Low-Dose CT Image Synthesis for Domain Adaptation Imaging Using a Generative Adversarial Network With Noise Encoding Transfer Learning.

Deep learning (DL) based image processing methods have been successfully applied to low-dose x-ray images based on the assumption that the feature distribution of the training data is consistent with that of the test data. However, low-dose computed tomography (LDCT) images from different commercial scanners may contain different amounts and types of image noise, violating this assumption. Moreover, in the application of DL based image processing methods to LDCT, the feature distributions of LDCT images from simulation and clinical CT examination can be quite different. Therefore, the network models trained with simulated image data or LDCT images from one specific scanner may not work well for another CT scanner and image processing task. To solve such domain adaptation problem, in this study, a novel generative adversarial network (GAN) with noise encoding transfer learning (NETL), or GAN-NETL, is proposed to generate a paired dataset with a different noise style. Specifically, we proposed a method to perform noise encoding operator and incorporate it into the generator to extract a noise style. Meanwhile, with a transfer learning (TL) approach, the image noise encoding operator transformed the noise type of the source domain to that of the target domain for realistic noise generation. One public and two private datasets are used to evaluate the proposed method. Experiment results demonstrated the feasibility and effectiveness of our proposed GAN-NETL model in LDCT image synthesis. In addition, we conduct additional image denoising study using the synthesized clinical LDCT data, which verified the merit of the proposed synthesis in improving the performance of the DL based LDCT processing method.

Domain-adaptive denoising network for low-dose CT via noise estimation and transfer learning.

BACKGROUND: In recent years, low-dose computed tomography (LDCT) has played an important role in the diagnosis CT to reduce the potential adverse effects of X-ray radiation on patients, while maintaining the same diagnostic image quality. PURPOSE: Deep learning (DL)-based methods have played an increasingly important role in the field of LDCT imaging. However, its performance is highly dependent on the consistency of feature distributions between training data and test data. Due to patient's breathing movements during data acquisition, the paired LDCT and normal dose CT images are difficult to obtain from realistic imaging scenarios. Moreover, LDCT images from simulation or clinical CT examination often have different feature distributions due to the pollution by different amounts and types of image noises. If a network model trained with a simulated dataset is used to directly test clinical patients' LDCT data, its denoising performance may be degraded. Based on this, we propose a novel domain-adaptive denoising network (DADN) via noise estimation and transfer learning to resolve the out-of-distribution problem in LDCT imaging. METHODS: To overcome the previous adaptation issue, a novel network model consisting of a reconstruction network and a noise estimation network was designed. The noise estimation network based on a double branch structure is used for image noise extraction and adaptation. Meanwhile, the U-Net-based reconstruction network uses several spatially adaptive normalization modules to fuse multi-scale noise input. Moreover, to facilitate the adaptation of the proposed DADN network to new imaging scenarios, we set a two-stage network training plan. In the first stage, the public simulated dataset is used for training. In the second transfer training stage, we will continue to fine-tune the network model with a torso phantom dataset, while some parameters are frozen. The main reason using the two-stage training scheme is based on the fact that the feature distribution of image content from the public dataset is complex and diverse, whereas the feature distribution of noise pattern from the torso phantom dataset is closer to realistic imaging scenarios. RESULTS: In an evaluation study, the trained DADN model is applied to both the public and clinical patient LDCT datasets. Through the comparison of visual inspection and quantitative results, it is shown that the proposed DADN network model can perform well in terms of noise and artifact suppression, while effectively preserving image contrast and details. CONCLUSIONS: In this paper, we have proposed a new DL network to overcome the domain adaptation problem in LDCT image denoising. Moreover, the results demonstrate the feasibility and effectiveness of the application of our proposed DADN network model as a new DL-based LDCT image denoising method.

Targeted Deletion of Interleukin-6 in a Mouse Model of Chronic Inflammation Demonstrates Opposing Roles in Aging: Benefit and Harm.

Chronic inflammation (CI) in older adults is associated with reduced health span and life span. Interleukin-6 (IL-6) is one CI marker that is strongly associated with adverse health outcomes and mortality in aging. We have previously characterized a mouse model of frailty and chronic inflammatory pathway activation (IL-10tm/tm, IL-10 KO) that demonstrates the upregulation of numerous proinflammatory cytokines, including IL-6. We sought to identify a more specific role for IL-6 within the context of CI and aging and developed a mouse with targeted deletion of both IL-10 and IL-6 (IL-10tm/tm/IL-6tm/tm, DKO). Phenotypic characteristics, cytokine measurements, cardiac myocardial oxygen consumption, physical function, and survival were measured in DKO mice and compared to age- and gender-matched IL-10 KO and wild-type mice. Our findings demonstrate that selective knockdown of IL-6 in a frail mouse with CI resulted in the reversal of some of the CI-associated changes. We observed increased protective mitochondrial-associated lipid metabolites, decreased cardiac oxaloacetic acid, improved myocardial oxidative metabolism, and better short-term functional performance in DKO mice. However, the DKO mice also demonstrated higher mortality. This work shows the pleiotropic effects of IL-6 on aging and frailty.

Virtual clinical trials in medical imaging: a review.

The accelerating complexity and variety of medical imaging devices and methods have outpaced the ability to evaluate and optimize their design and clinical use. This is a significant and increasing challenge for both scientific investigations and clinical applications. Evaluations would ideally be done using clinical imaging trials. These experiments, however, are often not practical due to ethical limitations, expense, time requirements, or lack of ground truth. Virtual clinical trials (VCTs) (also known as in silico imaging trials or virtual imaging trials) offer an alternative means to efficiently evaluate medical imaging technologies virtually. They do so by simulating the patients, imaging systems, and interpreters. The field of VCTs has been constantly advanced over the past decades in multiple areas. We summarize the major developments and current status of the field of VCTs in medical imaging. We review the core components of a VCT: computational phantoms, simulators of different imaging modalities, and interpretation models. We also highlight some of the applications of VCTs across various imaging modalities.

Association of PET-measured myocardial flow reserve with echocardiography-estimated pulmonary artery systolic pressure in patients with hypertrophic cardiomyopathy.

BACKGROUND: Pulmonary hypertension (PH) is a known complication of HCM and is a strong predictor of mortality. We aim to investigate the relationship between microvascular dysfunction measured by quantitative PET and PH in HCM patients. METHODS: Eighty-nine symptomatic HCM patients were included in the study. Each patient underwent two 20-min 13N-NH3 dynamic PET scans for rest and stress conditions, respectively. A 2-tissue irreversible compartmental model was used to fit the segments time activity curves for estimating segmental and global myocardial blood flow (MBF) and myocardial flow reserve (MFR). Echocardiographic derived PASP was utilized to estimate PH. RESULTS: Patients were categorized into two groups across PASP: PH (PASP > 36 mmHg) and no-PH (PASP ≤ 36 mmHg). patients with PH had larger left atrium, ratio of higher inflow early diastole (E) and atrial contraction (A) waves, E/A, and ratio of inflow and peak early diastolic waves, E/e', significantly reduced global stress MBF (1.85 ± 0.52 vs. 2.13 ± 0.56 ml/min/g; p = 0.024) and MFR (2.21 ± 0.57 vs. 2.62 ± 0.75; p = 0.005), while the MBFs at rest between the two groups were similar. There were significant negative correlations between global stress MBF/MFR and PASP (stress MBF: r = -0.23, p = 0.03; MFR: r = -0.32, p = 0.002); for regional MBF and MFR measurements, the highest linear correlation coefficients were observed in the septal wall (stress MBF: r = -0.27, p = 0.01; MFR: r = -0.31, p = 0.003). Global MFR was identified to be independent predictor for PH in multivariate regression analysis. CONCLUSION: Echocardiography-derived PASP is negatively correlated with global MFR measured by 13N-NH3 dynamic PET. Global MFR is suggested to be an index of PH in HCM patients.

Advances in Computational Human Phantoms and Their Applications in Biomedical Engineering - A Topical Review.

Over the past decades, significant improvements have been made in the field of computational human phantoms (CHPs) and their applications in biomedical engineering. Their sophistication has dramatically increased. The very first CHPs were composed of simple geometric volumes, e.g., cylinders and spheres, while current CHPs have a high resolution, cover a substantial range of the patient population, have high anatomical accuracy, are poseable, morphable, and are augmented with various details to perform functionalized computations. Advances in imaging techniques and semi-automated segmentation tools allow fast and personalized development of CHPs. These advances open the door to quickly develop personalized CHPs, inherently including the disease of the patient. Because many of these CHPs are increasingly providing data for regulatory submissions of various medical devices, the validity, anatomical accuracy, and availability to cover the entire patient population is of utmost importance. The article is organized into two main sections: the first section reviews the different modeling techniques used to create CHPs, whereas the second section discusses various applications of CHPs in biomedical engineering. Each topic gives an overview, a brief history, recent developments, and an outlook into the future.

A hyaluronic acid binding peptide-polymer system for treating osteoarthritis.

Hyaluronic acid (HA) is found naturally in synovial fluid and is utilized therapeutically to treat osteoarthritis (OA). Here, we employed a peptide-polymer cartilage coating platform to localize HA to the cartilage surface for the purpose of treating post traumatic osteoarthritis. The objective of this study was to increase efficacy of the peptide-polymer platform in reducing OA progression in a mouse model of post-traumatic OA without exogenous HA supplementation. The peptide-polymer is composed of an HA-binding peptide (HABP) conjugated to a heterobifunctional poly (ethylene glycol) (PEG) chain and a collagen binding peptide (COLBP). We created a library of different peptide-polymers and characterized their HA binding properties in vitro using quartz crystal microbalance (QCM-D) and isothermal calorimetry (ITC). The peptide polymers were further tested in vivo in an anterior cruciate ligament transection (ACLT) murine model of post traumatic OA. The peptide-polymer with the highest affinity to HA as tested by QCM-D (∼4-fold greater binding compared to other peptides tested) and by ITC (∼3.8-fold) was HABP2-8-arm PEG-COLBP. Biotin tagging demonstrated that HABP2-8-arm PEG-COLBP localizes to both cartilage defects and synovium. In vivo, HABP2-8-arm PEG-COLBP treatment and the clinical HA comparator Orthovisc lowered levels of inflammatory genes including IL-6, IL-1B, and MMP13 compared to saline treated animals and increased aggrecan expression in young mice. HABP2-8-arm PEG-COLBP and Orthovisc also reduced pain as measured by incapacitance and hotplate testing. Cartilage degeneration as measured by OARSI scoring was also reduced by HABP2-8-arm PEG-COLBP and Orthovisc. In aged mice, HABP2-8-arm PEG-COLBP therapeutic efficacy was similar to its efficacy in young mice, but Orthovisc was less efficacious and did not significantly improve OARSI scoring. These results demonstrate that HABP2-8-arm PEG-COLBP is effective at reducing PTOA progression.

Dual respiratory and cardiac motion estimation in PET imaging: Methods design and quantitative evaluation.

PURPOSE: The goal of this study was to develop and evaluate four post-reconstruction respiratory and cardiac (R&C) motion vector field (MVF) estimation methods for cardiac 4D PET data. METHOD: In Method 1, the dual R&C motions were estimated directly from the dual R&C gated images. In Method 2, respiratory motion (RM) and cardiac motion (CM) were separately estimated from the respiratory gated only and cardiac gated only images. The effects of RM on CM estimation were modeled in Method 3 by applying an image-based RM correction on the cardiac gated images before CM estimation, the effects of CM on RM estimation were neglected. Method 4 iteratively models the mutual effects of RM and CM during dual R&C motion estimations. Realistic simulation data were generated for quantitative evaluation of four methods. Almost noise-free PET projection data were generated from the 4D XCAT phantom with realistic R&C MVF using Monte Carlo simulation. Poisson noise was added to the scaled projection data to generate additional datasets of two more different noise levels. All the projection data were reconstructed using a 4D image reconstruction method to obtain dual R&C gated images. The four dual R&C MVF estimation methods were applied to the dual R&C gated images and the accuracy of motion estimation was quantitatively evaluated using the root mean square error (RMSE) of the estimated MVFs. RESULTS: Results show that among the four estimation methods, Methods 2 performed the worst for noise-free case while Method 1 performed the worst for noisy cases in terms of quantitative accuracy of the estimated MVF. Methods 4 and 3 showed comparable results and achieved RMSE lower by up to 35% than that in Method 1 for noisy cases. CONCLUSION: In conclusion, we have developed and evaluated 4 different post-reconstruction R&C MVF estimation methods for use in 4D PET imaging. Comparison of the performance of four methods on simulated data indicates separate R&C estimation with modeling of RM before CM estimation (Method 3) to be the best option for accurate estimation of dual R&C motion in clinical situation.

A Direct Algorithm for Optimization Problems With the Huber Penalty.

We present a direct (noniterative) algorithm for 1-D quadratic data fitting with neighboring intensity differences penalized by the Huber function. Applications of such an algorithm include 1-D processing of medical signals, such as smoothing of tissue time concentration curves in kinetic data analysis or sinogram preprocessing, and using it as a subproblem solver for 2-D or 3-D image restoration and reconstruction. dynamic programming was used to develop the direct algorithm. The problem was reformulated as a sequence of univariate optimization problems, for , where is the number of data points. The solution to the univariate problem at index is parameterized by the solution at , except at . Solving the univariate optimization problem at yields the solution to each problem in the sequence using back-tracking. Computational issues and memory cost are discussed in detail. Two numerical studies, tissue concentration curve smoothing and sinogram preprocessing for image reconstruction, are used to validate the direct algorithm and illustrate its practical applications. In the example of 1-D curve smoothing, the efficiency of the direct algorithm is compared with four iterative methods: the iterative coordinate descent, Nesterov's accelerated gradient descent algorithm, FISTA, and an off-the-shelf second order method. The first two methods were applied to the primal problem, the others to the dual problem. The comparisons show that the direct algorithm outperforms all other methods by a significant factor, which rapidly grows with the curvature of the Huber function. The second example, sinogram preprocessing, showed that robustness and speed of the direct algorithm are maintained over a wide range of signal variations, and that noise and streaking artifacts could be reduced with almost no increase in computation time. We also outline how the proposed 1-D solver can be used for imaging applications.

Optimization of imaging protocols for myocardial blood flow (MBF) quantification with 18F-flurpiridaz PET.

The new PET tracer, 18F-flurpiridaz, with high myocardial extraction allows quantitative myocardial blood flow (MBF) estimation from dynamic PET data and tracer kinetic modeling. The goal of this study is to determine the optimal imaging protocols and parameters using a realistic simulation study. The time activity curves (TACs) of different tissue organs from a 30-s infusion time (IT) of 18F-flurpiridaz in a dynamic PET study were extracted from a previous study. The TACs at different time points were incorporated in a series of realistic 3D XCAT phantoms from which the parameters of a 2-compartment model and the 'true' MBF of 18F-flurpiridaz were determined. The compartmental model was used to generate TACs from 7 additional ITs. PET projection data from the XCAT phantoms were generated using Monte Carlo simulation. They were reconstructed using an OS-EM reconstruction algorithm with different update number (N) to obtain dynamic PET images. The blood and myocardial TACs were derived from the dynamic images from which the MBF and %MBF error was estimated. The %MBF error decreases with increasing N of the OS-EM and levels off after ∼42. The 30-s IT gave the smallest %MBF error that decreases from ∼0.57% to ∼19.40%. The MBF for 2-min, 4-min, 8-min and 16-min IT were statistically significant different from the MBF for 30-s IT (P<0.05). Too fast or too slow infusion time gave higher %MBF error. The optimal imaging protocol in dynamic 18F-flurpiridaz PET for accurate quantitative MBF estimation was 30-s IT and N of ∼42 for the OS-EM.

Design and evaluation of two multi-pinhole collimators for brain SPECT.

OBJECTIVE: SPECT is a powerful tool for diagnosing or staging brain diseases such as Alzheimer's disease (AD) and Parkinson's disease (PD) but is limited by its inferior resolution and sensitivity. At the same time, pinhole SPECT provides superior resolution and detection efficiency trade-off as compared to the conventional parallel-hole collimator for imaging small field-of-view (FOV), which fits for the case of brain imaging. In this study, we propose to develop and evaluate two multi-pinhole (MPH) collimator designs to improve the imaging of cerebral blood flow and striatum. METHODS: We set the target resolutions to be 12 and 8 mm, respectively, and the FOV at 200 mm which is large enough to cover the whole brain. The constraints for system optimization include maximum and minimum detector-to-center-of-FOV (CFOV) distances of 344 and 294 mm, respectively, and minimal radius-of-rotation (ROR) of 135 mm to accommodate patients' shoulder. According to the targeted FOV, resolutions, and constraints, we determined the pinhole number, ROR, focal length, aperture acceptance angle, and aperture diameter which maximized the system sensitivity. We then assessed the imaging performance of the proposed MPH and standard low-energy high-resolution (LEHR) collimators using analytical simulations of a digital NCAT brain phantom with 99mTc-HMPAO/99mTc-TRODAT-1 distributions; Monte Carlo simulations of a hot-rod phantom; and a Defrise phantom using GATE v6.1. Projections were generated over 360° and reconstructed using the 3D MPH/LEHR OS-EM methods with up to 720 updates. The normalized mean square error (NMSE) was calculated over the cerebral and striatal regions extracted from the reconstructed images for 99mTc-HMPAO and 99mTc-TRODAT-1 simulations, respectively, and average normalized standard deviation (NSD) based on 20 noise realizations was assessed on selected uniform 3D regions as the noise index. Visual assessment and image profiles were applied to the results of Monte Carlo simulations. RESULTS: The optimized design parameters of the MPH collimators were 9 pinholes with 4.7 and 2.8 mm pinhole diameter, 73° acceptance angle, 127 mm focal length, 167 mm ROR for 12 mm and 8 mm target resolution, respectively. According to the optimization results, the detection efficiencies of the proposed collimators were 270 and 40% more as compared to LEHR. The Monte Carlo simulations showed that 7.9 and 6.4 mm rods can be discriminated for the MPH collimators with target resolutions of 12 and 8 mm, respectively. The eight 12 mm-thick discs of the Defrise phantom can also be resolved clearly in the axial plane as demonstrated by the image profiles generated with the MPH collimators. CONCLUSION: The two collimator designs provide superior image quality as compared to the conventional LEHR, and shows potential to improve current brain SPECT imaging based on a conventional SPECT scanner.

Modeling the respiratory motion of solitary pulmonary nodules and determining the impact of respiratory motion on their detection in SPECT imaging.

The objectives of this investigation were to model the respiratory motion of solitary pulmonary nodules (SPN) and then use this model to determine the impact of respiratory motion on the localization and detection of small SPN in SPECT imaging for four reconstruction strategies. The respiratory motion of SPN was based on that of normal anatomic structures in the lungs determined from breath-held CT images of a volunteer acquired at two different stages of respiration. End-expiration (EE) and time-averaged (Frame Av) non-uniform-B-spline cardiac torso (NCAT) digital-anthropomorphic phantoms were created using this information for respiratory motion within the lungs. SPN were represented as 1 cm diameter spheres which underwent linear motion during respiration between the EE and end-inspiration (EI) time points. The SIMIND Monte Carlo program was used to produce SPECT projection data simulating Tc-99m depreotide (NeoTect) imaging. The projections were reconstructed using 1) no correction (NC), 2) attenuation correction (AC), 3) resolution compensation (RC), and 4) attenuation correction, scatter correction, and resolution compensation (AC_SC_RC). A human-observer localization receiver operating characteristics (LROC) study was then performed to determine the difference in localization and detection accuracy with and without the presence of respiratory motion. The LROC comparison determined that respiratory motion degrades tumor detection for all four reconstruction strategies, thus correction for SPN motion would be expected to improve detection accuracy. The inclusion of RC in reconstruction improved detection accuracy for both EE and Frame Av over NC and AC. Also the magnitude of the impact of motion was least for AC_SC_RC.

Theory and realization of a 2D high resolution and high sensitivity SPECT system with an angle-encoding attenuator pattern.

The camera of the conventional SPECT system requires a collimator to allow incoming photons from a specific range of incident angle to reach the detector. It is the major factor that determines the spatial resolution of the camera. Moreover, it also greatly reduces the number of detected photons and hence increases statistical fluctuations in the acquired image data. The goal of this paper is to propose a theory and design for a novel high resolution and high sensitivity SPECT system without conventional collimators. The key is to resolve the incident photons from all directional angles and detected by every detector bin. Special 'attenuators' were designed to 'encode' the incoming photons from different directions similar to coded aperture to form projection data for image reconstruction. Each encoded angular pattern of detected photons was recorded as one measurement. Different angular patterns were achieved by changing the configurations of the attenuators so that angular pattern of different measurements or measurement matrix (MM) is invertible, which guarantee a unique reconstructed image. In simulation, the attenuators were fitted on a virtual full-ring gamma camera, as an alternative to the collimators in conventional SPECT systems. To evaluate the performance of the new SPECT system, analytical simulated projection data in 2D scenario were generated from the XCAT phantom. Noisy simulation using 100 noise realizations suggests that the new attenuator design provides much improved image quality in terms of contrast-noise trade-offs (~30% improvement). The results suggest that the new design of using attenuators to replace collimator is feasible and could potentially improve sensitivity without sacrificing resolution in today's SPECT systems.

Design and evaluation of an adaptive multipinhole collimator for high-performance clinical and preclinical imaging.

OBJECTIVE: Pinhole single-photon emission computed tomography provides superior trade-off between resolution and detection efficiency as compared with conventional parallel-hole collimators for imaging small objects. This study aims to design and evaluate an optimized adaptive multipinhole (MPH) collimator for improved clinical myocardial perfusion single-photon emission computed tomography imaging (MPI) and preclinical small-animal imaging (SAI) of rats based on a clinical scanner. METHODS: The target resolution and field of view was set to be 1/20 cm for MPI and 0.15/5 cm for SAI, respectively. We determined the design parameters by maximizing the detection efficiency based on system constraints. Point source simulations using Geant4 Application for Emission Tomography were performed for different collimator-to-center of field of view distances to assess the detection efficiency and resolution trade-off. The XCAT phantom with Tc-99m sestamibi distribution and the four-dimensional mouse whole-body phantom with Tc-99m methylene diphosphonate distribution were used to generate noise-free and noisy projections using a three-dimensional analytical MPH projector. Projections were reconstructed using a three-dimensional MPH ordered-subset expectation maximization algorithm. Noise and bias were assessed on the reconstructed images for different collimators. RESULTS: The design parameters are (i) 14 pinholes with 3.42 mm aperture size, 14.5 cm collimator-to-detector distance for MPI; (ii) six pinholes with an aperture size of 0.94 mm, 21.2 cm collimator-to-detector distance for SAI. For MPI, the projected full width at half maximum values were 10.68 and 8.19 mm for low energy high resolution (LEHR) and MPH, respectively, whereas MPH had double detection efficiency. For SAI, the projected full width at half maximum values for LEHR and MPH were 4.93 and 1.20 mm, respectively, whereas the detection efficiency of MPH showed 17.5% improvement as compared with LEHR. The noise-bias trade-off improved for MPH as compared with LEHR for both MPI and SAI. The proposed collimator will have adjustable collimator-to-detector distances - that is, 14.5 cm for MPI and 21.2 cm for SAI. CONCLUSION: The new collimator yields substantial improvement in image quality as compared with current MPI using LEHR with extra capability for SAI, bridging the clinical and preclinical imaging based on the same platform.

Realistic analytical polyhedral MRI phantoms.

PURPOSE: Analytical phantoms have closed form Fourier transform expressions and are used to simulate MRI acquisitions. Existing three-dimensional (3D) analytical phantoms are unable to accurately model shapes of biomedical interest. The goal of this study was to demonstrate that polyhedral analytical phantoms have closed form Fourier transform expressions and can accurately represent 3D biomedical shapes. METHODS: The Fourier transform of a polyhedron was implemented and its accuracy in representing faceted and smooth surfaces was characterized. Realistic anthropomorphic polyhedral brain and torso phantoms were constructed and their use in simulated 3D and two-dimensional (2D) MRI acquisitions was described. RESULTS: Using polyhedra, the Fourier transform of faceted shapes can be computed to within machine precision. Smooth surfaces can be approximated with increasing accuracy by increasing the number of facets in the polyhedron; the additional accumulated numerical imprecision of the Fourier transform of polyhedra with many faces remained small. Simulations of 3D and 2D brain and 2D torso cine acquisitions produced realistic reconstructions free of high frequency edge aliasing compared with equivalent voxelized/rasterized phantoms. CONCLUSION: Analytical polyhedral phantoms are easy to construct and can accurately simulate shapes of biomedical interest. Magn Reson Med 76:663-678, 2016. © 2015 Wiley Periodicals, Inc.

Image-derived and arterial blood sampled input functions for quantitative PET imaging of the angiotensin II subtype 1 receptor in the kidney.

PURPOSE: The radioligand 11C-KR31173 has been introduced for positron emission tomography (PET) imaging of the angiotensin II subtype 1 receptor in the kidney in vivo. To study the biokinetics of 11C-KR31173 with a compartmental model, the input function is needed. Collection and analysis of arterial blood samples are the established approach to obtain the input function but they are not feasible in patients with renal diseases. The goal of this study was to develop a quantitative technique that can provide an accurate image-derived input function (ID-IF) to replace the conventional invasive arterial sampling and test the method in pigs with the goal of translation into human studies. METHODS: The experimental animals were injected with [11C]KR31173 and scanned up to 90 min with dynamic PET. Arterial blood samples were collected for the artery derived input function (AD-IF) and used as a gold standard for ID-IF. Before PET, magnetic resonance angiography of the kidneys was obtained to provide the anatomical information required for derivation of the recovery coefficients in the abdominal aorta, a requirement for partial volume correction of the ID-IF. Different image reconstruction methods, filtered back projection (FBP) and ordered subset expectation maximization (OS-EM), were investigated for the best trade-off between bias and variance of the ID-IF. The effects of kidney uptakes on the quantitative accuracy of ID-IF were also studied. Biological variables such as red blood cell binding and radioligand metabolism were also taken into consideration. A single blood sample was used for calibration in the later phase of the input function. RESULTS: In the first 2 min after injection, the OS-EM based ID-IF was found to be biased, and the bias was found to be induced by the kidney uptake. No such bias was found with the FBP based image reconstruction method. However, the OS-EM based image reconstruction was found to reduce variance in the subsequent phase of the ID-IF. The combined use of FBP and OS-EM resulted in reduced bias and noise. After performing all the necessary corrections, the areas under the curves (AUCs) of the AD-IF were close to that of the AD-IF (average AUC ratio=1±0.08) during the early phase. When applied in a two-tissue-compartmental kinetic model, the average difference between the estimated model parameters from ID-IF and AD-IF was 10% which was within the error of the estimation method. CONCLUSIONS: The bias of radioligand concentration in the aorta from the OS-EM image reconstruction is significantly affected by radioligand uptake in the adjacent kidney and cannot be neglected for quantitative evaluation. With careful calibrations and corrections, the ID-IF derived from quantitative dynamic PET images can be used as the input function of the compartmental model to quantify the renal kinetics of 11C-KR31173 in experimental animals and the authors intend to evaluate this method in future human studies.

Hyaluronic acid-serum hydrogels rapidly restore metabolism of encapsulated stem cells and promote engraftment.

BACKGROUND: Cell death due to anoikis, necrosis and cell egress from transplantation sites limits functional benefits of cellular cardiomyoplasty. Cell dissociation and suspension, which are a pre-requisite for most cell transplantation studies, lead to depression of cellular metabolism and anoikis, which contribute to low engraftment. OBJECTIVE: We tissue engineered scaffolds with the goal of rapidly restoring metabolism, promoting viability, proliferation and engraftment of encapsulated stem cells. METHODS: The carboxyl groups of HA were functionalized with N-hydroxysuccinimide (NHS) to yield HA succinimidyl succinate (HA-NHS) groups that react with free amine groups to form amide bonds. HA-NHS was cross-linked by serum to generate HA:Serum (HA:Ser) hydrogels. Physical properties of HA:Ser hydrogels were measured. Effect of encapsulating cardiosphere-derived cells (CDCs) in HA:Ser hydrogels on viability, proliferation, glucose uptake and metabolism was assessed in vitro. In vivo acute intra-myocardial cell retention of (18)FDG-labeled CDCs encapsulated in HA:Ser hydrogels was quantified. Effect of CDC encapsulation in HA:Ser hydrogels on in vivo metabolism and engraftment at 7 days was assessed by serial, dual isotope SPECT-CT and bioluminescence imaging of CDCs expressing the Na-iodide symporter and firefly luciferase genes respectively. Effect of HA:Ser hydrogels ± CDCs on cardiac function was assessed at 7 days & 28 days post-infarct. RESULTS: HA:Ser hydrogels are highly bio-adhesive, biodegradable, promote rapid cell adhesion, glucose uptake and restore bioenergetics of encapsulated cells within 1 h of encapsulation, both in vitro and in vivo. These metabolic scaffolds can be applied epicardially as a patch to beating hearts or injected intramyocardially. HA:Ser hydrogels markedly increase acute intramyocardial retention (∼6 fold), promote in vivo viability, proliferation, engraftment of encapsulated stem cells and angiogenesis. CONCLUSION: HA:Ser hydrogels serve as 'synthetic stem cell niches' that rapidly restore metabolism of encapsulated stem cells, promote stem cell engraftment and angiogenesis. These first ever, tissue engineered metabolic scaffolds hold promise for clinical translation in conjunction with CDCs and possibly other stem cell types.

Task-based evaluation of a 4D MAP-RBI-EM image reconstruction method for gated myocardial perfusion SPECT using a human observer study.

We evaluated the performance of a new 4D image reconstruction method for improved 4D gated myocardial perfusion (MP) SPECT using a task-based human observer study. We used a realistic 4D NURBS-based Cardiac-Torso (NCAT) phantom that models cardiac beating motion. Half of the population was normal; the other half had a regional hypokinetic wall motion abnormality. Noise-free and noisy projection data with 16 gates/cardiac cycle were generated using an analytical projector that included the effects of attenuation, collimator-detector response, and scatter (ADS), and were reconstructed using the 3D FBP without and 3D OS-EM with ADS corrections followed by different cut-off frequencies of a 4D linear post-filter. A 4D iterative maximum a posteriori rescaled-block (MAP-RBI)-EM image reconstruction method with ADS corrections was also used to reconstruct the projection data using various values of the weighting factor for its prior. The trade-offs between bias and noise were represented by the normalized mean squared error (NMSE) and averaged normalized standard deviation (NSDav), respectively. They were used to select reasonable ranges of the reconstructed images for use in a human observer study. The observers were trained with the simulated cine images and were instructed to rate their confidence on the absence or presence of a motion defect on a continuous scale. We then applied receiver operating characteristic (ROC) analysis and used the area under the ROC curve (AUC) index. The results showed that significant differences in detection performance among the different NMSE-NSDav combinations were found and the optimal trade-off from optimized reconstruction parameters corresponded to a maximum AUC value. The 4D MAP-RBI-EM with ADS correction, which had the best trade-off among the tested reconstruction methods, also had the highest AUC value, resulting in significantly better human observer detection performance when detecting regional myocardial wall motion abnormality. We concluded that the NMSE-NSDav trade-off was shown to agree with observer performance for the detection task of the regional motion abnormality, and the optimized 4D MAP-RBI-EM method with ADS corrections provides significant improvement compared to 3D FBP and 3D OS-EM with ADS corrections in detecting regional myocardial wall motion abnormali in 4D gated MP SPECT.

Improved intrinsic motion detection using time-of-flight PET.

Intrinsic or data-driven respiratory and cardiac motion detection often track the center-of-mass (COM) change in PET data to derive a motion gating signal. The effectiveness of this method depends on the contrast of the moving target to the relatively stationary background. The stationary background leads to a reduced COM displacement in PET data. Further, the COM calculated using axially truncated PET data is biased. To improve intrinsic motion detection for motion compensated image reconstruction, we use the time-of-flight (TOF) PET data of the original object f(x) to calculate the non-TOF PET data of a volume-of-interest (VOI) weighted object f(x)w(x) . The VOI-weighting w(x) can be chosen to reduce contribution from the stationary background. The reduced background in f(x)w(x) leads to an observed increase in the COM displacement. We also derive rebinning equations to obtain the exact axial COM using axially truncated PET data. To assess the quality of the motion gating signal, we analyze the variance property of the COM using different methods, including with(out) VOI weighting and with(out) compensation for axial data truncation. Analytical simulations, phantom and patient data demonstrate the effectiveness of the proposed approach in identifying the motion phase and in deriving a gating signal to be used for motion-compensated image reconstruction.

Development of 4D mathematical observer models for the task-based evaluation of gated myocardial perfusion SPECT.

This paper presents two 4D mathematical observer models for the detection of motion defects in 4D gated medical images. Their performance was compared with results from human observers in detecting a regional motion abnormality in simulated 4D gated myocardial perfusion (MP) SPECT images. The first 4D mathematical observer model extends the conventional channelized Hotelling observer (CHO) based on a set of 2D spatial channels and the second is a proposed model that uses a set of 4D space-time channels. Simulated projection data were generated using the 4D NURBS-based cardiac-torso (NCAT) phantom with 16 gates/cardiac cycle. The activity distribution modelled uptake of (99m)Tc MIBI with normal perfusion and a regional wall motion defect. An analytical projector was used in the simulation and the filtered backprojection (FBP) algorithm was used in image reconstruction followed by spatial and temporal low-pass filtering with various cut-off frequencies. Then, we extracted 2D image slices from each time frame and reorganized them into a set of cine images. For the first model, we applied 2D spatial channels to the cine images and generated a set of feature vectors that were stacked for the images from different slices of the heart. The process was repeated for each of the 1,024 noise realizations, and CHO and receiver operating characteristics (ROC) analysis methodologies were applied to the ensemble of the feature vectors to compute areas under the ROC curves (AUCs). For the second model, a set of 4D space-time channels was developed and applied to the sets of cine images to produce space-time feature vectors to which the CHO methodology was applied. The AUC values of the second model showed better agreement (Spearman's rank correlation (SRC) coefficient = 0.8) to human observer results than those from the first model (SRC coefficient = 0.4). The agreement with human observers indicates the proposed 4D mathematical observer model provides a good predictor of the performance of human observers in detecting regional motion defects in 4D gated MP SPECT images. The result supports the use of the observer model in the optimization and evaluation of 4D image reconstruction and compensation methods for improving the detection of motion abnormalities in 4D gated MP SPECT images.