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Head-to-head comparison of the diagnostic performances of Rubidium-PET and SPECT with CZT camera for the detection of myocardial ischemia in a population of women and overweight individuals
摘要： Background. The aim of this study was to compare the diagnostic performances for the detection of myocardial ischemia of 82-Rb-PET-MPS and 99m-Tc-SPECT-MPS in overweight individuals and women. Methods and Results. Men with BMI ≥ 25 and women referred for MPS were considered for inclusion. All individuals underwent 99m-Tc-SPECT-MPS with CZT cameras and 82-Rb-PET-MPS in 3D-mode. Individuals with at least one positive MPS were referred for coronary angiography (CA) with FFR measurements. A criterion for positivity was a composite endpoint including significant stenosis on CA or, in the absence of CA, the occurrence of acute coronary event during the following year. 313 patients (46% women) with mean BMI of 31.8 ± 6.5 were included. Sensitivity for the detection of myocardial ischemia was higher with 82-Rb-PET-MPS compared with 99m-Tc-SPECT-MPS (85% vs. 57%, P < .05); specificity was equally high with both imaging techniques (93% vs. 94%, P > .05). 82-Rb-PET allowed for a more accurate detection of patients with a high-risk coronary artery disease (HR-CAD) than 99m-Tc-SPECT-MPS (AUC = 0.86 vs. 0.75, respectively; P = .04). Conclusions. In women and overweight individuals, 82-Rb-PET-MPS provides higher sensitivity for the detection of myocardial ischemia than 99m-Tc-SPECT-MPS thanks to a better image quality and an improved detection of HR-CAD.
关键词： CZT camera,MPI,Diagnostic and prognostic application,PET,Myocardial blood flow,SPECT,82-Rubidium,CAD
更新于2025-09-23 15:23:52
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Personalized Models for Injected Activity Levels in SPECT Myocardial Perfusion Imaging
摘要： We propose a patient-specific ("personalized") approach for tailoring the injected activities to individual patients in order to achieve dose reduction in SPECT-myocardial perfusion imaging (MPI). First, we develop a strategy to determine the minimum dose levels required for each patient in a large set of clinical acquisitions (857 subjects) such that the reconstructed images are sufficiently similar to that obtained at conventional clinical dose. We then apply machine learning models to predict the required dose levels on an individual basis based on a set of patient attributes which include body measurements and various clinical variables. We demonstrate the personalized dose models for two commonly used reconstruction methods in clinical SPECT-MPI: 1) conventional filtered backprojection (FBP) with post-filtering, and 2) ordered-subsets expectation-maximization (OS-EM) with attenuation, scatter and resolution corrections, and evaluate their performance in perfusion-defect detection by using the clinical Quantitative Perfusion SPECT (QPS) software package. The results indicate that the achieved dose reduction can vary greatly among individuals from their conventional clinical dose, and that the personalized dose models can achieve further reduction on average compared to a global (non-patient specific) dose reduction approach. In particular, the average personalized dose level can be reduced to 58% and 54% of the full clinical dose, respectively, for FBP and OS-EM reconstruction, while without deteriorating in perfusion-defect detection. Furthermore, with the average personalized dose further reduced to only 16% of full dose, OS-EM can still achieve a detection accuracy level comparable to that of FBP with full dose.
关键词： personalized imaging,Dose reduction,SPECT-MPI
更新于2025-09-23 15:19:57
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Efficient thermal finite element modeling of selective laser melting of Inconel 718
摘要： In the powder bed fusion process, an accurate prediction of the transient temperature field of a part is essential to calculate the subsequent thermal stress evolution and microstructure propagation in that part. The experimental method is time-consuming and expensive since the temperature field is controlled by many process parameters. Numerical heat transfer models can be used to estimate the temperature field at any time point. However, traditional numerical simulation schemes are not suitable for the layer-wised fabrication process due to the extremely high computational cost. The computational cost mainly relies on the element number and time step size. This research provides a new efficient and part-level simulation scheme based on an open-source finite element library, which is able to adaptively refine and coarsen the mesh and solve finite element equations with multiple processors in a parallel way. Here, a new mesh strategy that aims to reduce the element number while keeping the solution accuracy is developed. The simulation speed is 12× to 18× faster compared with the traditional simulation scheme depending on the scale of the simulated domain and number of processors. Simulation results have been compared with the experimental results of an Inconel 718 component. It is shown that the testing point in the simulation experiences the same thermal cycles of the same point in the experiment. This simulation scheme can also be used to optimize the process parameters such as scanning pattern, scan velocity, and layer thickness and can be easily extended to other additive manufacturing processes.
关键词： Selective laser melting,Finite element method,MPI,Heat transfer,Adaptive mesh
更新于2025-09-11 14:15:04
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Design and implementation of optical fiber SSD exploiting FPGA accelerated NVMe (May 2019)
摘要： In recent years, GPU-based platforms have received significant success for parallel applications. In addition to highly optimized computation kernels on GPUs, the cost of data movement on GPU clusters plays critical roles in delivering high performance for end applications. Many recent studies have been proposed to optimize the performance of GPU- or CUDA-aware communication runtimes and these designs have been widely adopted in the emerging GPU-based applications. These studies mainly focus on improving the communication performance on native environments, i.e., physical machines, however GPU-based communication schemes on cloud environments are not well studied yet. This paper first investigates the performance characteristics of state-of-the-art GPU-based communication schemes on both native and container-based environments, which show a significant demand to design high-performance container-aware communication schemes in GPU-enabled runtimes to deliver near-native performance for end applications on clouds. Next, we propose the C-GDR approach to design high-performance Container-aware GPUDirect communication schemes on RDMA networks. C-GDR allows communication runtimes to successfully detect process locality, GPU residency, NUMA, architecture information, and communication pattern to enable intelligent and dynamic selection of the best communication and data movement schemes on GPU-enabled clouds. We have integrated C-GDR with the MVAPICH2 library. Our evaluations show that MVAPICH2 with C-GDR has clear performance benefits on container-based cloud environments, compared to default MVAPICH2-GDR and Open MPI. For instance, our proposed C-GDR can outperform default MVAPICH2-GDR schemes by up to 66% on micro-benchmarks and up to 26% on HPC applications over a container-based environment.
关键词： RDMA,Container,MPI,GPU,Cloud Computing
更新于2025-09-11 14:15:04
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[IEEE 2018 New York Scientific Data Summit (NYSDS) - New York, NY, USA (2018.8.6-2018.8.8)] 2018 New York Scientific Data Summit (NYSDS) - High-Performance Multi-Mode Ptychography Reconstruction on Distributed GPUs
摘要： Ptychography is an emerging imaging technique that is able to provide wavelength-limited spatial resolution from specimen with extended lateral dimensions. As a scanning microscopy method, a typical two-dimensional image requires a number of data frames. As a diffraction-based imaging technique, the real-space image has to be recovered through iterative reconstruction algorithms. Due to these two inherent aspects, a ptychographic reconstruction is generally a computation-intensive and time-consuming process, which limits the throughput of this method. We report an accelerated version of the multi-mode difference map algorithm for ptychography reconstruction using multiple distributed GPUs. This approach leverages available scienti?c computing packages in Python, including mpi4py and PyCUDA, with the core computation functions implemented in CUDA C. We ?nd that interestingly even with MPI collective communications, the weak scaling in the number of GPU nodes can still remain nearly constant. Most importantly, for realistic diffraction measurements, we observe a speedup ranging from a factor of 10 to 103 depending on the data size, which reduces the reconstruction time remarkably from hours to typically about 1 minute and is thus critical for real-time data processing and visualization.
关键词： MPI,Python,CUDA,GPU,X-ray ptychography
更新于2025-09-10 09:29:36