In-house Developed Tool Research Articles

EmiRIT: a text-mining-based resource for microRNA information.

microRNAs (miRNAs) are essential gene regulators, and their dysregulation often leads to diseases. Easy access to miRNA information is crucial for interpreting generated experimental data, connecting facts across publications and developing new hypotheses built on previous knowledge. Here, we present extracting miRNA Information from Text (emiRIT), a text-miningbased resource, which presents miRNA information mined from the literature through a user-friendly interface. We collected 149 ,233 miRNA –PubMed ID pairs from Medline between January 1997 and May 2020. emiRIT currently contains ‘miRNA –gene regulation’ (69 ,152 relations), ‘miRNA disease (cancer)’ (12 ,300 relations), ‘miRNA –biological process and pathways’ (23, 390 relations) and circulatory ‘miRNAs in extracellular locations’ (3782 relations). Biological entities and their relation to miRNAs were extracted from Medline abstracts using publicly available and in-house developed text-mining tools, and the entities were normalized to facilitate querying and integration. We built a database and an interface to store and access the integrated data, respectively. We provide an up-to-date and user-friendly resource to facilitate access to comprehensive miRNA information from the literature on a large scale, enabling users to navigate through different roles of miRNA and examine them in a context specific to their information needs. To assess our resource’s information coverage, we have conducted two case studies focusing on the target and differential expression information of miRNAs in the context of cancer and a third case study to assess the usage of emiRIT in the curation of miRNA information. Database URL: https://research.bioinformatics.udel.edu/emirit/

The polybasic insert, the RBD of the SARS-CoV-2 spike protein, and the feline coronavirus – evolved or yet to evolve

Recent research on the SARS-CoV-2 pandemic has exploded around the furin-cleavable polybasic insert PRRAR↓S, found within the spike protein. The insert and the receptor-binding domain, (RBD), are vital clues in the Sherlock Holmes-like investigation into the origin of the virus and in its zoonotic crossover. Based on comparative analysis of the whole genome and the sequence features of the insert and the RBD domain, the bat and the pangolin have been proposed as very likely intermediary hosts. In this study, using the various databases, in-house developed tools, sequence comparisons, structure-guided docking, and molecular dynamics simulations, we cautiously present a fresh, theoretical perspective on the SARS-CoV-2 virus activation and its intermediary host. They are a) the SARS-CoV-2 has not yet acquired a fully optimal furin binding site or this seemingly less optimal sequence, PRRARS, has been selected for survival; b) in structural models of furin complexed with peptides, PRRAR↓S binds less well and with distinct differences as compared to the all basic RRKRR↓S; c) these differences may be exploited for the design of virus-specific inhibitors; d) the novel polybasic insert of SARS-CoV-2 may be promiscuous enough to be cleaved by multiple enzymes of the human airway epithelium and tissues which may explain its unexpected broad tropism; e) the RBD domain of the feline coronavirus spike protein carries residues that are responsible for high-affinity binding of the SARS-CoV-2 to the ACE 2 receptor; f) en route zoonotic transfer, the virus may have passed through the domestic cat whose very human-like ACE2 receptor and furin may have played some role in optimizing the traits required for zoonotic transfer.

Tools and methodologies for box-wing aircraft conceptual aerodynamic design and aeromechanic analysis

A way to face the challenge of moving towards a new greener aviation is to exploit disruptive aircraft architectures; one of the most promising concept is the PrandtlPlane, a box-wing aircraft based on the Prandtl's studies on multiplane lifting systems. A box-wing designed accordingly the Prandtl “best wing system” minimizes the induced drag for given lift and span, and thus it has the potential to reduce fuel consumption and noxious emissions. For disruptive aerodynamic concepts, physic-based aerodynamic design is needed from the very early stages of the design process, because of the lack of available statistical data; this paper describes two different in-house developed aerodynamic design tools for the PrandtlPlane conceptual aerodynamic design: AEROSTATE, for the design of the box-wing lifting system in cruise condition, and THeLMA, aiming to define the layout of control surfaces and high lift devices. These two tools have been extensively used to explore the feasible space for the aerodynamic design of the box-wing architecture, aiming to define preliminary correlations between performance and design variables, and guidelines to properly initialize the design process. As a result, relevant correlations have been identified between the rear-front wing loading ratio and the performance in cruise condition, and for the rear-front flap deflections and the aeromechanic characteristics in low speed condition.

Screening of world approved drugs against highly dynamical spike glycoprotein of SARS-CoV-2 using CaverDock and machine learning

The new severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) causes pathological pulmonary symptoms. Most efforts to develop vaccines and drugs against this virus target the spike glycoprotein, particularly its S1 subunit, which is recognised by angiotensin-converting enzyme 2. Here we use the in-house developed tool CaverDock to perform virtual screening against spike glycoprotein using a cryogenic electron microscopy structure (PDB-ID: 6VXX) and the representative structures of five most populated clusters from a previously published molecular dynamics simulation. The dataset of ligands was obtained from the ZINC database and consists of drugs approved for clinical use worldwide. Trajectories for the passage of individual drugs through the tunnel of the spike glycoprotein homotrimer, their binding energies within the tunnel, and the duration of their contacts with the trimer’s three subunits were computed for the full dataset. Multivariate statistical methods were then used to establish structure-activity relationships and select top candidate for movement inhibition. This new protocol for the rapid screening of globally approved drugs (4359 ligands) in a multi-state protein structure (6 states) showed high robustness in the rate of finished calculations. The protocol is universal and can be applied to any target protein with an experimental tertiary structure containing protein tunnels or channels. The protocol will be implemented in the next version of CaverWeb (https://loschmidt.chemi.muni.cz/caverweb/) to make it accessible to the wider scientific community.

Quantifying the Influence of the Electrode Porous Structure on Lithium-Ion Battery Performance

The growing demand of lithium-ion batteries (LIBs) on portable electronics, electric vehicles urgently requires higher energy density, longer cycling life, and better safety to satisfy the needs of environmental factors and economics. In order to have higher energy density, simply increasing the volume of the single electrodes of LIB results in poor capacity due to inefficient mass transport of Li ions through the irregular microstructure of the electrode. Since understanding the influence of geometrical properties electrodes is of considerable significance to battery performance, we investigate two basic cells: (i) an irregular microstructure intercalation host and (ii) a periodically aligned microchannel intercalation hosts. Our in-house developed simulation tool solves Nernst-Planck and electron conduction equations with proper interfacial reactions by considering experimentally verified ageing mechanism (2-layered SEI and lithium-plating) into account and compute the associated characteristic voltage vs. state of charge curves under various geometric and design parameters. The proposed model is parameterized and optimised for mass transport based on fresh cell and validated against experimental results available on the literature. We show that the nanostructured electrode design yields better battery performance because the uniformity of electrodes yields elimating the nonuniform intercalation and side reactions on active material electrode surface. This work presents a design concept for higher energy and power densities that are not limited to LIBs.*This work has been supported by The Warwick Research Development Fund, UK, through the Grant No. RDF19035. Figure 1

Current practice and challenges in screening for visual perception deficits after stroke: a qualitative study

Purpose We document current clinical practice and needs in screening for visual perception problems after stroke to inform development of new screening tools. Materials and methods We interviewed 12 occupational therapists and 13 orthoptists. Interviews were thematically analysed using the Value Proposition Canvas, a model which establishes challenges and facilitators in what people want to achieve. Results Participants’ understanding of visual perception varied and often included sensory and cognitive deficits. Occupational therapists commonly screened for visual field deficits and hemispatial neglect, while other aspects of visual cognition were rarely assessed. A positive screening result triggered an orthoptic referral. Screening generally occurred during functional assessments and/or with in-house developed tools. Challenges to practice were: lack of time, lack of training, environmental and stroke survivor factors (e.g., aphasia), insufficient continuation of care, and test characteristics (e.g., not evidence-based). Facilitators were: quick and practical tools, experienced staff or tools with minimal training requirements, a streamlined care pathway. Conclusions Screening employs non-standardised assessments and rarely covers higher visual perceptual deficits. We demonstrates the need for an evidence-based visual perception screen, which should ideally be 15 min or less, be portable, and require minimal equipment. The screen should be suitable for bedside testing and aphasia-friendly. Implications for rehabilitation There is a high demand for training on what visual perception deficits are and how to screen for them. Building local relationships between orthoptists and occupational therapists is perceived as highly beneficial for providing good vision and visual perception care for stroke survivors. Occupational therapists should be alert for visual perceptual deficits in their patients preferably through systematic screening with standardised assessments such as the shortened version of the Rivermead Perceptual Assessment Battery or Occupational Therapy Adult Perceptual Screening Test.

A knowledge-based process planning framework for wire arc additive manufacturing

Wire arc additive manufacturing (WAAM) provides a rapid and cost-effective solution for fabricating low-to-medium complexity and medium-to-large size metal parts. In WAAM, process settings are well-recognized as fundamental factors that determine the performance of the fabricated parts such as geometry accuracy and microstructure. However, decision-making on process variables for WAAM still heavily relies on knowledge from domain experts. For achieving reliable and automated production, process planning systems that can capture, store, and reuse knowledge are needed. This study proposes a process planning framework by integrating a WAAM knowledge base together with our in-house developed computer-aided tools. The knowledge base is construed with a data-knowledge-service structure to incorporate various data and knowledge including metamodels and planning rules. Process configurations are generated from the knowledge base and then used as inputs to computer-aided tools. Moreover, the process planning system also supports the early-stage design of products in the context of design for additive manufacturing. The proposed framework is demonstrated in a digital workflow of fabricating industrial-grade components with overhang features.

Development and investigations on a hybrid tooling concept for coaxial and concurrent application of electrochemical and laser micromachining processes

In hybrid laser-electrochemical micromachining, both laser and electrochemical process energies act along the same machining axis and thus both influence material removal by their interaction. The traditional nozzle based laser assisted jet-ECM concepts require laser to be focused on workpiece surface in an electrochemical environment and are limited in aspect ratios as the nozzle stays above the workpiece surface. In this work, a hybrid tooling concept is proposed for a novel process scheme of precision hybrid laser-electrochemical micromachining. The tool serves the function of both an ECM electrode as well as a leaky-type multimode waveguide for the laser and delivers laser homogeneously together with the electrolyte on the workpiece surface without requiring laser to be focused on the workpiece surface. A precision prototype hybrid machine-tool is developed which employs short pulsed nano-second laser and micro-second pulsed voltage source for precision micromachining. For this system, ray tracing and detailed multiphysics electrochemical micromachining process simulations are carried out to demonstrate the applicability of this hybrid tooling concept and explain the shape evolution. Successful experimental realization of coaxial and concurrent application of electrochemical and laser processes is presented. Prototype tool electrodes are fabricated and experiments are carried out on an in-house developed prototype hybrid machine tool. The results reveal that the proposed hybrid tool is successfully capable of concentrating laser and electrochemical process energies simultaneously in the same machining zone. However, with the initial design of this hybrid tool, a maximum of 30–40% of laser power is available in the machining zone. Some suggestions for further research will be presented.

NavIC performance over the service region: availability and solution quality

Navigation with Indian Constellation (NavIC) is designed and deployed by Indian Space Research Organization (ISRO) as an indigenous, regional navigational system to provide precise PVT information over the Indian region and surrounding areas. This paper presents a detailed analysis of NavIC visibility under open sky and constrained condition over the service region using an in-house developed simulation tool, the effects of NavIC satellite geometry on single-point solution accuracy and NavIC single and dual frequency solution performances. The results show the potential of NavIC as an alternative navigation system for India and the neighbouring countries in south and south-east Asia, and over an economically important area containing major sea-routes. Even in constrained-visibility conditions, NavIC with its typical constellation design can offer seamless navigation solution over a large region of the globe; the unique S-Band NavIC signal supports enhanced accuracy for stand-alone operation. The results would be beneficial for understanding the potential of NavIC for the user community.

A new decoupled tangential contouring control scheme for multi-dimensional motion

Contour error, which is defined as the distance from the actual tool position to the desired tool trajectory, is directly related to the dimensional precision of the machined parts. In this paper, a new decoupled tangential contouring control scheme (DTCCS), which focuses on directly reducing the contour error, is proposed for multi-dimensional motion. The DTCCS decouples the coupling effect between tangential and contouring error control. Because of this decoupling, the DTCCS realizes controlling the tangential error and the contour error in a separate, independent and time-invariant way. At the same time, various control strategies can be integrated into the DTCCS. The stability of the DTCCS is theoretically proved. Based on the proposed DTCCS, a pole placement tangential tracking error controller and a PID contour error controller are designed and integrated together to implement the DTCCS. Experiments, which are carried out on an in-house developed open architecture CNC machine tool, show that the DTCCS can realize the decoupling of tangential control and contouring control, and can greatly reduce the contour error.

Predictive modeling of laser and electron beam powder bed fusion additive manufacturing of metals at the mesoscale

We present the results of 3D modeling of the laser and electron beam powder bed fusion process at the mesoscale with an in-house developed advanced multiphysical numerical tool. The hydrodynamics and thermal conductivity core of the tool is based on the lattice Boltzmann method. The numerical tool takes into account the random distributions of powder particles by size in a layer and the propagation of the laser (electron beam) with a full ray tracing (Monte Carlo) model that includes multiple reflections, phase transitions, thermal conductivity, and detailed liquid dynamics of the molten metal, influenced by evaporation of the metal and the recoil pressure. The model has been validated by a number of physical tests. We numerically demonstrate a strong dependence of the net energy absorption of the incoming heat source beam by the powder bed and melt pool on the beam power. We show the ability of our model to predict the measurable properties of a single track on a bare substrate as well as on a powder layer. We obtain good agreement with experimental data for the depth, width and shape of a track for a number of materials and a wide range of energy source parameters. We further apply our model to the simulation of the entire layer formation and demonstrate the strong dependence of the resulting layer morphology on the hatch spacing. The presented model could be very helpful for optimizing the additive process without carrying out a large number of experiments in a common trial-and-error method, developing process parameters for new materials, and assessing novel modalities of powder bed fusion additive manufacturing.

The impact of thermophysical properties and hysteresis effects on the energy performance simulation of PCM wallboards: Experimental studies, modelling, and validation

This paper presents a combined experimental and numerical procedure, developed to test the thermophysical behaviour of a real scale PCM wallboard, aiming at providing reliable data for the validation of building energy performance simulation tools. Data obtained from two experimental tests, conducted on real building elements integrating PCM undergoing complete and incomplete phase change, are considered for assessing the impact of thermal properties and hysteresis. A comprehensive comparative numerical analysis, performed by means of an in-house developed simulation tool, called DETECt, is carried out to investigate the reliability of several modelling and simulation approaches available in literature.Monitored data are used to compare the reliability of several modelling and simulation approaches (three different specific heat curves and four modelling approaches for hysteresis) to find out the appropriate temperature dependent heat capacity curves which realistically describe the PCM performance. ResultsThe use of cp – temperature curves characterized through thermophysical analysis (e.g. DSC) under conditions much different than those that the PCM can undergo during the operation of a building can lead to significant discrepancies in performances with the actual data. Moreover, in case of incomplete phase transitions, the lower the accuracy of the cp – temperature curves, the higher the influence of the hysteresis modelling approach on the reliability of simulation results; a better agreement between monitored data and simulation results is observed when hysteresis is modelled by considering the transition between heating and cooling (and vice versa), by switching from the melting to the solidification curves according to the liquid and solid mass fraction.The study shows that the more refined modelling of the phase change allows results to be consistent with the thermo-physics phenomena of composite PCM under real conditions and achieve more reliable results.

OPEN ACCESS ROUTES DICHOTOMY AND OPPORTUNITIES: CONSOLIDATION, ANALYSIS AND TRENDS AT THE SPANISH NATIONAL RESEARCH COUNCIL

This article gives a comprehensive overview of recent Spanish National Research Council (CSIC) publications available in Open Access. With a focus on research articles from the last decade (2008–2018), this work aims to fill the gap in previous studies about publishing trends and impact monitoring of publications by researchers from the Spanish National Research Council. Evolution and main trends of Green and Gold Open Access routes at CSIC are addressed through a close insight into DIGITAL.CSIC repository and institutional Open Access Publishing Support Programme. The article draws on major conclusions at a time when an institutional Open Access mandate has just entered into force. The article also relates findings about performance of institutional Open Access Publishing Initiative and total volume of CSIC articles published in Open Access with an estimation of overall costs on article processing charges during these years. Furthermore, the data serve as a basis to make preliminary considerations as to opportunities to move from a subscription-based model to one fully aligned with Gold Open Access publishing. The data analyzed come from a variety of sources, including public information and internal records maintained by the CSIC E-resources Subscription programme, DIGITAL.CSIC and data retrieved from GesBIB, an internal, in-house development tool that integrates bibliographic information about CSIC publications as well as data from several external APIs, including Unpaywall, DOAJ and Sherpa Romeo.

Building to Vehicle to Building concept: A comprehensive parametric and sensitivity analysis for decision making aims

This paper focuses on the energy and economic analysis of the Building To Vehicle To Building (V2B2) concept, conducted through a comprehensive parametric and sensitivity analysis. The idea behind this novel vehicle to building energy management is to exploit the use of electric vehicles as energy vectors to exchange electricity among buildings with the aim to accelerate the development of a novel zero energy paradigm, while promoting the deployment of renewable energy sources, accelerating the widespread usage of electric vehicles, and streamlining the regulation of charging stations in our future communities. In order to evaluate the potentials of the proposed schemes, a comprehensive parametric analysis is conducted to size the design and operating parameters which maximize the self-production and self-consumption of building integrated renewable energy technologies at a cluster level. The paper investigates the energy and economic performance of different V2B2 energy management schemes including a residential building, an office building, and an electric vehicle, which feature a basic cluster of human-linked energy consumers. The study is conducted by means of a novel in-house developed dynamic simulation tool, suitably enhanced to model the system operation. Numerical results, obtained for a representative weather zone (Mediterranean climate of Naples, South-Italy), show that through the V2B2 scheme, a remarkable exploitation of off-site renewable energy production is achieved, producing a significant reduction of fossil fuel consumption from the grid.

WLCG Dashboards with Unified Monitoring

Monitoring of the CERN Data Centres and the WLCG infrastructure is now largely based on the new monitoring infrastructure provided by CERN IT. This is the result of the migration from several old in-house developed monitoring tools into a common monitoring infrastructure based on open source technologies such as Collectd, Flume, Kafka, Spark, InfluxDB, Grafana and others. This new infrastructure relies on CERN IT services (OpenStack, Puppet, Gitlab, DBOD, etc) and covers the full range of monitoring tasks: metrics and logs collection, alarms generation, data validation and transport, data enrichment and aggregation (where applicable), dashboards visualisation, reports generation, etc. This contribution will present the different services offered by the infrastructure today, highlight the main monitoring use cases from the CERN Data Centres and WLCG, and analyse the last years experience of moving from legacy well-established custom monitoring tools into a common open source-based infrastructure.

A robust methodology for the design optimization of diffuser augmented wind turbine shrouds

Shrouded wind turbines represent an attractive solution of high potential that could improve significantly the feasibility of renewable energy production at sites characterized by poor wind resources. This work presents the development of a modular optimization scheme for the aerodynamic shape optimization of diffuser-augmented wind turbine (DAWT) shrouds. For the numerical simulation of the incompressible flow field, an axisymmetric RANS solver has been implemented, based on the artificial compressibility method and SST turbulence model. The major features of the RANS solver are demonstrated, while its validity is assessed against both numerical and experimental data. Mesh and geometry parameterization are simultaneously succeeded by employing an in-house developed computational tool, based on the well-known Free-Form Deformation (FFD) technique. The backbone of the optimization framework is formed by a parallel and asynchronous Differential Evolution (DE) algorithm, which is assisted by Artificial Neural Network (ANN) meta-models. The proposed methodology is applied to the design optimization of an axisymmetric shroud (diffuser) for a 15 kW wind turbine, aiming to maximize the mean velocity speed-up ratio and minimize drag, under geometrical constrains. The resulting designs are capable of providing high velocity accelerations, accompanied by considerable reduction in drag and volume.

Rectum Dose Constraints for Carbon Ion Therapy: Relative Biological Effectiveness Model Dependence in Relation to Clinical Outcomes.

The clinical application of different relative biological effectiveness (RBE) models for carbon ion RBE-weighted dose calculation hinders a global consensus in defining normal tissue constraints. This work aims to update the local effect model (LEM)-based constraints for the rectum using microdosimetric kinetic model (mMKM)-defined values, relying on RBE translation and the analysis of long-term clinical outcomes. LEM-optimized plans of treated patients, having suffered from prostate adenocarcinoma (n = 22) and sacral chordoma (n = 41), were recalculated with the mMKM using an in-house developed tool. The relation between rectum dose-volume points in the two RBE systems (DLEM|v and DMKM|v) was fitted to translate new LEM-based constraints. Normal tissue complication probability (NTCP) values, predicting late rectal toxicity, were obtained by applying published parameters. No late rectal toxicity events were reported within the patient cohort. The rectal toxicity outcome was confirmed using dosimetric analysis: DMKMVHs lay largely below original constraints; the translated DLEM|v values were 4.5%, 8.3%, 18.5%, and 35.4% higher than the nominal DMKM|v of the rectum volume, v—1%, 5%, 10% and 20%. The average NTCP value ranged from 5% for the prostate adenocarcinoma, to 0% for the sacral chordoma group. The redefined constraints, to be confirmed prospectively with clinical data, are DLEM|5cc ≤ 61 Gy(RBE) and DLEM|1cc ≤ 66 Gy(RBE).

Assessment of a coupled approach to determine the stress caused by gun blast loads

This paper aims at assessing a custom numerical procedure built to predict the level of stress in the structural components and equipment in proximity of a cannon-like weapon system when firing. In such a blast scenario, the structures adjacent to a gun may undergo sudden and unwanted damages, since they are commonly subjected to the blast load due to the impingement and propagation of the shock waves expanding from the weapon muzzle. The proposed procedure pertains the coupled use of an in-house developed tool (GUNWave3D) based on the power-law scaling technique and a general-purpose commercial fast dynamic solver to compute the structural response of the loaded components. The in-house tool, in particular, allows one to rapidly calculate the blast parameters over the surfaces of the items of interest in the function of the weapon characteristics and launch conditions, also accounting for the asymmetric shape characterizing the gun blast wave. Taking as reference the numerical free field peak overpressure profiles of a 30 mm gun, whose blast quantities were already validated in a previously published work, the final stage of the assessment was accomplished. Such an estimation consists of the comparison between the structural stresses calculated using the blast loads predicted through the in-house tool and those computed adopting the free spherical air blast of the tri-nitro-toluene model. This operation has the objective to quantify the discrepancy between the computational results of two Lagrangian techniques that can be alternatively adopted in industrial gun blast design procedures and methodologies.

Deep learning for caries lesion detection in near-infrared light transillumination images: A pilot study

ObjectivesIn this pilot study, we applied deep convolutional neural networks (CNNs) to detect caries lesions in Near-Infrared-Light Transillumination (NILT) images. Methods226 extracted posterior permanent human teeth (113 premolars, 113 molars) were allocated to groups of 2 + 2 teeth, and mounted in a pilot-tested diagnostic model in a dummy head. NILT images of single-tooth-segments were generated using DIAGNOcam (KaVo, Biberach). For each segment (on average 435 × 407 × 3 pixels), occlusal and/or proximal caries lesions were annotated by two experienced dentists using an in-house developed digital annotation tool. The pixel-based annotations were translated into binary class levels. We trained two state-of-the-art CNNs (Resnet18, Resnext50) and validated them via 10-fold cross validation. During the training process, we applied data augmentation (random resizing, rotations and flipping) and one-cycle-learning rate policy, setting the minimum and maximum learning rates to 10−5 and 10-3, respectively. Metrics for model performance were the area-under-the-receiver-operating-characteristics-curve (AUC), sensitivity, specificity, and positive/negative predictive values (PPV/NPV). Feature visualization was additionally applied to assess if the CNNs built on features dentists would also use. ResultsThe tooth-level prevalence of caries lesions was 41%. The two models performed similar on predicting caries on tooth segments of NILT images. The marginal better model with respect to AUC was Resnext50, where we retrained the last 9 network layers, using the Adam optimizer, a learning rate of 0.5 × 10−4, and a batch size of 10. The mean (95% CI) AUC was 0.74 (0.66-0.82). Sensitivity and specificity were 0.59 (0.47-0.70) and 0.76 (0.68-0.84) respectively. The resulting PPV was 0.63 (0.51-0.74), the NPV 0.73 (0.65-0.80). Visual inspection of model predictions found the model to be sensitive to areas affected by caries lesions. ConclusionsA moderately deep CNN trained on a limited amount of NILT image data showed satisfying discriminatory ability to detect caries lesions. Clinical significanceCNNs may be useful to assist NILT-based caries detection. This could be especially relevant in non-conventional dental settings, like schools, care homes or rural outpost centers.

Towards standardization of absolute SPECT/CT quantification: a multi-center and multi-vendor phantom study

Absolute quantification of radiotracer distribution using SPECT/CT imaging is of great importance for dosimetry aimed at personalized radionuclide precision treatment. However, its accuracy depends on many factors. Using phantom measurements, this multi-vendor and multi-center study evaluates the quantitative accuracy and inter-system variability of various SPECT/CT systems as well as the effect of patient size, processing software and reconstruction algorithms on recovery coefficients (RC).MethodsFive SPECT/CT systems were included: Discovery™ NM/CT 670 Pro (GE Healthcare), Precedence™ 6 (Philips Healthcare), Symbia Intevo™, and Symbia™ T16 (twice) (Siemens Healthineers). Three phantoms were used based on the NEMA IEC body phantom without lung insert simulating body mass indexes (BMI) of 25, 28, and 47 kg/m2. Six spheres (0.5–26.5 mL) and background were filled with 0.1 and 0.01 MBq/mL 99mTc-pertechnetate, respectively. Volumes of interest (VOI) of spheres were obtained by a region growing technique using a 50% threshold of the maximum voxel value corrected for background activity. RC, defined as imaged activity concentration divided by actual activity concentration, were determined for maximum (RCmax) and mean voxel value (RCmean) in the VOI for each sphere diameter. Inter-system variability was expressed as median absolute deviation (MAD) of RC. Acquisition settings were standardized. Images were reconstructed using vendor-specific 3D iterative reconstruction algorithms with institute-specific settings used in clinical practice and processed using a standardized, in-house developed processing tool based on the SimpleITK framework. Additionally, all data were reconstructed with a vendor-neutral reconstruction algorithm (Hybrid Recon™; Hermes Medical Solutions).ResultsRC decreased with decreasing sphere diameter for each system. Inter-system variability (MAD) was 16 and 17% for RCmean and RCmax, respectively. Standardized reconstruction decreased this variability to 4 and 5%. High BMI hampers quantification of small lesions (< 10 ml).ConclusionAbsolute SPECT quantification in a multi-center and multi-vendor setting is feasible, especially when reconstruction protocols are standardized, paving the way for a standard for absolute quantitative SPECT.