Mean Intraclass Correlation Coefficient Research Articles

AudBility: confiabilidade teste-reteste em crianças com desenvolvimento típico de 6 e 7 anos

ABSTRACT Purpose to investigate the test-retest reliability of the AudBility program in typically developing children aged six-seven years. Methods 29 children, male and female, right-handed, native Portuguese speakers and adequate school performance for the age group studied, underwent previous meatoscopy, immittance measurements and the AudBility program was applied, composed of a self-perception questionnaire and auditory tasks, being analyzed the abilities of sound localization, auditory closure, figure-ground, dichotic digits test, temporal resolution, and temporal ordering of frequency and duration. The program was designed and reapplied with an interval of one week under the same conditions. The performance in each task was presented from central tendency and dispersion data and was conducted using the Intraclass Correlation Coefficient (ICC), based on the 95% confidence interval (CI). Results The analyses showed a positive and significant ICC (p<0.01) for the questionnaire and auditory tasks, except for auditory closure, in the right and left ears and figure-ground in the left ear. The questionnaire mean ICC was 0.742 and ranged from −0.012 to 0.698 for the auditory tasks. Conclusion Based on mean results and upper limit of the CI, the findings showed agreement between moments, classified as good for the questionnaire and moderate to good for five of the seven auditory analyzed tasks (ICC>0.05 and <0.9). The results of the reliability study represent an important parameter for validating the program for the studied age group.

AudBility: test-retest reliability in typically developing children aged 6 to 7 years.

to investigate the test-retest reliability of the AudBility program in typically developing children aged six-seven years. 29 children, male and female, right-handed, native Portuguese speakers and adequate school performance for the age group studied, underwent previous meatoscopy, immittance measurements and the AudBility program was applied, composed of a self-perception questionnaire and auditory tasks, being analyzed the abilities of sound localization, auditory closure, figure-ground, dichotic digits test, temporal resolution, and temporal ordering of frequency and duration. The program was designed and reapplied with an interval of one week under the same conditions. The performance in each task was presented from central tendency and dispersion data and was conducted using the Intraclass Correlation Coefficient (ICC), based on the 95% confidence interval (CI). The analyses showed a positive and significant ICC (p<0.01) for the questionnaire and auditory tasks, except for auditory closure, in the right and left ears and figure-ground in the left ear. The questionnaire mean ICC was 0.742 and ranged from -0.012 to 0.698 for the auditory tasks. Based on mean results and upper limit of the CI, the findings showed agreement between moments, classified as good for the questionnaire and moderate to good for five of the seven auditory analyzed tasks (ICC>0.05 and <0.9). The results of the reliability study represent an important parameter for validating the program for the studied age group.

The CRECHE study: testing the urban myth that chocolate Santa Clauses are re-wrapped Easter Bunnies.

To test the urban myth that surplus chocolate Easter Bunnies are re-packaged as Santa Clauses for the following Christmas holiday season. Prospective radiographic cohort study of seasonal chocolate figurines, supplemented by anonymous 5-item questionnaire survey of belief in the re-wrapping myth (Generic Risk Items Noted by Chocolate consumers in Health care settings; GRINCH). Two tertiary referral trauma centres in Germany (Berlin and Duisburg). Eighteen chocolate Easter Bunnies and 15 chocolate Santa Clauses from different manufacturers purchased during 2020; 502 randomly selected people passing through the entrance halls of the two hospitals during 16 September - 12 October 2020. Whole body computed tomography (WBCT) images of chocolate Easter Bunnies and Santa Clauses assessed by four independent, board-certified radiologists using a visual contour resemblance scale (CRS); survey participants' views on statements related to the re-wrapping myth. Expert examiners clearly distinguished the WBCT images of chocolate Easter Bunnies and Santa Clauses; the mean difference in CRS was 84.2 points (95% CI, 78.5-90.0 points), with excellent inter-observer agreement (mean intra-class correlation coefficient, 0.99; 95% CI, 0.99-1.00). A total of 214 survey participants (43%) disagreed and 145 (29%) agreed with the proposition that seasonal chocolate figurines are re-packaged and re-sold the following season. Although about one-third of our survey respondents did not rule out the possibility of seasonal sweets being re-used, WBCT imaging found no similarity between chocolate foil-wrapped Easter and Christmas figurines, providing solid evidence against this urban myth. Chocolate Santa Clauses are unlikely to pose a significant threat to hospital food hygiene requirements. Current Controlled Trials, ISRCTN16847363 (prospective).

The effect of a post-scan processing denoising system on image quality and morphometric analysis

Purpose: MR image quality and subsequent brain morphometric analysis are inevitably affected by noise. The purpose of this study was to evaluate the effectiveness of an artificial intelligence (AI)-based post-scan processing denoising system, intelligent Quick Magnetic Resonance (iQMR), on MR image quality and brain morphometric analysis.Methods: We used 1.5T MP-RAGE MR images acquired from the Alzheimer's Disease Neuroimaging Initiative 1 database. The images of 21 subjects were used for cross-sectional analysis and 15 for longitudinal analysis. In the longitudinal analysis, two timepoints over a 2-year interval were used. Each subject was scanned twice at each timepoint. MR images processed with and without the denoising system were compared both visually and objectively using FreeSurfer cortical thickness analysis.Results: The denoising system reduced the noise with good white–gray matter contrast (noise: p < 0.001; contrast: p = 0.49). The mean intraclass correlation coefficients (ICCs) of cortical thickness were slightly better in the images processed with the denoising system (0.739/0.859/0.883; Gaussian smoothing kernel of full width at half maximum = 0/10/20) compared with the unprocessed images (0.718/0.854/0.880). In the longitudinal analysis, the mean ICCs of symmetrized percent change improved in images processed with the denoising system (0.202/0.349/0.431) compared with the unprocessed images (0.167/0.325/0.404). In addition, the detectability of significant cortical thickness atrophy improved with denoising.Conclusion: We confirm that the AI-based denoising system could effectively reduce the noise while retaining the contrast. We also confirm the improvement of the reliability and detectability of brain morphometric analysis with the denoising system.

Reliability of structural MRI measurements: The effects of scan session, head tilt, inter-scan interval, acquisition sequence, FreeSurfer version and processing stream

BackgroundLarge-scale longitudinal and multi-centre studies are used to explore neuroimaging markers of normal ageing, and neurodegenerative and mental health disorders. Longitudinal changes in brain structure are typically small, therefore the reliability of automated techniques is crucial. Determining the effects of different factors on reliability allows investigators to control those adversely affecting reliability, calculate statistical power, or even avoid particular brain measures with low reliability. This study examined the impact of several image acquisition and processing factors and documented the test-retest reliability of structural MRI measurements. MethodsIn Phase I, 20 healthy adults (11 females; aged 20–30 years) were scanned on two occasions three weeks apart on the same scanner using the ADNI-3 protocol. On each occasion, individuals were scanned twice (repetition), after re-entering the scanner (reposition) and after tilting their head forward. At one year follow-up, nine returning individuals and 11 new volunteers were recruited for Phase II (11 females; aged 22–31 years). Scans were acquired on two different scanners using the ADNI-2 and ADNI-3 protocols. Structural images were processed using FreeSurfer (v5.3.0, 6.0.0 and 7.1.0) to provide subcortical and cortical volume, cortical surface area and thickness measurements. Intra-class correlation coefficients (ICC) were calculated to estimate test-retest reliability. We examined the effect of repetition, reposition, head tilt, time between scans, MRI sequence and scanner on reliability of structural brain measurements. Mean percentage differences were also calculated in supplementary analyses. ResultsUsing the FreeSurfer v7.1.0 longitudinal pipeline, we observed high reliability for subcortical and cortical volumes, and cortical surface areas at repetition, reposition, three weeks and one year (mean ICCs>0.97). Cortical thickness reliability was lower (mean ICCs>0.82). Head tilt had the greatest adverse impact on ICC estimates, for example reducing mean right cortical thickness to ICC=0.74. In contrast, changes in ADNI sequence or MRI scanner had a minimal effect. We observed an increase in reliability for updated FreeSurfer versions, with the longitudinal pipeline consistently having a higher reliability than the cross-sectional pipeline. DiscussionLongitudinal studies should monitor or control head tilt to maximise reliability. We provided the ICC estimates and mean percentage differences for all FreeSurfer brain regions, which may inform power analyses for clinical studies and have implications for the design of future longitudinal studies.

Comparison of time-to-event machine learning models in predicting oral cavity cancer prognosis

BackgroundApplying machine learning to predicting oral cavity cancer prognosis is important in selecting candidates for aggressive treatment following diagnosis. However, models proposed so far have only considered cancer survival as discrete rather than dynamic outcomes. ObjectivesTo compare the model performance of different machine learning-based algorithms that incorporate time-to-event data. These algorithms included DeepSurv, DeepHit, neural net-extended time-dependent cox model (Cox-Time), and random survival forest (RSF). Materials and MethodsRetrospective cohort of 313 oral cavity cancer patients were obtained from electronic health records. Models were trained on patient data following preprocessing. Predictors were based on demographic, clinicopathologic, and treatment information of the cases. Outcomes were the disease-specific and overall survival. Multivariable analyses were conducted to select significant prognostic features associated with tumor prognosis. Two models were generated per algorithm based on all-prognostic features and significant-prognostic features following statistical analysis. Concordance index (c-index) and integrated Brier scores were used as performance evaluators and model stability was assessed using intraclass correlation coefficients (ICC) calculated from these measures obtained from the cross-validation folds. ResultsWhile all models were satisfactory, better discriminatory performance and calibration was observed for disease-specific than overall survival (mean c-index: 0.85 vs 0.74; mean integrated Brier score: 0.12 vs 0.17). DeepSurv performed best in terms of discrimination for both outcomes (c-indices: 0.76 -0.89) while RSF produced better calibrated survival estimates (integrated Brier score: 0.06 -0.09). Model stability of the algorithms varied with the outcomes as Cox-Time had the best intraclass correlation coefficient (mean ICC: 1.00) for disease-specific survival while DeepSurv was most stable for overall survival prediction (mean ICC: 0.99). ConclusionsMachine learning algorithms based on time-to-event outcomes are successful in predicting oral cavity cancer prognosis with DeepSurv and RSF producing the best discriminative performance and calibration.

Measurement properties of the Pain Self-Efficacy Questionnaire in populations with musculoskeletal disorders: a systematic review.

A higher level of pain self-efficacy has been suggested as a predictor of a better outcome in patients with musculoskeletal disorders. The Pain Self-Efficacy Questionnaire (PSEQ) is one of the most frequently used patient-reported outcome measures for pain self-efficacy. The purpose of this study was to conduct a systematic review that would identify, appraise, and synthetize the psychometric properties of the PSEQ. Embase, MEDLINE, and CINAHL databases were searched for publications reporting on psychometric properties of the PSEQ in populations with musculoskeletal disorders. After applying selection criteria on identified citations, 28 studies (9853 participants) were included. The methodological quality as measured with the COSMIN risk of bias tool varied from adequate to very good for most measurement properties. The results showed a weighted mean intraclass correlation coefficient of 0.86 (range: 0.75-0.93) for test-retest reliability for the original 10-item PSEQ and the minimal detectable change at 95% confidence interval was 11.52 out of 60 points. Effect size and standardized response mean values were 0.53 and 0.63, respectively, whereas the minimal clinically important difference ranged from 5.5 to 8.5 in patients with chronic low back pain. Internal consistency (Cronbach alpha) ranged from 0.79 to 0.95. The results also showed that the PSEQ has low to moderate correlations with measures of quality of life, disability, pain, pain interference, anxiety, depression, and catastrophizing. Finally, the PSEQ has been adapted and validated in 14 languages. Overall, the results demonstrate that the PSEQ has excellent validity, reliability, and responsiveness. Further high-quality studies are needed to determine responsiveness in populations other than chronic low back pain.

Impact of complex, partially nested clustering in a three-arm individually randomized group treatment trial: A case study with the wHOPE trial.

When participants in individually randomized group treatment trials are treated by multiple clinicians or in multiple group treatment sessions throughout the trial, this induces partially nested clusters which can affect the power of a trial. We investigate this issue in the Whole Health Options and Pain Education trial, a three-arm pragmatic, individually randomized clinical trial. We evaluate whether partial clusters due to multiple visits delivered by different clinicians in the Whole Health Team arm and dynamic participant groups due to changing group leaders and/or participants across treatment sessions during treatment delivery in the Primary Care Group Education arm may impact the power of the trial. We also present a Bayesian approach to estimate the intraclass correlation coefficients. We present statistical models for each treatment arm of Whole Health Options and Pain Education trial in which power is estimated under different intraclass correlation coefficients and mapping matrices between participants and clinicians or treatment sessions. Power calculations are based on pairwise comparisons. In practice, sample size calculations depend on estimates of the intraclass correlation coefficients at the treatment sessions and clinician levels. To accommodate such complexities, we present a Bayesian framework for the estimation of intraclass correlation coefficients under different participant-to-session and participant-to-clinician mapping scenarios. We simulated continuous outcome data based on various clinical scenarios in Whole Health Options and Pain Education trial using a range of intraclass correlation coefficients and mapping matrices and used Gibbs samplers with conjugate priors to obtain posteriors of the intraclass correlation coefficients under those different scenarios. Posterior means and medians and their biases are calculated for the intraclass correlation coefficients to evaluate the operating characteristics of the Bayesian intraclass correlation coefficient estimators. Power for Whole Health Team versus Primary Care Group Education is sensitive to the intraclass correlation coefficient in the Whole Health Team arm. In these two arms, an increased number of clinicians, more evenly distributed workload of clinicians, or more homogeneous treatment group sizes leads to increased power. Our simulation study for the intraclass correlation coefficient estimation indicates that the posterior mean intraclass correlation coefficient estimator has less bias when the true intraclass correlation coefficients are large (i.e. 0.10), but when the intraclass correlation coefficient is small (i.e. 0.01), the posterior median intraclass correlation coefficient estimator is less biased. Knowledge of intraclass correlation coefficients and the structure of clustering are critical to the design of individually randomized group treatment trials with partially nested clusters. We demonstrate that the intraclass correlation coefficient of the Whole Health Team arm can affect power in the Whole Health Options and Pain Education trial. A Bayesian approach provides a flexible procedure for estimating the intraclass correlation coefficients under complex scenarios. More work is needed to educate the research community about the individually randomized group treatment design and encourage publication of intraclass correlation coefficients to help inform future trial designs.

Impact of image averaging on vessel detection using optical coherence tomography angiography in eyes with macular oedema and in healthy eyes.

To assess the repeatability of multiple automatic vessel density (VD) measurements and the effect of image averaging on vessel detection by optical coherence tomography angiography (OCTA). An observational study was conducted in a series of healthy volunteers and patients with macular oedema. Five sequential OCTA images were acquired for each eye using the OptoVue HD device. The effect of the averaging of the 5 acquisitions on vessel detection was analysed quantitatively using a pixel-by-pixel automated analysis. In addition, two independent retina experts qualitatively assessed the change in vessel detection in averaged images segmented in 9 boxes and compared to the first non-averaged image. The automatic VD measurement in OCTA images showed a good repeatability with an overall mean intra-class correlation coefficient (ICC) of 0.924. The mean ICC was higher in healthy eyes compared to eyes with macular oedema (0.877 versus 0.960; p < 0.001) and in the superficial vascular plexus versus the deep vascular complex (0.967 versus 0.888; p = 0.001). The quantitative analysis of the effect of the averaging showed that averaged images had a mean gain of 790.4 pixels/box, located around or completing interruptions in the vessel walls, and a mean loss of 727.2 pixels/box. The qualitative analysis of the averaged images showed that 99.6% of boxes in the averaged images had a gain in vessel detection (i.e., vessels detected in the averaged image but not in the non-averaged image). The loss of pixels was due to a reduction in background noise and motion artifacts in all cases and no case of loss of vessel detection was observed. The automatic VD measurement using the OptoVue HD device showed a good repeatability in 5 acquisitions in a row setting. Averaging images increased vessel detection, and in about a third of boxes, decreased the background noise, both in healthy eyes and, in a greater proportion, in eyes with macular oedema.

India ink artifact on Dixon out-of-phase images can be used as a landmark to measure joint space width at MRI

PurposeThe purpose of this study was to test the feasibility of joint space width (JSW) measurement on Dixon MR images with the “India ink” artifact between cartilage and bone marrow as a landmark for the subchondral plate and to correlate it with radiographic JSW. Materials and methodsBoth hands of six volunteers (three women, three men; mean age, 36.7 ± 10.4 [SD] years) and 24 patients with early rheumatoid arthritis (16 women, 8 men; mean age, 45.7 ± 14.5 [SD] years) were imaged with MRI Dixon sequences and radiographs. Two radiologists (R1, R2) separately measured JSW in 11 joints per hand on all Dixon images in volunteers, on contrast-enhanced T1-weighted out-of-phase images in patients and on radiographs in both groups. Inter-technique, intra-observer and inter-observer agreements were assessed using intraclass correlation coefficient (ICC) and Bland Altman analysis. ResultsIn volunteers, agreement between JSW measurements on MRI and radiographs was the highest with T1-weighted Dixon out-of-phase images (mean ICC ranging from 0.69 to 0.76 for R1 and 0.65 to 0.74 for R2). In patients, median bias between JSW measurements at first and second readings was not statistically significantly different from 0 on T1-weighted Dixon out-of-phase images (mean bias of 0.00 and + 0.01 mm) and radiographs (mean bias of 0.00 and +0.01 mm). Median bias of the difference between measurements of R1 and R2 was statistically significantly different from 0 on T1-weighted Dixon out-of-phase images (mean bias of -0.11 and -0.09 mm; P < 0.039) and radiographs (mean bias of -0.24 and -0.20 mm; P < 0.035). ConclusionMeasurement of hand JSW on T1-weighted Dixon out-of-phase images using India ink artifact as a landmark for the subchondral plate is repeatable and reproducible.

Reproducibility of Longitudinal Changes in Cortical Thickness Determined by Surface-Based Morphometry Between Non-Accelerated and Accelerated MR Imaging.

Scan acceleration such as parallel imaging reduces scan time, but shorter scan time may reduce the signal-to-noise ratio and affect image quality. The reproducibility of longitudinal changes in the brain structure between non-accelerated and accelerated imaging by surface-based analysis is unclear. To determine the reproducibility of longitudinal changes in cortical thickness, measured by surface-based morphometry, between non-accelerated and accelerated structural T1 -weighted imaging in the healthy elderly and those with mild cognitive impairment (MCI) and Alzheimer's disease (AD). Retrospective. Fifty healthy elderly subjects (age=73 ± 5 years, 29 females, 21 males), 54 MCI patients (age=71 ± 7 years, 23 females, 31 males), and 8 AD patients (age=78 ± 6 years, 6 females, 2 males). 3 T, magnetization-prepared rapid gradient-echo. Longitudinal changes in cortical thickness estimated by the longitudinal stream in FreeSurfer from 2-year interval data, and visual assessment of image quality by three radiologists. Intraclass correlation coefficient (ICC) and Kruskal-Wallis test. A P value <0.05 was considered significant. Healthy elderly subjects, MCI patients, and AD patients showed different patterns in the ICC maps. For the smoothing of 20 mm full width at half maximum, the mean ICC was 0.45 overall (healthy elderly, 0.33; MCI patients, 0.49; AD patients, 0.31). The within-subject SDs of the symmetrized percent changes were similar between healthy elderly subjects (mean, 1.3%/year) and MCI patients (mean, 1.3%/year) but larger in AD patients (mean, 1.7%/year). Image quality did not significantly differ per group (P=0.18). The results of this study indicate the reproducibility of longitudinal changes in cortical thickness measured by surface-based morphometry between non-accelerated and accelerated imaging, and that the reproducibility varies by disease and region. 3 TECHNICAL EFFICACY: Stage 1.

Hepatic Iron Quantification Using a Free-Breathing 3D Radial Gradient Echo Technique and Validation With a 2D Biopsy-Calibrated R2* Relaxometry Method.

Hepatic iron content (HIC) is an important parameter for the management of iron overload. Non-invasive HIC assessment is often performed using biopsy-calibrated two-dimensional breath-hold Cartesian gradient echo (2D BH GRE) R2* -MRI. However, breath-holding is not possible in most pediatric patients or those with respiratory problems, and three-dimensional free-breathing radial GRE (3D FB rGRE) has emerged as a viable alternative. To evaluate the performance of a 3D FB rGRE and validate its R2* and fat fraction (FF) quantification with 3D breath-hold Cartesian GRE (3D BH cGRE) and biopsy-calibrated 2D BH GRE across a wide range of HICs. Retrospective. Twenty-nine patients with hepatic iron overload (22 females, median age: 15 [5-25] years). Three-dimensional radial and 2D and 3D Cartesian multi-echo GRE at 1.5 T. R2* and FF maps were computed for 3D GREs using a multi-spectral fat model and 2D GRE R2* maps were calculated using a mono-exponential model. Mean R2* and FF values were calculated via whole-liver contouring and T2* -thresholding by three operators. Inter- and intra-observer reproducibility was assessed using Bland-Altman and intraclass correlation coefficient (ICC). Linear regression and Bland-Altman analysis were performed to compare R2* and FF values among the three acquisitions. One-way repeated-measures ANOVA and Wilcoxon signed-rank tests, respectively, were used to test for significant differences between R2* and FF values obtained with different acquisitions. Statistical significance was assumed at P < 0.05. The mean biases and ICC for inter- and intra-observer reproducibility were close to 0% and >0.99, respectively for both R2* and FF. The 3D FB rGRE R2* and FF values were not significantly different (P > 0.44) and highly correlated (R2 ≥ 0.98) with breath-hold Cartesian GREs, with mean biases ≤ ±2.5% and slopes 0.90-1.12. In non-breath-holding patients, Cartesian GREs showed motion artifacts, whereas 3D FB rGRE exhibited only minimal streaking artifacts. Free-breathing 3D radial GRE is a viable alternative in non-breath-hold patients for accurate HIC estimation. 3 TECHNICAL EFFICACY: Stage 2.

Reproducibility of Brain Volume Changes in Longitudinal Voxel-Based Morphometry Between Non-Accelerated and Accelerated Magnetic Resonance Imaging.

Scan acceleration techniques, such as parallel imaging, can reduce scan times, but reliability is essential to implement these techniques in neuroimaging. To evaluate the reproducibility of the longitudinal changes in brain morphology determined by longitudinal voxel-based morphometry (VBM) between non-accelerated and accelerated magnetic resonance images (MRI) in normal aging, mild cognitive impairment (MCI), and Alzheimer's disease (AD). Using data from the Alzheimer's Disease Neuroimaging Initiative (ADNI) 2 database, comprising subjects who underwent non-accelerated and accelerated structural T1-weighted MRI at screening and at a 2-year follow-up on 3.0 T Philips scanners, we examined the reproducibility of longitudinal gray matter volume changes determined by longitudinal VBM processing between non-accelerated and accelerated imaging in 50 healthy elderly subjects, 54 MCI patients, and eight AD patients. The intraclass correlation coefficient (ICC) maps differed among the three groups. The mean ICC was 0.72 overall (healthy elderly, 0.63; MCI, 0.75; AD, 0.63), and the ICC was good to excellent (0.6-1.0) for 81.4%of voxels (healthy elderly, 64.8%; MCI, 85.0%; AD, 65.0%). The differences in image quality (head motion) were not significant (Kruskal-Wallis test, p = 0.18) and the within-subject standard deviations of longitudinal gray matter volume changes were similar among the groups. The results indicate that the reproducibility of longitudinal gray matter volume changes determined by VBM between non-accelerated and accelerated MRI is good to excellent for many regions but may vary between diseases and regions.

Computer-based three-dimensional measurement of carpal alignment: measurement techniques and normal ranges.

The three-dimensional carpal alignment was measured in the neutral wrist position in 121 asymptomatic volunteers using computer-based cone-beam CT analysis. Normal values and the reliability of the automated analysis are reported. An analysis software based on segmentation of CT images and mathematical modelling was used to determine several axis variants based on different landmarks and to calculate the intercarpal angles automatically. Twenty wrists were imaged twice to determine intra-observer reliability. Mean values using the preferred axis variants were: scapholunate angle 57° (SD 9°), radiolunate angle 2° (SD 10°), lunocapitate angle -14° (SD 9°). Using alternate axis variants notably changed the angles produced. The intra-observer reliability of the analysis was excellent (mean intraclass correlation coefficient 0.97, SD 0.03). Computer-based CT analysis enables highly reproducible and automated assessment of carpal alignment. This study provides a reference database for measurement techniques and normal carpal angle values in three-dimensional imaging.

Reliability and Validity of Visual Estimation of Femoral Head Hypoperfusion on Perfusion MRI in Legg-Calve-Perthes Disease.

Assessing the severity of Legg-Calve-Perthes disease is important for treatment decision-making and determining prognosis. Perfusion magnetic resonance imaging (MRI) scans have improved our ability to assess femoral head hypoperfusion, and the use of an image analysis software called HipVasc (Scottish Rite for Children, Dallas TX) has allowed precise quantification for research purposes. In the clinical setting, using HipVasc software is not practical, and visual estimation is used to assess hypoperfusion. Currently, the reliability of visual estimation is unknown. The purpose of this study was to determine the reliability and validity of visual estimation of hypoperfusion on perfusion MRI and compare the results to measurements obtained with the HipVasc software. Fourteen pediatric orthopaedic surgeons, divided into 4 groups, participated in this study. Each surgeon completed a 30-minute in-person training on HipVasc before proceeding. Stratified by category of severity, 122 MRIs were randomly assigned to 1 of the 4 groups so that each group member measured the same set of ∼30 MRIs. Each surgeon documented their visual estimation of hypoperfusion first, then used HipVasc to measure the hypoperfusion and recorded their results. Interobserver reliability was assessed at the group level by calculating the intraclass correlation coefficient. Good correlation and reliability was found between the visual estimate and HipVasc measurements with an overall mean intraclass correlation coefficient of 0.87 and mean Pearson coefficient of 0.90. The mean interobserver reliability of visual estimation was 0.84. Observers had a tendency to overestimate hypoperfusion with visual estimation. This study demonstrates the reliability and validity of visual estimation as a clinically applicable method for determining femoral head hypoperfusion. Our study is the first to measure the reliability of visual estimation and HipVasc with a large cohort of clinicians, specifically pediatric orthopaedic surgeons with varied experience in graphical software analysis. We recommend using visual estimation as a clinically applicable method to make treatment decisions, and its accuracy is comparable to HipVasc software analysis. Level III-diagnostic.

Assessment of hip displacement in children with cerebral palsy using machine learning approach.

Manual measurements of migration percentage (MP) on pelvis radiographs for assessing hip displacement are subjective and time consuming. A deep learning approach using convolution neural networks (CNNs) to automatically measure the MP was proposed. The pre-trained Inception ResNet v2 was fine tuned to detect locations of the eight reference landmarks used for MP measurements. A second network, fine-tuned MobileNetV2, was trained on the regions of interest to obtain more precise landmarks' coordinates. The MP was calculated from the final estimated landmarks' locations. A total of 122 radiographs were divided into 57 for training, 10 for validation, and 55 for testing. The mean absolute difference (MAD) and intra-class correlation coefficient (ICC [2,1]) of the comparison for the MP on 110 measurements (left and right hips) were 4.5 [Formula: see text] 4.3% (95% CI, 3.7-5.3%) and 0.91, respectively. Sensitivity and specificity were 87.8% and 93.4% for the classification of hip displacement (MP-threshold of 30%), and 63.2% and 94.5% for the classification of surgery-needed hips (MP-threshold of 40%). The prediction results were returned within 5s. The developed fine-tuned CNNs detected the landmarks and provided automatic MP measurements with high accuracy and excellent reliability, which can assist clinicians to diagnose hip displacement in children with CP.

FreeSurfer based cortical mapping and T1-relaxometry with MPnRAGE: Test-retest reliability with and without retrospective motion correction

A test-retest study of FreeSurfer derived cortical thickness, cortical surface area, and cortical volume, as well as quantitative R1 relaxometry assessed on the midpoint of the cortex, was performed on a cohort of pediatric subjects (6-12 years old) scanned without sedation using SNARE-MPnRAGE (self navigated retrospective motion corrected magnetization prepared with n rapid gradient echoes) imaging. Reliability was assessed with coefficients of variation (CoVs) and intraclass correlation coefficients (ICCs) and statistical tests were used to determine differences with and without SNARE motion correction. Comparison of the test-retest measures of SNARE-MPnRAGE with prospectively motion corrected PROMO MPRAGE were also performed. When SNARE motion correction was used all parameters had statistically significant improvements and demonstrated high reliability. Reliability varied depending on parameter, region, and measurement type (vertex or region of interest). For mean thickness/surface area/volume/mean R1 across the regions of FreeSurfer's DK Atlas, the mean CoVs (% x100) were (1.2/1.6/1.9/0.9) and the mean ICCs were (0.88/0.96/0.94/0.83). When assessed on a per-vertex basis, the CoVs and ICCs for thickness/R1 had mean values of (2.9/1.9) and (0.82/0.68) across the regions of the DK Atlas. Retrospectively motion corrected MPnRAGE had significantly lower CoVs and higher ICCs for the morphological measures than PROMO MPRAGE. Motion correction effectively removed motion related biases in nearly all regions for R1 and morphometric measures.

The Effect of Aberrant Rotation on Radiographic Patellar Height Measurement Using Canton-Deschamps Index: A Cadaveric Analysis.

The Caton-Deschamps Index (CDI) is a measurement used to evaluate patella alta based on true lateral radiographs; however, no prior study has investigated how altering the degree of radiograph aberrancy affects CDI measurement. The primary and secondary purpose of this study was to evaluate effects of rotational radiographic changes on patella height measurements and compare these findings to MRI measurements, respectively. Five cadaver knees (n = 5) were utilized in this study. True lateral radiographs were obtained for each specimen by using a fluoroscopic C-arm machine. The C-arm was then altered in two planes (axial and coronal) in both the clockwise and counterclockwise direction and radiographs were taken at 5, 10, and 15 degrees of error from the true lateral position. A CDI measurement of each specimen was performed based on sagittal magnetic resonance imaging (MRI) slices and compared with radiographic CDI measurements. Three orthopedic surgeons measured the CDI for each radiograph and MRI performed. Interrater reliability and changes in CDI were analyzed. Clinically significant difference in CDI was set to 0.1. Mean intraclass correlation coefficient was high (≥0.7) at true lateral and at all varying degrees of error. When performing a pairwise comparison of mean CDI from the true lateral position to increasing degrees of error, statistically significant differences were observed in the axial plane. The largest change in CDI measurements was seen with rotational malposition in the axial plane and counterclockwise direction. No statistically significant differences in mean CDI were observed in the coronal plane. The change in CDI from the true lateral position reached an absolute maximum of at least 0.1 in all four scenarios at each tested degree of error. This study found that aberrant radiographic rotation in the axial plane resulted in a significantly different mean CDI measurement when compared with true lateral radiographs. All degrees of error in both directions and in both planes could have a clinically significant effect on CDI (≥0.1). Our findings confirm the importance of a perfect true lateral radiograph when measuring patella height.

Comparison of dried blood spot and plasma sampling for untargeted metabolomics.

Introduction.Untargeted metabolomics holds significant promise for biomarker detection and development. In resource-limited settings, a dried blood spot (DBS)-based platform would offer significant advantages over plasma-based approaches that require a cold supply chain.Objectives.The primary goal of this study was to compare the ability of DBS- and plasma-based assays to characterize maternal metabolites. Utility of the two assays was also assessed in the context of a case-control predictive model in pregnant women living with HIV.Methods.Untargeted metabolomics was performed on archived paired maternal plasma and dried blood spots from n=79 women enrolled in a large clinical trial.Results.A total of 984 named biochemicals were detected across both plasma and DBS samples, of which 627 (63.7%), 260 (26.4%), and 97 (9.9%) were detected in both plasma and DBS, plasma alone, and DBS alone, respectively. Variation attributable to study individual (R2=0.54, p<0.001) exceeded that of the sample type (R2=0.21, p<0.001), suggesting that both plasma and DBS were capable of differentiating individual metabolomic profiles. Log-transformed metabolite abundances were strongly correlated (mean Spearman rho=0.51) but showed low agreement (mean intraclass correlation of 0.15). However, following standardization, DBS and plasma metabolite profiles were strongly concordant (mean intraclass correlation of 0.52). Random forests classification models for cases versus controls identified distinct feature sets with comparable performance in plasma and DBS (86.5% versus 91.2% mean accuracy, respectively).Conclusion.Maternal plasma and DBS samples yield distinct metabolite profiles highly predictive of the individual subject. In our case study, classification models showed similar performance albeit with distinct feature sets. Appropriate normalization and standardization methods are critical to leverage data from both sample types. Ultimately, the choice of sample type will likely depend on the compounds of interest as well as logistical demands.

Accelerometry-Based Step Count Validation for Horse Movement Analysis During Stall Confinement.

Quantitative tracking of equine movement during stall confinement has the potential to detect subtle changes in mobility due to injury. These changes may warn of potential complications, providing vital information to direct rehabilitation protocols. Inertial measurement units (IMUs) are readily available and easily attached to a limb or surcingle to objectively record step count in horses. The objectives of this study were: (1) to compare IMU-based step counts to a visually-based criterion measure (video) for three different types of movements in a stall environment, and (2) to compare three different sensor positions to determine the ideal location on the horse to assess movement. An IMU was attached at the withers, right forelimb and hindlimb of six horses to assess free-movement, circles, and figure-eights recorded in 5 min intervals and to determine the best location, through analysis of all three axes of the triaxial accelerometer, for step count during stall confinement. Mean step count difference, absolute error (%) and intraclass correlation coefficients (ICCs) were determined to assess the sensor's ability to track steps compared to the criterion measure. When comparing sensor location for all movement conditions, the right-forelimb vertical-axis produced the best results (ICC = 1.0, % error = 6.8, mean step count difference = 1.3) followed closely by the right-hindlimb (ICC = 0.999, % error = 15.2, mean step count difference = 1.8). Limitations included the small number of horse participants and the lack of random selection due to limited availability and accessibility. Overall, the findings demonstrate excellent levels of agreement between the IMU's vertical axis and the video-based criterion at the forelimb and hindlimb locations for all movement conditions.