The effect of Q.Clear reconstruction on quantification and spatial resolution of 18F-FDG PET in simultaneous PET/MR

Abstract Background Q.Clear is a block sequential regularized expectation maximization penalized-likelihood reconstruction algorithm for Positron Emission Tomography (PET). It has shown high potential in improving image reconstruction quality and quantification accuracy in PET/CT system. However, the evaluation of Q.Clear in PET/MR system, especially for clinical applications, is still rare. This study aimed to evaluate the impact of Q.Clear on the 18F-fluorodeoxyglucose (FDG) PET/MR system and to determine the optimal penalization factor β for clinical use. Methods A PET National Electrical Manufacturers Association/ International Electrotechnical Commission (NEMA/IEC) phantom was scanned on GE SIGNA PET/MR, based on NEMA NU 2-2012 standard. Metrics including contrast recovery (CR), background variability (BV), signal-to-noise ratio (SNR) and spatial resolution were evaluated for phantom data. For clinical data, lesion SNR, signal to background ratio (SBR), noise level and visual scores were evaluated. PET images reconstructed from OSEM + TOF and Q.Clear were visually compared and statistically analyzed, where OSEM + TOF adopted point spread function as default procedure, and Q.Clear used different β values of 100, 200, 300, 400, 500, 800, 1100 and 1400. Results For phantom data, as β value increased, CR and BV of all sizes of spheres decreased in general; images reconstructed from Q.Clear reached the peak SNR with β value of 400 and generally had better resolution than those from OSEM + TOF. For clinical data, compared with OSEM + TOF, Q.Clear with β value of 400 achieved 138% increment in median SNR (from 58.8 to 166.0), 59% increment in median SBR (from 4.2 to 6.8) and 38% decrement in median noise level (from 0.14 to 0.09). Based on visual assessment from two physicians, Q.Clear with β values ranging from 200 to 400 consistently achieved higher scores than OSEM + TOF, where β value of 400 was considered optimal. Conclusions The present study indicated that, on 18F-FDG PET/MR, Q.Clear reconstruction improved the image quality compared to OSEM + TOF. β value of 400 was optimal for Q.Clear reconstruction.

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Assessment of the Impacts of Image Signal-to-Noise Ratios in Impervious Surface Mapping

Remote Sensing ◽

10.3390/rs11222603 ◽

2019 ◽

Vol 11 (22) ◽

pp. 2603

Author(s):

George Xian ◽

Hua Shi ◽

Cody Anderson ◽

Zhuoting Wu

Keyword(s):

Spatial Resolution ◽

Signal To Noise Ratio ◽

Spatial Scales ◽

Regression Tree ◽

Remote Sensing Data ◽

Impervious Surface ◽

Landsat 8 ◽

Signal To Noise ◽

Study Results ◽

The Impact

Medium spatial resolution satellite images are frequently used to characterize thematic land cover and a continuous field at both regional and global scales. However, high spatial resolution remote sensing data can provide details in landscape structures, especially in the urban environment. With upgrades to spatial resolution and spectral coverage for many satellite sensors, the impact of the signal-to-noise ratio (SNR) in characterizing a landscape with highly heterogeneous features at the sub-pixel level is still uncertain. This study used WorldView-3 (WV3) images as a basis to evaluate the impacts of SNR on mapping a fractional developed impervious surface area (ISA). The point spread function (PSF) from the Landsat 8 Operational Land Imager (OLI) was used to resample the WV3 images to three different resolutions: 10 m, 20 m, and 30 m. Noise was then added to the resampled WV3 images to simulate different fractional levels of OLI SNRs. Furthermore, regression tree algorithms were incorporated into these images to estimate the ISA at different spatial scales. The study results showed that the total areal estimate could be improved by about 1% and 0.4% at 10-m spatial resolutions in our two study areas when the SNR changes from half to twice that of the Landsat OLI SNR level. Such improvement is more obvious in the high imperviousness ranges. The root-mean-square-error of ISA estimates using images that have twice and two-thirds the SNRs of OLI varied consistently from high to low when spatial resolutions changed from 10 m to 20 m. The increase of SNR, however, did not improve the overall performance of ISA estimates at 30 m.

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A Study of Membrane Impact on Spatial Resolution of Liquid In Situ Transmission Electron Microscope

Microscopy and Microanalysis ◽

10.1017/s143192761901523x ◽

2020 ◽

Vol 26 (1) ◽

pp. 126-133

Author(s):

Ming Li ◽

Ruth Knibbe

Keyword(s):

Electron Microscope ◽

Spatial Resolution ◽

Transmission Electron Microscope ◽

Signal To Noise Ratio ◽

Chromatic Aberration ◽

Membrane Thickness ◽

Additional Material ◽

Transmission Electron ◽

The Impact

AbstractMicrochip technology with electron transparent membranes is a key component for in situ liquid transmission electron microscope (TEM) characterization. The membranes can significantly influence the TEM imaging spatial resolution, not only due to introducing additional material layers but also due to the associated bulging. The membrane bulging is largely defined by the membrane materials, thickness, and short dimension. The impact of the membrane on the spatial resolution, especially the extent of its bulging, was systematically investigated through the impact on the signal-to-noise ratio, chromatic aberration, and beam broadening. The optimization of the membrane parameters is the key component when designing the in situ TEM liquid cell. The optimal membrane thickness of 50 nm was found which balances the impact of membrane bulging and membrane thickness. Beyond this, the short membrane window dimension and the chip nominal spacing should be minimized. However, these two parameters have practical limitations in regards to chip handling.

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The Impact of Bayesian Penalized Likelihood Reconstruction Algorithm on Quantitative Accuracy of Positron Emission Tomography Volumetric Measurements

10.21203/rs.3.rs-68767/v1 ◽

2020 ◽

Author(s):

Liang Chen ◽

Dongfang Chen ◽

Tao Huang ◽

Cen Lou

Keyword(s):

Positron Emission Tomography ◽

Measurement Errors ◽

Measurement Accuracy ◽

Penalized Likelihood ◽

Reconstruction Algorithm ◽

Emission Tomography ◽

International Electrotechnical Commission ◽

Positron Emission ◽

Significant Difference ◽

The Impact

Abstract Objectives The metabolic tumor volume (MTV) of positron emission tomography/computed tomography (PET/CT) is an important index to evaluate the prognosis and the responses of treatments. The purpose of this study is to assess the impact of Bayesian Penalized Likelihood (BPL) reconstruction algorithm and segmentation methods on the accuracy of MTV via a phantom study.Methods Using the National Electrical Manufactures Association/International Electrotechnical Commission (NEMA/IEC) image quality phantom, six hot spheres and background were filled with 21.56 KBq/ml and 5.39 KBq/ml Na 18 F (a sphere to background ratio of 4: 1). Acquired images were reconstructed using BPL (β = 400) and non-BPL (Ordered subsets expectation maximization + time of flight + point spread function, OSEM+TOF+PSF) algorithms, respectively. MTVs of six spheres were delineated using maximum standardized uptake value (SUV max ) percentage threshold method and iterative adaptive method, respectively. The actual measured volumes of spheres were used as the standard for comparative analysis.Results The MTVs measurement errors in BPL were 4.96%, -3.00%, 6.18%, 5.20%, -10.00% and 18.33%, which was significantly lower than that in non-BPL ( Z = - 2.562, p = 0.009), and the measurement errors in non-BPL were 16.70%, 10.77%, 26.00%, 30.00%, 61.82% and 113.33%. The optimal percentage SUV max threshold of spheres in BPL algorithm was raged in 40% - 45%, which was not affected by the ball size. And there was no significant difference of MTVs measurement accuracy between the 42%SUV max and iterative adaptive threshold (Z = -0.48, p = 0.699). However, using the non-BPL algorithm, the measurement errors of 42%SUV max and iterative adaptive delineation methods were 16.70%, 10.77%, 26.00%, 30.00%, 61.82%, 113.33%, and -7.70%, -9.00%, -8.73%, -5.20%, -12.91%, 38.33% respectively. The MTVs measurement accuracy of iterative adaptive was significantly better than that of the 42%SUV max threshold (Z = -2.24, p = 0.026). The iterative adaptive and 42%SUV max threshold methods had excellent interobserver reliability (ICCs=1.00 for all of six spheres) for MTVs measurement.Conclusion BPL reconstruction algorithm can improve the accuracy of MTVs measurements, especially for small lesions. In the case of using non-BPL methods, the iterative adaptive delineation method should be adopted to improve the accuracy of MTVs measurements.

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The Impact of a Bayesian Penalized Likelihood Reconstruction Algorithm on the Evaluation of Indeterminate Pulmonary Nodules by Dual–Time Point 18F-FDG PET/CT

Clinical Nuclear Medicine ◽

10.1097/rlu.0000000000001713 ◽

2017 ◽

Vol 42 (7) ◽

pp. e352-e354 ◽

Cited By ~ 6

Author(s):

Tiago Sampaio Vieira ◽

Diogo Borges Faria ◽

Fernando Azevedo Silva ◽

Francisco Pimentel ◽

José Pereira de Oliveira

Keyword(s):

Fdg Pet ◽

Penalized Likelihood ◽

Pulmonary Nodules ◽

Reconstruction Algorithm ◽

Pet Ct ◽

18F Fdg ◽

Dual Time Point ◽

Fdg Pet Ct ◽

The Impact ◽

Time Point

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Optimization of Spatial Resolution and Image Reconstruction Parameters for the Small-Animal MetisTM PET/CT System

10.21203/rs.3.rs-1228467/v1 ◽

2022 ◽

Author(s):

Jie Zhao ◽

Qiong Liu ◽

Chaofan Li ◽

Yunfeng Song ◽

Ying Zhang ◽

...

Keyword(s):

Image Reconstruction ◽

Image Quality ◽

Spatial Resolution ◽

Small Animal ◽

Reconstruction Algorithm ◽

Visual Assessment ◽

Pet Ct ◽

Noise Ratio ◽

Ct System ◽

Post Filter

Abstract The aim of this study was to investigate the optimization of spatial resolution and image reconstruction parameters related to image quality in an iterative reconstruction algorithm for the small-animal MetisTM PET/CT system. We used a homemade Derenzo phantom to evaluate the image quality by visual assessment, signal-to-noise ratio, contrast, coefficient of variation, and contrast-to-noise ratio of the 0.8 mm hot rods of 8 slices in the centre of the phantom PET images. A healthy mouse study was performed to analyze the influence of optimal reconstruction parameters and Gaussian post-filter FWHM. In the phantom study, the best image quality was obtained by placing the phantom at one end, keeping the central axis parallel to X-axis of the system, selecting iterations between 30 and 40, with a reconstruction voxel of 0.314 mm and a Gaussian post-filter FWHM of 1.57 mm. The optimization of spatial resolution can reach 0.6-mm. In the animal study, it was suitable to choose a voxel size of 0.472-mm, iterations between 30 and 40, and 2.36-mm Gaussian post-filter FWHM. Our results indicate that optimal imaging conditions and reconstruction parameters are necessary to obtain high-resolution images and quantitative accuracy, especially for the high-precision identification of tiny lesions.

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Nondestructive Inspection of Thin, Low-Z Samples using Multiplexed Compton Scatter Tomography

MRS Proceedings ◽

10.1557/proc-503-297 ◽

1997 ◽

Vol 503 ◽

Cited By ~ 1

Author(s):

B. L. Evans ◽

J. B. Martin ◽

L. W. Burggraf

Keyword(s):

Signal To Noise Ratio ◽

Reconstruction Algorithm ◽

Filtered Backprojection ◽

Line Broadening ◽

Compton Scatter ◽

X Ray ◽

Tomography System ◽

Transmission Computed Tomography ◽

High Purity Germanium ◽

Scattered Energy

ABSTRACTThe viability of a Compton scattering tomography system for nondestructively inspecting thin, low Z samples for corrosion is examined. This technique differs from conventional x-ray backscatter NDI because it does not rely on narrow collimation of source and detectors to examine small volumes in the sample. Instead, photons of a single energy are backscattered from the sample and their scattered energy spectra are measured at multiple detector locations, and these spectra are then used to reconstruct an image of the object. This multiplexed Compton scatter tomography technique interrogates multiple volume elements simultaneously. Thin samples less than 1 cm thick and made of low Z materials are best imaged with gamma rays at or below 100 keV energy. At this energy, Compton line broadening becomes an important resolution limitation. An analytical model has been developed to simulate the signals collected in a demonstration system consisting of an array of planar high-purity germanium detectors. A technique for deconvolving the effects of Compton broadening and detector energy resolution from signals with additive noise is also presented. A filtered backprojection image reconstruction algorithm with similarities to that used in conventional transmission computed tomography is developed. A simulation of a 360–degree inspection gives distortion-free results. In a simulation of a single-sided inspection, a 5 mm × 5 mm corrosion flaw with 50% density is readily identified in 1-cm thick aluminum phantom when the signal to noise ratio in the data exceeds 28.

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The impact of a multi-domain intervention on cerebral glucose metabolism: analysis from the randomized ancillary FDG PET MAPT trial

Alzheimer s Research & Therapy ◽

10.1186/s13195-020-00683-6 ◽

2020 ◽

Vol 12 (1) ◽

Author(s):

Julien Delrieu ◽

Thierry Voisin ◽

Laure Saint-Aubert ◽

Isabelle Carrie ◽

Christelle Cantet ◽

...

Keyword(s):

Glucose Metabolism ◽

Fdg Pet ◽

Primary Outcome ◽

Cognitive Stimulation ◽

Cerebral Glucose Metabolism ◽

Parahippocampal Gyrus ◽

Cerebral Magnetic Resonance Imaging ◽

Brain Glucose ◽

Brain Glucose Metabolism ◽

The Impact

Abstract Background The Multidomain Alzheimer Preventive Trial (MAPT) was designed to assess the efficacy of omega-3 fatty acid supplementation, multidomain intervention (MI), or a combination of both on cognition. Although the MAPT study was negative, an effect of MI in maintaining cognitive functions compared to placebo group was showed in positive amyloid subjects. A FDG PET study (MAPT-NI) was implemented to test the impact of MI on brain glucose metabolism. Methods MAPT-NI was a randomized, controlled parallel-group single-center study, exploring the effect of MI on brain glucose metabolism. Participants were non-demented and had memory complaints, limitation in one instrumental activity of daily living, or slow gait. Participants were randomly assigned (1:1) to “MI group” or “No MI group.” The MI consisted of group sessions focusing on 3 domains: cognitive stimulation, physical activity, nutrition, and a preventive consultation. [18F]FDG PET scans were performed at baseline, 6 months, and 12 months, and cerebral magnetic resonance imaging scans at baseline. The primary objective was to evaluate the MI effect on brain glucose metabolism assessed by [18F]FDG PET imaging at 6 months. The primary outcome was the quantification of regional metabolism rate for glucose in cerebral regions involved early in Alzheimer disease by relative semi-quantitative SUVr (FDG-based AD biomarker). An exploratory voxel-wise analysis was performed to assess the effect of MI on brain glucose metabolism without anatomical hypothesis. Results The intention-to-treat population included 67 subjects (34 in the MI group and 33 in the No MI group. No significant MI effect was observed on primary outcome at 6 months. In the exploratory voxel-wise analysis, we observed a difference in favor of MI group on the change of cerebral glucose metabolism in limbic lobe (right hippocampus, right posterior cingulate, left posterior parahippocampal gyrus) at 6 months. Conclusions MI failed to show an effect on metabolism in FDG-based AD biomarker, but exploratory analysis suggested positive effect on limbic system metabolism. This finding could suggest a delay effect of MI on AD progression. Trial registration ClinicalTrials.gov Identifier, NCT01513252.

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The impact of particulate electron paramagnetic resonance oxygen sensors on fluorodeoxyglucose imaging characteristics detected via positron emission tomography

Scientific Reports ◽

10.1038/s41598-021-82754-8 ◽

2021 ◽

Vol 11 (1) ◽

Author(s):

Philip E. Schaner ◽

Ly-Binh-An Tran ◽

Bassem I. Zaki ◽

Harold M. Swartz ◽

Eugene Demidenko ◽

...

Keyword(s):

Fdg Pet ◽

Oxygen Sensor ◽

Oxygen Sensors ◽

Paramagnetic Resonance ◽

Imaging Characteristics ◽

Positron Emission ◽

Pet Ct ◽

Fdg Pet Ct ◽

The Impact ◽

Electron Paramagnetic

AbstractDuring a first-in-humans clinical trial investigating electron paramagnetic resonance tumor oximetry, a patient injected with the particulate oxygen sensor Printex ink was found to have unexpected fluorodeoxyglucose (FDG) uptake in a dermal nodule via positron emission tomography (PET). This nodule co-localized with the Printex ink injection; biopsy of the area, due to concern for malignancy, revealed findings consistent with ink and an associated inflammatory reaction. Investigations were subsequently performed to assess the impact of oxygen sensors on FDG-PET/CT imaging. A retrospective analysis of three clinical tumor oximetry trials involving two oxygen sensors (charcoal particulates and LiNc-BuO microcrystals) in 22 patients was performed to evaluate FDG imaging characteristics. The impact of clinically used oxygen sensors (carbon black, charcoal particulates, LiNc-BuO microcrystals) on FDG-PET/CT imaging after implantation in rat muscle (n = 12) was investigated. The retrospective review revealed no other patients with FDG avidity associated with particulate sensors. The preclinical investigation found no injected oxygen sensor whose mean standard uptake values differed significantly from sham injections. The risk of a false-positive FDG-PET/CT scan due to oxygen sensors appears low. However, in the right clinical context the potential exists that an associated inflammatory reaction may confound interpretation.

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Prognostic implications of troponin T variations in inherited cardiomyopathies using systems biology

npj Genomic Medicine ◽

10.1038/s41525-021-00204-w ◽

2021 ◽

Vol 6 (1) ◽

Author(s):

Rameen Shakur ◽

Juan Pablo Ochoa ◽

Alan J. Robinson ◽

Abhishek Niroula ◽

Aneesh Chandran ◽

...

Keyword(s):

Heart Failure ◽

Systems Biology ◽

Sudden Cardiac Death ◽

Risk Stratification ◽

Clinical Data ◽

Cardiac Death ◽

Troponin T ◽

Management Options ◽

Familial Cardiomyopathy ◽

The Impact

AbstractThe cardiac troponin T variations have often been used as an example of the application of clinical genotyping for prognostication and risk stratification measures for the management of patients with a family history of sudden cardiac death or familial cardiomyopathy. Given the disparity in patient outcomes and therapy options, we investigated the impact of variations on the intermolecular interactions across the thin filament complex as an example of an unbiased systems biology method to better define clinical prognosis to aid future management options. We present a novel unbiased dynamic model to define and analyse the functional, structural and physico-chemical consequences of genetic variations among the troponins. This was subsequently integrated with clinical data from accessible global multi-centre systematic reviews of familial cardiomyopathy cases from 106 articles of the literature: 136 disease-causing variations pertaining to 981 global clinical cases. Troponin T variations showed distinct pathogenic hotspots for dilated and hypertrophic cardiomyopathies; considering the causes of cardiovascular death separately, there was a worse survival in terms of sudden cardiac death for patients with a variation at regions 90–129 and 130–179 when compared to amino acids 1–89 and 200–288. Our data support variations among 90–130 as being a hotspot for sudden cardiac death and the region 131–179 for heart failure death/transplantation outcomes wherein the most common phenotype was dilated cardiomyopathy. Survival analysis into regions of high risk (regions 90–129 and 130–180) and low risk (regions 1–89 and 200–288) was significant for sudden cardiac death (p = 0.011) and for heart failure death/transplant (p = 0.028). Our integrative genomic, structural, model from genotype to clinical data integration has implications for enhancing clinical genomics methodologies to improve risk stratification.

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Model-based reconstruction algorithm in the detection of acute trauma-related lesions in brain CT examinations

The Neuroradiology Journal ◽

10.1177/19714009211008751 ◽

2021 ◽

pp. 197140092110087

Author(s):

Andrea De Vito ◽

Cesare Maino ◽

Sophie Lombardi ◽

Maria Ragusi ◽

Cammillo Talei Franzesi ◽

...

Keyword(s):

Image Quality ◽

Iterative Reconstruction ◽

Signal To Noise Ratio ◽

Reconstruction Algorithm ◽

Signal To Noise ◽

Subjective Image Quality ◽

Model Based ◽

Hybrid Iterative Reconstruction ◽

Noise Ratio ◽

Enhanced Computed Tomography

Background and purpose To evaluate the added value of a model-based reconstruction algorithm in the assessment of acute traumatic brain lesions in emergency non-enhanced computed tomography, in comparison with a standard hybrid iterative reconstruction approach. Materials and methods We retrospectively evaluated a total of 350 patients who underwent a 256-row non-enhanced computed tomography scan at the emergency department for brain trauma. Images were reconstructed both with hybrid and model-based iterative algorithm. Two radiologists, blinded to clinical data, recorded the presence, nature, number, and location of acute findings. Subjective image quality was performed using a 4-point scale. Objective image quality was determined by computing the signal-to-noise ratio and contrast-to-noise ratio. The agreement between the two readers was evaluated using k-statistics. Results A subjective image quality analysis using model-based iterative reconstruction gave a higher detection rate of acute trauma-related lesions in comparison to hybrid iterative reconstruction (extradural haematomas 116 vs. 68, subdural haemorrhages 162 vs. 98, subarachnoid haemorrhages 118 vs. 78, parenchymal haemorrhages 94 vs. 64, contusive lesions 36 vs. 28, diffuse axonal injuries 75 vs. 31; all P<0.001). Inter-observer agreement was moderate to excellent in evaluating all injuries (extradural haematomas k=0.79, subdural haemorrhages k=0.82, subarachnoid haemorrhages k=0.91, parenchymal haemorrhages k=0.98, contusive lesions k=0.88, diffuse axonal injuries k=0.70). Quantitatively, the mean standard deviation of the thalamus on model-based iterative reconstruction images was lower in comparison to hybrid iterative one (2.12 ± 0.92 vsa 3.52 ± 1.10; P=0.030) while the contrast-to-noise ratio and signal-to-noise ratio were significantly higher (contrast-to-noise ratio 3.06 ± 0.55 vs. 1.55 ± 0.68, signal-to-noise ratio 14.51 ± 1.78 vs. 8.62 ± 1.88; P<0.0001). Median subjective image quality values for model-based iterative reconstruction were significantly higher ( P=0.003). Conclusion Model-based iterative reconstruction, offering a higher image quality at a thinner slice, allowed the identification of a higher number of acute traumatic lesions than hybrid iterative reconstruction, with a significant reduction of noise.

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