (SMEIR) for 4D cone-beam CT

Area of Science:

• Medical Imaging
• Image Reconstruction
• Computational Imaging

Background:

• Four-dimensional cone-beam CT (4D-CBCT) is crucial for image-guided radiation therapy, but suffers from artifacts due to sequential image reconstruction and motion estimation.
• Limited projection data in 4D-CBCT degrades image quality and reduces the accuracy of motion modeling, impacting treatment precision.
• Conventional methods often involve separate steps for image reconstruction and motion estimation, leading to suboptimal results.

Purpose of the Study:

• To develop and evaluate a novel strategy for simultaneous motion estimation and image reconstruction (SMEIR) to improve 4D-CBCT.
• To enhance both the image quality of 4D-CBCT and the accuracy of motion model estimation.
• To address limitations of sequential processing in 4D-CBCT.

Main Methods:

• The SMEIR algorithm employs alternating steps of model-based iterative image reconstruction (using SART with total variation minimization) and motion model estimation (DVFs).
• It utilizes projections from all 4D-CBCT phases for reconstructing a motion-compensated primary CBCT (m-pCBCT).
• Performance was evaluated using the 4D NCAT phantom and a lung cancer patient dataset, comparing SMEIR against conventional FDK and TV minimization methods.

Main Results:

• SMEIR significantly improved 4D-CBCT image quality, reducing relative reconstruction error to 7.6% compared to 18.9% (TV) and 32.1% (FDK).
• Tumor motion trajectory estimation accuracy was substantially enhanced, with maximum errors reduced to 0.8, 0.4, and 1.5 mm in L-R, A-P, and S-I directions, respectively.
• Phantom and patient studies demonstrated superior performance of SMEIR over conventional sequential approaches.

Conclusions:

• The SMEIR algorithm effectively integrates motion model estimation and 4D-CBCT reconstruction.
• SMEIR offers improved accuracy in both image reconstruction and tumor motion trajectory estimation.
• This simultaneous approach represents a significant advancement over conventional sequential methods in 4D-CBCT.