Variability Of Measurements Research Articles

Aortic integral distensibility based on the auto-segmented dynamic motion of the aortic wall

Abstract Background Aortic stiffness is important in cardiovascular diseases and predicting outcomes. Echocardiography is a widely used noninvasive imaging modality for assessing aortic stiffness, but its accuracy can be limited by the low spatial resolution of ultrasound-based images and the subjectivity of manual measurements of aortic dimensions. Automated segmentation analysis can provide a more accurate and objective measure. Objective An automated algorithm and software have been developed for segmenting the aortic wall. A new measurement technique called "Aortic Integral Distensibility (AID)" has been formulated using this framework. This method overcomes limitations of traditional method focusing solely on the two positions of Aortic Distensibility (AD). Method In this particular investigation, 112 participants were subjected to echocardiography in order to quantify the dynamics of the aortic wall. An automated algorithm was devised to delineate the aortic wall by utilizing an M-mode echocardiography scan. The statistical analysis encompassed the measurement of AD and AID before and after the age of 65 group. This analysis was conducted considering various risk factors, including age, gender, weight, BMI, smoking, and blood pressure. Additionally, clinical parameters, specifically AIx @75 (Augmentation Index) and Framingham Risk Score (FRS), were evaluated as well. Inter-rater reliability was conducted between the traditional AD and the newly implemented AID. Results The results indicate that the group under 65 had more distensibility than the group over 65, and AID measurements were slightly higher than AD measurements. SBP showed a strong correlation with AID, rather than AD. AIx @75 and FRS had a negative relationship with distensibility. In the 65 years or older group, there was a significant negative correlation observed between AIx @75 and AID (r = -0.4, p = 0.012). Furthermore, a strong correlation was also observed between FRS and AID (r = -0.53, p = 0.002). Bland-Altman analysis demonstrated that the automated methodology had better reproducibility and less variability in distensibility measurements than the manual methodology. Conclusion The study suggests that AID could be valuable for assessing aortic stiffness. AID could help clinicians diagnose and manage cardiovascular diseases more accurately. The automatic approach provides reliable measurements for aortic distensibility and strain, which has clinical implications.Schematic Chart of the Study Process

Radiographic Indicators of Craniocervical Instability: Analyzing Variance of Normative Supine and Upright Imaging in a Healthy Population.

Single-institution retrospective review. To establish baseline ranges and variability of 7 radiographic measurements of the cervical spine in a healthy patient population as potential diagnostic tools for craniocervical instability. Craniocervical instability, common in patients with connective tissue disease such as Ehlers-Danlos Syndrome, often presents with a wide range of symptoms, including neck pain. Current diagnostic methods employ a range of clinical and radiographic features, but diagnostic challenges remain due to missed indications on static imaging and a lack of standardized measurement values and normalized variance. Seventy-two healthy patients with cervical imaging were analyzed. Surgimap software was used to annotate supine computed tomography images, flexion, extension, and neutral x-ray images for measurement. These measurements included the atlanto-dental interval, clival-axial angle, basion-dens interval, basion-axis interval, perpendicular basion to the inferior aspect of C2, also known as Grabb Oakes measurement, and the hard palate to C1 and hard palate to C2. Statistical analysis assessed differences among imaging modalities, and coefficients of variation were calculated for each measurement. Our cohort consisted of a total of 72 patients with a mean age of 64 (SD: 13.54). All measurements except for the basion-axial interval and atlanto-dental interval demonstrated a significant difference between extension and flexion x-ray measurements. clivo-axial angle, hard palate to C1, and hard palate to C2 demonstrated the lowest coefficients of variance across imaging modalities. Understanding normal variance in cervical measurements is invaluable for accurate CCI diagnosis. Using a cohort of healthy patients, this study delineates the distribution and spread of 7 cervical measurements, delineating reference values and variability in these key measurements and highlighting their potential for use as imaging markers for CCI. Level III.

Inter-Vendor differences in speckle tracking strain - A ten year follow-up on the Strain Standardization Task Force Inter-Vendor Comparison Study

Abstract Background Global longitudinal strain (GLS) derived from two-dimensional speckle-tracking echocardiography is feasible and accurate. Nonetheless, in 2013, the Inter-Vendor Comparison Study showed significant differences of measurement results among vendors. In order to make tracking-based strain imaging a clinically accepted and useful parameter, it is of outmost importance to have interchangeable and accurate measurement results from all vendors. Purpose To investigate if the efforts of the EACVI/ASE/Industry Task Force to Standardize Deformation Imaging have led to a reduction of inter-vendor differences during the past ten years. Methods In an unique setting, in one single room, 372 echocardiographic examinations were performed in sixty-two subjects (50 male, age 56.1 ± 16.98) with a wide range of left ventricular (LV) function (ejection fraction from 30% to 64%) using ultrasound systems from six manufacturers. Each subject was scanned consecutively on all machines by the same assigned experienced sonographer. For each subject two image sets of LV apical views were acquired in order to assess reproducibility in a true test-retest setting. We assessed mean GLS (GLSAV) as average peak systolic global strain from the three apical views on five vendor-specific and five vendor-independent software solutions. We measured endocardial and mid-/full-wall GLS. Since there is no gold standard method to measure GLS, we compared GLSAV of each vendor to the average of the GLS values only from vendors that provide tracking software solutions (SWS) for clinical use. Results For both endocardial (Figure 1) and mid-/full-wall (Figure 2) GLS measurements from clinical SWS were comparable and within a very narrow range (mean GLS of vendors 17.25 ± 0.3% and 15.36 ± 0.3% respectively). The maximum absolute difference between all SWS was 4.1% and 4.9% strain units for endocardial and mid-/full-wall GLS respectively. GLSAV of each software versus the mean of clinical SWS showed significant correlation for most of the companies (r² >0.8, p<0.001). Test-retest variability of GLS measurements expressed as relative mean error was good and lower than for LV ejection fraction (6.3% on average for mean GLS and 7% for LV ejection fraction, p>0.05). Conclusions Our data show a substantial inter-vendor bias in GLS measurements. Nevertheless, in contrast to the situation ten years ago, companies that provide tracking software solutions for clinical use provide now very similar GLS values. In addition, most companies do now allow mid-/full-wall tracking. Our data indicate that the efforts of the strain standardization task force have been fruitful. A continuing effort is needed until all software providers adhere to the task force consensus recommendations.Figure 1Figure 2

Core laboratory versus center-reported echocardiographic assessment of the native and bioprosthetic aortic valve

Abstract Background The use of a central echocardiographic core laboratory (ECL) is advised to minimize measurement variation and heterogeneity in clinical trials. Insights into quantitative differences between ECL and center-reported echocardiographic assessment of the native and bioprosthetic aortic valve are lacking. We aimed to explore clinically relevant differences between these evaluations. Methods Data were used from the PERIcardial SurGical AOrtic Valve ReplacemeNt (PERIGON) Pivotal Trial for the Avalus valve. In this trial, patients with an indication for surgical aortic valve replacement (SAVR) due to aortic stenosis or regurgitation (AR) were enrolled. Serial echocardiographic examinations were performed at each center and reanalyzed by an independent ECL. For the bioprosthetic valve analysis, postoperative data throughout 5-year follow-up were pooled. Differences between the ECL and the centers in continuous parameters were quantified in mean differences and intraclass correlation coefficients (ICCs). Between-center differences were illustrated by plotting standardized mean differences (SMDs) between centers and the ECL for the 10 sites that implanted the most prostheses. Agreement on AR, paravalvular leak (PVL), and prosthesis-patient mismatch (PPM) classification was investigated using Cohen’s kappa coefficients. Results The analysis on the native aortic valve was performed on 1118 patients. The relative mean difference was largest for the left ventricular outflow tract (LVOT) area, followed by stroke volume and effective orifice area (index), with center-reported values being 11-7% higher (Table 1). High ICCs of around 0.90 were observed for peak aortic jet velocity, mean pressure gradient, and the velocity-time integral across the aortic valve. More than 5000 echocardiograms were available for the bioprosthetic valve analysis. Therein, comparable results were observed. In Figure 1, differences in assessment on center level are illustrated. The SMDs for peak velocity were between 0 and 0.5 for all centers, while there was more heterogeneity between centers for other parameters. The kappa coefficient was 0.59 (95% confidence interval [CI] 0.56, 0.63) for agreement on native AR, 0.28 (95% CI 0.18, 0.37) for PVL, and 0.42 (95% CI 0.40, 0.44) for PPM. Conclusions For echocardiographic assessment of the native and bioprosthetic aortic valve, agreement between the ECL and the clinical centers varies by parameter and by center. There is high agreement on continuous-wave Doppler-related measurements. On the contrary, agreement is low for parameters that involve measurement of the LVOT diameter. These results provide important context for the interpretation of aortic valve performance in studies that lack central ECL evaluation.

AI derived myocardial left ventricular volumes outperforms clinician segmentation for prediction of all-cause mortality

Abstract Background Measuring heart structure and function drives much cardiac decision making and therapy. Precise quantification is therefore of high importance, but manual (clinician) segmentation introduces measurement variability. Purpose Automated segmentation of cardiac MRI (CMR) left ventricular (LV) volumes provides improved precision but how this translates into clinical outcomes has yet to be defined. In order to test predictive accuracy in a wide range of adverse LV morphologies, we applied AI LV segmentation to patients with coronary disease or cardiomyopathy. Methods Scans were analysed from a retrospective clinical CMR database and mortality data was obtained from a national database. Clinician measurement of indexed LV end-diastolic volume (LVEDVi), LV mass (LVMi), myocardial contraction fraction (MCF: ratio of stroke volume to myocardial volume; a measure of myocardial efficiency) and EF were recorded from clinical reports (all senior clinicians with >5 years level 3 experience) and compared to AI measurement using a segmentation algorithm. This has previously been shown to exceed human precision and required no manual correction (1,2). Random survival forests were built to identify overall predictive value of AI vs clinician derived LV volumes. These are machine-learning algorithms for predicting time-to-event outcomes and can capture complex relationships between predictors and outcome. Random survival forests were built from AI and clinician models with EF, EDVi, LVMi and MCF as predictors for all-cause mortality. A train:test (80:20) split, stratified for outcome was employed. Concordance (C)-indices (measuring predictive accuracy) and permutation importances (measuring significance of each predictor within the model) (Table) with 1000 bootstrapped 95% confidence intervals and p-values were derived. Results 8,299 patients were analysed. Patients were 60(51-70) years old and 37% female. 49% had coronary disease, 25% had DCM and 19% had HCM. At a median follow-up of 5.3 years (IQR 4.2-6.6 years) there were 1,384 deaths (17%). AI derived LV-parameter models had higher predictive accuracy than clinician derived models (C-Indices: 0.66±0.002 vs 0.65±0.005, p<0.001). A subgroup analysis of patients undergoing ischaemia testing for coronary disease was performed (n=3,560) and markers of ischaemia (positive vs negative) and infarction (non-viable vs viable) were included in the models. AI had a higher predictive accuracy compared to clinicians when including these additional predictors (C-Indices: 0.68±0.03 vs 0.63±0.01, p<0.001). Conclusion AI derived LV volumes outperforms clinicians in prediction of all-cause mortality reflecting improved precision. Improvements in predictive accuracy are likely to be clinically important when applied to populations and high-risk groups. Manual clinician segmentation should be superseded by clinician-supervised AI.

The importance of heart rate on left ventricular global longitudinal strain in echocardiography: novel insights facilitated by automated deep learning methods

Abstract Background Heart rate (HR) is assumed to influence echocardiographic measurements. Consequently, HR needs to be considered for accurate assessment of cardiac function. Despite left ventricular global longitudinal strain (LV GLS) being recognised as a valuable measure of cardiac function, its normal reference ranges remain confined to patients within a limited range of resting HR. So far, time-consuming manual analyses and high measurement variability have precluded comprehensive assessment of the interplay between HR and LV GLS. Using fully automated GLS measurements provided by novel deep learning (DL) methods, it is now possible to evaluate changes in LV GLS across a wide range of HR. Purpose To improve echocardiographic assessments across a wide range of HR intervals, we aimed to study the influence of controlled HR variations on LV GLS using programmable pacemakers and fully automated DL measurements. Methods Participants with sinus node dysfunction and implanted programmable pacemakers were enrolled. Echocardiographic acquisitions were obtained at baseline HR and during stepwise increments by 10 beats/min, targeting a range from 50 to 140 beats/min. Recordings of cine-loops including 10 cardiac cycles were obtained for the four-chamber, two-chamber, and apical long axis view. LV GLS was measured for all cycles using a fully automated DL method developed by our group, and presented as mean of the three standard apical views for all patients at each HR level. A linear mixed model was used for construction of an overall trendline based on the estimated fixed effects across all 50 patients, stating patient number as the random effect. The correlation between HR and LV GLS was evaluated by a likelihood ratio test. Results Fifty patients were included, 52% females, mean age 68 years (27 to 88 years). All patients had preserved atrioventricular conduction. Resting HR ranged from 50 to 87 beats/min (mean 64 beats/min). At baseline echocardiographic acquisition, most participants were within normal ranges for LV volumes, systolic and diastolic function. A total of about 13,000 cardiac cycles were automatically analysed by the DL method. The overall trend demonstrated a linear relation between increasing HR and decreasing absolute LV GLS (Figure 1). Across HR increments from 50 to 140 beats/min, there was a 32% (22%–42%) reduction in absolute LV GLS, declining from -17.1% to -11.7%. The strong correlation between changes in HR and LV GLS was further supported by a highly significant likelihood ratio test (p-value <0.001). Conclusions There was a reduction of absolute LV GLS with increasing HR. These findings emphasize the importance of integrating HR considerations into clinical echocardiography practice. Moreover, the results highlight that DL methods can unlock substantially richer insights from individual patient data, offering a new pathway towards more personalized and precise cardiac diagnostics.Figure 1

The relationship between post-anastomosis brachial artery flow rate and brachiocephalic arteriovenous fistula access maturity in end-stage kidney disease patients with diabetes mellitus

Background: From previous studies, evaluation of post-anastomosis draining-vein volume flow rate with Doppler ultrasound can be a predictor for arteriovenous fistula maturation. Due to the high variation in measurements by the effect of probe pressure in draining vein, measuring volume flow rate based on post-anastomosis feeding-artery may be an early alternative predictor of arteriovenous fistula maturation. This study aims to investigate the correlation of post-creation brachial artery volume flow rate on maturity of brachiocephalic arteriovenous fistula access in patients with end-stage kidney disease with diabetes mellitus. Methods: A retrospective cohort study was conducted on end-stage kidney disease patients with diabetes mellitus who underwent brachiocephalic arteriovenous fistula creation at three hospitals from July 2019 to March 2020. Doppler ultrasound examination of the brachial artery and draining vein volume flow rate was conducted at pre-operative, post-creation, 2 weeks, and 6 weeks post-creation. Maturity was evaluated at 6 weeks post-anastomosis. Results: A total of 71 subjects met the inclusion and exclusion criteria, with 44 (62%) achieving maturation within 6 weeks. There was a correlation between post-anastomosis brachial artery (p < 0.001) and draining vein volume flow rate (p < 0.001) with arteriovenous fistula maturity after 6 weeks post-operatively. Brachial artery volume flow rate of ⩾350 mL/min can predict AVF maturity with a sensitivity of 95.45% (95% confidence interval = 84.86–98.74) and a specificity of 85.19% (95% confidence interval = 67.52–94.08). Conclusion: Post-anastomosis brachial artery flow volume can be a valuable parameter to predict brachiocephalic arteriovenous fistula maturity. It is a potential alternative to draining vein volume flow, which is technically a difficult examination.

Sexual activity and climatic adaptation assessment of West African Dwarf goats introduced into Algeria

This study aimed to highlight the effects of variations in age, seasons and climatic conditions on the reproductive activity of West African Dwarf Goats imported from tropical zones in Algeria, and to verify the degree of their adaptation to Mediterranean climatic conditions. For this purpose, testicular biometry and hormonal analysis (testosterone and LH levels) using the radioimmunological method were carried out monthly. In total, seven goats aged between 18 to 48+ months were surveyed during the period from September 2021 to March 2022. The results showed a considerable effect of age on testicular measurements. Bucks less than 18 months recorded the lowest average testicular length, width, thickness and volume, scrotal width and circumference, as levels of testosterone concentrations. All variables were strong correlated. Seasonal variations in the average testicular measurements and hormonal concentrations were observed, without affecting testicular activity. Apart from thenegative action of ambient temperature, no effects of relative humidity or atmospheric pressure were revealed. West African Dwarf Goats showed a good capacity to adapt to Mediterranean climatic conditions through their continuous testicular activity during the year.

Repeatability and reproducibility of artificial intelligence-acquired fetal brain measurements (SonoCNS) in the second and third trimesters of pregnancy

Artificial Intelligence (AI)-based algorithms are increasingly entering clinical practice, aiding in the assessment of fetal anatomy and biometry. One such tool for evaluating the fetal head and central nervous system structures is SonoCNS™, which delineates appropriate planes for measuring head circumference (HC), biparietal diameter (BPD), occipitofrontal diameter (OFD), transcerebellar diameter (TCD), width of the posterior horn of the lateral ventricle (Vp), and cisterna magna (CM) based on a 3D volume acquired at the level of the fetal head’s thalamic plane. This study aimed to evaluate the intra- and interobserver variability of measurements obtained using this software. The study included 381 patients, 270 in their second trimester of pregnancy (70%) and 111 in the third trimester. Each patient underwent manual biometric measurements of the aforementioned structures and twice using the SonoCNS software. We calculated the intraobserver variability between the manual measurements and the average of the automated measurements, as well as the interobserver variability for automated measurements. We also compared the median examination time for manual and automated measurements. The interclass correlation coefficients (ICC) for interobserver and intraobserver variability for parameters BPD, HC, and OFD ranged from good to excellent reproducibility in the general population and subgroups (> 0.75). CM and Vp measurements, both in the general population and subgroups, fell into the category of moderate (0.5–0.75) and poor reproducibility (< 0.5). TCD measurements showed moderate (> 0.5) to good reproducibility (0.75–0.9), and OFD showed good and excellent reproducibility. The assessment of the biometry of fetal head structures using SonoCNS took an average of 63 s compared to 14 s for manual measurement (p < 0.001). The SonoCNS™ software is characterized by good to excellent reproducibility and repeatability in the measurement of fetal skull biometry (BPD, HC, and OFD), with poorer performance in measurements of intracranial structures (CM, Vp, TCD). Apart from biometric parameters, the software is useful in clinical practice for delineating appropriate planes from the acquired volume of the fetal head and shortening examination time.

Repeatability of Corneal Epithelial Thickness Map Using Anterior Segment Optical Coherence Tomography in Normal and Corneal Disease Patients.

To evaluate the repeatability of corneal epithelial thickness (CET) measurements in normal eyes and eyes diagnosed with corneal disease using the epithelial thickness map (ETM) of anterior segment optical coherence tomography (OCT). In this retrospective study, patients with 3 OCT scans using the ETM mode of Cirrus OCT (Carl Zeiss Meditec AG, Jena, Germany) between October 2021 and January 2024 were reviewed. Two groups of subjects were included: (1) normal subjects with no history of ophthalmic surgery, corneal diseases, and topical antiglaucoma medication uses; and (2) subjects with corneal diseases including dry eye syndrome, recurrent corneal erosion, pterygium, and others. 57 eyes of 57 normal subjects and 106 eyes of 76 patients with corneal disease were included. ETM was analyzed in 25 zones (1 zone within 0-2 mm diameter, 8 zones within 2-5 mm diameter, 8 zones within 5-7 mm diameter, and 8 zones within 7-9 mm diameter). Repeatability was evaluated by calculating intraclass correlation coefficient (ICC), coefficient of variation (CoV), within-subject standard deviation (Sw), and Bland-Altman plot. Among a total of 25 sectors, the normal eyes showed high repeatability (ICC > 0.75, CoV 2.17%-5.29%, and Sw 0.76-1.65 μm) in 23 sectors, and in corneal diseases patients also showed high repeatability (ICC >0.75, CoV 4.17%-9.61%, and Sw 1.29-3.34 μm) in 22 sectors. However, the wide range of 95% limit of agreement (LoA) width of Bland-Altman plot presented in corneal disease group and some peripheral zones in normal eyes indicates some variability of CET measurements. Except for a few peripheral sectors, ETM of Cirrus OCT provides repeatable CET measurements in normal eyes, however in corneal disease group, repeatability was not consistently high. To measure CET accurately, performing multiple measurements is advised especially in patients with corneal disease and patients in whom peripheral CET values.

Interobserver Reproducibility of Ultrasound Attenuation Imaging Technology in Liver Fat Quantification.

This study aims to investigate the interobserver variability in the quantitative assessment of liver fat content using ultrasound attenuation imaging technology (USAT). This prospective, single-center study included 96 adult patients who were either diagnosed with or suspected of having metabolic dysfunction-associated steatotic liver disease. Independent observers, blinded to each other's assessments, evaluated hepatic steatosis visually and through USAT measurements. Separate measurements were taken at five intercostal and subcostal sites, and the median values of these measurements were recorded. The correlation between USAT measurements and visual steatosis grades was examined using Spearman's correlation test. Intraclass correlation coefficient (ICC) and Bland-Altman analysis were used to evaluate the interobserver variability of USAT measurements. Interobserver agreement for USAT measurements was excellent for the intercostal examination and good for the subcostal examination (p < 0.001). Body mass index did not significantly affect the level of interobserver agreement. Interobserver variability in Bland-Altman plots of USAT measurements was within the 95% limits of agreement. USAT measurements correlated very strongly with the visual degree of hepatic steatosis, both intercostal and subcostal (p < 0.001). USAT measurements were also significantly different between different visual degrees of hepatic steatosis (p < 0.001). In the assessment of hepatic steatosis, USAT measurements obtained from the intercostal space showed excellent agreement in terms of interobserver reproducibility.

On the Parasitic Surface Adsorption of Pyrrolidinium and Phosphonium-based Ionic Liquids Preventing Accurate Differential Capacitance Measurements

Abstract Differential capacitance measurements are known to provide vital information regarding electrical double layer charging as well as interfacial structuring of ionic liquids and ionic liquid-based electrolytes. Several hurdles have prevented these types of measurements from becoming widely used, including the fact that there exists no real consensus as to how the measurement needs to be performed and the results analyzed. To add to the difficulty, some ionic liquids are known to display a hysteresis process, thus inducing measurement variabilities. In this report, we study pyrrolidinium and phosphonium-based ionic liquid electrolytes and show that hysteresis processes indeed exist and that these are mostly the consequence of cationic adsorption on the surface. Atomic force microscopy experiments reveal that pyrrolidinium-based systems display a much denser degree of ionic compaction at the interface, compared to the phosphonium-based systems, a fact that we correlate with the much more intense hysteresis measured in pyrrolidinium-based systems. We further propose a new method for the measurement of differential capacitance and compare it with other methods in use. It is found that the proposed method allows to minimize hysteresis phenomena, thereby leading to better accuracy.

Measurement variability of blood-brain barrier permeability using dynamic contrast-enhanced magnetic resonance imaging.

Dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) is used to quantify the blood-brain barrier (BBB) permeability-surface area product. Serial measurements can indicate changes in BBB health, of interest to the study of normal physiology, neurological disease, and the effect of therapeutics. We performed a scan-rescan study to inform both sample size calculation for future studies and an appropriate reference change value for patient care. The final dataset included 28 healthy individuals (mean age 53.0 years, 82% female) scanned twice with mean interval 9.9 weeks. DCE-MRI was performed at 3T using a 3D gradient echo sequence with whole brain coverage, T1 mapping using variable flip angles, and a 16-min dynamic sequence with a 3.2-s time resolution. Segmentation of white and grey matter (WM/GM) was performed using a 3D magnetization-prepared gradient echo image. The influx constant Ki was calculated using the Patlak method. The primary outcome was the within-subject coefficient of variation (CV) of Ki in both WM and GM. Ki values followed biological expectations in relation to known GM/WM differences in cerebral blood volume (CBV) and consequently vascular surface area. Subject-derived arterial input functions showed marked within-subject variability which were significantly reduced by using a venous input function (CV of area under the curve 46 vs. 12%, p < 0.001). Use of the venous input function significantly improved the CV of Ki in both WM (30 vs. 59%, p < 0.001) and GM (21 vs. 53%, p < 0.001). Further improvement was obtained using motion correction, scaling the venous input function by the artery, and using the median rather than the mean of individual voxel data. The final method gave CV of 27% and 17% in WM and GM, respectively. No further improvement was obtained by replacing the subject-derived input function by one standard population input function. CV of Ki was shown to be highly sensitive to dynamic sequence duration, with shorter measurement periods giving marked deterioration especially in WM. In conclusion, measurement variability of 3D brain DCE-MRI is sensitive to analysis method and a large precision improvement is obtained using a venous input function.

Load spectra of a light unmanned aircraft – data recording frequencies and resulting measurement variations

The article focuses on the load spectrum of a lightweight unmanned aircraft. It examines the impact of load signal sampling frequency on the load spectrum derived from the load signal. The flight sessions followed two scenarios: a maneuvering flight causing a wide range of load factor variations and a calm photogrammetric flight. The recorded load signals from two types of sensors were initially rescaled into load factor time series, with an optional signal smoothing process. These series were then downsampled by selecting every nth term, resulting in load factor sequences recorded at a lower frequency. Next, all sequences were transformed into sequences of local extremes of the Load Levels, resulting from quantifying the operational load variability into 32 intervals. Two options were considered: without filtering or with filtering of sequential pairs of terms generating small Load Level increments. Subsequently, the Rainflow Counting algorithm was applied, producing 32x32 load half-cycle arrays. Based on these arrays, incremental load spectra were calculated. The study provides a detailed comparison of load spectra for different load signal sources and recording frequencies. Additionally, calculations of the fatigue life of a structural element subjected to various load spectra were performed, leading to the formulated conclusions.

From Simulations to Inference: Using Machine Learning to Tune Patient-Specific Finite-Element Models of the Middle Ear Towards Objective Diagnosis.

Computational models, particularly finite-element (FE) models, are essential for interpreting experimental data and predicting system behavior, especially when direct measurements are limited. A major challenge in tuning these models is the large number of parameters involved. Traditional methods, such as one-by-one sensitivity analyses, are time-consuming, subjective, and often return only a single set of parameter values, focusing on reproducing averaged data rather than capturing the full variability of experimental measurements. In this study, we applied simulation-based inference (SBI) using neural posterior estimation (NPE) to tune an FE model of the human middle ear. The training dataset consisted of 10,000 FE simulations of stapes velocity, ear-canal (EC) input impedance, and absorbance, paired with seven FE parameter values randomly sampled within plausible ranges. The neural network learned the association between parameters and simulation outcomes, returning the probability distribution of parameter values that can reproduce experimental data. Our approach successfully identified parameter sets that reproduced three experimental datasets simultaneously. By accounting for experimental noise and variability during training, the method provided a probability distribution of parameters, representing all valid combinations that could fit the data, rather than tuning to averaged values. The network demonstrated robustness to noise and exhibited an efficient learning curve due to the large training dataset. SBI offers an objective alternative to laborious sensitivity analyses, providing probability distributions for each parameter and uncovering interactions between them. This method can be applied to any biological FE model, and we demonstrated its effectiveness using a middle-ear model. Importantly, it holds promise for objective differential diagnosis of conductive hearing loss by providing insight into the mechanical properties of the middle ear.

Advancements and challenges in Shear-Wave Elastography of tendons: a comprehensive review.

Shear-Wave Elastography (SWE) has emerged as a promising non-invasive imaging technique for assessing the mechanical properties of tendons, particularly larger and more superficially located tendons of the body. Despite its potential, significant variability in SWE measurements exists due to differences in protocols, positioning, and equipment. Standardizing these factors, enhancing operator training, and reporting reliability metrics are crucial to improve the consistency and comparability of SWE data. This review aims to synthesize current knowledge and report on the existing practices in tendon SWE. By addressing the current challenges and variability, SWE has the potential to become a reliable tool for diagnosing and monitoring tendon pathologies, ultimately enhancing patient care and outcomes.

Inconsistency in ferritin reference intervals across laboratories: a major concern for clinical decision making.

Iron deficiency anemia is a significant global health concern, diagnosed by measuring hemoglobin concentrations in combination with plasma ferritin concentration. This study investigated the variability in ferritin reference intervals among laboratories in the Netherlands and examined how this affects the identification of iron-related disorders. Ferritin reference intervals from 52 Dutch ISO15189-certified medical laboratories were collected. Ferritin, hemoglobin and mean corpuscular volume data of non-anemic apparently healthy primary care patients, measured by four laboratory platforms (Beckman, Abbott, Siemens, and Roche), were collected (n=397,548). Median ferritin levels were determined per platform, stratified by sex and age. The proportion of ferritin measurements outside of the reference interval was calculated using the reference intervals from the 52 laboratories (using a total of n=1,093,442 ferritin measurements). Lastly, ferritin data from 3,699 patients as captured in general practitioner (GP) data from the PHARMO Data Network were used to assess the variation of abnormal ferritin measurements per GP. Median plasma ferritin concentrations were approximately four times higher in men and twice as high in postmenopausal women compared to premenopausal women. Moreover, there are substantial differences in the median plasma ferritin concentration between the four platforms. However, even among laboratories using the same platform, ferritin reference intervals differ widely. This leads to significant differences in the percentages of measurements classified as abnormal, with the percentage of ferritin measurements below the reference limit in premenopausal women ranging from 11 to 53 %, in postmenopausal women from 3 to 37 %, and in men from 2 to 19 %. The percentage of ferritin measurements above the reference limit in premenopausal women ranged from 0.2 to 11 %, in postmenopausal women from 3 to 36 % and in men from 7 to 32 %. The lack of harmonization in ferritin measurement and the disagreement in plasma ferritin reference intervals significantly impact the interpretation of the iron status of patients and thereby the number of iron disorder diagnoses made. Standardization or harmonization of the ferritin assays and establishing uniform reference intervals and medical decision limits are essential to reduce the substantial variability in clinical interpretations of ferritin results.

Influences of Variability in Attenuation Compensation on the Estimation of Backscatter Coefficient of Median Nerves in Vivo.

Peripheral nerves remain a challenging target for medical imaging, given their size, anatomical complexity, and structural heterogeneity. Quantitative ultrasound (QUS) applies a set of techniques to estimate tissue acoustic parameters independent of the imaging platform. Many useful medical and laboratory applications for QUS have been reported, but challenges remain for deployment in vivo, especially for heterogeneous tissues. Several phenomena introduce variability in attenuation estimates, which may influence the estimation of other QUS parameters. For example, estimating the backscatter coefficient (BSC) requires compensation for the attenuation of overlying tissues between the transducer and the underlying tissue of interest. The purpose of this study is to extend prior studies by investigating the efficacy of several analytical methods of estimating attenuation compensation on QUS outcomes in the human median nerve. Median nerves were imaged at the volar wrist in vivo and beam-formed radiofrequency (RF) data were acquired. Six analytical approaches for attenuation compensation were compared: 1-2) attenuation estimated by applying spectral difference method (SDM) and spectral log difference method (SLDM) independently to regions of interest (ROIs) overlying the nerve and to the nerve ROI itself; 3-4) attenuation estimation by applying SDM and SLDM to ROIs overlying the nerve, and transferring these properties to the nerve ROI; and 5-6) methods that apply previously published values of tissue attenuation to the measured thickness of each overlying tissue. Mean between-subject estimates of BSC-related outcomes as well as within-subject variability of these outcomes were compared among the 6 methods. Compensating for attenuation using SLDM and values from the literature reduced variability in BSC-based outcomes, compared to SDM. Variability in attenuation coefficients contributes substantially to variability in backscatter measurements. This work has implications for the application of QUS to in vivo diagnostic assessments in peripheral nerves and possibly other heterogeneous tissues.

Inter-laboratory study for extraction testing of medical devices

Biocompatibility evaluation of medical devices often relies on chemical testing according to ISO 10993–18 as a critical component for consideration. However, the precision associated with these non–targeted chemical characterization assessments has not been well established. Therefore, we have conducted a study to characterize intra–laboratory (repeatability) and inter–laboratory (reproducibility) variability associated with chemical testing of extractables from polymeric materials. To accomplish this, this study focused on two polymers, each with nine chemicals that were intentionally compounded into the materials. Eight different laboratories performed extraction testing in two solvents and subsequently characterized the extracts using gas chromatography and liquid chromatography methods. Analysis of the resulting data revealed the central 90 % range for the repeatability and reproducibility relative standard deviations are (0.09, 0.22) and (0.30, 0.85), respectively, for the participating laboratory methods. This finding implies that if the same sample was tested by two different laboratories using the same extraction conditions, there is 95 % confidence for 95 % of systems that the test results could exhibit differences up to 240 %. While the study was not designed to evaluate the relative impact of specific underlying factors that may contribute to variability in quantitation, the data obtained suggest the variability associated with analytical method alone is a substantial contribution to the overall variability. The relatively large reproducibility limits we observed may have significant implications where variability in extraction measurements can impact aspects of biocompatibility risk evaluation, such as exposure dose estimation and chemical equivalence assessments.

Is there dietary macronutrient malabsorption in children with environmental enteropathy?

Assessing the digestive and absorptive capacity of the gastro-intestinal tract (GIT) using minimally- or non-invasive methods, particularly in children, has been difficult owing to the complex physiology and variability in functional measurements. However, measuring GIT function is increasingly important with the emerging relevance of childhood environmental enteropathy (EE) as a mediating factor in linear growth faltering, severe acute malnutrition, poor oral vaccine uptake and impaired cognition. In EE, sub-optimal nutrient digestion and absorption (malabsorption) forms the critical link to the conditions mentioned above. The present narrative review discusses probable mechanisms that can cause malabsorption of macronutrients, along with mechanistic and experimental evidence, in children (if not, in adults) with EE. The strengths and limitations of the human experimental studies are examined in relation to a battery of existing and potential tests that are used to measure malabsorption. From the available studies conducted in children, lactose and fat malabsorption are more likely to occur in EE. Breath tests (non-invasive) measuring carbohydrate (13C-starch/sucrose/lactose), fat (13C-mixed triglyceride) and dipeptide (benzoyl-L-tyrosyl-L-1-13C-alanine) malabsorption with modifications to the existing protocols seem suitable for use in children with EE. Future research should focus on understanding the degree of macronutrient malabsorption using these tests, in different settings, and link them to functional outcomes (such as growth, muscle strength, cognition).