NURBS-based Cardiac-torso Phantom Research Articles

Bilateral filtering based sliding motion compensated 4D-CBCT: a simulation study

Objective This study reconstructed 4D-CBCT for fully automatic compensated sliding motion by incorporating the bilateral filtering into the Deformable Vector Field (DVF). Methods First, a motion compensated simultaneous algebraic reconstruction technique (Modified Simultaneous Algebra Reconstruction Technique, mSART) was used to generate a high quality reference phase by using all phase projection stogether with the initial 4D-DVFs, which were generated via Demons registration between 0% phase and each other phaseimage. The 4D-DVF was optimized by matching the forward projection of the deformed 0% phase with the measured projection of the target phase. The loss function’s DVF smoothing constrain term contained bilateral filtering kernel that contained: 1) an spatial domain Guassian kernel; 2) animage intensity domain Guassian kernel; and 3) a DVF domain Guassian kernel. By choosing suitable kernel variances, the sliding motion can be extracted. A non-linear conjugate gradient optimizer wasused. We validated the algorithm on a Non-Uniform Rotational B-spline based Cardiac-Torso (NCAT) phantom. Quantification was evaluated by: 1) the Root-Mean-Square-Error (RMSE) together with the Maximum-Error (MaxE); 2) the Dice coefficient of the extracted lung contour from the final reconstructed images and 3) the relative reconstruction error (RE) to evaluate the algorithm’s performance. Results The motion trajectory’s RMSE/MaxEare 0.796/1.02 mm for bilateral filtering reconstruction; and 2.704/4.08 mm for original reconstruction. Image content such a stherib position, the hearted gedefinition, the fibrous structures all had been better corrected with bilateral filtering. Conclusion We developed a bilateral filtering based fully automatic sliding motion compensated 4D-CBCT scheme. Digital phantom study confirmed the improved motion estimation and image reconstruction ability. It can be used as a 4D-CBCT image guidance tool for lung SBRT treatment. 摘要： 目的 将双边滤波引入基于可变形矢量场 (DVF) 的 4D-CBCT 重建, 实现全自动滑动运动补偿 4D-CBCT 重 建。 方法 首先利用所有相位投影, 用改良的运动补偿瞬时代数重建技术 (Modified Simultaneous Algebra Reconstruction Technique, mSART) 生成高质 量参考相位。初始 4D-DVF 通过 0% 相位和其他相位图像依次配准生成。之后通过 配准目标相位测量投影和参考相位变形到目标相位后的正投来优化求解 4D-DVF。优化过程中的损失函数平滑约束 项中引入双边滤波。其包含 3 个子核:空间域 Guassian 核; 图像强度域 Guassian 核; 和 DVF 域 Guassian 核。选择合适 的子核方差提取滑动运动, 采用非线性共轭梯度算子优化, 用 B 样条心脏躯干体模 (NURBS-based Cardiac-Torso phantom, NCAT phantom) 验证算法。采用量化评价指标: Root-Mean-Square-Error (RMSE) 和最大误差 (MaxE); 重建图 像提取的肺轮廓 Dice 系数和相对重建误差 (RE) 评价算法性能。 结果 NCAT 模体的双边滤波重建运动轨迹的 RMSE/MaxE 为 0.796/1.02 mm; 原始重建方法的相应结果为 2.704/4.08 mm。图像中的特定结构如肋骨位置, 心脏边缘 的定义, 纤维结构通过双边过滤都得到了更好的纠正。 结论 开发了一种基于双边滤波的全自动滑动运动补偿 4D-CBCT 方案, 数字模体研宄证实了改进的运动估计和图像重建能力, 其可被用作肺 SBRT 治疗的 4D-CBCT 图像引 导工具。

Attenuation correction in single-photon emission computed tomography for NURBS-based cardiac-torso phantom using dual-energy acquisition.

Single photon emission tomography is widely used to detect photons emitted from the patient. Some of these emitted photons suffer from scattering and absorption because of the attenuation occurred through their path in patient's body. Therefore, the attenuation is the most important problem in single-photon emission computed tomography (SPECT) imaging. Some of the radioisotopes emit gamma rays in different energy levels, and consequently, they have different counts and attenuation coefficients. Calculation of the parameters used in the attenuation equation Nout=αNin = e−μl Nin by mathematical methods is useful for the attenuation correction. Nurbs-based cardiac-torso (NCAT) phantom with an adequate attenuation coefficient and activity distribution is used in this study. Simulations were done using SimSET in 20–70 and 20–167 keV. A total of 128 projections were acquired over 360°. The corrected and reference images were compared using a universal image quality index (UIQI). The simulation repeated using NCAT phantom by SimSET. In the first group, no attenuation correction was used, but the Zubal coefficients were used for attenuation correction in the second image group. After the image reconstruction, a comparison between image groups was done using optimized UIQI to determine the quality of used reconstruction methods. Similarities of images were investigated by considering the average sinogram for every block size. The results showed that the proposed method improved the image quality. This study showed that simulation studies are useful tools in the investigation of nuclear medicine researches. We produced a nonattenuated model using Monte Carlo simulation method and compared it with an attenuated model. The proposed reconstruction method improved image resolution and contrast. Regional and general similarities of images could be determined, respectively, from acquired UIQI of small and large block sizes. Resulted curves from both small and large block sizes showed a good similarity between reconstructed and ideal images.

Feasibility of using Medical Imaging Interaction Toolkit in volumetric studies to accurate diagnosing of vascular emboli by Extended NURBS-based Cardiac-Torso phantom

Introduction: Important complications of venous thromboembolism (VTE) are a longer hospital stay, readmission, recurrence of the emboli, complications of anticoagulant therapy and death in a sever condition. In present study, the volume measurement accuracy of the medical imaging interaction toolkit (MITK) software on determining VTE in computed tomography images was evaluated. Methods: Several VTEs, ranged from 0.1 to 20 mm, were simulated in the arteries of a XCAT Phantom. Then, the MITK software was used for localization and volume measurement of the produced VTEs on the images of the simulated phantom. Results: The scatter plot and correlation coefficient were showed a high correlation between the calculated emboli volume measures by MITK software with those designed in the XCAT Phantom (r=0.98; p<0.001), The differences of the calculated measures and the simulated clots were mostly related to the clot volumes less than 0.1 ml (mainly due to the inability of the software to measure the range), which may be clinically ignored. However, a difference of about 0.01 ml for the clot volumes greater than 0.1 ml was in acceptable range. Conclusion: MITK software may be used for volume measurement studies in medical diagnosis, also for VTE accurate measurement to achieve a more accurate diagnosis and to eliminate the need to onsite diagnosis by the imaging system due to MITK capability on running in a personal computer.

TH-CD-207A-03: A Surface Deformation Driven Respiratory Model for Organ Motion Tracking in Lung Cancer Radiotherapy

Purpose: To propose and validate a novel real-time surface-mesh-based internal organ-external surface motion and deformation tracking method for lung cancer radiotherapy. Methods: Deformation vector fields (DVFs) which characterizes the internal and external motion are obtained by registering the internal organ and tumor contours and external surface meshes to a reference phase in the 4D CT images using a recent developed local topology preserved non-rigid point matching algorithm (TOP). A composite matrix is constructed by combing the estimated internal and external DVFs. Principle component analysis (PCA) is then applied on the composite matrix to extract principal motion characteristics and finally yield the respiratory motion model parameters which correlates the internal and external motion and deformation. The accuracy of the respiratory motion model is evaluated using a 4D NURBS-based cardiac-torso (NCAT) synthetic phantom and three lung cancer cases. The center of mass (COM) difference is used to measure the tumor motion tracking accuracy, and the Dice's coefficient (DC), percent error (PE) and Housdourf's distance (HD) are used to measure the agreement between the predicted and ground truth tumor shape. Results: The mean COM is 0.84±0.49mm and 0.50±0.47mm for the phantom and patient data respectively. The mean DC, PE and HD are 0.93±0.01, 0.13±0.03 and 1.24±0.34 voxels for the phantom, and 0.91±0.04, 0.17±0.07 and 3.93±2.12 voxels for the three lung cancer patients, respectively. Conclusions: We have proposed and validate a real-time surface-mesh-based organ motion and deformation tracking method with an internal-external motion modeling. The preliminary results conducted on a synthetic 4D NCAT phantom and 4D CT images from three lung cancer cases show that the proposed method is reliable and accurate in tracking both the tumor motion trajectory and deformation, which can serve as a potential tool for real-time organ motion and deformation monitoring in lung cancer radiotherapy. This work is supported in part by grant from VARIAN MEDICAL SYSTEMS INC, the National Natural Science Foundation of China (no 81428019 and no 81301940), the Guangdong Natural Science Foundation (2015A030313302)and the 2015 Pearl River S&T Nova Program of Guangzhou (201506010096).

Patient motion effects on the quantification of regional myocardial blood flow with dynamic PET imaging.

Patient motion is a common problem during dynamic positron emission tomography (PET) scans for quantification of myocardial blood flow (MBF). The purpose of this study was to quantify the prevalence of body motion in a clinical setting and evaluate with realistic phantoms the effects of motion on blood flow quantification, including CT attenuation correction (CTAC) artifacts that result from PET-CT misalignment. A cohort of 236 sequential patients was analyzed for patient motion under resting and peak stress conditions by two independent observers. The presence of motion, affected time-frames, and direction of motion was recorded; discrepancy between observers was resolved by consensus review. Based on these results, patient body motion effects on MBF quantification were characterized using the digital NURBS-based cardiac-torso phantom, with characteristic time activity curves (TACs) assigned to the heart wall (myocardium) and blood regions. Simulated projection data were corrected for attenuation and reconstructed using filtered back-projection. All simulations were performed without noise added, and a single CT image was used for attenuation correction and aligned to the early- or late-frame PET images. In the patient cohort, mild motion of 0.5 ± 0.1 cm occurred in 24% and moderate motion of 1.0 ± 0.3 cm occurred in 38% of patients. Motion in the superior/inferior direction accounted for 45% of all detected motion, with 30% in the superior direction. Anterior/posterior motion was predominant (29%) in the posterior direction. Left/right motion occurred in 24% of cases, with similar proportions in the left and right directions. Computer simulation studies indicated that errors in MBF can approach 500% for scans with severe patient motion (up to 2 cm). The largest errors occurred when the heart wall was shifted left toward the adjacent lung region, resulting in a severe undercorrection for attenuation of the heart wall. Simulations also indicated that the magnitude of MBF errors resulting from motion in the superior/inferior and anterior/posterior directions was similar (up to 250%). Body motion effects were more detrimental for higher resolution PET imaging (2 vs 10 mm full-width at half-maximum), and for motion occurring during the mid-to-late time-frames. Motion correction of the reconstructed dynamic image series resulted in significant reduction in MBF errors, but did not account for the residual PET-CTAC misalignment artifacts. MBF bias was reduced further using global partial-volume correction, and using dynamic alignment of the PET projection data to the CT scan for accurate attenuation correction during image reconstruction. Patient body motion can produce MBF estimation errors up to 500%. To reduce these errors, new motion correction algorithms must be effective in identifying motion in the left/right direction, and in the mid-to-late time-frames, since these conditions produce the largest errors in MBF, particularly for high resolution PET imaging. Ideally, motion correction should be done before or during image reconstruction to eliminate PET-CTAC misalignment artifacts.

The development and initial evaluation of a realistic simulated SPECT dataset with simultaneous respiratory and cardiac motion for gated myocardial perfusion SPECT

We developed a realistic simulation dataset for simultaneous respiratory and cardiac (R&C) gated SPECT/CT using the 4D NURBS-based Cardiac-Torso (NCAT) Phantom and Monte Carlo simulation methods, and evaluated it for a sample application study. The 4D NCAT phantom included realistic respiratory motion and beating heart motion based on respiratory gated CT and cardiac tagged MRI data of normal human subjects. To model the respiratory motion, a set of 24 separate 3D NCAT phantoms excluding the heart was generated over a respiratory cycle. The beating heart motion was modeled separately with 48 frames per cardiac cycle for each of the 24 respiratory phases. The resultant set of 24 × 48 3D NCAT phantoms provides a realistic model of a normal human subject at different phases of combined R&C motions. An almost noise-free SPECT projection dataset for each of the 1152 3D NCAT phantoms was generated using Monte Carlo simulation techniques and the radioactivity uptake distribution of 99mTc sestamibi in different organs. By grouping and summing the separate projection datasets, separate or simultaneous R&C gated acquired data with different gating schemes could be simulated. In the initial evaluation, we combined the projection datasets into ungated, 6 respiratory-gates only, 8 cardiac-gates only, and combined 6 respiratory-gates & 8 cardiac-gates projection datasets. Each dataset was reconstructed using 3D OS-EM without and with attenuation correction using the averaged and respiratory-gated attenuation maps, and the resulting reconstructed images were compared. These results were used to demonstrate the effects of R&C motions and the reduction of image artifact due to R&C motions by gating and attenuation corrections. We concluded that the realistic 4D NCAT phantom and Monte Carlo simulated SPECT projection datasets with R&C motions are powerful tools in the study of the effects of R&C motions, as well as in the development of R&C gating schemes and motion correction methods for improved SPECT/CT imaging.

Development and evaluation of convergent and accelerated penalized SPECT image reconstruction methods for improved dose-volume histogram estimation in radiopharmaceutical therapy.

Three-dimensional (3D) dosimetry has the potential to provide better prediction of response of normal tissues and tumors and is based on 3D estimates of the activity distribution in the patient obtained from emission tomography. Dose-volume histograms (DVHs) are an important summary measure of 3D dosimetry and a widely used tool for treatment planning in radiation therapy. Accurate estimates of the radioactivity distribution in space and time are desirable for accurate 3D dosimetry. The purpose of this work was to develop and demonstrate the potential of penalized SPECT image reconstruction methods to improve DVHs estimates obtained from 3D dosimetry methods. The authors developed penalized image reconstruction methods, using maximum a posteriori (MAP) formalism, which intrinsically incorporate regularization in order to control noise and, unlike linear filters, are designed to retain sharp edges. Two priors were studied: one is a 3D hyperbolic prior, termed single-time MAP (STMAP), and the second is a 4D hyperbolic prior, termed cross-time MAP (CTMAP), using both the spatial and temporal information to control noise. The CTMAP method assumed perfect registration between the estimated activity distributions and projection datasets from the different time points. Accelerated and convergent algorithms were derived and implemented. A modified NURBS-based cardiac-torso phantom with a multicompartment kidney model and organ activities and parameters derived from clinical studies were used in a Monte Carlo simulation study to evaluate the methods. Cumulative dose-rate volume histograms (CDRVHs) and cumulative DVHs (CDVHs) obtained from the phantom and from SPECT images reconstructed with both the penalized algorithms and OS-EM were calculated and compared both qualitatively and quantitatively. The STMAP method was applied to patient data and CDRVHs obtained with STMAP and OS-EM were compared qualitatively. The results showed that the penalized algorithms substantially improved the CDRVH and CDVH estimates for large organs such as the liver compared to optimally postfiltered OS-EM. For example, the mean squared errors (MSEs) of the CDRVHs for the liver at 5 h postinjection obtained with CTMAP and STMAP were about 15% and 17%, respectively, of the MSEs obtained with optimally filtered OS-EM. For the CDVH estimates, the MSEs obtained with CTMAP and STMAP were about 16% and 19%, respectively, of the MSEs from OS-EM. For the kidneys and renal cortices, larger residual errors were observed for all algorithms, likely due to partial volume effects. The STMAP method showed promising qualitative results when applied to patient data. Penalized image reconstruction methods were developed and evaluated through a simulation study. The study showed that the MAP algorithms substantially improved CDVH estimates for large organs such as the liver compared to optimally postfiltered OS-EM reconstructions. For small organs with fine structural detail such as the kidneys, a large residual error was observed for both MAP algorithms and OS-EM. While CTMAP provided marginally better MSEs than STMAP, given the extra effort needed to handle misregistration of images at different time points in the algorithm and the potential impact of residual misregistration, 3D regularization methods, such as that used in STMAP, appear to be a more practical choice.

An Initial Study for PET Imaging Simulation

Simulation play an important role in the research of PET/CT imaging technology. In this paper, GATE (Geant4 Application Tomography Emission) software packages and NCAT(dynamic NURBS-based cardiac-torso phantom) were used to simulate GE ST PET/CT imaging. GATE provides abundant of functions to simulate both PET/CT imaging procedure and geometric phantom generation. NCAT can generate voxlised body torso phantom. Three different kinds of digital phantoms were designed and generated for PET/CT imaging simulation. The simulation output of GATE was converted to the data format that the STIR (Software for Tomographic Image Reconstruction) requires to reconstruct image by the OSEM (ordered subsets expectation-maximization) algorithm. The experiment results validate that GATE and NCAT are able to simulate PET/CT imaging.

Dual energy CT for attenuation correction with PET/CT

The authors evaluate the energy dependent noise and bias properties of monoenergetic images synthesized from dual-energy CT (DECT) acquisitions. These monoenergetic images can be used to estimate attenuation coefficients at energies suitable for positron emission tomography (PET) and single-photon emission computed tomography (SPECT) imaging. This is becoming more relevant with the increased use of quantitative imaging by PET/CT and SPECT/CT scanners. There are, however, potential variations in the noise and bias of synthesized monoenergetic images as a function of energy. The authors used analytic approximations and simulations to estimate the noise and bias of synthesized monoenergetic images of water-filled cylinders with different shapes and the NURBS-based cardiac-torso (NCAT) phantom from 40 to 520 keV, the range of SPECT and PET energies. The dual-kVp spectra were based on the GE Lightspeed VCT scanner at 80 and 140 kVp with added filtration of 0.5 mm Cu. The authors evaluated strategies of noise suppression with sinogram smoothing and dose minimization with reduction of tube currents at the two kVp settings. The authors compared the impact of DECT-based attenuation correction with single-kVp CT-based attenuation correction on PET quantitation for the NCAT phantom for soft tissue and high-Z materials of bone and iodine contrast enhancement. Both analytic calculations and simulations displayed the expected minimum noise value for a synthesized monoenergetic image at an energy between the mean energies of the two spectra. In addition the authors found that the normalized coefficient of variation in the synthesized attenuation map increased with energy but reached a plateau near 160 keV, and then remained constant with increasing energy up to 511 keV and beyond. The bias was minimal, as the linear attenuation coefficients of the synthesized monoenergetic images were within 2.4% of the known true values across the entire energy range. Compared with no sinogram smoothing, sinogram smoothing can dramatically reduce noise in the DECT-derived attenuation map. Through appropriate selection of tube currents for high and low kVp scans, DECT can deliver roughly the same amount of radiation dose as that of a single kVp CT scan, but could be used for PET attenuation correction with reduced bias in contrast agent regions by a factor of ≈ 2.6 and slightly reduced RMSE for the total image. When DECT is used for attenuation correction at higher energies, there is a noise amplification that is dependent on the energy of the synthesized monoenergetic image of linear attenuation coefficients. Sinogram smoothing reduces the noise amplification in DECT-derived attenuation maps without increasing bias. With an appropriate selection of CT techniques, a DECT scan with the same radiation dose as a single CT scan can result in a PET image with improved quantitative accuracy.

Four‐dimensional cone beam CT reconstruction and enhancement using a temporal nonlocal means method

Four-dimensional cone beam computed tomography (4D-CBCT) has been developed to provide respiratory phase-resolved volumetric imaging in image guided radiation therapy. Conventionally, it is reconstructed by first sorting the x-ray projections into multiple respiratory phase bins according to a breathing signal extracted either from the projection images or some external surrogates, and then reconstructing a 3D CBCT image in each phase bin independently using FDK algorithm. This method requires adequate number of projections for each phase, which can be achieved using a low gantry rotation or multiple gantry rotations. Inadequate number of projections in each phase bin results in low quality 4D-CBCT images with obvious streaking artifacts. 4D-CBCT images at different breathing phases share a lot of redundant information, because they represent the same anatomy captured at slightly different temporal points. Taking this redundancy along the temporal dimension into account can in principle facilitate the reconstruction in the situation of inadequate number of projection images. In this work, the authors propose two novel 4D-CBCT algorithms: an iterative reconstruction algorithm and an enhancement algorithm, utilizing a temporal nonlocal means (TNLM) method. The authors define a TNLM energy term for a given set of 4D-CBCT images. Minimization of this term favors those 4D-CBCT images such that any anatomical features at one spatial point at one phase can be found in a nearby spatial point at neighboring phases. 4D-CBCT reconstruction is achieved by minimizing a total energy containing a data fidelity term and the TNLM energy term. As for the image enhancement, 4D-CBCT images generated by the FDK algorithm are enhanced by minimizing the TNLM function while keeping the enhanced images close to the FDK results. A forward-backward splitting algorithm and a Gauss-Jacobi iteration method are employed to solve the problems. The algorithms implementation on GPU is designed to avoid redundant and uncoalesced memory access, in order to ensure a high computational efficiency. Our algorithms have been tested on a digital NURBS-based cardiac-torso phantom and a clinical patient case. The reconstruction algorithm and the enhancement algorithm generate visually similar 4D-CBCT images, both better than the FDK results. Quantitative evaluations indicate that, compared with the FDK results, our reconstruction method improves contrast-to-noise-ratio (CNR) by a factor of 2.56-3.13 and our enhancement method increases the CNR by 2.75-3.33 times. The enhancement method also removes over 80% of the streak artifacts from the FDK results. The total computation time is 509-683 s for the reconstruction algorithm and 524-540 s for the enhancement algorithm on an NVIDIA Tesla C1060 GPU card. By innovatively taking the temporal redundancy among 4D-CBCT images into consideration, the proposed algorithms can produce high quality 4D-CBCT images with much less streak artifacts than the FDK results, in the situation of inadequate number of projections.

Comparison study of temporal regularization methods for fully 5D reconstruction of cardiac gated dynamic SPECT

Temporal regularization plays a critical role in cardiac gated dynamic SPECT reconstruction, of which the goal is to obtain an image sequence from a single acquisition which simultaneously shows both cardiac motion and tracer distribution change over the course of imaging (termed 5D). In our recent work, we explored two different approaches for temporal regularization of the dynamic activities in gated dynamic reconstruction without the use of fast camera rotation: one is the dynamic EM (dEM) approach which is imposed on the temporal trend of the time activity of each voxel, and the other is a B-spline modeling approach in which the time activity is regulated by a set of B-spline basis functions. In this work, we extend the B-spline approach to fully 5D reconstruction and conduct a thorough quantitative comparison with the dEM approach. In the evaluation of the reconstruction results, we apply a number of quantitative measures on two major aspects of the reconstructed dynamic images: (1) the accuracy of the reconstructed activity distribution in the myocardium and (2) the ability of the reconstructed dynamic activities to differentiate perfusion defects from normal myocardial wall uptake. These measures include the mean square error (MSE), bias-variance analysis, accuracy of time-activity curves (TAC), contrast-to-noise ratio of a defect, composite kinetic map of the left ventricle wall and perfusion defect detectability with channelized Hotelling observer. In experiments, we simulated cardiac gated imaging with the NURBS-based cardiac-torso phantom and Tc99m-Teboroxime as the imaging agent, where acquisition with the equivalent of only three full camera rotations was used during the imaging period. The results show that both dEM and B-spline 5D could achieve similar overall accuracy in the myocardium in terms of MSE. However, compared to dEM 5D, the B-spline approach could achieve a more accurate reconstruction of the voxel TACs; in particular, B-spline 5D could achieve a much smaller bias level in the early uptake stage of the imaging period. Furthermore, it could allow better separation of the perfusion defect from the normal at both the early and the late stages of the imaging period.

A quantitative study of motion estimation methods on 4D cardiac gated SPECT reconstruction.

Motion-compensated temporal processing can have a major impact on improving the image quality in gated cardiac single photon emission computed tomography (SPECT). In this work, we investigate the effect of different optical flow estimation methods for motion-compensated temporal processing in gated SPECT. In particular, we explore whether better motion estimation can substantially improve reconstructed image quality, and how the estimated motion would compare to the ideal case of known motion in terms of reconstruction. We consider the following three methods for obtaining the image motion in 4D reconstruction: (1) the Horn-Schunck optical flow equation (OFE) method, (2) a recently developed periodic OFE method, and (3) known cardiac motion derived from the NURBS-based cardiac-torso (NCAT) phantom. The periodic OFE method is used to exploit the inherent periodic nature in cardiac gated images. In this method, the optical flow in a sequence is modeled by a Fourier harmonic representation, which is then estimated from the image data. We study the impact of temporal processing on 4D reconstructions when the image motion is obtained with the different methods above. For quantitative evaluation, we use simulated imaging with multiple noise realizations from the NCAT phantom, where different patient geometry and lesion sizes are also considered. To quantify the reconstruction results, we use the following measures of reconstruction accuracy and defect detection in the myocardium: (1) overall error level in the myocardium, (2) regional accuracy of the left ventricle (LV) wall, (3) accuracy of regional time activity curves of the LV, and (4) perfusion defect detectability with a channelized Hotelling observer (CHO). In addition, we also examine the effect of noise on the distortion in the reconstructed LV wall shape by detecting its contours. As a preliminary demonstration, these methods are also tested on two sets of clinical acquisitions. For the different quantitative measures considered, the periodic OFE further improved the reconstruction accuracy of the myocardium compared to OFE in 4D reconstruction; its improvement in reconstruction almost matched that of the known motion. Specifically, the overall mean-squared error in the myocardium was reduced by over 20% with periodic OFE; with noise level fixed at 10%, the regional bias on the LV was reduced from 20% (OFE) to 14% (periodic OFE), compared to 11% by the known motion. In addition, the CHO results show that there was also improvement in lesion detectability with the periodic OFE. The regional time activity curves obtained with the periodic OFE were also observed to be more consistent with the reference; in addition, the contours of the reconstructed LV wall with the periodic OFE were demonstrated to show less degree of variations among different noise realizations. Such improvements were also consistent with the results obtained from the clinical acquisitions. Use of improved optical flow estimation can further improve the accuracy of reconstructed images in 4D. The periodic OFE method not only can achieve improvements over the traditional OFE, but also can almost match that of the known motion in terms of the several quality measures considered.

TU-E-BRA-09: Evaluation of a Patient-Specific Respiratory Motion Model in Thoracic and Abdominal Phantom and Patient CT Images.

We have previously described a model of patient-specific respiratory motion to predict organ deformations without assuming repeatable breath cycles. The model is derived from deformable image registration (DIR) between respiration-correlated images (RCCT), followed by a principal component analysis (PCA) which relates the first two principal components of 3D deformations to the position and direction of motion of the diaphragm or implanted fiducials. This study examines model accuracy in phantom and patient images. We compare model and DIR accuracy using 3 types of image sets, each exhibiting different deformation patterns: (1) synthetic images in lung and abdomen from the 4D NURBS-based cardiac torso (NCAT) phantom with known deformations; (2) CT scans of physical deformable phantom with implanted markers in liver; and (3) liver structures in patient RCCT images using rigid registration in a small VOI as approximate ground truth. The model is calibrated by applying fast free-form DIR between a reference image set at end expiration and each of the other images at different motion states, defined by diaphragm or, in some patient cases, implanted fiducials as surrogate signals. Following PCA, the first two principal components are selected to yield a model-predicted displacement field for the given surrogate signal. Discrepancy between model prediction and ground truth (mean ± stand deviation) in 3D displacements is 3.3±2.0 mm in lung and 3.7±1.9 mm in abdomen in NCAT phantom, 3.8±2.7 mm in physical deformable phantom and 2.8±2.9 mm in patient data (N=7). Corresponding DIR discrepancies are 3.8±2.0 mm (NCAT lung), 3.7±1.8 mm (NCAT abdomen), 3.6±2.8 mm (physical phantom), and 2.0±2.2 mm (patient data). Motion model accuracy is found to be comparable to fast free-form in all three types of images, indicating that the assumption of two principal components is sufficient to describe the fast free-form DIR-derived deformations. NIH/NCI award R01 CA126993.

Half-time myocardial perfusion SPECT imaging with attenuation and Monte Carlo-based scatter correction

To test the potential of a new reconstruction algorithm with Monte Carlo-based scatter correction in half-time myocardial perfusion single-photon emission computed tomography (SPECT). The mathematical four-dimensional NURBS-based Cardiac-Torso phantom and the SIMIND Monte Carlo simulation package were used to simulate full-time and half-time SPECT projection data. The data were reconstructed using the standard ordered subset expectation maximization-based algorithm and the new Monte Carlo-based algorithm. Defect contrast, myocardium versus ventricle contrast and resolution were calculated. In addition to the simulation studies, full-time and half-time SPECT projection data of 30 patients were reconstructed with the standard and the new method. The patient data were qualitatively evaluated by four nuclear medicine experts on a scale from 1 (poor quality) to 5 (high quality). The new reconstruction method with half-time data produced higher contrast and better resolution in the simulations and also achieved higher qualitative scores in the patient study than the standard reconstruction with full-time data. Half-time myocardial perfusion imaging using the new reconstruction algorithm with Monte Carlo-based scatter correction produced images with superior quality when compared with full-time imaging with standard reconstruction.

Detectability of perfusion defect in five-dimensional gated-dynamic cardiac SPECT images.

In previous work, the authors developed and demonstrated the concept of an image reconstruction procedure aimed to unify gated and dynamic nuclear cardiac imaging, which the authors have termed five-dimensional (5D) SPECT. Gated imaging permits the clinician to evaluate wall motion and, through the use of stress and rest scans, allows perfusion defects to be observed. Dynamic imaging depicts kinetics in the myocardium, which can be used to evaluate perfusion, but traditional dynamic images are motionless and do not depict wall motion. In this article, the authors investigate the degree to which perfusion defects can be detected from the dynamic information conveyed by 5D images, a problem that is particularly challenging in the absence of multiple fast camera rotations. The authors first demonstrate the usefulness of dynamic reconstructed images for perfusion detection by using linear discriminant analyses (Fisher linear discriminant analysis and principal component analysis) and a numerical channelized Hotelling observer. The authors then derive three types of discriminant metrics for characterizing the temporal kinetic information in reconstructed dynamic images for differentiating perfusion defects from normal cardiac perfusion, which are the Fisher linear discriminant map, temporal derivative map, and kinetic parametric images. Results are based on the NURBS-based cardiac-torso phantom with simulation of Tc99m-teboroxime as the imaging agent. The derived metric maps and quantitative contrast-to-noise ratio results demonstrate that the reconstructed dynamic images could yield higher detectability of the perfusion defect than conventional gated reconstruction while providing wall motion information simultaneously. The proposed metrics can be used to produce new types of visualizations, showing wall motion and perfusion information, that may potentially be useful for clinical evaluation. Since 5D imaging permits wall motion and kinetics to be observed simultaneously, it may ultimately obviate the need for separate stress and rest scans.

Myocardial perfusion SPECT using a rotating multi-segment slant-hole collimator

A rotating multi-segment slant-hole (RMSSH) collimator is able to provide much higher (approximately 3 times for four-segment collimator with 30 degrees slant angle) sensitivity than a parallel-hole (PH) collimator with the similar spatial resolution for imaging small organs such as the heart and the breast. In this article, the authors evaluated the performance of myocardial perfusion SPECT (MPS) using a RMSSH collimator compared to MPS using the low-energy high-resolution parallel-hole collimators. The authors conducted computer simulation studies using the NURBS-based cardiac-torso phantom, receiver operative characteristic (ROC) analysis using the channelized Hotelling observer, physical phantom experiments, and pilot patient studies to evaluate the performance of MPS using a rotating four-segment slant-hole (R4SSH) collimator with respect to MPS using a PH collimator. In the simulation study, the R4SSH MPS provides images with superior contrast-noise trade-off than those of PH MPS with the same acquisition time. The defect detectability in terms of the largest area under the ROC curve for R4SSH MPS is significantly higher than those of PH MPS with p-values < 0.01. In the phantom experiments, the R4SSH MPS images with 7.5 min acquisition had similar noise level and overall image quality as those of PH MPS with 21 min acquisition. Pilot patient studies showed that with the same acquisition time, the R4SSH SPECT using a single-head camera gave images with similar quality as those of PH SPECT using a dual-head camera. The RMSSH SPECT has a potential to improve the coronary artery disease detection and workflow of SPECT imaging acquisition due to the high sensitivity property of the RMSSH collimator.

Incorporating Patient-Specific Variability in the Simulation of Realistic Whole-Body $^{18}{\hbox{F-FDG}}$ Distributions for Oncology Applications

The purpose of the work described in this paper was the development of a framework for the creation of a realistic positron emission tomography (PET) simulated database incorporating patient-specific variability. The ground truth used was therefore based on clinical PET/computed tomography (CT) data of oncology patients. In the first step, the NURBS-based cardiac-torso phantom was adapted to the patient's CT acquisitions to reproduce their specific anatomy while the corresponding PET acquisitions were used to derive the activity distribution of each organ of interest. Secondly, realistic tumor shapes with homogeneous or heterogeneous activity distributions were modeled based on segmentation of the PET tumor volume and incorporated in the patient-specific models obtained at the first step. Lastly, patient-specific respiratory motion was also modeled. The derived patient-specific models were subsequently combined with the PET SORTEO Monte Carlo simulation tool for the simulation of the whole-body PET acquisition process. The accuracy of the simulated datasets was assessed in comparison to the original clinical patient images. In addition, a couple of applications for such simulated images were also demonstrated. Future work will focus on the creation of a comprehensive database of simulated raw data and reconstructed whole-body images, facilitating the rigorous evaluation of image-processing algorithms in PET for oncology applications.

SU‐GG‐J‐93: Feasibility Study On Artifact Reduction Using Dual Energy Digital Tomosynthesis

Purpose: We propose a simulation study to examine the feasibility of incorporating dual energy (DE) subtraction with digital tomosynthesis (DTS) to help reduce DTS reconstruction artifacts. Method and Materials: We have previously investigated the incorporation of DTS into radiation therapy for patient localization and found the initial results promising. Due to the limited sampling of the Fourier space, high contrast signals, such as bone, tend to bleed into other slices of the reconstruction. These artifacts could be misconstrued or reduce the conspicuity of low‐contrast signals, especially in the lungs. For this simulation study, an advanced 4D NURBS based Cardiac‐Torso (NCAT) phantom, which includes a detailed whole‐body anatomy of organs including the lungs, airway tree, heart, and vessels, was used. When combined with advanced models of the imaging process, the NCAT phantom can produce realistic imaging data. For this study, a unique x‐ray projection algorithm developed specifically for the NCAT phantom was used to generate limited angle projection data for DTS reconstruction. 81 images were acquired over a 40 degree arc. The breathing cycle was set to simulate breath‐hold imaging. Data sets were generated using spectra of 80 and 120 kVp. For this study, dual energy subtraction (DES) was performed on these two sets of limited angle images to remove the overlying bony anatomy. The resulting images were then reconstructed using a modified filtered back projection technique. This DE‐DTS volume was then visually compared to a standard DTS reconstruction of the 120 kVp data set. Results: The removal of the overlying bony anatomy of the chest in the DE‐DTS images helps to reduce the high contrast artifacts present in the standard DTS reconstruction. Conclusion: This feasibility study demonstrates that DE‐DTS imaging may provide increased visualization of low contrast regions in the chest by reducing high contrast DTS reconstruction artifacts.

Sources of attenuation-correction artefacts in cardiac PET/CT and SPECT/CT

Respiratory motion during myocardial perfusion imaging can cause artefacts in both positron emission tomography (PET) and single-photon emission computed tomography (SPECT) images when mismatches between emission and transmission datasets arise. In this study, artefacts from different breathing motions were quantified in both modalities to assess key factors in attenuation-correction accuracy. Activity maps were generated using the NURBS-based cardiac-torso phantom for different respiratory cycles, which were projected, attenuation-corrected and reconstructed to form PET and SPECT images. Attenuation-correction was performed with maps at mismatched respiratory phases to observe the effect on the left-ventricular myocardium. Myocardial non-uniformity was assessed in terms of the standard deviation in scores obtained from the 17-segment model and changes in uniformity were compared for each mismatch and modality. Certain types of mismatch led to artefacts and corresponding increases in the myocardial non-uniformity. For each mismatch in PET, the increases in non-uniformity relative to an artefact-free image were as follows: (a) cardiac translation mismatch, 84% +/- 11%; (b) liver mismatch, 59% +/- 10%, (c) lung mismatch from diaphragm contraction, 28% +/- 8%; and (d) lung mismatch from chest-wall motion, 6% +/- 7%. The corresponding factors for SPECT were (a) 61% +/- 8%, (b) 34% +/- 8%, (c) -2% +/- 7)% and (d) -4% +/- 6%. Attenuation-correction artefacts were seen in PET and SPECT images, with PET being more severely affected. The most severe artefacts were produced from mismatches in cardiac and liver position, whereas lung mismatches were less critical. Both cardiac and liver positions must, therefore, be correctly matched during attenuation correction.

Normal and Pathological NCAT Image and Phantom Data Based on Physiologically Realistic Left Ventricle Finite-Element Models

The four-dimensional (4-D) NURBS-based cardiac-torso (NCAT) phantom, which provides a realistic model of the normal human anatomy and cardiac and respiratory motions, is used in medical imaging research to evaluate and improve imaging devices and techniques, especially dynamic cardiac applications. One limitation of the phantom is that it lacks the ability to accurately simulate altered functions of the heart that result from cardiac pathologies such as coronary artery disease (CAD). The goal of this work was to enhance the 4-D NCAT phantom by incorporating a physiologically based, finite-element (FE) mechanical model of the left ventricle (LV) to simulate both normal and abnormal cardiac motions. The geometry of the FE mechanical model was based on gated high-resolution X-ray multislice computed tomography (MSCT) data of a healthy male subject. The myocardial wall was represented as a transversely isotropic hyperelastic material, with the fiber angle varying from -90 degrees at the epicardial surface, through 0 degrees at the midwall, to 90 degrees at the endocardial surface. A time-varying elastance model was used to simulate fiber contraction, and physiological intraventricular systolic pressure-time curves were applied to simulate the cardiac motion over the entire cardiac cycle. To demonstrate the ability of the FE mechanical model to accurately simulate the normal cardiac motion as well as the abnormal motions indicative of CAD, a normal case and two pathologic cases were simulated and analyzed. In the first pathologic model, a subendocardial anterior ischemic region was defined. A second model was created with a transmural ischemic region defined in the same location. The FE-based deformations were incorporated into the 4-D NCAT cardiac model through the control points that define the cardiac structures in the phantom which were set to move according to the predictions of the mechanical model. A simulation study was performed using the FE-NCAT combination to investigate how the differences in contractile function between the subendocardial and transmural infarcts manifest themselves in myocardial Single photon emission computed tomography (SPECT) images. The normal FE model produced strain distributions that were consistent with those reported in the literature and a motion consistent with that defined in the normal 4-D NCAT beating heart model based on tagged magnetic resonance imaging (MRI) data. The addition of a subendocardial ischemic region changed the average transmural circumferential strain from a contractile value of -0.09 to a tensile value of 0.02. The addition of a transmural ischemic region changed average circumferential strain to a value of 0.13, which is consistent with data reported in the literature. Model results demonstrated differences in contractile function between subendocardial and transmural infarcts and how these differences in function are documented in simulated myocardial SPECT images produced using the 4-D NCAT phantom. Compared with the original NCAT beating heart model, the FE mechanical model produced a more accurate simulation for the cardiac motion abnormalities. Such a model, when incorporated into the 4-D NCAT phantom, has great potential for use in cardiac imaging research. With its enhanced physiologically based cardiac model, the 4-D NCAT phantom can be used to simulate realistic, predictive imaging data of a patient population with varying whole-body anatomy and with varying healthy and diseased states of the heart that will provide a known truth from which to evaluate and improve existing and emerging 4-D imaging techniques used in the diagnosis of cardiac disease.