Reducing residual‐motion artifacts in iterative 3D CBCT reconstruction in image‐guided radiation therapy

Abstract

Recent evaluations of a 3D iterative cone-beam computed tomography (iCBCT) reconstruction method available on Varian radiation treatment devices demonstrated that iCBCT provides superior image quality when compared to analytical Feldkamp-Davis-Kress (FDK) method. However, iCBCT employs statistical penalized likelihood (PL) that is known to be highly sensitive to inconsistencies due to physiological motion occurring during the acquisition. We propose a computationally inexpensive extension of iCBCT addressing this deficiency. Methods: During the iterative process, the gradients of PL are modified to avoid the generation of motion-related artifacts. To assess the impact of this modification, we propose a motion simulation generating CBCT projections of a moving anatomy together with artifact-free images used as ground truth. Contrast-tonoise ratio and power spectra of difference images are computed to quantify the impact of the motion on reconstructed CBCT volumes as well as the effect of the proposed modification. Results: Using both simulated and clinical data, it is shown that the motion of patient's abdominal wall during the acquisition results in artifacts that can be quantified as low-frequency components in volumes reconstructed with iCBCT. Further, a quantitative evaluation demonstrates that the proposed modification of PL reduces these low-frequency components. While preserving the advantages of PL, it effectively suppresses the propagation of motion-related artifacts into clinically important regions, thus increasing the motion resiliency of iCBCT. Conclusions: The proposed modified iterative reconstruction method significantly improves the quality of CBCT images of anatomies suffering from residual motion.

Mitigation of motion‐induced artifacts in cone beam computed tomography using deep convolutional neural networks

“…Finally, a destination‐driven approach 61 is employed in forward projection (only for ART) and backward projection (both ART and FDK). The method has been discussed 62 as TV‐regularized OS‐SART with momentum as part of the iCBCT algorithm deployed clinically in Varian products.…”

“…The second method, called “average amplitude”, corresponds to a single deformed volume at a fixed time offset matching the average amplitude of the breathing signal. While the motion‐averaged ground truth is used more often in previous research 62 on motion compensation, images based on this method tend to smoothen sharp edges. On the other hand, images based on the average‐amplitude method are able to retain more sharp details.…”

Experimental evaluation of polychromatic reconstruction for quantitative CBCT

“…Similarly to our established iCBCT reconstruction, 7 for RED volume ρ e optimization, we use a penalized likelihood cost function with total variation (TV) regularization 11 with a modified expression for the data-fidelity gradient:…”

“…The polychromatic reconstruction pipeline is a natural extension of our iCBCT reconstruction pipeline, which is a two-pass approach. 7 In the first pass of the iCBCT pipeline, the initial HU volume is reconstructed with algebraic reconstruction technique (ART) from fASKS 15 scatter-corrected projections. In the second pass, the initial volume is further refined with statistical reconstruction based on penalized maximum likelihood (PL) using projection images scatter-corrected with Acuros ® CTS.…”

“…This concept is at the core of polychromatic reconstruction algorithms in the literature. [1][2][3][4][5][6] To directly reconstruct RED volumes, we expanded our non-clinical iterative CBCT (iCBCT) 7 reconstruction pipeline (iTools Reconstruction, Varian Medical Systems, Palo Alto, CA, USA) by implementing a polychromatic forward projection that maps RED volume to intensities in projection space, as described by Mason et al 4,5 The core component of the polychromatic forward projection is a piecewise linear approximation of the relation between polychromatic attenuation coefficients and RED values fitted for different materials. Together with an energy-resolved air norm, this polychromatic attenuation model accounts for beam hardening by construction.…”