Silicon Photomultiplier for the Plug & Imaging PET system: Physics, Technological Challenges and Application to Modern Nuclear Medicine

We propose the design of a Silicon Photomultiplier at the 180 nm GLOBALFOUNDRIES BCDLITE CMOS technology node. We perform a characterization of the device, in comparison with other results obtained a CMOS technology node and we investigate the limits and strengths of this approach. Finally we show possible future applications of the SiPM in Nuclear Medicine, in particular to digital positron emission tomography systems

A New Reduced Basis Method for Parabolic Equations Based on Single-Eigenvalue Acceleration

In this paper, we develop a new reduced basis (RB) method, named as Single Eigenvalue Acceleration Method (SEAM), for second-order parabolic equations with homogeneous Dirichlet boundary conditions. The high-fidelity numerical method adopts the backward Euler scheme and conforming finite elements for the temporal and spatial discretization, respectively. Under the assumption that the time step size is sufficiently small and time steps are not very large, we show that the singular value distribution of the high-fidelity solution matrix $U$ is close to that of a rank one matrix. We select the eigenfunction associated with the principal eigenvalue of the matrix $U^\top U$ as the basis of the Proper Orthogonal Decomposition (POD) method to obtain SEAM and a parallel SEAM. Numerical experiments confirm the efficiency of the new method

Kinetically Consistent Data Assimilation for Plant PET Sparse Time Activity Curve Signals

Time activity curve (TAC) signal processing in plant positron emission tomography (PET) is a frontier nuclear science technique to bring out the quantitative fluid dynamic (FD) flow parameters of the plant vascular system and generate knowledge on crops and their sustainable management, facing the accelerating global climate change. The sparse space-time sampling of the TAC signal impairs the extraction of the FD variables, which can be determined only as averaged values with existing techniques. A data-driven approach based on a reliable FD model has never been formulated. A novel sparse data assimilation digital signal processing method is proposed, with the unique capability of a direct computation of the dynamic evolution of noise correlations between estimated and measured variables, by taking into explicit account the numerical diffusion due to the sparse sampling. The sequential time-stepping procedure estimates the spatial profile of the velocity, the diffusion coefficient and the compartmental exchange rates along the plant stem from the TAC signals. To illustrate the performance of the method, we report an example of the measurement of transport mechanisms in zucchini sprouts

Effect of electro-acupuncture on gene expression in heart of rats with stress-induced pre-hypertension based on gene chip technology

AbstractObjectiveTo explore electro-acupuncture's (EA's) effect on gene expression in heart of rats with stress-induced pre-hypertension and try to reveal its biological mechanism based on gene chip technology.MethodsTwenty-seven Wistar male rats were randomly divided into 3 groups. The stress-induced hypertensive rat model was prepared by electric foot-shocks combined with generated noise. Molding cycle lasted for 14 days and EA intervene was applied on rats in model + EA group during model preparation. Rat Gene 2.0 Sense Target Array technology was used for the determination of gene expression profiles and the screened key genes were verified by real-time quantitative polymerase chain reaction (RT-PCR) method.ResultsCompared with blank control group, 390 genes were changed in model group; compared with model control group, 330 genes were changed in model+EA group. Significance analysis of gene function showed that the differentially expressed genes are those involved in biological process, molecular function and cellular components. RT-PCR result of the screened key genes is consistent with that of gene chip test.ConclutionEA could significantly lower blood pressure of stress-induced pre-hypertension rats and affect its gene expression profile in heart. Genes that related to the contraction of vascular smooth muscle may be involved in EA's anti-hypertensive mechanism

Kinetically Consistent Data Assimilation for Plant PET Sparse Time Activity Curve Signals

Time activity curve (TAC) signal processing in plant positron emission tomography (PET) is a frontier nuclear science technique to bring out the quantitative fluid dynamic (FD) flow parameters of the plant vascular system and generate knowledge on crops and their sustainable management, facing the accelerating global climate change. The sparse space-time sampling of the TAC signal impairs the extraction of the FD variables, which can be determined only as averaged values with existing techniques. A data-driven approach based on a reliable FD model has never been formulated. A novel sparse data assimilation digital signal processing method is proposed, with the unique capability of a direct computation of the dynamic evolution of noise correlations between estimated and measured variables, by taking into explicit account the numerical diffusion due to the sparse sampling. The sequential time-stepping procedure estimates the spatial profile of the velocity, the diffusion coefficient and the compartmental exchange rates along the plant stem from the TAC signals. To illustrate the performance of the method, we report an example of the measurement of transport mechanisms in zucchini sprouts

Incremental prognostic value of ADC histogram analysis in patients with high-risk prostate cancer receiving adjuvant hormonal therapy after radical prostatectomy

PurposeTo investigate the incremental prognostic value of preoperative apparent diffusion coefficient (ADC) histogram analysis in patients with high-risk prostate cancer (PCa) who received adjuvant hormonal therapy (AHT) after radical prostatectomy (RP).MethodsSixty-two PCa patients in line with the criteria were enrolled in this study. The 10th, 50th, and 90th percentiles of ADC (ADC10, ADC50, ADC90), the mean value of ADC (ADCmean), kurtosis, and skewness were obtained from the whole-lesion ADC histogram. The Kaplan–Meier method and Cox regression analysis were used to analyze the relationship between biochemical recurrence-free survival (BCR-fs) and ADC parameters and other clinicopathological factors. Prognostic models were constructed with and without ADC parameters.ResultsThe median follow-up time was 53.4 months (range, 41.1-79.3 months). BCR was found in 19 (30.6%) patients. Kaplan−Meier curves showed that lower ADCmean, ADC10, ADC50, and ADC90 and higher kurtosis could predict poorer BCR-fs (all p<0.05). After adjusting for clinical parameters, ADC50 and kurtosis remained independent prognostic factors for BCR-fs (HR: 0.172, 95% CI: 0.055-0.541, p=0.003; HR: 7.058, 95% CI: 2.288-21.773, p=0.001, respectively). By adding ADC parameters to the clinical model, the C index and diagnostic accuracy for the 24- and 36-month BCR-fs were improved.ConclusionADC histogram analysis has incremental prognostic value in patients with high-risk PCa who received AHT after RP. Combining ADC50, kurtosis and clinical parameters can improve the accuracy of BCR-fs prediction

Quantitative Analysis and Comparison Study of [18F]AlF-NOTA-PRGD2, [18F]FPPRGD2 and [68Ga]Ga-NOTA-PRGD2 Using a Reference Tissue Model

With favorable pharmacokinetics and binding affinity for αvβ3 integrin, 18F-labeled dimeric cyclic RGD peptide ([18F]FPPRGD2) has been intensively used as a PET imaging probe for lesion detection and therapy response monitoring. A recently introduced kit formulation method, which uses an 18F-fluoride-aluminum complex labeled RGD tracer ([18F]AlF-NOTA-PRGD2), provides a strategy for simplifying the labeling procedure to facilitate clinical translation. Meanwhile, an easy-to-prepare 68Ga-labeled NOTA-PRGD2 has also been reported to have promising properties for imaging integrin αvβ3. The purpose of this study is to quantitatively compare the pharmacokinetic parameters of [18F]FPPRGD2, [18F]AlF-NOTA-PRGD2, and [68Ga]Ga-NOTA-PRGD2. U87MG tumor-bearing mice underwent 60-min dynamic PET scans following the injection of three tracers. Kinetic parameters were calculated using Logan graphical analysis with reference tissue. Parametric maps were generated using voxel-level modeling. All three compounds showed high binding potential (BpND = k3/k4) in tumor voxels. [18F]AlF-NOTA-PRGD2 showed comparable BpND value (3.75±0.65) with those of [18F]FPPRGD2 (3.39±0.84) and [68Ga]Ga-NOTA-PRGD2 (3.09±0.21) (p>0.05). Little difference was found in volume of distribution (VT) among these three RGD tracers in tumor, liver and muscle. Parametric maps showed similar kinetic parameters for all three tracers. We also demonstrated that the impact of non-specific binding could be eliminated in the kinetic analysis. Consequently, kinetic parameter estimation showed more comparable results among groups than static image analysis. In conclusion, [18F]AlF-NOTA-PRGD2 and [68Ga]Ga-NOTA-PRGD2 have comparable pharmacokinetics and quantitative parameters compared to those of [18F]FPPRGD2. Despite the apparent difference in tumor uptake (%ID/g determined from static images) and clearance pattern, the actual specific binding component extrapolated from kinetic modeling appears to be comparable for all three dimeric RGD tracers