W Harris

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

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.

Accelerating volumetric cine MRI (VC-MRI) using undersampling for real-time 3D target localization/tracking in radiation therapy: a feasibility study

PURPOSE To accelerate volumetric cine MRI (VC-MRI) using undersampled 2D-cine MRI to provide real-time 3D guidance for gating/target tracking in radiotherapy. METHODS 4D-MRI is acquired during patient simulation. One phase of the prior 4D-MRI is selected as the prior images, designated as MRIprior. The on-board VC-MRI at each time-step is considered a deformation of the MRIprior. The deformation field map is represented as a linear combination of the motion components extracted by principal component analysis from the prior 4D-MRI. The weighting coefficients of the motion components are solved by matching the corresponding 2D-slice of the VC-MRI with the on-board undersampled 2D-cine MRI acquired. Undersampled Cartesian and radial k-space acquisition strategies were investigated. The effects of k-space sampling percentage (SP) and distribution, tumor sizes and noise on the VC-MRI estimation were studied. The VC-MRI estimation was evaluated using XCAT simulation of lung cancer patients and data from liver cancer patients. Volume percent difference (VPD) and Center of Mass Shift (COMS) of the tumor volumes and tumor tracking errors were calculated. RESULTS For XCAT, VPD/COMS were 11.93  ±  2.37%/0.90  ±  0.27 mm and 11.53  ±  1.47%/0.85  ±  0.20 mm among all scenarios with Cartesian sampling (SP  =  10%) and radial sampling (21 spokes, SP  =  5.2%), respectively. When tumor size decreased, higher sampling rate achieved more accurate VC-MRI than lower sampling rate. VC-MRI was robust against noise levels up to SNR  =  20. For patient data, the tumor tracking errors in superior-inferior, anterior-posterior and lateral (LAT) directions were 0.46  ±  0.20 mm, 0.56  ±  0.17 mm and 0.23  ±  0.16 mm, respectively, for Cartesian-based sampling with SP  =  20% and 0.60  ±  0.19 mm, 0.56  ±  0.22 mm and 0.42  ±  0.15 mm, respectively, for radial-based sampling with SP  =  8% (32 spokes). CONCLUSIONS It is feasible to estimate VC-MRI from a single undersampled on-board 2D cine MRI. Phantom and patient studies showed that the temporal resolution of VC-MRI can potentially be improved by 5-10 times using a 2D cine image acquired with 10-20% k-space sampling.

TH-EF-BRA-08: A Novel Technique for Estimating Volumetric Cine MRI (VC-MRI) From Multi-Slice Sparsely Sampled Cine Images Using Motion Modeling and Free Form Deformation

PURPOSE To develop a technique to estimate on-board VC-MRI using multi-slice sparsely-sampled cine images, patient prior 4D-MRI, motion-modeling and free-form deformation for real-time 3D target verification of lung radiotherapy. METHODS A previous method has been developed to generate on-board VC-MRI by deforming prior MRI images based on a motion model(MM) extracted from prior 4D-MRI and a single-slice on-board 2D-cine image. In this study, free-form deformation(FD) was introduced to correct for errors in the MM when large anatomical changes exist. Multiple-slice sparsely-sampled on-board 2D-cine images located within the target are used to improve both the estimation accuracy and temporal resolution of VC-MRI. The on-board 2D-cine MRIs are acquired at 20-30frames/s by sampling only 10% of the k-space on Cartesian grid, with 85% of that taken at the central k-space. The method was evaluated using XCAT(computerized patient model) simulation of lung cancer patients with various anatomical and respirational changes from prior 4D-MRI to onboard volume. The accuracy was evaluated using Volume-Percent-Difference(VPD) and Center-of-Mass-Shift(COMS) of the estimated tumor volume. Effects of region-of-interest(ROI) selection, 2D-cine slice orientation, slice number and slice location on the estimation accuracy were evaluated. RESULTS VCMRI estimated using 10 sparsely-sampled sagittal 2D-cine MRIs achieved VPD/COMS of 9.07±3.54%/0.45±0.53mm among all scenarios based on estimation with ROI_MM-ROI_FD. The FD optimization improved estimation significantly for scenarios with anatomical changes. Using ROI-FD achieved better estimation than global-FD. Changing the multi-slice orientation to axial, coronal, and axial/sagittal orthogonal reduced the accuracy of VCMRI to VPD/COMS of 19.47±15.74%/1.57±2.54mm, 20.70±9.97%/2.34±0.92mm, and 16.02±13.79%/0.60±0.82mm, respectively. Reducing the number of cines to 8 enhanced temporal resolution of VC-MRI by 25% while maintaining the estimation accuracy. Estimation using slices sampled uniformly through the tumor achieved better accuracy than slices sampled non-uniformly. CONCLUSIONS Preliminary studies showed that it is feasible to generate VC-MRI from multi-slice sparsely-sampled 2D-cine images for real-time 3D-target verification. This work was supported by the National Institutes of Health under Grant No. R01-CA184173 and a research grant from Varian Medical Systems.

A Novel method to generate on‐board 4D MRI using prior 4D MRI and on‐board kV projections from a conventional LINAC for target localization in liver SBRT

Purpose On‐board MRI can provide superb soft tissue contrast for improving liver SBRT localization. However, the availability of on‐board MRI in clinics is extremely limited. On the contrary, on‐board kV imaging systems are widely available on radiotherapy machines, but its capability to localize tumors in soft tissue is limited due to its poor soft tissue contrast. This study aims to explore the feasibility of using an on‐board kV imaging system and patient prior knowledge to generate on‐board four‐dimensional (4D)‐MRI for target localization in liver SBRT. Methods Prior 4D MRI volumes were separated into end of expiration (EOE) phase (MRIprior) and all other phases. MRIprior was used to generate a synthetic CT at EOE phase (sCTprior). On‐board 4D MRI at each respiratory phase was considered a deformation of MRIprior. The deformation field map (DFM) was estimated by matching DRRs of the deformed sCTprior to on‐board kV projections using a motion modeling and free‐form deformation optimization algorithm. The on‐board 4D MRI method was evaluated using both XCAT simulation and real patient data. The accuracy of the estimated on‐board 4D MRI was quantitatively evaluated using Volume Percent Difference (VPD), Volume Dice Coefficient (VDC), and Center of Mass Shift (COMS). Effects of scan angle and number of projections were also evaluated. Results In the XCAT study, VPD/VDC/COMS among all XCAT scenarios were 10.16 ± 1.31%/0.95 ± 0.01/0.88 ± 0.15 mm using orthogonal‐view 30° scan angles with 102 projections. The on‐board 4D MRI method was robust against the various scan angles and projection numbers evaluated. In the patient study, estimated on‐board 4D MRI was generated successfully when compared to the “reference on‐board 4D MRI” for the liver patient case. Conclusions A method was developed to generate on‐board 4D MRI using prior 4D MRI and on‐board limited kV projections. Preliminary results demonstrated the potential for MRI‐based image guidance for liver SBRT using only a kV imaging system on a conventional LINAC.

TH-EF-BRA-02: A Novel Markerless 4D CBCT Projection Phase Sorting Technique Using Prior Knowledge and Patient Motion Modeling: A Feasibility Study

PURPOSE To investigate the feasibility of a novel marker-less motion-modeling based method for automatic 4D-CBCT projection phase sorting. METHODS Patient on-board image volume at any instant is considered as a deformation of one phase of the prior planning 4D-CT. The deformation field map(DFM) is represented as a linear combination of three major deformation patterns extracted from the planning 4D-CT using principle-component-analysis(PCA). The PCA coefficients are solved for each single projection based on data fidelity constraint, and are used as motion information for phase sorting. Projections at the valleys of the Z direction coefficient are sorted as phase 0/100% and projection phases in between are linearly interpolated. 4D-digital-extended-cardiac-torso(XCAT) phantoms and 3 patient cases were used for evaluation. XCAT phantoms simulated different patient respiratory and anatomical changes from prior 4D-CT to on-board image volume, including changes of tumor size, locations, motion amplitudes and motion directions. Three patient cases include 2 full-fan slow-rotation and one half-fan normal-rotation case. Manual phase sorting based on visual inspection was used as the gold standard. The average absolute phase difference, and the pass rate (percentage of projections sorted within 10% phase error) were used to evaluate sorting accuracy. RESULTS The amplitude of PCA coefficient motion curve correlated with the actual motion amplitude. The algorithm was robust against respiratory and anatomical changes from prior to on-board imaging. For all XCAT cases, the average phase errors were lower than 1.43%, and the pass rate was 100%. The patient data set showed average phase error of 2.47%, 1.90% for full fan slow rotation case and 2.78% for half fan normal rotation case, respectively. The corresponding pass rates were 99.4%, 98.5% and 99.5%, respectively. CONCLUSION Preliminary results demonstrated the robustness and high accuracy of the marker-less PCA based phase sorting algorithm for different patient scenarios and 4D-CBCT scanning protocols.

TU-AB-BRA-09: A Novel Method of Generating Ultrafast Volumetric Cine MRI (VC-MRI) Using Prior 4D-MRI and On-Board Phase-Skipped Encoding Acquisition for Radiotherapy Target Localization

PURPOSE To develop a technique generating ultrafast on-board VC-MRI using prior 4D-MRI and on-board phase-skipped encoding k-space acquisition for real-time 3D target tracking of liver and lung radiotherapy. METHODS The end-of-expiration (EOE) volume in 4D-MRI acquired during the simulation was selected as the prior volume. 3 major respiratory deformation patterns were extracted through the principal component analysis of the deformation field maps (DFMs) generated between EOE and all other phases. The on-board VC-MRI at each instant was considered as a deformation of the prior volume, and the deformation was modeled as a linear combination of the extracted 3 major deformation patterns. To solve the weighting coefficients of the 3 major patterns, a 2D slice was extracted from VC-MRI volume to match with the 2D on-board sampling data, which was generated by 8-fold phase skipped-encoding k-space acquisition (i.e., sample 1 phase-encoding line out of every 8 lines) to achieve an ultrafast 16-24 volumes/s frame rate. The method was evaluated using XCAT digital phantom to simulate lung cancer patients. The 3D volume of end-ofinhalation (EOI) phase at the treatment day was used as ground-truth onboard VC-MRI with simulated changes in 1) breathing amplitude and 2) breathing amplitude/phase change from the simulation day. A liver cancer patient case was evaluated for in-vivo feasibility demonstration. RESULTS The comparison between ground truth and estimated on-board VC-MRI shows good agreements. In XCAT study with changed breathing amplitude, the volume-percent-difference(VPD) between ground-truth and estimated tumor volumes at EOI was 6.28% and the Center-of-Mass-Shift(COMS) was 0.82mm; with changed breathing amplitude and phase, the VPD was 8.50% and the COMS was 0.54mm. The study of liver patient case also demonstrated a promising in vivo feasibility of the proposed method CONCLUSION: Preliminary results suggest the feasibility to estimate ultrafast VC-MRI for on-board target localization with phase skipped-encoding k-space acquisition. Research grant from NIH R01-184173.

TH‐CD‐303‐06: Deformable Registration‐Based Image Estimation Method for 4D CBCT Using Region‐Based PCA

Purpose: To investigate the feasibility of using region-based principal component analysis (PCA) for motion modeling to estimate on-board 4D-CBCT using prior information and 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 this method, each phase of the 4D-CBCT is generated by deforming a prior CT volume. The DFM is solved by a motion modeling based on global PCA and free-form deformation (MM-FD) technique, using data fidelity constraint and the deformation energy minimization. For this study, a new region-based PCA method was developed to optimize the motion-modeling part of the MM-FD technique in order to estimate target delineation more accurately using fewer on-board projection angles. First, the DFMs are estimated using the region-based PCA divides the motion model extracted from planning 4D-CT into two regions: tumor and everything else. The motion model parameters of both regions are optimized together based on data fidelity constraint with relative weighting added to the tumor PCA model. The 4D digital extended cardiac-torso phantom was used to evaluate the region-based PCA MM-FD technique. A lung patient with a 30 mm diameter lesion was simulated with various anatomical and respirational changes from planning 4D CT to onboard volume. The reconstruction 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. Results: For patient scenarios with various shifts of tumor from planning CT to on-board acquisition with 15 degree orthogonal projections, the average VPD/COMS for the MM-FD technique was 5.04%/0.26 mm and 23.23%/2.4mm for region-based and global PCA MM-FD, respectively. Conclusion: The region-based PCA MM-FD technique can potentially further reduces the scan angle needed for onboard 4D CBCT reconstruction for ultra-fast 4D verification. National Institutes of Health Grant No. R01-CA184173 Varian Medical System

TH‐AB‐204‐06: Using Associated Particle Imaging and Time‐Of‐Flight Spectroscopy for Eliminating Tomographic Imaging for NSECT: A Simulation Study

Purpose: To evaluate feasibility of associated particle time-of-flight (AP-TOF) neutron imaging with a fan beam source using simulations in GEANT4 and determine its effect on improving scan time in Neutron Stimulated Emission Computed Tomography (NSECT). Previous NSECT experiments have used a pencil-beam, raster-scanned through the entire volume of interest with long scan durations. A fan beam could reduce the scan duration substantially, improving the clinical feasibility of the technique. Methods: A simulation of fast-neutron AP-TOF NSECT was developed in GEANT4. Fast neutrons that undergo inelastic scattering with elemental nuclei in the phantom lead to prompt gamma emission with energy specific to the emitting element used to identify the emitting elements. In the simulation, a 2-degree wide fan beam of 5 MeV neutrons was swept across a prone water breast phantom containing a cancerous lesion. For each neutron emitted, an alpha particle was coincidently emitted in the opposite direction and was used to determine the neutron’s flight path. The neutron’s time of flight was used to determine the depth of interaction along the flight path. Images were reconstructed for each element in the breast phantom to assess location accuracy with AP-TOF imaging. Results: Images reconstructed from H and Fe showed strong agreement with the locations and geometry of the breast (H-2224 keV) and lesion (Fe-847 keV), with <3% error between the measured and actual locations. Uncertainties in the lateral and axial (i.e., along the beam) directions were determined to arise from uncertainty in the source aperture opening when determining alpha particle location (lateral: 1–2cm) and gamma detection time (axial: 1–2ns). Conclusion: AP-TOF neutron imaging with a pseudo-fan beam is capable of generating clinically relevant images of biological objects without the need for tomographic rotation. With appropriate detection hardware, the ability to eliminate tomographic rotation could reduce NSECT acquisition time by a factor of 8–10.

SU-E-J-26: A Novel Technique for Markerless Self-Sorted 4D-CBCT Using Patient Motion Modeling: A Feasibility Study

Purpose: To develop an automatic markerless 4D-CBCT projection sorting technique by using a patient respiratory motion model extracted from the planning 4D-CT images. Methods: Each phase of onboard 4D-CBCT is considered as a deformation of one phase of the prior planning 4D-CT. The deformation field map (DFM) is represented as a linear combination of three major deformation patterns extracted from the planning 4D-CT using principle component analysis (PCA). The coefficients of the PCA deformation patterns are solved by matching the digitally reconstructed radiograph (DRR) of the deformed volume to the onboard projection acquired. The PCA coefficients are solved for each single projection, and are used for phase sorting. Projections at the peaks of the Z direction coefficient are sorted as phase 1 and other projections are assigned into 10 phase bins by dividing phases equally between peaks. The 4D digital extended-cardiac-torso (XCAT) phantom was used to evaluate the proposed technique. Three scenarios were simulated, with different tumor motion amplitude (3cm to 2cm), tumor spatial shift (8mm SI), and tumor body motion phase shift (2 phases) from prior to on-board images. Projections were simulated over 180 degree scan-angle for the 4D-XCAT. The percentage of accurately binned projections across entire dataset was calculated to represent the phase sorting accuracy. Results: With a changed tumor motion amplitude from 3cm to 2cm, markerless phase sorting accuracy was 100%. With a tumor phase shift of 2 phases w.r.t. body motion, the phase sorting accuracy was 100%. With a tumor spatial shift of 8mm in SI direction, phase sorting accuracy was 86.1%. Conclusion: The XCAT phantom simulation results demonstrated that it is feasible to use prior knowledge and motion modeling technique to achieve markerless 4D-CBCT phase sorting. National Institutes of Health Grant No. R01-CA184173 Varian Medical System

WE-G-BRD-06: Volumetric Cine MRI (VC-MRI) Estimated Based On Prior Knowledge for On-Board Target Localization

Purpose: To develop a technique to generate on-board VC-MRI using patient prior 4D-MRI, motion modeling and on-board 2D-cine MRI for real-time 3D target verification of liver and lung radiotherapy. Methods: The end-expiration phase images of a 4D-MRI acquired during patient simulation are used as patient prior images. Principal component analysis (PCA) is used to extract 3 major respiratory deformation patterns from the Deformation Field Maps (DFMs) generated between end-expiration phase and all other phases. On-board 2D-cine MRI images are acquired in the axial view. The on-board VC-MRI at any instant is considered as a deformation of the prior MRI at the end-expiration phase. The DFM is represented as a linear combination of the 3 major deformation patterns. The coefficients of the deformation patterns are solved by matching the corresponding 2D slice of the estimated VC-MRI with the acquired single 2D-cine MRI. The method was evaluated using both XCAT (a computerized patient model) simulation of lung cancer patients and MRI data from a real liver cancer patient. The 3D-MRI at every phase except end-expiration phase was used to simulate the ground-truth on-board VC-MRI at different instances, and the center-tumor slice was selected to simulate the on-board 2D-cine images. Results: Image subtraction of ground truth with estimated on-board VC-MRI shows fewer differences than image subtraction of ground truth with prior image. Excellent agreement between profiles was achieved. The normalized cross correlation coefficients between the estimated and ground-truth in the axial, coronal and sagittal views for each time step were >= 0.982, 0.905, 0.961 for XCAT data and >= 0.998, 0.911, 0.9541 for patient data. For XCAT data, the maximum-Volume-Percent-Difference between ground-truth and estimated tumor volumes was 1.6% and the maximum-Center-of-Mass-Shift was 0.9 mm. Conclusion: Preliminary studies demonstrated the feasibility to estimate real-time VC-MRI for on-board target localization before or during radiotherapy treatments. National Institutes of Health Grant No. R01-CA184173; Varian Medical System