Reduced Analysis Time Research Articles

Mathematically assisted UV-spectrophotometry as a greener alternative to HPLC-UV for quality control analysis of free-drug combinations

Here we introduce a novel and a comprehensive evaluation of the eco-friendliness of UV-spectrophotometry versus HPLC-UV, as used for the quality control testing of free-drug combinations. We offer a new perspective to improve the sustainability of quality control testing of pharmaceuticals, through utilization of UV-spectrophotometry coupled to mathematical signal processing as means to improve selectivity of analysis of multicomponent pharmaceutical samples. First, we developed two novel analytical methods based on UV-spectrophotometry and HPLC-UV, for the simultaneous determination of antidiabetic free-drug combination consisting of dapagliflozin (DAPA) and saxagliptin (SAXA), in the form of active pharmaceutical ingredients or finished pharmaceutical products. Furthermore, we perform qualitative and quantitative evaluation of methods’ greenness employing five reported tools namely: National Environmental Methods Index (NEMI), Raynie and Driver’s assessment tool, Green Analytical Procedure Index (GAPI), Eco-scale and Analytical GREEnness Metric (AGREE). Our results indicate that both methods were equally efficient in quantifying target analytes in the studied forms, however, UV-spectrophotometry was found to be superior to HPLC-UV from a green analytical chemistry perspective, with more than 20 folds reduction in organic solvent consumption, ~ 10 folds reduction in energy consumption and ~4 folds reduction in analysis time, making it a safer alternative to consider.

Analysis of hip joint cross-shear under variable activities using a novel virtual joint model within Visual3D.

Cross-shear forces occur between bearing surfaces at the hip and have been identified as a key contributor to prosthesis wear. Understanding the variation in relative motion paths between both individuals and activities, is a possible explanation for increased revision rates for younger patients and could assist in improved pre-clinical testing regimes. Additionally, there is little information for the pre-clinical testing of cartilage substitution therapies for younger more active individuals. The calculation of motion paths has previously relied on computational modelling software which can be complex and time-consuming. The aim of this study was to determine whether the motion paths calculations could be integrated into gait analysis software to improve batch processing, reduce analysis time and ultimately improve the efficiency of the analysis of cross-shear variation for a broader range of activities. A novel Virtual Joint model was developed within Visual3D for calculating motion paths. This model was compared to previous computational methods and found to provide a competitive solution for cross shear analysis (accuracy <0.01 mm error between methods). The virtual hip model was subsequently applied to 13 common activities to investigate local aspect ratio's, velocities and accelerations. Surprisingly walking produced the harshest cross shear motion paths in subjects. Within walking, of additional interest was that the localised change in acceleration for subjects was six times greater compared to the same point on an equivalent smoothed simulator cycle. The Virtual hip developed in Visual 3D provides a time saving technique for visualising and processing large data sets directly from motion files. The authors postulate that rather than focussing on a generalised smoothed cross-shear model that pre-clinical testing of more delicate structures should consider localised changes in acceleration as these may be more important in the assessment of cartilage substitutes sensitive to shear.

Further development of a liquid chromatography-high-resolution mass spectrometry/mass spectrometry-based strategy for analyzing eight biomarkers in human urine indicating toxic mushroom or Ricinus communis ingestions.

Recently, we presented a strategy for analysis of eight biomarkers in human urine to verify toxic mushroom or Ricinus communis ingestions. However, screening for the full panel is not always necessary. Thus, we aimed to develop a strategy to reduce analysis time and by focusing on two sets of analytes. One set (A) for biomarkers of late-onset syndromes, such as phalloides syndrome or the syndrome after castor bean intake. Another set (B) for biomarkers of early-onset syndromes, such as pantherine-muscaria syndrome and muscarine syndrome. Both analyses should be based on hydrophilic-interaction liquid chromatography coupled with high-resolution mass spectrometry (MS)/MS (HILIC-HRMS/MS). For A, urine samples were prepared by liquid-liquid extraction using dichloromethane and subsequent solid-phase extraction of the aqueous supernatant. For B urine was precipitated using acetonitrile. Method A was validated for ricinine and α- and β-amanitin and method B for muscarine, muscimol, and ibotenic acid according to the specifications for qualitative analytical methods. In addition, robustness of recovery and normalized matrix factors to matrix variability measured by urinary creatinine was tested. Moreover, applicability was tested using 10 urine samples from patients after suspected mushroom intoxication. The analytes α- and β-amanitin, muscarine, muscimol, and ibotenic acid could be successfully identified. Finally, psilocin-O-glucuronide could be identified in two samples and unambiguously distinguished from bufotenine-O-glucuronide via their MS2 patterns. In summary, the current workflow offers several advantages towards the previous method, particularly being more labor-, time-, and cost-efficient, more robust, and more sensitive.

Platform Incubator with Movable XY Stage: A New Platform for Implementing In-Cell Fast Photochemical Oxidation of Proteins

Fast Photochemical Oxidation of proteins (FPOP) coupled with mass spectrometry (MS) has become an invaluable tool in structural proteomics to interrogate protein interactions, structure, and protein conformational dynamics as a function of solvent accessibility. In recent years, the scope of FPOP, a hydroxyl radical protein foot printing (HRPF) technique, has been expanded to protein labeling in live cell cultures, providing the means to study protein interactions in the convoluted cellular environment. In-cell protein modifications can provide insight into ligand induced structural changes or conformational changes accompanying protein complex formation, all within the cellular context. Protein footprinting has been accomplished employing a customary flow-based system and a 248 nm KrF excimer laser to yield hydroxyl radicals via photolysis of hydrogen peroxide, requiring 20 minutes of analysis for one cell sample.To facilitate time-resolved FPOP experiments, the use of a new 6-well plate-based IC-FPOP platform was pioneered. In the current system, a single laser pulse irradiates one entire well, which truncates the FPOP experimental time frame resulting in 20 seconds of analysis time, a 60-fold decrease. This greatly reduced analysis time makes it possible to research cellular mechanisms such as biochemical signaling cascades, protein folding, and differential experiments (i.e., drug-free vs. drug bound) in a time-dependent manner. This new instrumentation, entitled Platform Incubator with Movable XY Stage (PIXY), allows the user to perform cell culture and IC-FPOP directly on the optical bench using a platform incubator with temperature, CO2 and humidity control. The platform also includes a positioning stage, peristaltic pumps, and mirror optics for laser beam guidance. IC-FPOP conditions such as optics configuration, flow rates, transient transfections, and H2O2 concentration in PIXY have been optimized and peer-reviewed. Automation of all components of the system will reduce human manipulation and increase throughput.

Platform Incubator with Movable XY Stage: A New Platform for Implementing In-Cell Fast Photochemical Oxidation of Proteins.

Fast Photochemical Oxidation of proteins (FPOP) coupled with mass spectrometry (MS) has become an invaluable tool in structural proteomics to interrogate protein interactions, structure, and protein conformational dynamics as a function of solvent accessibility. In recent years, the scope of FPOP, a hydroxyl radical protein foot printing (HRPF) technique, has been expanded to protein labeling in live cell cultures, providing the means to study protein interactions in the convoluted cellular environment. In-cell protein modifications can provide insight into ligand induced structural changes or conformational changes accompanying protein complex formation, all within the cellular context. Protein footprinting has been accomplished employing a customary flow-based system and a 248 nm KrF excimer laser to yield hydroxyl radicals via photolysis of hydrogen peroxide, requiring 20 minutes of analysis for one cell sample.To facilitate time-resolved FPOP experiments, the use of a new 6-well plate-based IC-FPOP platform was pioneered. In the current system, a single laser pulse irradiates one entire well, which truncates the FPOP experimental time frame resulting in 20 seconds of analysis time, a 60-fold decrease. This greatly reduced analysis time makes it possible to research cellular mechanisms such as biochemical signaling cascades, protein folding, and differential experiments (i.e., drug-free vs. drug bound) in a time-dependent manner. This new instrumentation, entitled Platform Incubator with Movable XY Stage (PIXY), allows the user to perform cell culture and IC-FPOP directly on the optical bench using a platform incubator with temperature, CO2 and humidity control. The platform also includes a positioning stage, peristaltic pumps, and mirror optics for laser beam guidance. IC-FPOP conditions such as optics configuration, flow rates, transient transfections, and H2O2 concentration in PIXY have been optimized and peer-reviewed. Automation of all components of the system will reduce human manipulation and increase throughput.

Common Reference-Based Tandem Mass Tag Multiplexing for the Relative Quantification of Peptides: Design and Application to Degradome Analysis of Diphtheria Toxoid.

Currently, animal tests are being used to confirm the potency and lack of toxicity of toxoid vaccines. In a consistency approach, animal tests could be replaced if production consistency (compared to known good products) can be proven in a panel of in vitro assays. By mimicking the in vivo antigen processing in a simplified in vitro approach, it may be possible to distinguish aberrant products from good products. To demonstrate this, heat-exposed diphtheria toxoid was subjected to partial digestion by cathepsin S (an endoprotease involved in antigen processing), and the peptide formation/degradation kinetics were mapped for various heated toxoids. To overcome the limitations associated with the very large number of samples, we used common reference-based tandem mass tag (TMT) labeling. Instead of using one label per condition with direct comparison between the set of labels, we compared multiple labeled samples to a common reference (a pooled sample containing an aliquot of each condition). In this method, the number of samples is not limited by the number of unique TMT labels. This TMT multiplexing strategy allows for a 15-fold reduction of analysis time while retaining the reliability advantage of TMT labeling over label-free quantification. The formation of the most important peptides could be followed over time and compared among several conditions. The changes in enzymatic degradation kinetics of diphtheria toxoid revealed several suitable candidate peptides for use in a quality control assay that can distinguish structurally aberrant diphtheria toxoid from compliant toxoids.

PE-Designer and PE-Analyzer: web-based design and analysis tools for CRISPR prime editing.

Prime editing technology is capable of generating targeted insertions, deletions, and base conversions. However, the process of designing prime editing guide RNAs (pegRNAs), which contain a primer binding site and a reverse-transcription template at the 3′ end, is more complex than that for the single guide RNAs used with CRISPR nucleases or base editors. Furthermore, the assessment of high-throughput sequencing data after prime editors (PEs) have been employed should consider the unique feature of PEs; thus, pre-existing assessment tools cannot directly be adopted for PEs. Here, we present two user-friendly web-based tools for PEs, named PE-Designer and PE-Analyzer. PE-Designer, a dedicated tool for pegRNA selection, provides all possible target sequences, pegRNA extension sequences, and nicking guide RNA sequences together with useful information, and displays the results in an interactive image. PE-Analyzer, a dedicated tool for PE outcome analysis, accepts high-throughput sequencing data, summarizes mutation-related information in a table, and provides interactive graphs. PE-Analyzer was mainly written using JavaScript so that it can analyze several data sets without requiring that huge sequencing data (>100MB) be uploaded to the server, reducing analysis time and increasing personal security. PE-Designer and PE-Analyzer are freely available at http://www.rgenome.net/pe-designer/ and http://www.rgenome.net/pe-analyzer/ without a login process.

Laser Ablation Inductive Coupled Plasma Mass Spectroscopy (LA-ICP-MS) Analysis on Lead-Acid Battery System: Development of Evaluation Method of Sub-ppm Metal Impurity Elements

In Lead-acid batteries, there are significant efforts to enhance battery performance, mainly by reducing metal impurities that negatively affect battery performance. Currently implemented impurity analysis requires significant time and effort. Wet chemical preparation method is not only hazardous due to the extensive use of acids, but generates environmental pollutants and hazardous waste which require more costly and comprehensive disposal processes. In industry, it is desirable to reduce sample processing and analysis time to improve productivity and efficiency. Laser ablation inductively coupled plasma mass spectroscopy (LA-ICP-MS) is a technique that has the potential to overcome the above issues. In this work, we demonstrate an analysis of impurities (Cu, As, Cd, Co, Se, and Te) in lead-based samples at the ppm/sub-ppm level by the LA-ICP-MS method and verify with matrix matching an accurate quantification of the impurity concentrations of interest. The resulting data, which determines to reduce analysis time more than 50% due to simple preparation step while not as accurate concentration as traditional ICP-MS with at least two times increment of relative standard deviation, provides a reasonable level of accuracy and precision in a substantially quick, cost-effective method that is viable for a high throughput industrial setting.

Fast and simultaneous analysis of carbamate pesticides and anticoagulant rodenticides used in suspected cases of animal poisoning

Carbamate pesticides (CBs) are reported as one of the main causes of intentional or accidental poisoning of animals. Anticoagulant rodenticides (ARs) form the main class of poisons implicated in analyzed poisoned baits. These two groups of pesticide compounds include multiple substances, and thus, the development of a simple and rapid multiclass/multiresidue analytical method for simultaneous identification of both toxicant classes should be a useful strategy for analytical laboratories to reduce analysis time and cost. The present study aimed to elaborate and validate a rapid method to simultaneously determine 11 CBs and 8 ARs in samples of real matrices (bait, stomach content, and liver) from suspected animal poisoning cases. QuEChERS sample treatment and liquid chromatography coupled to hybrid high resolution mass spectrometry were used. The method resulted in good linearity (R2 ≥ 0.98) for all compounds, recovery was between 70% and 120% for CBs and 40–90% for ARs, and precision was ≤ 20% for all compounds. The method was successfully applied to the analysis of 871 real samples originating from suspected cases of animal poisoning, collected from April 2019 to October 2020. Furthermore, full scan dependent data acquisition allowed qualitative retrospective data analysis of an additional 15 compounds outside the scope of the method to be performed; these compounds could potentially be involved in unresolved poisoning cases.

Prediction of Drill Bit Breakage Using an Infrared Sensor.

In this paper, a novel drill bit breakage prediction method featuring a low-cost commercial infrared sensor to monitor drill bit corner wear is proposed. In the proposed method, the drill bit outer corner wear state can be monitored by measuring reflected infrared light because the reflection phenomenon is influenced by wear, edge shape, and surface roughness of the drill bit. In the experiments, a titanium workpiece was drilled without using cutting fluid to accelerate drill bit fracture. After drilling a hole in the workpiece, reflected infrared light was measured for the drill bit rotating at 100 rpm. Collected data on intensity of infrared light reflected from the circumferential surface of the drill bit versus the rotation angle of the drill bit were considered to predict tool breakage; two significant positions to predict tool breakage were found from the reflected infrared light graphs. By defining gradient vectors from the slopes of the reflected infrared light curves, a reliable criterion for determining drill bit breakage could be established. The proposed method offers possibilities for new measurement and analysis methods that have not been used in conventional tool wear and damage studies. The advantage of the proposed method is that the measurement device is easy to install and the measured signal is resistant to electromagnetic noise and ambient temperature because optical fiber is used as the signal transmission medium. It also eliminates the need for complex analysis of the measured signal, eliminating the need for a high-performance analyzer and reducing analysis time.

Application of Capillary Electrophoresis to the Analysis of Bioactive Compounds in Herbal Raw Materials.

The article is a summary of scientific reports from the last 16 years (2005–2021) on the use of capillary electrophoresis to analyze polyphenolic compounds, coumarins, amino acids, and alkaloids in teas or different parts of plants used to prepare aqueous infusions, commonly known as “tea” or decoctions. This literature review is based on PRISMA guidelines and articles selected in base of criteria carried out using PICOS (Population, Intervention, Comparison, Outcome, Study type). The analysis showed that over 60% of articles included in this manuscript comes from China. The literature review shows that for the selective electrophoretic separation of polyphenolic and flavonoid compounds, the most frequently used capillary electromigration technique is capillary electrophoresis with ultraviolet detection. Nevertheless, the use of capillary electrophoresis-mass spectrometry allows for the sensitive determination of analytes with a lower limit of detection and gives hope for routine use in the analysis of functional foods. Moreover, using the modifications in electrochemical techniques allows methods sensitivity reduction along with the reduction of analysis time.

The Use of Multispectral Imaging and Single Seed and Bulk Near-Infrared Spectroscopy to Characterize Seed Covering Structures: Methods and Applications in Seed Testing and Research

The objective of seed testing is to provide high-quality seeds in terms of high varietal identity and purity, germination capacity, and seed health. Across the seed industry, it is widely acknowledged that quality assessment needs an upgrade and improvement by inclusion of faster and more cost-effective techniques. Consequently, there is a need to develop and apply new techniques alongside the classical testing methods, to increase efficiency, reduce analysis time, and meet the needs of stakeholders in seed testing. Multispectral imaging (MSI) and near-infrared spectroscopy (NIRS) are both quick and non-destructive methods that attract attention in seed research and in the seed industry. This review addresses the potential benefits and challenges of using MSI and NIRS for seed testing with a comprehensive focus on applications in physical and physiological seed quality as well as seed health.

Application of Vibrational Spectroscopies in the Qualitative Analysis of Gingival Crevicular Fluid and Periodontal Ligament during Orthodontic Tooth Movement

Optical vibrational techniques show a high potentiality in many biomedical fields for their characteristics of high sensitivity in revealing detailed information on composition, structure, and molecular interaction with reduced analysis time. In the last years, we have used these techniques for investigating gingival crevicular fluid (GCF) and periodontal ligament (PDL) during orthodontic tooth treatment. The analysis with Raman and infrared signals of GCF and PDL samples highlighted that different days of orthodontic force application causes modifications in the molecular secondary structure at specific wavenumbers related to the Amide I, Amide III, CH deformation, and CH3/CH2. In the present review, we report the most relevant results and a brief description of the experimental techniques and data analysis procedure in order to evidence that the vibrational spectroscopies could be a potential useful tool for an immediate monitoring of the individual patient’s response to the orthodontic tooth movement, aiming to more personalized treatment reducing any side effects.

Monitoring rocky reef biodiversity by underwater geo-referenced photoquadrats

Digital images are an excellent tool for divers to sample hard-bottom subtidal habitats as bottom time is limited and high-definition images can be collected quickly and accurately. The present paper describes a sampling protocol for benthic rocky reef communities using geo-referenced photoquadrats and tests the method over several rocky reefs of Atlantic Patagonia. This method was tested in two localities, separated by 100 km in a semi-enclosed gulf, covering a total of 5800 m of 11 rocky reefs using track roaming transects. The protocol is non-destructive, relatively low-cost and can adequately assess changes in marine habitats as rocky reefs. The implementation of artificial intelligence analysis using human expert training may reduce analysis time and increase the amount of data collected. The present study recommends this sampling methodology for programs aimed at monitoring changes in biodiversity.

New NEO Detection Techniques using the FPGA

Abstract We have developed a new method for detecting near-Earth objects (NEOs) based on a Field Programmable Gate-Array (FPGA). Unlike conventional methods, our technique uses 30–40 frames to detect faint NEOs that are almost invisible on a single frame. To reduce analysis time, image binarization and an FPGA-implemented algorithm were used. This method has aided in the discovery of 11 NEOs by analyzing frames captured with 20 cm class telescopes. This new method will contribute to discovering new NEOs that approach the Earth closely.

Determination of azoxystrobin, topramezone, acetamiprid, fluometuron and folpet in their commercially available pesticide formulations by liquid chromatography

A rapid, simple, precise and accurate high performance liquid chromatographic (HPLC) analytical method was developed and validated for the determination of the active substances (a.s.) azoxystrobin, topramezone, acetamiprid, fluometuron and folpet in their respective commercially available formulations. The method was used for the analysis of samples under the frame of the national quality control program of plant protection products in the Greek market. Chromatographic separation of the active substances from additives and co-formulants is achieved using isocratic elution with acetonitrile and 0.1% phosphoric acid solution (60:40 v/v) at a flow rate of 0.4 mL min−1 on a C18 monolithic column (Chromolith Performance-RP18e 100 × 4.6 mm) and UV detection at 230 nm. Validation parameters of the method fulfilled acceptability criteria. Recovery of all individual compounds was in the range 97.8–100.9%. Precision expressed as relative standard deviation was lower than the theoretical values of the modified Horwitz equation. Correlation coefficients of linearity of response were better than 0.999. The benefits of the proposed method are significant reduction in analysis time and total cost since all analytes were determined with the same extraction procedures and chromatographic system. Analysis of real samples for all active ingredients confirmed fitness for purpose of the suggested method.

Polymer film as starch azure container for the easy diastase activity determination in honey

A new original application for a polyacrylic film based on the monomers 2-(dimethylamino)ethyl methacrylate (NNDA), 2-hydroxyethyl acrylate (2HEA) and methylmethacrylate (MMA) as a starch azure container has been set up for a simple determination of honey diastase activity. The proposed method is based on the correlation of reducing sugars generated during the enzymatic process with the Schade reference assay. The polyacrylic film is charged with starch azure acting as a container for this substance; thus, the starch does not interfere in the measurement of reducing sugars, so that the diastase activity is easily calculated. The method has been contrasted with Schade method, showing good correlation and differences under 0.4% between methods in some honey samples. The polyacrylic film has great potential for the routine honey diastase activity assessment in small laboratories, dramatically reducing analysis time and cost.

Onset detection in surface electromyographic signals across isometric explosive and ramped contractions: a comparison of computer-based methods

Objective. Accurate identification of surface electromyography (EMG) muscle onset is vital when examining short temporal parameters such as electromechanical delay. The visual method is considered the ‘gold standard’ in onset detection. Automatic detection methods are commonly employed to increase objectivity and reduce analysis time, but it is unclear if they are sensitive enough to accurately detect EMG onset when relating them to short-duration motor events. Approach. This study aimed to determine: (1) if automatic detection methods could be used interchangeably with visual methods in detecting EMG onsets (2) if the Teager–Kaiser energy operator (TKEO) as a conditioning step would improve the accuracy of popular EMG onset detection methods. The accuracy of three automatic onset detection methods: approximated generalized likelihood ratio (AGLR), TKEO, and threshold-based method were examined against the visual method. EMG signals from fast, explosive, and slow, ramped isometric plantarflexor contractions were evaluated using each technique. Main results. For fast, explosive contractions, the TKEO was the best-performing automatic detection method, with a low bias level (4.7 ± 5.6 ms) and excellent intraclass correlation coefficient (ICC) of 0.993, however with wide limits of agreement (LoA) (−6.2 to +15.7 ms). For slow, ramped contractions, the AGLR with TKEO conditioning was the best-performing automatic detection method with the smallest bias (11.3 ± 32.9 ms) and excellent ICC (0.983) but produced wide LoA (−53.2 to +75.8 ms). For visual detection, the inclusion of TKEO conditioning improved inter-rater and intra-rater reliability across contraction types compared with visual detection without TKEO conditioning. Significance. In conclusion, the examined automatic detection methods are not sensitive enough to be applied when relating EMG onset to a motor event of short duration. To attain the accuracy needed, visual detection is recommended. The inclusion of TKEO as a conditioning step before visual detection of EMG onsets is recommended to improve visual detection reliability.

Cardiovascular magnetic resonance\u2010assessed fast global longitudinal strain parameters add diagnostic and prognostic insights in right ventricular volume and pressure loading disease conditions

BackgroundParameters of myocardial deformation may provide improved insights into right ventricular (RV) dysfunction. We quantified RV longitudinal myocardial function using a fast, semi-automated method and investigated its diagnostic and prognostic values in patients with repaired tetralogy of Fallot (rTOF) and pulmonary arterial hypertension (PAH), who respectively exemplify patients with RV volume and pressure overload conditions.Methods The study enrolled 150 patients (rTOF, n = 75; PAH, n = 75) and 75 healthy controls. RV parameters of interest were fast global longitudinal strain (GLS) and strain rates during systole (GLSRs), early diastole (GLSRe) and late diastole (GLSRa), obtained by tracking the distance from the medial and lateral tricuspid valve insertions to the RV epicardial apex on cine cardiovascular magnetic resonance (CMR).ResultsThe RV fast GLS exhibited good agreement with strain values obtained by conventional feature tracking approach (bias − 4.9%, error limits (± 2·standard deviation) ± 4.3%) with fast GLS achieving greater reproducibility and requiring reduced analysis time. Mean RV fast GLS was reduced in PAH and rTOF groups compared to healthy controls (PAH < rTOF < healthy controls: 15.1 ± 4.9 < 19.3 ± 2.4 < 24.4 ± 3.0%, all P < 0.001 in pairwise comparisons). In rTOF patients, RV fast GLS was significantly associated with metabolic equivalents, peak oxygen consumption (PVO2) and percentage of predicted PVO2 achieved during cardiopulmonary exercise testing. Lower RV fast GLS was associated with subnormal exercise capacity in rTOF (area under the curve (AUC) = 0.822, sensitivity = 72%, specificity = 91%, cut-off = 19.3%). In PAH patients, reduced RV fast GLS was associated with RV decompensated hemodynamics (AUC = 0.717, sensitivity = 75%, specificity = 58%, cut-off = 14.6%) and higher risk of clinical worsening (AUC = 0.808, sensitivity = 79%, specificity = 70 %, cut-off = 16.0%).ConclusionsQuantitative RV fast strain and strain rate parameters assessed from CMR identify abnormalities of RV function in rTOF and PAH and are predictive of exercise capacity, RV decompensation and clinical risks in these patients.Trial registry Clinicaltrials.gov: NCT03217240

Reinforcement machine learning-based aortic anatomical landmarks detection from phase-contrast enhanced magnetic resonance angiography

Abstract Funding Acknowledgements Type of funding sources: Public grant(s) – National budget only. Main funding source(s): Spanish Ministry of Science, Innovation and Universities; La Marató de TV3 Introduction Automatic analysis of medical imaging data may improve their clinical impact by reducing analysis time and improving reproducibility. Many medical imaging data, like 4D-flow magnetic resonance imaging (MRI), are often quantified regionally, implying the need for anatomical landmark identification to locate correspondences in the extracted data and compare among patients. Machine learning (ML) techniques hold potential for automatic analysis of medical imaging. Phase-contrast enhanced magnetic resonance angiography (PC-MRA) is a class of angiograms not requiring the administration of contrast agents. Purpose We aimed to test whether a machine learning algorithm can be trained to identify key anatomical cardiovascular landmarks on PC-MRA images and compare its performance with humans. Methods Three-hundred twenty-three aortic PC-MRA were manually annotated with the location of 4 landmarks: sinotubular junction, pulmonary artery bifurcation and first and third supra-aortic vessels (Figure 1), often used to separate the aorta in sub-regions. Patients included in the training dataset comprised healthy volunteers (40), bicuspid aortic valve patients (141), patients with degenerative aortic disease (60) and patients with genetically-triggered aortic disease (82), all without previous aortic surgery and with native aortic valve. PC-MRA images and manual annotations were used to train a DQN, a reinforcement learning algorithm that combines Q-learning with deep neural networks. The agents can navigate the images and optimally find the landmarks by following the policies learned during training. Data from thirty patients, distributed in terms of aortic condition as the training set, unseen by the algorithm in the training phase, were used to quantify intra-observer reproducibility and to assess ML algorithm performance. Distance between points was used as metric for comparisons, original human annotation was used as ground-truth and repeated-measures ANOVA was used for statistical testing. Results Human and machine learning performed similarly in the identification of the sinotubular junction (distance between points of 11.0 ± 8.1 vs. 11.1 ± 8.6 mm, respectively, p = 0.949) and first (6.6 ± 3.9 vs. 6.8 ± 5.6 mm, p = 0.886) and third (6.8 ± 4.0 vs. 8.4 ± 7.4 mm, p = 0.161) supra-aortic vessels branches but human annotation outperformed ML landmark detection in the identification of the pulmonary artery bifurcation (10.2 ± 7.0 vs. 15.2 ± 13.1 mm, p = 0.008). Computation time for landmark detection by ML was between 0.8 and 1.6 seconds on a standard computer while human annotation took approximatively two minutes. Conclusions ML-based aortic landmarks detection from phase-contrast enhanced magnetic resonance angiography is feasible and fast and performs similarly to human. Reinforced learning anatomical landmark identification unlock automatic extraction of a variety of regional aortic data, including complex 4D flow parameters. Abstract Figure