Mean Coefficient Of Variation Research Articles

Using seasonal oscillations in fin ray microchemistry to chemically age Lake Sturgeon

AbstractObjectiveNonlethally sampled pectoral fin rays are commonly used as aging structures for Lake Sturgeon Acipenser fulvescens, but they tend to underestimate the true age in older, slow‐growing individuals (age > 14 years). Current aging practices involve counting bands along the structure, which are construed as annuli. Oscillations of certain trace elements corresponding with annuli have been seen across various fish species, with patterns continuing to the marginal edge of hard structures. This study explored the aging of fin rays by using microchemistry patterns in Lake Sturgeon of known age (n = 94; ages 5–21) to determine the potential use of this method as an alternative or supplementary aging technique.MethodsElements were chosen for age determination analysis by examining the relationship between profile minima/maxima and visually interpreted annuli. Fish were assigned ages using three different methods: (1) traditional interpretation (counting annuli along the structure), (2) chemical interpretation (examination of seasonal variations in elemental profiles with visually identified annuli), and (3) a statistical model (multivariate multiple changepoint analysis with finite differencing using raw elemental profiles).ResultMean absolute differences between age estimates and known age were significantly higher for the traditional interpretation method than for the chemical interpretation method. The mean coefficient of variation in estimated age was 11.14% for the traditional interpretation method and 4.04% for the chemical interpretation method. The changepoint model was able to correctly classify age for 100% of the samples within ±1 year in one population (ages 5–8) but could not classify samples from the second population (ages 12–21).ConclusionOur results suggest that chemical aging techniques could provide more reliable age estimates for juvenile and subadult Lake Sturgeon when fin rays are the only aging option. Further work is required to determine the applicability of the model for assigning ages to older fish and for use with different populations and structures.

Repeat it without me: Crowdsourcing the T1 mapping common ground via the ISMRM reproducibility challenge.

T1 mapping is a widely used quantitative MRI technique, but its tissue-specific values remain inconsistent across protocols, sites, and vendors. The ISMRM Reproducible Research and Quantitative MR study groups jointly launched a challenge to assess the reproducibility of a well-established inversion-recovery T1 mapping technique, using acquisition details from a seminal T1 mapping paper on a standardized phantom and in human brains. The challenge used the acquisition protocol from Barral et al. (2010). Researchers collected T1 mapping data on the ISMRM/NIST phantom and/or in human brains. Data submission, pipeline development, and analysis were conducted using open-source platforms. Intersubmission and intrasubmission comparisons were performed. Eighteen submissions (39 phantom and 56 human datasets) on scanners by three MRI vendors were collected at 3 T (except one, at 0.35 T). The mean coefficient of variation was 6.1% for intersubmission phantom measurements, and 2.9% for intrasubmission measurements. For humans, the intersubmission/intrasubmission coefficient of variation was 5.9/3.2% in the genu and 16/6.9% in the cortex. An interactive dashboard for data visualization was also developed: https://rrsg2020.dashboards.neurolibre.org. The T1 intersubmission variability was twice as high as the intrasubmission variability in both phantoms and human brains, indicating that the acquisition details in the original paper were insufficient to reproduce a quantitative MRI protocol. This study reports the inherent uncertainty in T1 measures across independent research groups, bringing us one step closer to a practical clinical baseline of T1 variations in vivo.

Automated body length and body condition measurements of whales from drone videos for rapid assessment of population health

AbstractMonitoring body length and body condition of individuals helps determine overall population health and assess adaptation to environmental changes. Aerial photogrammetry from drone‐based videos is a valuable method for obtaining body length and body condition measurements of cetaceans. However, the laborious manual processing of drone‐based videos to select frames to measure animals ultimately delays assessment of population health and hinders conservation actions. Here, we apply deep learning methods to expedite the processing of drone‐based videos to improve efficiency of obtaining important morphological measurements of whales. We develop two user‐friendly models to automatically (1) detect and output frames containing whales from drone‐based videos (“DeteX”) and (2) extract body length and body condition measurements from input frames (“XtraX”). We use drone‐based videos of gray whales to compare manual versus automated measurements (n = 86). Our results show automated methods reduced processing times by one‐ninth, while achieving similar accuracy as manual measurements (mean coefficient of variation <5%). We also demonstrate how these methods are adaptable to other species and identify remaining challenges to help further improve automated measurements in the future. Importantly, these tools greatly speed up obtaining key morphological data while maintaining accuracy, which is critical for effectively monitoring population health.

Real-World Continuous Glucose Monitoring Data from a Population with Type 1 Diabetes in South Korea: Nationwide Single-System Analysis.

Background: We used continuous glucose monitoring (CGM) data to investigate glycemic outcomes in a real-world population with type 1 diabetes (T1D) from South Korea, where the widespread use of CGM and the nationwide education program began almost simultaneously. Methods: Data from Dexcom G6 users with T1D in South Korea were collected between January 2019 and January 2023. Users were included if they provided at least 90 days of glucose data and used CGM at least 70% of the days in the investigational period. The relationship between CGM utilization and glycemic metrics, including the percentage of time in range (TIR), time below range (TBR), and time above range (TAR), was assessed. The study was approved by the Institutional Review Board of Samsung Medical Center (SMC 2023-05-030). Results: A total of 2288 users were included. Mean age was 41.5 years (57% female), with average uploads of 428 days. Mean TIR was 62.4% ± 18.5%, mean TBR <70 mg/dL was 2.6% ± 2.8%, mean TAR >180 mg/dL was 35.0% ± 19.3%, mean glucose was 168.1 ± 35.8 mg/dL, mean glucose management indicator was 7.2% ± 0.9%, and mean coefficient of variation was 36.7% ± 6.0%. Users with higher CGM utilization had higher TIR (67.8% vs. 52.7%), and lower TBR <70 mg/dL (2.3% vs. 4.7%) and TAR >180 mg/dL (30.0% vs. 42.6%) than those with low CGM utilization (P < 0.001 for all). Users whose data were shared with others had higher TIR than those who did not (63.3% vs. 60.8%, P = 0.001). Conclusions: In this South Korean population, higher CGM utilization was associated with a favorably higher mean TIR, which was close to the internationally recommended target. Using its remote data-sharing feature showed beneficial impact on TIR.

Corneal endothelial cell morphology in children with autosomal recessive Alport syndrome: a longitudinal study

ABSTRACT Purpose To evaluate the corneal endothelial cell morphology in children with autosomal recessive Alport syndrome (ARAS). Methods This is a longitudinal, prospective cohort study that evaluated pediatric patients with genetically diagnosed ARAS. Fifty-eight eyes of 29 pediatric patients (12 patients, 17 controls) underwent a full ophthalmic examination. Corneal endothelial cell density (ECD) (cells/mm²), coefficient variation (CV) of cell area (polymegathism), the percentage of hexagonal cells (HEX) (pleomorphism), and central corneal thickness (CCT) were analyzed automatically using a noncontact specular microscopy. Results The mean ECD was 2904 ± 355.48 cell/mm² in the ARAS group and 3263.20 ± 261.71 cell/mm² in the control group (p = 0.004). In the ARAS group, the mean CV was 46.53 ± 10.43, which was significantly higher than that in controls (p = 0.026). The mean HEX was 48.86 ± 14.71 in the ARAS group and 59.06 ± 10.64 in the control group (p = 0.038). The mean CCT was 565.26 ± 39.77 µm in the ARAS group and 579.66 ± 31.65 µm in the control group (p = 0.282). The comparison of endothelial cell characteristic of the ARAS group with 1-year follow-up is as follows: The mean ECD decreased from 2904 ± 355.48 cell/mm² to 2735 ± 241.58 cell/mm² (p = 0.003). The mean CV increased from 46.53 ± 10.43 to 47.93 ± 10.50 (p = 0.471). The mean HEX decreased from 48.86 ± 14.71 to 48.50 ± 10.06 (p = 0.916). The mean CCT decreased from 565.26 ± 39.77 µm to 542.86 ± 40.39 µm (p = 0.000). Conclusion Measurement of ECD and percentage of hexagonality can also be used as an indicator of the health of the corneal endothelium. In this study, the mean ECD and HEX were significantly lower in ARAS group than in age-matched pediatric controls. Polymegathism, which reflects cellular stress, was statistically significantly higher in ARAS group. The mean ECD and CCT decreased significantly at 1-year follow-up. This study may demostrated that endothelial damages and stress in ARAS patients appear in childhood and show a rapid increase with age.

Reduction of ADC bias in diffusion MRI with deep learning-based acceleration: A phantom validation study at 3.0 T

PurposeFurther acceleration of DWI in diagnostic radiology is desired but challenging mainly due to low SNR in high b-value images and associated bias in quantitative ADC values. Deep learning-based reconstruction and denoising may provide a solution to address this challenge. MethodsThe effects of SNR reduction on ADC bias and variability were investigated using a commercial diffusion phantom and numerical simulations. In the phantom, performance of different reconstruction methods, including conventional parallel (SENSE) imaging, compressed sensing (C-SENSE), and compressed SENSE acceleration with an artificial intelligence deep learning-based technique (C-SENSE AI), was compared at different acceleration factors and flip angles using ROI-based analysis. ADC bias was assessed by Lin's Concordance correlation coefficient (CCC) followed by bootstrapping to calculate confidence intervals (CI). ADC random measurement error (RME) was assessed by the mean coefficient of variation (CV¯) and non-parametric statistical tests. ResultsThe simulations predicted increasingly negative bias and loss of precision towards lower SNR. These effects were confirmed in phantom measurements of increasing acceleration, for which CCC decreased from 0.947 to 0.279 and CV¯ increased from 0.043 to 0.439, and of decreasing flip angle, for which CCC decreased from 0.990 to 0.063 and CV¯ increased from 0.037 to 0.508. At high acceleration and low flip angle, C-SENSE AI reconstruction yielded best denoised ADC maps. For the lowest investigated flip angle, CCC = {0.630, 0.771 and 0.987} and CV¯={0.508, 0.426 and 0.254} were obtained for {SENSE, C-SENSE, C-SENSE AI}, the improvement by C-SENSE AI being significant as compared to the other methods (CV: p = 0.033 for C-SENSE AI vs. C-SENSE and p < 0.001 for C-SENSE AI vs. SENSE; CCC: non-overlapping CI between reconstruction methods). For the highest investigated acceleration factor, CCC = {0.479,0.926,0.960} and CV¯={0.519,0.119,0.118} were found, confirming the reduction of bias and RME by C-SENSE AI as compared to C-SENSE (by trend) and to SENSE (CV: p < 0.001; CCC: non-overlapping CI). ConclusionADC bias and random measurement error in DWI at low SNR, typically associated with scan acceleration, can be effectively reduced by deep-learning based C-SENSE AI reconstruction.

Association between glycemic variability and short-term mortality in patients with acute kidney injury: a retrospective cohort study of the MIMIC-IV database

Acute kidney injury (AKI) represents a significant challenge to global public health problem and is associated with poor outcomes. There is still considerable debate about the effect of mean blood glucose (MBG) and coefficient of variation (CV) of blood glucose on the short-term mortality of AKI patients. This retrospective cohort study aimed to explore the association between glycemic variability and short-term mortality in patients with AKI. Data from the Medical Information Mart for Intensive Care IV (MIMIC-IV) database were analyzed, including 6,777 adult AKI patients. MBG and CV on the first day of ICU admission were calculated to represent the overall glycemic status and variability during the ICU stay in AKI patients. The primary outcome indicator was ICU 30-day mortality of AKI patients. Multivariate Cox regression analysis and smoothed curve fitting were used to assess the relationship between blood glucose levels and mortality. Eventually, the ICU 30-day mortality rate of AKI patients was 23.5%. The increased MBG and CV were significantly correlated with ICU 30-day mortality (hazards ratio (HR) = 1.20, 95% confidence interval (CI) 1.14–1.27; HR = 1.08, 95% CI 1.03–1.13). The smoothed curve fitting showed a U-shaped relationship between MBG on the first day of ICU admission and ICU 30-day mortality (inflection point = 111.3 mg/dl), while CV had a linear relationship with 30-day ICU mortality. Thus, we conclude that MBG and CV were significantly associated with short-term mortality in intensive care patients with AKI. Tighter glycemic control may be an effective measure to improve the prognosis of patients with AKI.

Unraveling the Intraday Variations in the Tear Fluid Proteome.

Tear fluid is a complex and dynamic biological fluid that plays essential roles in maintaining ocular homeostasis and protecting against the external environment. Owing to the small sample volume, studying the tear proteome is challenging. However, advances in high-resolution mass spectrometry have expanded tear proteome profiling, revealing >500 unique proteins. Tears are emerging as a noninvasive source of biomarkers for both ocular and systemic diseases; nevertheless, intraday variability of proteins in tear fluid remains questionable. This study investigates intraday variations in the tear fluid proteome to identify stable proteins that could act as candidate biomarkers. Tear samples from 15 individuals at four time points (10 am, 12 pm, 2 pm, and 4 pm) were analyzed using mass spectrometry to evaluate protein variation during these intervals. Technical variation was assessed by analyzing pooled samples and was subtracted from the total variation to isolate biological variability. Owing to high technical variation, low-abundant proteins were filtered, and only 115 proteins met the criteria for further analysis. These criteria include being detected at all four time points in at least eight subjects, having a mean peptide-spectrum match count greater than 5, and having a technical variation less than 0.10. Lactotransferrin, lipocalin-1, and several immunoglobulins were among the 51 stable proteins (mean biological coefficient of variation < 0.10). Additionally, 43 proteins displayed significant slopes across the 4 time points, with 17 increasing and 26 decreasing over time. These findings contribute to the understanding of tear fluid dynamics and further expand our knowledge of the tear proteome.

In-Season Test-Retest Reliability of Visual Smooth-Pursuit (EyeGuide Focus) Baseline Assessment in Female and Male Field-Sport Athletes.

Sport-related concussions (SRCs) are a mild traumatic brain injury (mTBI) that induces transient symptoms in athletes. These symptoms provide avenues for developing emerging technologies to diagnose SRCs, in particular ocular and vestibular dysfunction. The following study aims to assess the reliability of visual smooth-pursuit technology (EyeGuide Focus) in amateur field-sport athletes. A convenience sample of 30 mixed-gender athletes (mean age = 24.89 ± 6.81 years) completed two testing sessions separated by 2-7 days. Participants were tested at rest, free from distraction, and completed a 10 s smooth pursuit while seated. Participants completed 2-4 practice trials before completing three tests at each session. Appropriate difference, reliability, and repeatability tests were performed in Statistical Packages for the Social Sciences. No significant difference existed between the time points (p > 0.05). The reliability between sessions was poor (ICC = 0.24; 95% CI = 0.03-0.42), and the mean coefficients of variation were 20% and 21% for each session, indicating poor repeatability. However, the implementation of practice trials did prevent the familiarization effects that are evident in the previous literature (p > 0.05). The within-session reliability of EyeGuide Focus has varied from poor (ICC ≤ 0.50) to good (ICC = 0.75-0.90) in the previous literature, indicating the fact that greater research is required before this tool can be implemented in applied settings.

Imprecision of high-sensitivity cardiac troponin assays at the female 99th-percentile

BackgroundAn analytical benchmark for high-sensitivity cardiac troponin (hs-cTn) assays is to achieve a coefficient of variation (CV) of ≤ 10.0 % at the 99th percentile upper reference limit (URL) used for the diagnosis of myocardial infarction. Few prospective multicenter studies have evaluated assay imprecision and none have determined precision at the female URL which is lower than the male URL for all cardiac troponin assays. MethodsHuman serum and plasma matrix samples were constructed to yield hs-cTn concentrations near the female URLs for the Abbott, Beckman, Roche, and Siemens hs-cTn assays. These materials were sent (on dry ice) to 35 Canadian hospital laboratories (n = 64 instruments evaluated) participating in a larger clinical trial, with instructions for storage, handling, and monthly testing over one year. The mean concentration, standard deviation, and CV for each instrument type and an overall pooled CV for each manufacturer were calculated. ResultsThe CVs for all individual instruments and overall were ≤ 10.0 % for two manufacturers (Abbott CVpooled = 6.3 % and Beckman CVpooled = 7.0 %). One of four Siemens Atellica instruments yielded a CV > 10.0 % (CVpooled = 7.7 %), whereas 15 of 41 Roche instruments yielded CVs > 10.0 % at the female URL of 9 ng/L used worldwide (6 cobas e411, 1 cobas e601, 4 cobas e602, and 4 cobas e801) (CVpooled = 11.7 %). Four Roche instruments also yielded CVs > 10.0 % near the female URL of 14 ng/L used in the United States (CVpooled = 8.5 %). ConclusionsThe number of instruments achieving a CV ≤ 10.0 % at the female 99th-percentile URL varies by manufacturer and by instrument. Monitoring assay precision at the female URL is necessary for some assays to ensure optimal use of this threshold in clinical practice.

Comparison of Endothelial Cell Loss after Phacoemulsification Surgery between Patients with Diabetes Mellitus and Non-Diabetic Patients at Kariadi Hospital: A Prospective Study

Abstract&#x0D; Introduction &amp; Objectives : To compare the endothelial cell loss after phacoemulsification surgery in patients with DM and non- DM patients&#x0D; Methods : This was a prospective study conducted at Kariadi Hospital, Semarang, Indonesia. A total of 20 eyes of 20 patients (10 DM and 10 non-DM) who underwent phacoemulsification surgery were included in this study. The central corneal thickness (CCT), endothelial cell density (ECD), coefficient of variation (CV), and hexagonality (HEX) were measured preoperatively and on day-7 postoperatively. The percentage of endothelial cell loss (%ECL) was calculated and compared between the two groups.&#x0D; Results : The mean pre-operative and post-operative CCT was similar in both groups (DM =546.6±44.26μm, non-DM=516.7±42.2μm, p=0.949 ;DM=562.8±46.1μm, non-DM=533.7±46.6μm, p=0.997). The mean percentage of endothelial cell loss was slightly higher in the DM group compared to the non- DM group but not significant (6.66±2.36% vs. 2.31±1.72%, p=0.566). There were no significant differences between the CV and HEX on pre-operative and day-7 after surgery&#x0D; Conclusion : Patients with DM have a slightly higher percentage of endothelial cell loss after phacoemulsification surgery compared to non-DM patients. The mean CCT, CV and HEX pre-operation and day-7 were quite similar in both groups. These findings suggest that patients with DM may require more careful monitoring and follow-up after phacoemulsification surgery.

Performance and accuracy of cross‐section tracking methods for hydromorphological habitat assessment in wadable rivers with sparse canopy conditions

AbstractThis article investigates the performance and accuracy of continuous Real‐Time Kinematic (RTK) Global Navigation Satellite System (GNSS) position tracking for hydromorphological surveys, based on a comprehensive river restoration monitoring campaign. The aim of the research was to assess the method's suitability for efficient data collection in turbid, wadable rivers with sparse canopy conditions, and responds to the water management sector's increasing demand for efficient, low‐cost, and robust survey techniques. The methodological approach involved comparing manual, cross‐sectional water depth measurements to water depth estimations obtained by applying different interpolation methods to the continuous tracking data. The results demonstrate good agreement between both datasets (R2 = 0.77, RMSE = 0.13 m). When using a local standard deviation filter to remove noisy RTK‐GNSS measurements, estimation performance increased significantly (R2 = 0.96, RMSE = 0.06 m). The filter's influence on the hydromorphological habitat statistics mean water depth and coefficient of variation was limited but proved to be relevant for reach‐scale assessments of hydromorphological diversity. Based on a correlation analysis of &gt;106 RTK‐GNSS position logs, we furthermore assessed the impact of tree canopy on RTK‐GNSS measurement accuracy and observed a strong influence within 6.5 m from the canopy border. Estimated accuracy deteriorated noticeably when canopy penetration exceeded 1 m, and accuracies &gt;1 m were common beyond 4 m penetration. The study highlights the efficiency gains achieved with RTK‐GNSS tracking, and showcases its potential for hydromorphological surveys and streamgaging applications in challenging conditions, making it a promising alternative to traditional methods and remote sensing techniques.

Seasonal Variability of Arctic Mid-Level Clouds and the Relationships with Sea Ice from 2003 to 2022: A Satellite Perspective

Mid-level clouds play a crucial role in the Arctic. Due to observational limitations, there is scarce research on the long-term evolution of Arctic mid-level clouds. From a satellite perspective, this study attempts to analyze the seasonal variations in Arctic mid-level clouds and explore the possible relationships with sea ice changes using observations from the hyperspectral Atmospheric Infrared Sounder (AIRS) over the past two decades. For mid-level clouds of three layers (648, 548, and 447 hPa) involved in AIRS, high values of effective cloud fraction (ECF) occur in summer, and low values primarily occur in early spring, while the seasonal variations are different. The ECF anomalies are notably larger at 648 hPa than those at 548 and 447 hPa. Meanwhile, the ECF values at 648 hPa show a clear reduced seasonal variability for the regions north of 80°N, which has its minimum coefficient of variation (CV) during 2019 to 2020. The seasonal CV is relatively lower in the regions dominated by Greenland and sea areas with less sea ice coverage. Analysis indicates that the decline in mid-level ECF’s seasonal mean CV is closely correlated to the retreat of Arctic sea ice during September. Singular value decomposition (SVD) analysis reveals a reverse spatial pattern in the seasonal CV anomaly of mid-level clouds and leads anomaly. However, it is worth noting that this pattern varies by region. In the Greenland Sea and areas near the Canadian Arctic Archipelago, both CV and leads demonstrate negative (positive) anomalies, probably attributed to the stronger influence of atmospheric and oceanic circulations or the presence of land on the sea ice in these areas.

Mitigating the influence of topographies on hyperspectral images for the sorting of iron ore based on variational mode decomposition and spectral property

Hyperspectral imaging (HSI) can be applied for the purpose of sorting iron ores with varying total iron (TFe) content. However, the surface topographies of iron ore can negatively impact its hyperspectral images, consequently affecting the sorting effectiveness for each individual piece of iron ore. To address this issue, this study conducted an experiment on hyperspectral image of the iron ores. Firstly, variational mode decomposition (VMD) was employed to decompose the spectra of iron ore into trend signals and peak-valley signals. The two signals were then used for the calculation of three spectral properties (baseline-shift level, steepness level, and amplitude level). To identify the critical property capable of distinguishing normal spectra and the topographies-affected, the difference of the three spectral properties between the topographies-affected and the normal spectra were analyzed. According to the analysis results, a VMD-based correction model (VMDC) was proposed, which aims to identify the topographies-affected spectra in an ore and then correct them to resemble the normal spectra. Finally, the coefficient of variation (CV) for the correction was assessed and a test was conducted for TFe content prediction and sorting of each piece of iron ore. There are three primary conclusions summarized as follows:1. The mean Jeffries–Matusita distance (JMD) of baseline-shift level, steepness level, and amplitude level between normal spectra and topographies-affected spectra were 1.889, 1.307, and 1.170, respectively. This implies that baseline-shift level can be regarded as a key property for distinguishing whether a spectrum is topographies-affected or not. 2. After correction, there was a noticeable improvement in the topographies-affected areas of the ore samples, and the topographies-affected spectra showed the consistence with the normal spectra. Upon examination, the mean CV for VMDC is 0.115, whereas the uncorrected data has a mean CV of 0.315, indicating a reduction in spectral variability after VMDC correction. The results demonstrate the effectiveness of VMDC in mitigating the impact of topographies. 3. In the TFe content prediction and sorting, VMDC consistently demonstrates the best performance, for example when using RF as the regressor, coefficient of determination (R2) and accuracy of Original Data-RF, MSC-RF and VMDC-RF were 84.3% and 0.894, 86.7% and 0.903, and 88.7% and 0.921. The evaluation results confirm that VMDC can improve iron ore sorting. Overall, the proposed method shows potential for practical applications in iron ore sorting.

Consistency of convolutional neural networks in dermoscopic melanoma recognition: A prospective real-world study about the pitfalls of augmented intelligence.

Deep-learning convolutional neural networks (CNNs) have outperformed even experienced dermatologists in dermoscopic melanoma detection under controlled conditions. It remains unexplored how real-world dermoscopic image transformations affect CNN robustness. To investigate the consistency of melanoma risk assessment by two commercially available CNNs to help formulate recommendations for current clinical use. A comparative cohort study was conducted from January to July 2022 at the Department of Dermatology, University Hospital Basel. Five dermoscopic images of 116 different lesions on the torso of 66 patients were captured consecutively by the same operator without deliberate rotation. Classification was performed by two CNNs (CNN-1/CNN-2). Lesions were divided into four subgroups based on their initial risk scoring and clinical dignity assessment. Reliability was assessed by variation and intraclass correlation coefficients. Excisions were performed for melanoma suspicion or two consecutively elevated CNN risk scores, and benign lesions were confirmed by expert consensus (n = 3). 117 repeated image series of 116 melanocytic lesions (2 melanomas, 16 dysplastic naevi, 29 naevi, 1 solar lentigo, 1 suspicious and 67 benign) were classified. CNN-1 demonstrated superior measurement repeatability for clinically benign lesions with an initial malignant risk score (mean variation coefficient (mvc): CNN-1: 49.5(±34.3)%; CNN-2: 71.4(±22.5)%; p = 0.03), while CNN-2 outperformed for clinically benign lesions with benign scoring (mvc: CNN-1: 49.7(±22.7)%; CNN-2: 23.8(±29.3)%; p = 0.002). Both systems exhibited lowest score consistency for lesions with an initial malignant risk score and benign assessment. In this context, averaging three initial risk scores achieved highest sensitivity of dignity assessment (CNN-1: 94%; CNN-2: 89%). Intraclass correlation coefficients indicated 'moderate'-to-'good' reliability for both systems (CNN-1: 0.80, 95% CI:0.71-0.87, p < 0.001; CNN-2: 0.67, 95% CI:0.55-0.77, p < 0.001). Potential user-induced image changes can significantly influence CNN classification. For clinical application, we recommend using the average of three initial risk scores. Furthermore, we advocate for CNN robustness optimization by cross-validation with repeated image sets. ClinicalTrials.gov (NCT04605822).

Phenotypic characterization for milk traits in crossbred cattle population from the state of Norte de Santander

Crossbred cattle are used in dual-purpose systems to obtain meat and milk, becoming one of Colombia's systems with the greatest presence. However, studies characterizing productive variables in crossbred individuals are scarce, making it pertinent to conduct analyses evaluating their potential. The objective of this study was to phenotypically characterize a population of crossbred cattle from the state of Norte de Santander (Colombia) in terms of milk traits. Up to a maximum of 4 controls per female was obtained, and information on milk yield (MY), fat percentage (FP), protein percentage (PP), and somatic cell count (SCC) of first parity crossbred females was evaluated. The information was filtered and analyzed with the R program. The mean, standard deviation, and general variation coefficient were calculated for each trait and the means and deviations by non-genetic categorical factors. For the numeric factors, graphs of trends related to the response variables were made. Multiple correspondence analysis was performed, and the standardized residual values were estimated to recognize associations between levels of non-genetic factors and each trait. Mean values for controls were: 3.06±1.40 kg/day (MY), 3.21±0.40% (PP), 3.32±0.77% (FP), and 357±256x103 cells/ml (SCC). The non-genetic factors that showed the most significance were the pasture type, the control season, and the region. Thus, MY from 1.00 to 2.00 kg is associated with the levels of region 1 (R1) and summer 1 (S1), MY from 2.10 to 3.99 kg with region 2 (R2), group 1 (G1) and winter 1 (W1), MY from 4.00 to 8.30 kg with R1, group 3 (G3) and W1, PP from 2.45 to 2.99% there was association with G1, PP from 3.00 to 3.40% with group 2 (G2), PP from 3.41 to 6.04% with G3, FP of 1.94 to 3.00% is associated with R1, G3, S1, and S2, FP of 3.01 to 4.00% with R2, G1 and W1, FP from 4 to 4.82 % with region 3 (R3), G2, and S1, SCC from 8.00 to 100x103 cells/ml is associated with R1, R3, and S1, SCC of 101 to 499x103 cells/ml with R2, G1, and W1. Finally, SCC of 500 to 888x103 cells/ml is associated with R2 and W1. A variation of medium to high magnitude of the traits evaluated within the population was evidenced, revealing that no standards that allow unifying the management of animals within herds, which can affect the efficiency of dual-purpose systems.

Performance evaluation of the LumiraDx quantitative microfluidic point-of-care CRP test

C-reactive protein (CRP) is an established acute-phase marker for infection, inflammation and tissue injury, used to guide clinical decision-making in primary and secondary care. This study compared the analytical performance of the quantitative microfluidic point-of-care LumiraDx CRP Test to a laboratory-based reference method (Siemens RCRP Flex assay on the Dimension® Xpand®) and evaluated equivalence of sample matrices (blood versus plasma) in point-of-care settings using samples from patients presenting with symptoms of infection or inflammation. The LumiraDx CRP Test demonstrated close agreement with the lab reference test (range, 5.1 to 245.2 mg/L, r = 0.992, slope = 0.998, intercept = –0.476; n = 205) and notable agreement between fingerstick and venous blood and plasma (r = 0.974–0.983; n = 44). Paired replicate precision had mean coefficients of variation of 6.4 % (plasma), 6.6 % (capillary direct) and 8.1 % (venous blood); overall error rates were 2.9 %. The quantitative LumiraDx CRP Test showed robust analytical performance across sample matrices and close agreement compared to the laboratory reference method when used at the point of care.

Systematic Comparison of Reproducibility of Diffusion MRI‐Derived Free‐Water Measures Across Two Multi‐Shell Protocols

AbstractBackgroundFree‐water (FW) measures have been widely used to understand and predict the progression of various neurodegenerative disorders1,2. However, the estimation of FW in a brain voxel needs a multi‐shell acquisition to ensure reproducible fit3,4. With the availability of multi‐shell diffusion MRI (dMRI) protocol using simultaneous multislice technique from the Human Connectome Project (HCP) and Alzheimer’s Disease Neuroimaging Initiative (ADNI‐3), such protocols can now be harmonized across various centers and MRI vendors. However, limited knowledge exists on whether the results obtained for FW measures across HCP protocols are generalizable across ADNI‐3 protocols along with which protocol is more reproducible that will assist us in understanding the variability of FW measure in an individual participant longitudinally. Hence, in this study, we compared the reproducibility of FW across major white matter (WM) tracts across both HCP and ADNI‐3 protocols.MethodA 32‐year‐old healthy male participant was scanned over five weeks, both with Basic (2mm3, b‐value = 1000s/mm2) and Advanced ADNI‐3 protocol and 2 variants of the HCP sequence (1.5mm3 and 2mm3) both with 3 b‐values (500s/mm2, 1000s/mm2, and 2500s/mm2) and 213 directions on a clinical 3T Skyra scanner. FW dMRI measures were obtained using the original Matlab implementation (Matlab)5 and DiPY implementation6 of multi‐shell dMRI acquisition (DiPY). WM atlas from Johns Hopkins University (JHU) of 20 major WM tracts pre‐registered to MNI152 was then used as a mask to obtain FW at each WM tract, and the coefficient of variance (CoV) was computed across each protocol. The total acquisition scan time was 75 minutes.ResultFW estimated using Matlab had a mean CoV = 2.78±1.09 across all the protocols with the least CoV for Basic ADNI‐3 (CoV = 1.31±0.54) and the maximum CoV for 2mm3 HCP sequence (CoV = 4.98±1.83) (Fig.1A) while FW estimated using DiPY had a mean CoV = 6.71±2.86 across all the protocols with the least CoV for Advanced ADNI‐3 (CoV = 4.31±1.85) and the maximum CoV for 2mm3 HCP sequence (CoV = 9.66±4.15) (Fig.1A).ConclusionBoth acquisition parameters and processing techniques significantly affect the absolute quantification of FW measures. Furthermore, our data suggest that the pooling of dMRI data across various protocols should be performed with caution.

Systematic Comparison of Reproducibility of Diffusion MRI‐Derived Free‐Water Measures Across Two Multi‐Shell Protocols

AbstractBackgroundFree‐water (FW) measures have been widely used to understand and predict the progression of various neurodegenerative disorders1,2. However, the estimation of FW in a brain voxel needs a multi‐shell acquisition to ensure reproducible fit3,4. With the availability of multi‐shell diffusion MRI (dMRI) protocol using simultaneous multislice technique from the Human Connectome Project (HCP) and Alzheimer’s Disease Neuroimaging Initiative (ADNI‐3), such protocols can now be harmonized across various centers and MRI vendors. However, limited knowledge exists on whether the results obtained for FW measures across HCP protocols are generalizable across ADNI‐3 protocols along with which protocol is more reproducible that will assist us in understanding the variability of FW measure in an individual participant longitudinally. Hence, in this study, we compared the reproducibility of FW across major white matter (WM) tracts across both HCP and ADNI‐3 protocols.MethodsA 32‐year‐old healthy male participant was scanned over five weeks, both with Basic (2mm3, b‐value = 1000s/mm2) and Advanced ADNI‐3 protocol and 2 variants of the HCP sequence (1.5mm3 and 2mm3) both with 3 b‐values (500s/mm2, 1000s/mm2, and 2500s/mm2) and 213 directions on a clinical 3T Skyra scanner. FW dMRI measures were obtained using the original Matlab implementation (Matlab)5 and DiPY implementation6 of multi‐shell dMRI acquisition (DiPY). WM atlas from Johns Hopkins University (JHU) of 20 major WM tracts pre‐registered to MNI152 was then used as a mask to obtain FW at each WM tract, and the coefficient of variance (CoV) was computed across each protocol. The total acquisition scan time was 75 minutes.ResultFW estimated using Matlab had a mean CoV = 2.78±1.09 across all the protocols with the least CoV for Basic ADNI‐3 (CoV = 1.31±0.54) and the maximum CoV for 2mm3 HCP sequence (CoV = 4.98±1.83) (Fig.1A) while FW estimated using DiPY had a mean CoV = 6.71±2.86 across all the protocols with the least CoV for Advanced ADNI‐3 (CoV = 4.31±1.85) and the maximum CoV for 2mm3 HCP sequence (CoV = 9.66±4.15) (Fig.1A).ConclusionBoth acquisition parameters and processing techniques significantly affect the absolute quantification of FW measures. Furthermore, our data suggest that the pooling of dMRI data across various protocols should be performed with caution.

Anti-motion Ultrafast T2 Mapping Technique for Quantitative Detection of the Normal-Appearing Corticospinal Tract Changes in Subacute-Chronic Stroke Patients with Distal Lesions

Rational and ObjectivesStroke patients commonly face challenges during magnetic resonance imaging (MRI) examinations due to involuntary movements. This study aims to overcome these challenges by utilizing multiple overlapping-echo detachment (MOLED) quantitative technology. Through this technology, we also seek to detect microstructural changes of the normal-appearing corticospinal tract (NA-CST) in subacute-chronic stroke patients. Materials and Methods79 patients underwent 3.0T MRI scans, including routine scans and MOLED technique. A deep learning network was utilized for image reconstruction, and the accuracy, reliability, and resistance to motion of the MOLED technique were validated on phantoms and volunteers. Subsequently, we assessed motor dysfunction severity, ischemic lesion volume, T2 values of the bilateral NA-CST, and the T2 ratio (rT2) between the ipsilesional and contralesional NA-CST in patients. ResultsThe MOLED technique showed high accuracy (P<0.001) and excellent repeatability, with a mean coefficient of variation (CoV) of 1.11%. It provided reliable quantitative results even under head movement, with a mean difference (Meandiff) = 0.28% and a standard deviation difference (SDdiff)= 1.34%. Additionally, the T2 value of the ipsilesional NA-CST was significantly higher than contralesional side (P<0.001), and a positive correlation was observed between rT2 and the severity of motor dysfunction (rs = 0.575, P<0.001). Furthermore, rT2 successfully predicted post-stroke motor impairment, with an area under the curve (AUC) was 0.883. ConclusionsThe MOLED technique offers significant advantages for quantitatively imaging stroke patients with involuntary movements. Additionally, T2 mapping from MOLED can detect microstructural changes in the NA-CST, potentially aiding in monitoring stroke-induced motor impairment.