Quantitative Reproducibility Research Articles

Left ventricular mass on positron emission tomography: Validation against cardiovascular magnetic resonance

BackgroundLeft ventricular hypertrophy (LVH) is an important clinical finding that is independently associated with mortality and cardiovascular events. We aimed to assess the interstudy variability of LV mass quantitation between PET and CMR. MethodsPatients who underwent both PET and CMR within 1 year were identified from prospective institutional registries. LV mass on PET was compared against LV mass on CMR using several statistical measures of agreement. ResultsA total of 105 patients (mean age 60 ± 14 years, 67.6% male) were included. The median (interquartile range, IQR) duration between CMR and PET was 47 (11-154) days. The median (IQR) LV mass values were 168.0 g (126.0-202.0) on CMR and 174.0 g (150.0-212.0) with PET (absolute mean difference 29.42 ± 25.3). There was a good correlation (Spearman ρ = 0.81, P < 0.001; Intraclass Correlation Coefficient 0.78, 95% CI 0.70–0.85, P < 0.001) with moderate limits of agreement (95% limits of agreement − 63.78 to 83.7.) Results were consistent, albeit with moderate correlation, in subgroups of patients with LVH, in patients with myocardial infarction, in patients with LV ejection fraction < 50%, and those with limited image quality. LV mass on PET tended to be underestimated at high values compared to CMR. ConclusionWe demonstrate good correlation and reproducibility of LV mass quantitation by PET against the reference standard of CMR across a wide range of normal and diseased hearts with a tendency of PET to underestimate mass at higher mass values.

Targeted profiling of rodent unconjugated bile acids using GC-MS to determine the influence of high-fat diet.

Unconjugated bile acids (BAs) have gained more attention than conjugated BAs in the association studies among diet, gut microbiota, and diseases. GC-MS is probably a good choice for specialized analysis of unconjugated BAs due to its high separation capacity and identification convenience. However, few reports have focused on the rodent unconjugated BAs using GC-MS, and the main library for identification has not included rodent-specific BAs. We developed a GC-MS method for targeted profiling of eight main unconjugated BAs in rodent models, which showed excellent performance on sensitivity, reproducibility, and accuracy. Quantitative reproducibility in terms of relative standard deviation (RSD) was in the range of 2.05-2.91%, with detection limits of 3-55 ng/mL, quantitation limits of 9-182 ng/mL, and the recovery rate of 72-115%. All the calibration curves displayed good linearity with correlation coefficient values (R2 ) more than 0.99. Using the established method, the influence of high-fat diet on the metabolism of unconjugated BAs was revealed. Significant increase in fecal unconjugated BAs induced by high-fat diet would be a potential risk to gut inflammation and cancer. The study provides a convenient and targeted GC-MS method for specialized profiling of rodent unconjugated BAs in physiological and pathological studies.

Recent Developments in the Diagnosis of Mucormycosis.

Mucormycosis is a potentially fatal infection that presents in different clinical forms and occurs in patients with various risk factors. Recently, the COVID-19 epidemic has been responsible for an increase in the incidence of mucormycosis, particularly in India. As with other invasive filamentous fungal infections, there are no specific clinical or radiological signs, and we have fewer diagnostic tools available than for other invasive fungal infections. Therefore, the diagnosis of Mucormycosis remains difficult. Nevertheless, for optimal management, early and accurate diagnosis is important. According to the latest recommendations, diagnosis is based on direct examination of clinical specimens, and/or histopathology, and culture. There are also molecular tools for direct detection from clinical specimens, but these techniques are moderately recommended. The main problems with these molecular techniques are that, until now, they were not very well standardized; there was a great heterogeneity of DNA targets and methods, which resulted in variable sensitivity. It is in this field that most advances have been made in the last two years. Indeed, recent studies have evaluated the performance and kinetics of Mucorales qPCR in serum and have shown good sensitivity and specificity. Large inter-laboratory evaluations of qPCR in serum have also been performed and have demonstrated good qualitative and quantitative reproducibility. These new results suggest the use of Mucorales qPCR as part of the diagnostic strategy for mucormycosis. One way to achieve better reproducibility could be to use commercial methods. Currently, there are at least three commercial qPCRs for Mucorales (MucorGenius from PathoNostics, MycoGenie from Ademtech, and Fungiplex from Bruker) that can be used to test serum, respiratory samples, or biopsies. However, to date, there has been little evaluation of these methods. Overall, Mucorales PCR in tissue samples, in respiratory samples, and in serum is promising and its addition as a diagnostic tool in the definitions of invasive mucormycosis should be discussed.

Development and validation of a high resolving power absolute quantitative per- and polyfluoroalkyl substances method incorporating Skyline data processing.

RationaleThe ability to perform absolute quantitation and non‐targeted analysis on a single mass spectrometry instrument would be advantageous to many researchers studying per‐ and polyfluoroalkyl substances (PFAS). High‐resolution accurate mass (HRAM) instrumentation (typically deployed for non‐targeted work) carries several advantages over traditional triple quadrupole workflows when performing absolute quantitation. Processing this data using a vendor‐neutral software would promote collaboration for these environmental studies.MethodsLC‐MS (Orbitrap Exploris 240) was used for absolute quantitation of 45 PFAS using precursor (MS1) peak areas for quantitation, whereas isotope pattern matching and fragmentation (MS2) pattern matching were used for qualitative identification. In addition, a fluorinated chromatographic column achieved superior separation compared to the typical C18 columns typically used in PFAS analyses. This method was validated across eight different chemical classes using recommended guidelines found in EPA Method 537.1 and Skyline data processing software.ResultsThe validated limits of all 45 compounds, as well as metrics or accuracy and reproducibility, are reported. Most compounds achieved limits of quantitation in the range of 2‐50 ng/L. Four newly released Chemours‐specific compounds (PEPA, PFO3OA, PFO4DA, and PFO5DoA) were also validated. Aspects of data analysis specific to high resolving power absolute quantitation are reviewed as are the details of processing these data via Skyline.ConclusionsThis method shows the feasibility of performing reproducible absolute quantitation of PFAS on an HRAM platform and does so using an open‐source vendor‐neutral data processing software to facilitate sharing of data across labs and institutions.

A Real-Life Reproducibility Assessment for NMR Metabolomics.

Nuclear magnetic resonance (NMR) metabolomics is currently popular enough to attract both specialized and non-specialized NMR groups involving both analytical trained personnel and newcomers, including undergraduate students. Recent interlaboratory studies performed by established NMR metabolomics groups demonstrated high reproducibility of the state-of-the-art NMR equipment and SOPs. There is, however, no assessment of NMR reproducibility when mixing both analytical experts and newcomers. An interlaboratory assessment of NMR quantitation reproducibility was performed using two NMR instruments belonging to different laboratories and involving several operators with different backgrounds and metabolomics expertise for the purpose of assessing the limiting factors for data reproducibility in a multipurpose NMR environment. The variability induced by the operator, automatic pipettes, NMR tubes and NMR instruments was evaluated in order to assess the limiting factors for quantitation reproducibility. The results estimated the expected reproducibility data in a real-life multipurpose NMR laboratory to a maximum 4% variability, demonstrating that the current NMR equipment and SOPs may compensate some of the operator-induced variability.

Optimization of proteomics sample preparation for identification of host and bacterial proteins in mouse feces.

Bottom-up proteomics is a powerful method for the functional characterization of mouse gut microbiota. To date, most of the bottom-up proteomics studies of the mouse gut rely on limited amounts of fecal samples. With mass-limited samples, the performance of such analyses is highly dependent on the protein extraction protocols and contaminant removal strategies. Here, protein extraction protocols (using different lysis buffers) and contaminant removal strategies (using different types of filters and beads) were systematically evaluated to maximize quantitative reproducibility and the number of identified proteins. Overall, our results recommend a protein extraction method using a combination of sodium dodecyl sulfate (SDS) and urea in Tris-HCl to yield the greatest number of protein identifications. These conditions led to an increase in the number of proteins identified from gram-positive bacteria, such as Firmicutes and Actinobacteria, which is a challenging task. Our analysis further confirmed these conditions led to the extraction of non-abundant bacterial phyla such as Proteobacteria. In addition, we found that, when coupled to our optimized extraction method, suspension trap (S-Trap) outperforms other contaminant removal methods by providing the most reproducible method while producing the greatest number of protein identifications. Overall, our optimized sample preparation workflow is straightforward and fast, and requires minimal sample handling. Furthermore, our approach does not require high amounts of fecal samples, a vital consideration in proteomics studies where mice produce smaller amounts of feces due to a particular physiological condition. Our final method provides efficient digestion of mouse fecal material, is reproducible, and leads to high proteomic coverage for both host and microbiome proteins.

Machine Learning for Scientific Imaging 2022 Conference Overview and Papers Program

Machine learning for scientific imaging is a rapidly growing area of research used to characterize physical, material, chemical, and biological processes in both large and small scale scientific experiments. Physics inspired machine learning differs from more general machine learning research in that it emphasizes quantitative reproducibility and the incorporation of physical models. ML methods used for scientific imaging typically incorporate physics-based imaging processes or physics-based models of the underlying data. These models can be based on partial differential equations (PDEs), integral equations, symmetries or other regularity conditions in two or more dimensions. Physics aware models enhance the ability of the ML methods to generalize and robustly operate in the presence of modeling error, incomplete data, and measurement uncertainty. Contributions to the conference are solicited on topics ranging from fundamental theoretical advances to detailed implementations and novel applications for scientific discovery.

Evaluation of cancer stem cells markers expression in HCC trough real-time polymerase chain reaction.

Quantitative real-time polymerase chain reaction (qRT-PCR) flexibility, robustness and reproducibility have rapidly extended the scope of the method. Cancer stem cells are gaining increasing importance since their role in cancer initiation, treatment resistance and recurrence give rise to a wide range of potential diagnostic and therapeutic applications. The expression of several characteristic markers is proven a reliable method to assess stem-like-phenotype of cancer cells. Here, we provided a thorough protocol for the study of cancer stem cells in hepatocellular carcinoma mouse models and cell cultures using qRT-PCR.

Immuno-MALDI-MS for Accurate Quantitation of Targeted Peptides from Volume-Restricted Samples.

The immuno-MALDI-MS method can be used to quantify low-abundance proteins from clinical samples that offer only a limited amount of material for analysis. An internal standard, in the form of a stable isotope-labeled peptide, is used to ensure reproducible and absolute quantitation. The protocol described here was optimized for the quantitation of AKT1 and AKT2, but we offer instructions on how to adapt the method to target other proteins. The described workflow is compatible with automation via a liquid handling robot for high-throughput applications.

Plug-and-play microfluidic production of monodisperse giant unilamellar vesicles using droplet transfer across Water–Oil interface

Giant unilamellar vesicles (GUVs) are cell-sized compartments widely used in biological and chemical applications. The monodispersity of GUVs is essential for quantitative analysis and experimental reproducibility in biomimetic microreactor studies. In this study, we established a highly reproducible plug-and-play microfluidics-based method to generate monodisperse GUVs without surface treatment of the channel or precise flow-rate adjustment. In the microfluidic channel, we generated water-in-oil (W/O) droplets through hydrodynamic flow focusing and transferred across the W–O interface to form thin-shelled water-in-oil-in-water (W/O/W) droplets as precursors to GUVs. The success rate of the W/O droplet transfer reached nearly 100% by stabilizing the co-flow of oil and water and adjusting the curvature of the W–O interface. Owing to interfacial energy minimization, the thin oil layer of the W/O/W droplets dewetted and detached to form GUVs. We performed a membrane-protein insertion assay to confirm the unilamellarity of the GUVs and their shrinkage caused by osmotic action.

Multiplexed Cross-Linking with Isobaric Quantitative Protein Interaction Reporter Technology.

Chemical cross-linking with mass spectrometry (XL-MS) has emerged as a useful technique for interrogating protein structures and interactions. When combined with quantitative proteomics strategies, protein conformational and interaction dynamics can be probed. Quantitative XL-MS has been demonstrated with the use of stable isotopes incorporated metabolically or into the cross-linker molecules. Isotope-labeled cross-linkers have primarily utilized deuterium and rely on MS1-based quantitation of precursor ion extracted ion chromatograms. Recently the development and application of isobaric quantitative protein interaction reporter (iqPIR) cross-linkers were reported, which utilize 13C and 15N isotope labels. Quantitation is accomplished using relative fragment ion isotope abundances in tandem mass spectra. Here we describe the synthesis and initial evaluation of a multiplexed set of iqPIR molecules, allowing for up to six cross-linked samples to be quantified simultaneously. To analyze data for such cross-linkers, the two-channel mode of iqPIR quantitative analysis was adapted to accommodate any number of channels with defined ion isotope peak mass offsets. The summed ion peak intensities in the overlapping channel isotope envelopes are apportioned among the channels to minimize the difference with respect to the predicted ion isotope envelopes. The result is accurate and reproducible relative quantitation enabling direct comparison among six differentially labeled cross-linked samples. The approach described here is generally extensible for the iqPIR strategy, accommodating future iqPIR reagent design, and enables large-scale in vivo quantitative XL-MS investigation of the interactome.

Automated proteomic sample preparation: The key component for high throughput and quantitative mass spectrometry analysis.

Sample preparation for mass spectrometry-based proteomics has many tedious and time-consuming steps that can introduce analytical errors. In particular, the steps around the proteolytic digestion of protein samples are prone to inconsistency. One route for reliable sample processing is the development and optimization of a workflow utilizing an automated liquid handling workstation. Diligent assessment of the sample type, protocol design, reagents, and incubation conditions can significantly improve the speed and consistency of preparation. When combining robust liquid chromatography-mass spectrometry with either discovery or targeted methods, automated sample preparation facilitates increased throughput and reproducible quantitation of biomarker candidates. These improvements in analysis are also essential to process the large patient cohorts necessary to validate a candidate biomarker for potential clinical use. This article reviews the steps in the workflow, optimization strategies, and known applications in clinical, pharmaceutical, and research fields that demonstrate the broad utility for improved automation of sample preparation in the proteomic field.

Eight-Color Flow Cytometry Phenotypic Markers and Disease Progression in Monoclonal Gammopathy of Unknown Significance

Introduction: Flow cytometric immunophenotyping is considered an indispensable tool for the diagnosis, classification, and monitoring of plasma cell disorders. Herein, we seek to study the clinical significance of expression of phenotype markers in monoclonal gammopathy of unknown significance (MGUS).Methods: We identified a cohort of patients with a diagnosis of MGUS from the institutional myeloma database. Bone marrow (BM) aspirate assessment was performed using 8-color immunophenotypic next-generation flow cytometric (NGF) analysis with a minimum sensitivity of 10 -5 cells at the time of diagnosis or first visit to our institution. BM aspirate samples were immunophenotyped on a FACSCanto II flow cytometer using antibodies (BD) to delineate normal and abnormal plasma cells [CD138 (V-500), CD38 (FITC), CD19 (PE-Cy7), CD45 (V-450), CD27 (PercpCy5.5), CD81 (APC-H-7), CD56 (APC) and CD20 (PE)]. The sensitivity or the Limit of Detection (LOD) for this assay was validated to 20 cells in 2 ×10 6 events (0.001%), and the reproducibility or Lower Limit of Quantitation (LLOQ) is 50 cells in 2 ×10 6 events. Clinical and laboratory variables were also collected. Based on previously published data, expression (CD19, CD45, CD81), and lack of expression (CD56, CD27, CD20) of the above-mentioned surface antigens were analyzed. Additional variables such as IgA isotype, size of M-protein (≥15 g/L), and abnormal free light chain ratio(abnFLR) (defined as <0.1 or >10) were included in regression fitting models.Results: A total of 157 patients with MGUS were included in this analysis. The median age at diagnosis was 60 years (range 24- 84), 84 (53 %) patients were female and 25 (16%) were African American. Overall, IgG Kappa (75/148, 50%) was the most common isotype. Fluorescent-in-situ hybridization (FISH) data were available in 35 patients with t (4:14) and t (14;16) seen in 3 patients each. At a median follow-up of 18.15 years (quantiles 11.35, 33.62), 28 patients experienced disease progression (25 to MM, 2 to Waldenstrom macroglobulinemia, and 1 Smoldering myeloma). The median progression-free survival of this cohort was 17.3 years. Among these, occurrences of the bone lesion (8/28; 28.6%) were the most common pattern of disease progression to MM. This analysis showed lower odds of progression with the expression of CD27 (OR-0.39, 95% CI 0.15-0.99) (figure 1A). Disease progression was more common in patients with an abnormal plasma cell clone size ≥ of 3.1% at diagnosis (60% vs. 12.5%, p=0.0005). An abnormal plasma cell clone of ≥3.1% at diagnosis, was associated with increased odds of progression (OR-10.79, 95% CI 4.02-28.98) and a shorter PFS (12.5 years versus NR, p=0.01) (figure 1B). Serum M-spike ≥1.5 g/dL (OR-3.54;95% 1.30-9.62) and abnFLR (OR-2.30, 95% CI 1.00-5.32) were also associated with a higher odds of progression. However, in this population, the presence of IgA isotype did not increase the odds of MGUS progression. In a stepwise regression model, serum M-spike≥1.5 g/dL, abnFLR, and the lack of expression of CD27 were associated with the risk of disease progression.Conclusion: In addition to previously published risk factors, our cohort shows that the expression of CD27 antigen by eight-color flow cytometry confers a lower risk of disease progression of MGUS. This is consistent with our previous report that CD27 is progressively down-regulated in the transition from normal plasma cells (NPC) to MGUS to MM (Zhan et al, Blood 2006). Furthermore, we show that size of the myeloma clone (≥ 3.1% ) is a possible surrogate marker for disease progression in MGUS.Figure 1: 1A shows forest plot of odds ratios for flow cytometry markers, IgA isotype, size of M protein, abnFLR and plasma cell clone size. 1B shows the Kaplan Meier estimates of PFS for patients stratifies by plasma cell clone size. [Display omitted] DisclosuresMohan: Medical College of Wisconsin: Current Employment. Atrash: GSK: Research Funding; AMGEN: Research Funding; Jansen: Research Funding, Speakers Bureau.

Chemiluminescence Measurement of Reactive Sulfur and Nitrogen Species.

Significance: Reactive sulfur and nitrogen species such as hydrogen sulfide (H2S) and nitric oxide (NO•) are ubiquitous cellular signaling molecules that play central roles in physiology and pathophysiology. A deeper understanding of these signaling pathways will offer new opportunities for therapeutic treatments and disease management. Recent Advances: Chemiluminescence methods have been fundamental in detecting and measuring biological reactive sulfur and nitrogen species, and new approaches are emerging for imaging these analytes in living intact specimens. Ozone-based and luminol-based chemiluminescence methods have been optimized for quantitative analysis of hydrogen sulfide and nitric oxide in biological samples and tissue homogenates, and caged luciferin and 1,2-dioxetanes are emerging as a versatile approach for monitoring and imaging reactive sulfur and nitrogen species in living cells and animal models. Critical Issues: This review article will cover the major chemiluminescence approaches for detecting, measuring, and imaging reactive sulfur and nitrogen species in biological systems, including a brief history of the development of the most established approaches and highlights of the opportunities provided by emerging approaches. Future Directions: Emerging chemiluminescence approaches offer new opportunities for monitoring and imaging reactive sulfur and nitrogen species in living cells, animals, and human clinical samples. Widespread adoption and translation of these approaches, however, requires an emphasis on rigorous quantitative methods, reproducibility, and effective technology transfer. Antioxid. Redox Signal. 36, 337-353.

Comparison of Multiplex Real-Time PCR and Droplet Digital PCR for Detection of Plasma Epstein-Barr Virus DNA in Nasopharyngeal Carcinoma

Plasma Epstein-Barr Virus (EBV) DNA is an established biomarker for endemic nasopharyngeal carcinoma (NPC) and EBV-associated lymphoproliferative disorders. The ongoing NRG-HN001 randomized trial is testing one biomarker-directed treatment approach using real-time PCR (qPCR). Existing qPCR assays are limited by inter-laboratory imprecision secondary to external calibrators, and development of a standardized assay would facilitate reproducible quantitation. We hypothesized that droplet digital PCR (ddPCR) would have similar analytical sensitivity, precision, and accuracy relative to qPCR.We designed a multiplex ddPCR assay to detect two single-copy EBV targets (EBNA-1, EBER), a variable-repeat EBV target (BamHI-W), and a human internal control (RNaseP) in plasma across two reactions. This was compared against the NRG-HN001 qPCR assay, which detects EBNA-1, BamHI-W, and an internal control across two reactions. Quantitation for the ddPCR assay was based on Poisson statistics and automated threshold determination without external calibrators. Quantitation for the qPCR assay was based on two external calibrators traceable to the WHO EBV standard. Assays were compared by measuring sensitivity, specificity, 95% lower limit of detection (LLOD), lower limit of quantitation (LLOQ), accuracy (difference from nominal concentration), and precision (reproducibility). The WHO EBV standard was used as control material. Clinical specimens sent for routine plasma EBV testing were collected from patients with EBV-associated neoplasms. For clinical specimens, a composite reference standard was defined as positivity by at least two targets.The 95% LLOD for BamHI-W, EBNA-1, and EBER ddPCR were 1.49, 13.26, and 9.77 international units (IU) per well, respectively. Analytical sensitivity was not significantly different than BamHI-W qPCR (1.75 IU/well, P = 0.99) or EBNA-1 qPCR (7.58 IU/well, P = 0.60). The LLOQ for both assays was 100 IU/mL. Across the range of prognostic cutoffs for plasma EBV DNA copy number (1,500-40,000 IU/mL), within-laboratory precision was highest with BamHI-W qPCR (0.04-0.06) and ddPCR (0.04-0.08) and lower with EBNA-1 qPCR (0.04-0.14). Across this range, ddPCR had modestly improved accuracy (absolute mean difference from nominal, BamHI-W: 1104 IU/mL; EBER: 1206 IU/mL) relative to qPCR (BamHI-W: 1565 IU/mL; EBNA-1: 1874 IU/mL, P = 0.77 across platforms). Sensitivity (100% vs. 95%, P = 0.50) and specificity (100% vs. 100%) were similar between BamHI-W ddPCR and BamHI-W qPCR for clinical specimens. Sensitivity was lower for all single-copy targets (80-85%).A multiplex ddPCR amplifying single- and variable-copy EBV targets in plasma offers similar analytical performance as the existing NRG-HN001 qPCR assay without the need for external calibrators. Further research will inform whether inter-laboratory precision is superior with ddPCR, which may facilitate standardization of EBV DNA quantitation.

Leveraging homologies for cross-species plasma proteomics in ungulates using data-independent acquisition

The collection of blood plasma is minimally invasive, and the fluid is a rich source of proteins for biomarker studies in both humans and animals. Plasma protein analysis by mass spectrometry (MS) can be challenging, though modern data acquisition strategies, such as sequential window acquisition of all theoretical fragment ion spectra (SWATH), enable reproducible quantitation of hundreds of proteins in non-depleted plasma from humans and laboratory model animals. Although there is strong potential to enhance veterinary and translational research, SWATH-based plasma proteomics in non-laboratory animals is virtually non-existent. One limitation to date is the lack of comprehensively annotated genomes to aid protein identification. The current study established plasma peptide spectral repositories for sheep and cattle that enabled quantification of over 200 proteins in non-depleted plasma using SWATH approach. Moreover, bioinformatics pipeline was developed to leverage inter-species homologies to enhance the depth of baseline libraries and plasma protein quantification in bovids. Finally, the practical utility of using bovid libraries for SWATH data extraction in taxonomically related non-domestic ungulate species (giraffe) has been demonstrated. SignificanceAbility to quickly generate comprehensive spectral libraries is limiting the applicability of data-independent acquisition, such as SWATH, to study proteomes of non-laboratory animals. We describe an approach to obtain relatively shallow foundational plasma repositories from domestic ruminants and employ homology searches to increase the depth of data, which we subsequently extend to unsequenced ungulates using SWATH method. When applied to cross-species proteomics, the number of proteins quantified by our approach far exceeds what is traditionally used in plasma protein tests.

Protocol for safe, affordable, and reproducible isolation and quantitation of SARS-CoV-2 RNA from wastewater.

The following protocol describes our workflow for processing wastewater with the goal of detecting the genetic signal of SARS-CoV-2. The steps include pasteurization, virus concentration, RNA extraction, and quantification by RT-qPCR. We include auxiliary steps that provide new users with tools and strategies that will help troubleshoot key steps in the process. This protocol is one of the safest, cheapest, and most reproducible approaches for the detection of SARS-CoV-2 RNA in wastewater. Owing to a pasteurization step, it is safe for use in a BSL2 facility. In addition to making the protocol safe for the personnel involved, pasteurization had the added benefit of increasing the SARS-CoV-2 genetic signal. Furthermore, the RNA obtained using this protocol can be sequenced using both Sanger and Illumina sequencing technologies. The protocol was adopted by the New York City Department of Environmental Protection in August 2020 to monitor SARS-CoV-2 prevalence in wastewater in all five boroughs of the city. In the future, this protocol could be used to detect a variety of other clinically relevant viruses in wastewater and serve as a foundation of a wastewater surveillance strategy for monitoring community spread of known and emerging viral pathogens.

Calculation of Apparent Diffusion Coefficients in Prostate Cancer Using Deep Learning Algorithms: A Pilot Study.

BackgroundApparent diffusion coefficients (ADCs) obtained with diffusion-weighted imaging (DWI) are highly valuable for the detection and staging of prostate cancer and for assessing the response to treatment. However, DWI suffers from significant anatomic distortions and susceptibility artifacts, resulting in reduced accuracy and reproducibility of the ADC calculations. The current methods for improving the DWI quality are heavily dependent on software, hardware, and additional scan time. Therefore, their clinical application is limited. An accelerated ADC generation method that maintains calculation accuracy and repeatability without heavy dependence on magnetic resonance imaging scanners is of great clinical value.ObjectivesWe aimed to establish and evaluate a supervised learning framework for synthesizing ADC images using generative adversarial networks.MethodsThis prospective study included 200 patients with suspected prostate cancer (training set: 150 patients; test set #1: 50 patients) and 10 healthy volunteers (test set #2) who underwent both full field-of-view (FOV) diffusion-weighted imaging (f-DWI) and zoomed-FOV DWI (z-DWI) with b-values of 50, 1,000, and 1,500 s/mm2. ADC values based on f-DWI and z-DWI (f-ADC and z-ADC) were calculated. Herein we propose an ADC synthesis method based on generative adversarial networks that uses f-DWI with a single b-value to generate synthesized ADC (s-ADC) values using z-ADC as a reference. The image quality of the s-ADC sets was evaluated using the peak signal-to-noise ratio (PSNR), root mean squared error (RMSE), structural similarity (SSIM), and feature similarity (FSIM). The distortions of each ADC set were evaluated using the T2-weighted image reference. The calculation reproducibility of the different ADC sets was compared using the intraclass correlation coefficient. The tumor detection and classification abilities of each ADC set were evaluated using a receiver operating characteristic curve analysis and a Spearman correlation coefficient.ResultsThe s-ADCb1000 had a significantly lower RMSE score and higher PSNR, SSIM, and FSIM scores than the s-ADCb50 and s-ADCb1500 (all P < 0.001). Both z-ADC and s-ADCb1000 had less distortion and better quantitative ADC value reproducibility for all the evaluated tissues, and they demonstrated better tumor detection and classification performance than f-ADC.ConclusionThe deep learning algorithm might be a feasible method for generating ADC maps, as an alternative to z-ADC maps, without depending on hardware systems and additional scan time requirements.

2D and 3D Imaging and Quantification of Mitral Regurgitation

Decisions on techniques used to treat structural heart disease has evolved rapidly, especially in the areas of surgery and noninvasive interventional cardiology. The need for accurate and detailed imaging of these structures has made the roles of cardiac sonographers very dynamic. In order to provide valuable information, which is used in surgical or interventional planning, cardiac sonographers perform a comprehensive transthoracic echocardiogram (TTE) and transesophageal echocardiogram (TEE). However, classifying the severity of regurgitation could be challenging as cardiac structures are three-dimensional (3D), yet most imaging is performed with two-dimensional (2D) modalities. Specifically, in cases where there is a reduction in the functioning of left ventricular (LV), relying only on a single-plane 2D image has limitations and could drastically underestimate the severity of regurgitation. With guidance, newer clinical applications, such as 3D imaging, allows capturing of accurate and reproducible quantitation.

A novel canine nuclear magnetic resonance spectroscopy-based metabolomics platform: Validation and sample handling.

Metabolomics has been proven to be an invaluable research tool by providing comprehensive insight into systemic metabolism. However, the lack of scalable and quantitative methods with known reference intervals (RIs) and documented reproducibility has prevented the use of metabolomics in the clinical setting. The objective of this study was to validate the developed quantitative nuclear magnetic resonance (NMR) spectroscopy-based metabolomics platform for canine serum and plasma samples and determine optimal sample handling conditions for its use. Altogether, 8247 canine samples were analyzed using a Bruker's 500MHz NMR spectrometer. Using statistical approaches derived from international guidelines, we studied method precision, measurand stability in various long- and short-term storage conditions, as well as the effect of prolonged contact with red blood cells (RBCs), and differences among blood collection tubes. We also screened interferences with lipemia, hemolysis, and bilirubinemia. The results were compared against routine clinical chemistry methods, and RIs were defined for all measurands. We determined RIs for 123 measurands, most of which were previously unpublished. The reproducibility of the results of the NMR platform appeared generally outstanding, and the integrity of the results can be ensured by following standard blood drawing and processing guidelines. Owing to the advantages of quantitative results, high reproducibility, and scalability, this canine metabolomics platform holds great potential for numerous clinical and research applications to improve canine health and well-being.