Estimating 4D-CBCT from prior information and extremely limited angle projections using structural PCA and weighted free-form deformation for lung radiotherapy

Abstract

Purpose: To investigate the feasibility of using structural-based principal component analysis (PCA) motion-modeling and weighted free-form deformation to estimate on-board 4D-CBCT using prior information and extremely limited angle projections for potential 4D target verification of lung radiotherapy.

Methods: A technique for lung 4D-CBCT reconstruction has been previously developed using a deformation field map (DFM)-based strategy. In the previous method, each phase of the 4D-CBCT was generated by deforming a prior CT volume. The DFM was solved by a motion model extracted by a global PCA and free-form deformation (GMM-FD) technique, using a data fidelity constraint and deformation energy minimization. In this study, a new structural PCA method was developed to build a structural motion model (SMM) by accounting for potential relative motion pattern changes between different anatomical structures from simulation to treatment. The motion model extracted from planning 4DCT was divided into two structures: tumor and body excluding tumor, and the parameters of both structures were optimized together. Weighted free-form deformation (WFD) was employed afterwards to introduce flexibility in adjusting the weightings of different structures in the data fidelity constraint based on clinical interests. XCAT (computerized patient model) simulation with a 30 mm diameter lesion was simulated with various anatomical and respiratory changes from planning 4D-CT to on-board volume to evaluate the method. The estimation accuracy was evaluated by the volume percent difference (VPD)/center-of-mass-shift (COMS) between lesions in the estimated and "ground-truth" on-board 4D-CBCT. Different on-board projection acquisition scenarios and projection noise levels were simulated to investigate their effects on the estimation accuracy. The method was also evaluated against three lung patients.

Results: The SMM-WFD method achieved substantially better accuracy than the GMM-FD method for CBCT estimation using extremely small scan angles or projections. Using orthogonal 15° scanning angles, the VPD/COMS were 3.47 ± 2.94% and 0.23 ± 0.22 mm for SMM-WFD and 25.23 ± 19.01% and 2.58 ± 2.54 mm for GMM-FD among all eight XCAT scenarios. Compared to GMM-FD, SMM-WFD was more robust against reduction of the scanning angles down to orthogonal 10° with VPD/COMS of 6.21 ± 5.61% and 0.39 ± 0.49 mm, and more robust against reduction of projection numbers down to only 8 projections in total for both orthogonal-view 30° and orthogonal-view 15° scan angles. SMM-WFD method was also more robust than the GMM-FD method against increasing levels of noise in the projection images. Additionally, the SMM-WFD technique provided better tumor estimation for all three lung patients compared to the GMM-FD technique.

Conclusion: Compared to the GMM-FD technique, the SMM-WFD technique can substantially improve the 4D-CBCT estimation accuracy using extremely small scan angles and low number of projections to provide fast low dose 4D target verification.

Keywords: 4D CBCT; free-form deformation; limited angle; motion modeling.

Figure 1

Comparison of CBCT _prior at end‐expiration phase, ground‐truth CBCT (CBCT_GT ) at end‐inspiration phase, estimated CBCT using global MM (CBCT_GMM ) and estimated CBCT using structural MM (CBCT_SMM ) using orthogonal‐view 15° scan angle with 52 projections for (a) XCAT scenario 5, (b) XCAT scenario 6, and (c) XCAT scenario 8. [Colour figure can be viewed at wileyonlinelibrary.com]

Figure 2

Subtraction images for axial, coronal, and sagittal images shown in Fig. 1(a), (b), and (c), respectively.

Figure 3

This is an example of the ROI selected within a projection image. The weightings would be applied everywhere inside the ROI within the data fidelity constraint of the free‐form deformation model. [Colour figure can be viewed at wileyonlinelibrary.com]

Figure 4

Comparison of CBCT _prior at end‐expiration phase, ground‐truth CBCT (CBCT_GT ) at end‐inspiration phase, estimated CBCT using global MMFD (CBCT_GMMFD ) and estimated CBCT using structure MM‐WFD (CBCT_{SMM ‐ WFD} ) using orthogonal‐view 15° projection acquisition with 52 projections for (a) XCAT scenario 5, (b) XCAT scenario 6, and (c) XCAT scenario 8. [Colour figure can be viewed at wileyonlinelibrary.com]

Figure 5

Subtraction images for axial, coronal and sagittal images shown in Fig. 4(a), (b), and (c), respectively.

Figure 6

Visual comparison of the same projection images for XCAT scenario 2. The arrows indicate the level of noise in the bony region of the projection images. The noise level gradually increased from left to right: (a) No noise, (b) Poisson noise, (c) Poisson noise + normal(0, 10), (d) Poisson noise + normal(0, 50), and (e) Poisson noise + normal(0, 100). [Colour figure can be viewed at wileyonlinelibrary.com]

Figure 7

Patient image results for patient 1 (P1), patient 2 (P2), and patient 3 (P3). ‘CT_{P rior}’ image refers to the end‐expiration phase image of the 4D‐CT, ‘Clinical CBCT’ image refers to the CBCT image reconstructed with 200° projections using FDK in the end‐expiration phase, ‘GMM‐FD’ image refers to the end‐expiration phase CBCT image reconstructed with 10° orthogonal scan angles using the GMM‐FD technique, and ‘SMM‐WFD’ image refers to the end‐expiration phase CBCT image reconstructed with 10° orthogonal scan angles using the SMM‐WFD technique. The arrows and horizontal line provide references for evaluating the tumor volume differences in the images. [Colour figure can be viewed at wileyonlinelibrary.com]

Figure 8

Data fidelity errors of the GMM‐FD and SMM‐WFD techniques for image estimation of XCAT scenario 8 using orthogonal‐view 15° scan angle with 52 projections. The dashed line shows where the motion modeling optimization converges, and where the free‐form deformation starts. The data fidelity error was calculated within the ROI around the tumor in the projection data. [Colour figure can be viewed at wileyonlinelibrary.com]

Figure 9

CT _prior and sample on‐board CBCT projection image for the XCAT simulation with a tumor in the upper lobe of the left lung.