A generalization of the maximum likelihood expectation maximization (MLEM) method: Masked-MLEM.

Objective.In our previous work on image reconstruction for single-layer collimatorless scintigraphy, we developed the min-min weighted robust least squares (WRLS) optimization algorithm to address the challenge of reconstructing images when both the system matrix and the projection data are uncertain. Whereas the WRLS algorithm has been successful in two-dimensional (2D) reconstruction, expanding it to three-dimensional (3D) reconstruction is difficult since the WRLS optimization problem is neither smooth nor strongly-convex. To overcome these difficulties and achieve robust image reconstruction in the presence of system uncertainties and projection noise, we propose a generalized iterative method based on the maximum likelihood expectation maximization (MLEM) algorithm, hereinafter referred to as the Masked-MLEM algorithm.Approach.In the Masked-MLEM algorithm, only selected subsets ('masks') from the system matrix and the projection contribute to the image update to satisfy the constraints imposed by the system uncertainties. We validate the Masked-MLEM algorithm and compare it to the standard MLEM algorithm using experimental data obtained from both collimated and uncollimated imaging instruments, including parallel-hole collimated SPECT, 2D collimatorless scintigraphy, and 3D collimatorless tomography. Additionally, we conduct comprehensive Monte Carlo simulations for 3D collimatorless tomography to further validate the effectiveness of the Masked-MLEM algorithm in handling different levels of system uncertainties.Main results.The Masked-MLEM and standard MLEM reconstructions are similar in cases with negligible system uncertainties, whereas the Masked-MLEM algorithm outperforms the standard MLEM algorithm when the system matrix is an approximation. Importantly, the Masked-MLEM algorithm ensures reliable image reconstruction across varying levels of system uncertainties.Significance.With a good choice of system uncertainty and without requiring accurate knowledge of the actual system matrix, the Masked-MLEM algorithm yields more robust image reconstruction than the standard MLEM algorithm, effectively reducing the likelihood of erroneously reconstructing higher activities in regions without radioactive sources.

Compton and proximity imaging of 225Ac in vivo with a CZT gamma camera: a proof of principle with simulations.

In vivo imaging of 225Ac is a major challenge in the development of targeted alpha therapy radiopharmaceuticals due to the extremely low injected doses. In this paper, we present the design of a multi-modality gamma camera that integrates both proximity and Compton imaging in order to achieve the demanding sensitivities required to image 225Ac with good image quality. We consider a dual-head camera, each of the heads consisting of two planar cadmium zinc telluride detectors acting as scatterer and absorber for Compton imaging, and with the scatterer practically in contact with the subject to allow for proximity imaging. We optimize the detector's design and characterize the detector's performance using Monte Carlo simulations. We show that Compton imaging can resolve features of up to 1.5 mm for hot rod phantoms with an activity of 1 µCi, and can reconstruct 3D images of a mouse injected with 0.5 µCi after a 15 minutes exposure and with a single bed position, for both 221Fr and 213Bi. Proximity imaging is able to resolve two 1 mm-radius sources of less than 0.1 µCi separated by 1 cm and at 1 mm from the detector, as well as it can provide planar images of 221Fr and 213Bi biodistributions of the mouse phantom in 5 minutes.

Data Management and Network Architecture Effect on Performance Variability in Direct Attenuation Correction via Deep Learning for Cardiac SPECT: A Feasibility Study.

Attenuation correction (AC) is important for accurate interpretation of SPECT myocardial perfusion imaging (MPI). However, it is challenging to perform AC in dedicated cardiac systems not equipped with a transmission imaging capability. Previously, we demonstrated the feasibility of generating attenuation-corrected SPECT images using a deep learning technique (SPECTDL) directly from non-corrected images (SPECTNC). However, we observed performance variability across patients which is an important factor for clinical translation of the technique. In this study, we investigate the feasibility of overcoming the performance variability across patients for the direct AC in SPECT MPI by proposing to develop an advanced network and a data management strategy. To investigate, we compared the accuracy of the SPECTDL for the conventional U-Net and Wasserstein cycle GAN (WCycleGAN) networks. To manage the training data, clustering was applied to a representation of data in the lower-dimensional space, and the training data were chosen based on the similarity of data in this space. Quantitative analysis demonstrated that DL model with an advanced network improves the global performance for the AC task with the limited data. However, the regional results were not improved. The proposed data management strategy demonstrated that the clustered training has potential benefit for effective training.

Monte Carlo Simulation and Reconstruction: Assessment of Myocardial Perfusion Imaging of Tracer Dynamics With Cardiac Motion Due to Deformation and Respiration Using Gamma Camera With Continuous Acquisition.

Purpose: Myocardial perfusion imaging (MPI) with single photon emission computed tomography (SPECT) is routinely used for stress testing in nuclear medicine. Recently, our group extended its potential going from 3D visual qualitative image analysis to 4D spatiotemporal reconstruction of dynamically acquired data to capture the time variation of the radiotracer concentration and the estimated myocardial blood flow (MBF) and coronary flow reserve (CFR). However, the quality of reconstructed image is compromised due to cardiac deformation and respiration. The work presented here develops an algorithm that reconstructs the dynamic sequence of separate respiratory and cardiac phases and evaluates the algorithm with data simulated with a Monte Carlo simulation for the continuous image acquisition and processing with a slowly rotating SPECT camera. Methods: A clinically realistic Monte Carlo (MC) simulation is developed using the 4D Extended Cardiac Torso (XCAT) digital phantom with respiratory and cardiac motion to model continuous data acquisition of dynamic cardiac SPECT with slowly rotating gamma cameras by incorporating deformation and displacement of the myocardium due to cardiac and respiratory motion. We extended our previously developed 4D maximum-likelihood expectation-maximization (MLEM) reconstruction algorithm for a data set binned from a continuous list mode (LM) simulation with cardiac and respiratory information. Our spatiotemporal image reconstruction uses splines to explicitly model the temporal change of the tracer for each cardiac and respiratory gate that delineates the myocardial spatial position as the tracer washes in and out. Unlike in a fully list-mode data acquisition and reconstruction the accumulated photons are binned over a specific but very short time interval corresponding to each cardiac and respiratory gate. Reconstruction results are presented showing the dynamics of the tracer in the myocardium as it continuously deforms. These results are then compared with the conventional 4D spatiotemporal reconstruction method that models only the temporal changes of the tracer activity. Mean Stabilized Activity (MSA), signal to noise ratio (SNR) and Bias for the myocardium activities for three different target-to-background ratios (TBRs) are evaluated. Dynamic quantitative indices such as wash-in (K1) and wash-out (k2) rates at each gate were also estimated. Results: The MSA and SNR are higher with higher TBRs while biases were improved with higher TBRs to less than 10%. The correlation between exhalation-inhalation sequence with the ground truth during respiratory cycle was excellent. Our reconstruction method showed better resolved myocardial walls during diastole to systole as compared to the ungated 4D image. Estimated values of K1 and k2 were also consistent with the ground truth. Conclusion: The continuous image acquisition for dynamic scan using conventional two-head gamma cameras can provide valuable information for MPI. Our study demonstrated the viability of using a continuous image acquisition method on a widely used clinical two-head SPECT system. Our reconstruction method showed better resolved myocardial walls during diastole to systole as compared to the ungated 4D image. Precise implementation of reconstruction algorithms, better segmentation techniques by generating images of different tissue types and background activity would improve the feasibility of the method in real clinical environment.

An Analytical Algorithm for Tensor Tomography From Projections Acquired About Three Axes.

Tensor fields are useful for modeling the structure of biological tissues. The challenge to measure tensor fields involves acquiring sufficient data of scalar measurements that are physically achievable and reconstructing tensors from as few projections as possible for efficient applications in medical imaging. In this paper, we present a filtered back-projection algorithm for the reconstruction of a symmetric second-rank tensor field from directional X-ray projections about three axes. The tensor field is decomposed into a solenoidal and irrotational component, each of three unknowns. Using the Fourier projection theorem, a filtered back-projection algorithm is derived to reconstruct the solenoidal and irrotational components from projections acquired around three axes. A simple illustrative phantom consisting of two spherical shells and a 3D digital cardiac diffusion image obtained from diffusion tensor MRI of an excised human heart are used to simulate directional X-ray projections. The simulations validate the mathematical derivations and demonstrate reasonable noise properties of the algorithm. The decomposition of the tensor field into solenoidal and irrotational components provides insight into the development of algorithms for reconstructing tensor fields with sufficient samples in terms of the type of directional projections and the necessary orbits for the acquisition of the projections of the tensor field.

Accuracy and Reproducibility of Myocardial Blood Flow Quantification by Single Photon Emission Computed Tomography Imaging in Patients With Known or Suspected Coronary Artery Disease.

BACKGROUND: Single photon emission computed tomography (SPECT) has limited ability to identify multivessel and microvascular coronary artery disease. Gamma cameras with cadmium zinc telluride detectors allow the quantification of absolute myocardial blood flow (MBF) and myocardial flow reserve (MFR). However, evidence of its accuracy is limited, and of its reproducibility is lacking. We aimed to validate 99mTc-sestamibi SPECT MBF and MFR using standard and spline-fitted reconstruction algorithms compared with 13N-ammonia positron emission tomography in a cohort of patients with known or suspected coronary artery disease and to evaluate the reproducibility of this technique. METHODS: Accuracy was assessed in 34 participants who underwent dynamic 99mTc-sestamibi SPECT and 13N-ammonia positron emission tomography and reproducibility in 14 participants who underwent 2 99mTc-sestamibi SPECT studies, all within 2 weeks. A rest/pharmacological stress single-day SPECT protocol was performed. SPECT images were reconstructed using a standard ordered subset expectation maximization (OSEM) algorithm with (N=21) and without (N=30) application of spline fitting. SPECT MBF was quantified using a net retention kinetic model' and MFR was derived as the stress/rest MBF ratio. RESULTS: SPECT global MBF with splines showed good correlation with 13N-ammonia positron emission tomography (r=0.81, P<0.001) and MFR estimates (r=0.74, P<0.001). Correlations were substantially weaker for standard reconstruction without splines (r=0.61, P<0.001 and r=0.34, P=0.07, for MBF and MFR, respectively). Reproducibility of global MBF estimates with splines in paired SPECT scans was good (r=0.77, P<0.001), while ordered subset expectation maximization without splines led to decreased MBF (r=0.68, P<0.001) and MFR correlations (r=0.33, P=0.3). There were no significant differences in MBF or MFR between the 2 reproducibility scans independently of the reconstruction algorithm (P>0.05 for all). CONCLUSIONS: MBF and MFR quantification using 99mTc-sestamibi cadmium zinc telluride SPECT with spatiotemporal spline fitting improved the correlation with 13N-ammonia positron emission tomography flow estimates and test/retest reproducibility. The use of splines may represent an important step toward the standardization of SPECT flow estimation.

X-ray bi-prism interferometry-A design study of proposed novel hardware.

PURPOSE: Advances in X-ray phase-contrast imaging can obtain excellent soft-tissue contrast of phase-shift, attenuation, and small-angle scatter. Here, we present fringe patterns for different design parameters of X-ray bi-prism interferometry imaging systems. Our aim is to develop bi-prism interferometry imaging systems with excellent polychromatic performance that produce high-contrast fringes with spatially incoherent X-ray illumination. We also introduce a novel X-ray tube design that uses temporal multiplexing to provide simultaneous virtual "electronic phase stepping" that replace "mechanical phase stepping" popular with grating-based interferometry setups. METHODS: In our investigation, we develop expressions for the irradiance distribution pattern of a bi-prism interferometer composed of multiple point sources and multiple bi-prisms. These expressions are used to plot fringe patterns for X-ray design parameters, including size of point source, number of point sources, and point source separation, and bi-prism design parameters including material, angle, number of bi-prisms, period, and bi-prism array to X-ray source and detector distances. RESULTS: Results show that the fringe patterns for a bi-prism interferometry system are not longitudinally periodic as with grating interferometers that produce a Talbot-Lau carpet. It is also shown that at 59 keV X-rays the bi-prism material should be something comparable to nickel to obtain reasonable fringe visibility. CONCLUSION: The irradiance distribution pattern demonstrates that bi-prism interferometry may provide comparable or improved fringe visibility to that of gratings. Special care is given to present our findings within the context of previous advancements. A single-shot image acquisition approach using a temporal multiplexed, high-power X-ray source provides virtual electronic phase stepping without focal spot sweeping. This provides multiple images, each at the same exposure and the same projection view, from different fringe locations that allow one to derive the attenuation, phase, and dark-field images of the sample without mechanical phase stepping of a grating.

Tomography of dark-field scatter including single-exposure Moiré fringe analysis with X-ray biprism interferometry-A simulation study.

PURPOSE: In this work, we present tomographic simulations of a new hardware concept for X-ray phase-contrast interferometry wherein the phase gratings are replaced with an array of Fresnel biprisms, and Moiré fringe analysis is used instead of "phase stepping" popular with grating-based setups. METHODS: Projections of a phantom consisting of four layers of parallel carbon microfibers is simulated using wave optics representation of X-ray electromagnetic waves. Simulated projections of a phantom with preferential scatter perpendicular to the direction of the fibers are performed to analyze the extraction of small-angle scatter from dark-field projections for the following: (1) biprism interferometry using Moiré fringe analysis; (2) grating interferometry using phase stepping with eight grating steps; and (3) grating interferometry using Moiré fringe analysis. Dark-field projections are modeled as projections of voxel intensities represented by a fixed finite vector basis set of scattering directions. An iterative MLEM algorithm is used to reconstruct, from simulated projection data, the coefficients of a fixed set of seven basis vectors at each voxel representing the small-angle scatter distribution. RESULTS: Results of reconstructed vector coefficients are shown comparing the three simulated imaging configurations. The single-exposure Moiré fringe analysis shows not only an increase in noise because of one-eighth the number of projection samples but also is obtained with less dose and faster acquisition times. Furthermore, replacing grating interferometry with biprism interferometry provides better contrast-to-noise. CONCLUSION: The simulations demonstrate the feasibility of the reconstruction of dark-field data acquired with a biprism interferometry system. With the potential of higher fringe visibility, biprism interferometry with Moiré fringe analysis might provide equal or better image quality to that of phase stepping methods with less imaging time and lower dose.

CT-less Direct Correction of Attenuation and Scatter in the Image Space Using Deep Learning for Whole-Body FDG PET: Potential Benefits and Pitfalls.

PURPOSE: To demonstrate the feasibility of CT-less attenuation and scatter correction (ASC) in the image space using deep learning for whole-body PET, with a focus on the potential benefits and pitfalls. MATERIALS AND METHODS: In this retrospective study, 110 whole-body fluorodeoxyglucose (FDG) PET/CT studies acquired in 107 patients (mean age ± standard deviation, 58 years ± 18; age range, 11-92 years; 72 females) from February 2016 through January 2018 were randomly collected. A total of 37.3% (41 of 110) of the studies showed metastases, with diverse FDG PET findings throughout the whole body. A U-Net-based network was developed for directly transforming noncorrected PET (PETNC) into attenuation- and scatter-corrected PET (PETASC). Deep learning-corrected PET (PETDL) images were quantitatively evaluated by using the standardized uptake value (SUV) of the normalized root mean square error, the peak signal-to-noise ratio, and the structural similarity index, in addition to a joint histogram for statistical analysis. Qualitative reviews by radiologists revealed the potential benefits and pitfalls of this correction method. RESULTS: The normalized root mean square error (0.21 ± 0.05 [mean SUV ± standard deviation]), mean peak signal-to-noise ratio (36.3 ± 3.0), mean structural similarity index (0.98 ± 0.01), and voxelwise correlation (97.62%) of PETDL demonstrated quantitatively high similarity with PETASC. Radiologist reviews revealed the overall quality of PETDL. The potential benefits of PETDL include a radiation dose reduction on follow-up scans and artifact removal in the regions with attenuation correction- and scatter correction-based artifacts. The pitfalls involve potential false-negative results due to blurring or missing lesions or false-positive results due to pseudo-low-uptake patterns. CONCLUSION: Deep learning-based direct ASC at whole-body PET is feasible and potentially can be used to overcome the current limitations of CT-based approaches, benefiting patients who are sensitive to radiation from CT.Supplemental material is available for this article.© RSNA, 2020.

Novel Methodology for Measuring Regional Myocardial Efficiency.

Our approach differs from the usual global measure of cardiac efficiency by using PET/MRI to measure efficiency of small pieces of cardiac tissue whose limiting size is equal to the spatial resolution of the PET scanner. We initiated a dynamic cardiac PET study immediately prior to the injection of 15.1 mCi of 11C-acetate acquiring data for 25 minutes while simultaneously acquiring MRI cine data. 1) A 3D finite element (FE) biomechanical model of the imaged heart was constructed by utilizing nonrigid deformable image registration to alter the Dassault Systèmes FE Living Heart Model (LHM) to fit the geometry in the cardiac MRI cine data. The patient specific FE cardiac model with estimates of stress, strain, and work was transformed into PET/MRI format. 2) A 1-tissue compartment model was used to calculate wash-in (K1) and the linear portion of the decay in the PET 11C-acetate time activity curve (TAC) was used to calculate the wash-out k2(mono) rate constant. K1 was used to calculate blood flow and k2(mono) was used to calculate myocardial volume oxygen consumption ( MVO2 ). 3) Estimates of stress and strain were used to calculate Myocardial Equivalent Minute Work ( MEMW ) and Cardiac Efficiency = MEMW/MVO2 was then calculated for 17 tissue segments of the left ventricle. The global MBF was 0.96 ± 0.15 ml/min/gm and MVO2 ranged from 8 to 17 ml/100gm/min. Six central slices of the MRI cine data provided a range of MEMW of 0.1 to 0.4 joules/gm/min and a range of Cardiac Efficiency of 6 to 18%.

Evaluation of a variable-aperture full-ring SPECT system using large-area pixelated CZT modules: A simulation study for brain SPECT applications.

PURPOSE: Single photon emission computed tomography (SPECT) scanners using cadmium zinc telluride (CZT) offer compact, lightweight, and improved imaging capability over conventional NaI(Tl)-based SPECT scanners. The main purpose in this study is to propose a full-ring SPECT system design with eight large-area CZT detectors that can be used for a broad spectrum of SPECT radiopharmaceuticals and demonstrate the performance of our system in comparison to the reference conventional NaI(Tl)-based two-head Anger cameras. METHODS: A newly designed full-ring SPECT system is composed of eight large-area CZT cameras (128 mm × 179.2 mm effective area) that can be independently swiveled around their own axes of rotation independently and can have radial motion for varying aperture sizes that can be adapted to different sizes of imaging volume. Extended projection data were generated by conjoining projections of two adjacent detectors to overcome the limited field-of-view (FOV) by each CZT camera. Using Monte Carlo simulations, we evaluated this new system design with digital phantoms including a Derenzo hot rod phantom and a Zubal brain phantom. Comparison of performance metrics such as spatial resolution, sensitivity, contrast-to-noise ratio (CNR), and contrast-recovery ratio was made between our design and conventional SPECT scanners having different pixel sizes and radii of rotation (one clinically well-known type and two arbitrary types matched to our proposed CZT-SPECT geometries). RESULTS: The proposed scanner could result in up to about three times faster in acquisition time over conventional scan time at same acquisition time per step. The spatial resolution improvement, or deterioration, of our proposed scanner compared to the clinical-type scanner was dependent upon the location of the point source. However, there were overall performance improvements over the three different setups of the conventional scanner particularly in volume sensitivity (approximately up to 1.7 times). Overall, we successfully reconstructed the phantom image for both 99m Tc-based perfusion and 123 I-based dopamine transporter (DaT) brain studies simulated for our new design. In particular, the striatal/background contrast-recovery ratio in 3-to-1 reference ratio was over 0.8 for the 123 I-based DaT study. CONCLUSIONS: We proposed a variable-aperture full-ring SPECT system using combined pixelated CZT and energy-optimized parallel-hole collimator modules and evaluated the performance of this scanner using relevant digital phantoms and MC simulations. Our studies demonstrated the potential of our new full-ring CZT-SPECT design, showing reduced acquisition time and improved sensitivity with acceptable CNR and spatial resolution.

Direct Image-Based Attenuation Correction using Conditional Generative Adversarial Network for SPECT Myocardial Perfusion Imaging.

Attenuation correction (AC) is important for an accurate interpretation and quantitative analysis of SPECT myocardial perfusion imaging. Dedicated cardiac SPECT systems have invaluable efficacy in the evaluation and risk stratification of patients with known or suspected cardiovascular disease. However, most dedicated cardiac SPECT systems are standalone, not combined with a transmission imaging capability such as computed tomography (CT) for generating attenuation maps for AC. To address this problem, we propose to apply a conditional generative adversarial network (cGAN) for generating attenuation-corrected SPECT images (SPECTGAN ) directly from non-corrected SPECT images (SPECTNC ) in image domain as a one-step process without requiring additional intermediate step. The proposed network was trained and tested for 100 cardiac SPECT/CT data from a GE Discovery NM 570c SPECT/CT, collected retrospectively at Yale New Haven Hospital.The generated images were evaluated quantitatively through the normalized root mean square error (NRMSE), peak signal to noise ratio (PSNR), and structural similarity index (SSIM) and statistically through joint histogram and error maps. In comparison to the reference CT-based correction (SPECTCTAC ), NRMSEs were 0.2258±0.0777 and 0.1410±0.0768 (37.5% reduction of errors); PSNRs 31.7712±2.9965 and 36.3823±3.7424 (14.5% improvement in signal to noise ratio); SSIMs 0.9877±0.0075 and 0.9949±0.0043 (0.7% improvement in structural similarity) for SPECTNC and SPECTGAN , respectively. This work demonstrates that the conditional adversarial training can achieve accurate CT-less attenuation correction for SPECT MPI, that is quantitatively comparable to CTAC. Standalone dedicated cardiac SPECT scanners can benefit from the proposed GAN to reduce attenuation artifacts efficiently.

Direct Attenuation Correction Using Deep Learning for Cardiac SPECT: A Feasibility Study.

Dedicated cardiac SPECT scanners with cadmium-zinc-telluride cameras have shown capabilities for shortened scan times or reduced radiation doses, as well as improved image quality. Since most dedicated scanners do not have integrated CT, image quantification with attenuation correction (AC) is challenging and artifacts are routinely encountered in daily clinical practice. In this work, we demonstrated a direct AC technique using deep learning (DL) for myocardial perfusion imaging (MPI). Methods: In an institutional review board-approved retrospective study, 100 cardiac SPECT/CT datasets with 99mTc-tetrofosmin, obtained using a scanner specifically with a small field of view, were collected at the Yale New Haven Hospital. A convolutional neural network was used for generating DL-based attenuation-corrected SPECT (SPECTDL) directly from noncorrected SPECT (SPECTNC) without undergoing an additional image reconstruction step. The accuracy of SPECTDL was evaluated by voxelwise and segmentwise analyses against the reference, CT-based AC (SPECTCTAC), using the 17-segment myocardial model of the American Heart Association. Polar maps of representative (best, median, and worst) cases were visually compared to illustrate potential benefits and pitfalls of the DL approach. Results: The voxelwise correlations with SPECTCTAC were 92.2% ± 3.7% (slope, 0.87; R2 = 0.81) and 97.7% ± 1.8% (slope, 0.94; R2 = 0.91) for SPECTNC and SPECTDL, respectively. The segmental errors of SPECTNC scattered from -35% to 21% (P < 0.001), whereas the errors of SPECTDL stayed mostly within ±10% (P < 0.001). The average segmental errors (mean ± SD) were -6.11% ± 8.06% and 0.49% ± 4.35% for SPECTNC and SPECTDL, respectively. The average absolute segmental errors were 7.96% ± 6.23% and 3.31% ± 2.87% for SPECTNC and SPECTDL, respectively. Review of polar maps revealed successful reduction of attenuation artifacts; however, the performance of SPECTDL was not consistent for all subjects, likely because of different amounts of attenuation and different uptake patterns. Conclusion: We demonstrated the feasibility of direct AC using DL for SPECT MPI. Overall, our DL approach reduced attenuation artifacts substantially compared with SPECTNC, justifying further studies to establish safety and consistency for clinical applications in stand-alone SPECT systems suffering from attenuation artifacts.

Assessment of late-term progression of cardiac allograft vasculopathy in patients with orthotopic heart transplantation using quantitative cardiac 82Rb PET.

The risk stratification and long-term survival of patients with orthotopic heart transplantation (OHT) is impacted by the complication of cardiac allograft vasculopathy (CAV). This study evaluates changes in myocardial blood flow (MBF) and myocardial coronary flow reserve (CFR) in a group of long-term OHT patients using quantitative cardiac 82Rb-positron emission tomography (PET). Twenty patients (7 females and 13 males, mean age = 72.7 ± 12.2 years with CAV and 62.9 ± 7.2 years without CAV and post-OHT mean time = 13.9 years), were evaluated retrospectively using dynamic cardiac 82Rb-PET at rest and regadenoson-induced stress. The patients also underwent selective coronary angiography (SCA) for diagnosis and risk stratification. CAV was diagnosed based on SCA findings and maximal intimal thickness greater than 0.5 mm, as defined by International Society of Heart and Lung Transplantation (ISHLT). Global and regional MBFs were estimated in three vascular territories using the standard 1-tissue compartment model for dynamic 82Rb-PET. The myocardial CFR was also calculated as the ratio of peak stress MBF to rest MBF. Among twenty patients, seven had CAV in, at least, one major coronary artery (ISHLT CAV grade 1 or higher) while 13 patients did not have CAV (NonCAV). Mean rate-pressure products (RPP) at rest were significantly elevated in CAV patients compared to those without CAV (P = 0.002) but it was insignificant at stress (P = NS). There was no significant difference in the stress MBFs between CAV and NonCAV patients (P = NS). However, the difference in RPP-normalized stress MBFs was significant (P = 0.045), while RPP-normalized MBFs at rest was not significant (P = NS). Both CFR and RPP-normalized CFR were significantly lower in CAV compared to NonCAV patients (P < 0.001). There were significant correlations between MBFs and RPPs at rest for both CAV (ρ = 0.764, P = 0.047) and NonCAV patients (ρ = 0.641, P = 0.017), while there were no correlations at stress for CAV (ρ = 0.232, P = NS) and NonCAV patients (ρ = 0.068, P = NS). This study indicates that the resting MBF is higher in late-term post-OHT patients. The high resting MBF and reduced CFR suggest an unprecedented demand of blood flow and blunted response to stress due to impaired vasodilatory capacity that is exacerbated by the presence of CAV.

Transmural Remodeling of Cardiac Microstructure in Aged Spontaneously Hypertensive Rats by Diffusion Tensor MRI.

The long-standing high blood pressure (also known as hypertension) overworks the heart. Microstructural remodeling is a key factor of hypertensive heart disease progression. Diffusion tensor magnetic resonance imaging (DT-MRI) is a powerful tool for the rapid noninvasive nondestructive delineation of the cardiomyocyte organization. The spontaneously hypertensive rat (SHR) is a well-established model of genetic hypertension. The goal of this study was to employ high-resolution DT-MRI and the SHR animal model to assess the transmural layer-specific remodeling of myocardial microstructure associated with hypertension. Ex vivo experiments were performed on excised formalin-fixed hearts of aged SHRs (n = 4) and age-matched controls (n = 4). The DT-MRI-derived fractional anisotropy (FA), longitudinal diffusivity (λ L ), transversal diffusivity (λ T ), and mean diffusivity (MD) served as the readout parameters investigated at three transmural zones (i.e., endocardium, mesocardium, and epicardium). The helix angles (HAs) of the aggregated cardiomyocytes and the orientation of laminar sheetlets were also studied. Compared with controls, the SHRs exhibited decreased epicardial FA, while FA changes in the other two transmural regions were insignificant. No substantial differences were observed in the diffusivity parameters and the transmural course of HAs between the two groups. A consistent distribution pattern of laminar sheetlet orientation was not identified for either group. Our findings are in line with the known cellular microstructure from early painstaking histological studies. Biophysical explanations of the study outcomes are provided. In conclusion, our experimental findings indicate that the epicardial microstructure is more vulnerable to high blood pressure leading to more pronounced changes in this region during remodeling. DT-MRI is well-suited for elucidating these alterations. The revealed transmural nonuniformity of myocardial reorganization may shed light on the mechanisms of the microstructure-function relationship in hypertension progression. Our results provide insights into the management of patients with systemic arterial hypertension, thus prevent the progression toward heart failure. The findings of this study should be acknowledged by electromechanical models of the heart that simulate the specific cardiac pathology.

Multiresolution spatiotemporal mechanical model of the heart as a prior to constrain the solution for 4D models of the heart.

In several nuclear cardiac imaging applications (SPECT and PET), images are formed by reconstructing tomographic data using an iterative reconstruction algorithm with corrections for physical factors involved in the imaging detection process and with corrections for cardiac and respiratory motion. The physical factors are modeled as coefficients in the matrix of a system of linear equations and include attenuation, scatter, and spatially varying geometric response. The solution to the tomographic problem involves solving the inverse of this system matrix. This requires the design of an iterative reconstruction algorithm with a statistical model that best fits the data acquisition. The most appropriate model is based on a Poisson distribution. Using Bayes Theorem, an iterative reconstruction algorithm is designed to determine the maximum a posteriori estimate of the reconstructed image with constraints that maximizes the Bayesian likelihood function for the Poisson statistical model. The a priori distribution is formulated as the joint entropy (JE) to measure the similarity between the gated cardiac PET image and the cardiac MRI cine image modeled as a FE mechanical model. The developed algorithm shows the potential of using a FE mechanical model of the heart derived from a cardiac MRI cine scan to constrain solutions of gated cardiac PET images.

Joint correction of attenuation and scatter in image space using deep convolutional neural networks for dedicated brain 18F-FDG PET.

Dedicated brain positron emission tomography (PET) devices can provide higher-resolution images with much lower doses compared to conventional whole-body PET systems, which is important to support PET neuroimaging and particularly useful for the diagnosis of neurodegenerative diseases. However, when a dedicated brain PET scanner does not come with a combined CT or transmission source, there is no direct solution for accurate attenuation and scatter correction, both of which are critical for quantitative PET. To address this problem, we propose joint attenuation and scatter correction (ASC) in image space for non-corrected PET (PETNC) using deep convolutional neural networks (DCNNs). This approach is a one-step process, distinct from conventional methods that rely on generating attenuation maps first that are then applied to iterative scatter simulation in sinogram space. For training and validation, time-of-flight PET/MR scans and additional helical CTs were performed for 35 subjects (25/10 split for training and test dataset). A DCNN model was proposed and trained to convert PETNC to DCNN-based ASC PET (PETDCNN) directly in image space. For quantitative evaluation, uptake differences between PETDCNN and reference CT-based ASC PET (PETCT-ASC) were computed for 116 automated anatomical labels (AALs) across 10 test subjects (1160 regions in total). MR-based ASC PET (PETMR-ASC), a current clinical protocol in PET/MR imaging, was another reference for comparison. Statistical significance was assessed using a paired t test. The performance of PETDCNN was comparable to that of PETMR-ASC, in comparison to reference PETCT-ASC. The mean SUV differences (mean ± SD) from PETCT-ASC were 4.0% ± 15.4% (P < 0.001) and -4.2% ± 4.3% (P < 0.001) for PETDCNN and PETMR-ASC, respectively. The overall larger variation of PETDCNN (15.4%) was prone to the subject with the highest mean difference (48.5% ± 10.4%). The mean difference of PETDCNN excluding the subject was substantially improved to -0.8% ± 5.2% (P < 0.001), which was lower than that of PETMR-ASC (-5.07% ± 3.60%, P < 0.001). In conclusion, we demonstrated the feasibility of directly producing PET images corrected for attenuation and scatter using a DCNN (PETDCNN) from PETNC in image space without requiring conventional attenuation map generation and time-consuming scatter correction. Additionally, our DCNN-based method provides a possible alternative to MR-ASC for simultaneous PET/MRI.

A combined static-dynamic single-dose imaging protocol to compare quantitative dynamic SPECT with static conventional SPECT.

BACKGROUND: SPECT myocardial perfusion imaging (MPI) is a clinical mainstay that is typically performed with static imaging protocols and visually or semi-quantitatively assessed for perfusion defects based upon the relative intensity of myocardial regions. Dynamic cardiac SPECT presents a new imaging technique based on time-varying information of radiotracer distribution, which permits the evaluation of regional myocardial blood flow (MBF) and coronary flow reserve (CFR). In this work, a preliminary feasibility study was conducted in a small patient sample designed to implement a unique combined static-dynamic single-dose one-day visit imaging protocol to compare quantitative dynamic SPECT with static conventional SPECT for improving the diagnosis of coronary artery disease (CAD). METHODS: Fifteen patients (11 males, four females, mean age 71 ± 9 years) were enrolled for a combined dynamic and static SPECT (Infinia Hawkeye 4, GE Healthcare) imaging protocol with a single dose of 99mTc-tetrofosmin administered at rest and a single dose administered at stress in a one-day visit. Out of 15 patients, eleven had selective coronary angiography (SCA), 8 within 6 months and the rest within 24 months of SPECT imaging, without intervening symptoms or interventions. The extent and severity of perfusion defects in each myocardial region was graded visually. Dynamically acquired data were also used to estimate the MBF and CFR. Both visually graded images and estimated CFR were tested against SCA as a reference to evaluate the validity of the methods. RESULTS: Overall, conventional static SPECT was normal in ten patients and abnormal in five patients, dynamic SPECT was normal in 12 patients and abnormal in three patients, and CFR from dynamic SPECT was normal in nine patients and abnormal in six patients. Among those 11 patients with SCA, conventional SPECT was normal in 5, 3 with documented CAD on SCA with an overall accuracy of 64%, sensitivity of 40% and specificity of 83%. Dynamic SPECT image analysis also produced a similar accuracy, sensitivity, and specificity. CFR was normal in 6, each with CAD on SCA with an overall accuracy of 91%, sensitivity of 80%, and specificity of 100%. The mean CFR was significantly lower for SCA detected abnormal than for normal patients (3.86±1.06 vs 1.94±0. 0.67, P < 0.001). CONCLUSIONS: The visually assessed image findings in static and dynamic SPECT are subjective, and may not reflect direct physiologic measures of coronary lesion based on SCA. The CFR measured with dynamic SPECT is fully objective, with better sensitivity and specificity, available only with the data generated from the dynamic SPECT method.