Bland-Altman Limits Of Agreement Research Articles

Evaluating the validity and reliability of inertial measurement units for determining knee and trunk kinematics during athletic landing and cutting movements

Inertial Measurement Units (IMUs) are promising alternatives to laboratory-based motion capture methods in biomechanical assessment of athletic movements. The aim of this study was to investigate the validity of an IMU system for determining knee and trunk kinematics during landing and cutting tasks for clinical and research applications in sporting populations. Twenty-seven participants performed five cutting and landing tasks while being recorded using a gold-standard optoelectronic motion capture system and an IMU system. Intra-class coefficients, Pearson’s r, root-mean-square error (RMSE), bias, and Bland-Altman limits of agreements between the motion capture and IMU systems were quantified for knee and trunk sagittal- and frontal-plane range-of-motion (ROM) and peak angles. Our results indicate that IMU validity was task-, joint-, and plane-dependent. Based on good-to-excellent (ICC) correlation, reasonable accuracy (RMSE < 5°), bias within 2°, and limits of agreements within 10°, we recommend the use of this IMU system for knee sagittal-plane ROM estimations during cutting, trunk sagittal-plane peak angle estimation during the double-leg landing task, trunk sagittal-plane ROM estimation for almost all tasks, and trunk frontal-plane peak angle estimation for the right single-leg landing task. Due to poor comparisons with the optoelectronic system, we do not recommend this IMU system for knee frontal-plane kinematic estimations.

Measurement error and reliability of TMS metrics collected from biceps and triceps in individuals with chronic incomplete tetraplegia.

Transcranial magnetic stimulation (TMS) is used to investigate corticomotor neurophysiology associated with functional recovery in individuals with spinal cord injury (SCI). There is insufficient evidence about test-retest measurement properties of TMS in SCI. Therefore, we investigated test-retest agreement and reliability of TMS metrics representing corticomotor excitability, output, gain, map (representation), and inhibition in individuals with cervical SCI. We collected TMS metrics from biceps and triceps muscles because of the relevance of this proximal muscle pair to the cervical SCI population. Twelve individuals with chronic C3-C6 SCI participated in two TMS sessions separated by ≥ 2weeks. Measurement agreement was evaluated using t tests, Bland-Altman limits of agreement and relative standard error of measurement (SEM%), while reliability was investigated using intra-class correlation coefficient (ICC) and concordance correlation coefficient (CCC). We calculated the smallest detectable change for all TMS metrics. All TMS metrics except antero-posterior map coordinates and corticomotor inhibition were in agreement upon repeated measurement though limits of agreement were generally large. Measures of corticomotor excitability, output and medio-lateral map coordinates had superior agreement (SEM% < 10). Metrics representing corticomotor excitability, output, and inhibition had good-to-excellent reliability (ICC/CCC > 0.75). The smallest detectable change for TMS metrics was generally high for a single individual, but this value reduced substantially with increase in sample size. We recommend use of corticomotor excitability and recruitment curve area owing to their superior measurement properties. A modest group size (20 or above) yields more stable measurements, which may favor use of TMS metrics in group level modulation after SCI.

Reliability of a two-dimensional sock-clad footprint linear measurement method

A two-dimensional linear measurement approach for footprints, herein referred to as the “Reel Method,” has been shown to be valid and reliable when used on bare footprints, however, few measurement approaches have been examined on sock-clad footprints. The present investigation examines the validity and reliability of the Reel Method as a two-dimensional linear measurement approach for use on sock-clad footprints.A walking, mid-gait footprint was collected from 30 volunteer participants using the Identicator Inkless Shoe Print Model LE 25P system. The width of the ball of the foot, calcaneal width, and distance from the most posterior aspect of the heel to the most distal aspect of the first toe were each measured and compared between and within three raters. The statistical analysis demonstrated high reliability of the Reel Method among these three raters. The data were found to be normally distributed, and measurements were consistent between and within raters. 95% Intraclass Correlation coefficients, 95% Bland-Altman Limits of Agreement and 95% Standard Error of Measurement determined high statistical agreement between and within raters, demonstrating that the Reel Method is reliable and thus valid for the linear measurement of sock-clad footprints.

Cross-cultural adaptation and validation of the Amharic version of Roland Morris Disability Questionnaire in people with low back pain in Ethiopia

Purpose Cross-culturally translate, adapt, and validate Roland Morris Disability Questionnaire (RMDQ) in Amharic language in Ethiopia. Methods The English version RMDQ was translated into Amharic and back-translated into English. An expert review committee reviewed the translations and created Amharic version of the RMDQ (RMDQ-Am). Pilot testing and cognitive debriefing of the RMDQ-Am were conducted with a sample of 20 individuals with LBP. The RMDQ-Am was administered to 240 individuals with LBP from three rehabilitation centers to determine its psychometric properties. Internal consistency of the tool was determined by Cronbach’s alpha. Test-retest reliability was determined by the Intraclass correlation coefficient. The Standard Error of Measurement (SEM), Minimum Detectable Change (MDC), and the Bland Altman Limit of Agreement (LOA) was also determined. The Short-Form Health Survey (SF-36) Bodily Pain and Physical Functioning subscales were used to assess convergent validity. Exploratory Factor Analysis (EFA) was used to determine the dimensionality of the tool. Results RMDQ-Am demonstrated good internal consistency (α = 0.88), excellent test-retest reliability (ICC = 0.91), SEM (1.64), MDC (3.55), and good LOA. There is a significant moderate correlation between RMDQ-Am and the Physical Functioning (Rho = −0.62, p < 0.01) and Bodily Pain (BP) (Rho = −0.41, p < 0.01) subscales of the SF-36. Exploratory Factor Analysis demonstrates that the Amharic version of RMDQ is a primary one and secondary four-factor model [The Kaiser Meyer Olkin = 0.877, X 2 (df) =1413.278/190, p < 0.001]. Conclusion RMDQ-Am is a reliable and valid tool that can be used in both clinical practice and research with the Ethiopian LBP population. IMPLICATION FOR REHABILITATION Despite LBP being a concern in Ethiopia, the magnitude of disability related to this phenomenon is not studied in the country, mainly due to the absence of validated LBP specific patient-reported outcome measures such as the Roland Morris Disability Questionnaire (RMDQ). The RMDQ was successfully translated, adapted, and validated into the Amharic language and the Ethiopian context (RMDQ-Am). The RMDQ-Am is a reliable outcome measure among the Ethiopian population with LBP, as demonstrated by the good internal consistency (α = 0.88) and excellent test-retest reliability (ICC = 0.91). There is a moderate negative correlation between the RMDQ-Am and the Physical Functioning (Rho = −0.62, p < 0.01) and Bodily Pain (Rho = −0.41, p < 0.01) subscales of the SF-36. The RMDQ-Am can be used in clinical and research settings to measure LBP-related disability and its impact among individuals living with LBP in Ethiopia.

Accuracy and Reliability of Kinect Motion Sensing Input Device’s 3D Models: A Comparison to Direct Anthropometry and 2D Photogrammetry

AIM: This study aims to evaluate the accuracy and reliability of Kinect motion sensing input device’s three-dimensional (3D) models by comparing it with direct anthropometry and digital 2D photogrammetry. MATERIALS AND METHODS: Six profiles and four frontal parameters were directly measured on the faces of 80 participants. The same measurements were repeated using two-dimensional (2D) photogrammetry and (3D) images obtained from Kinect device. Another observer made the same measurements for 30% of the images obtained with 3D technique, and interobserver reproducibility was evaluated for 3D images. Intraobserver reproducibility was evaluated. Statistical analysis was conducted using the paired samples t-test, interclass correlation coefficient, and Bland-Altman limits of agreement. RESULTS: The highest mean difference was 0.0084 mm between direct measurement and photogrammetry, 0.027 mm between direct measurement and 3D Kinect’s models, and 0.018 mm between photogrammetry and 3D Kinect’s. The lowest agreement value was 0.016 in the all parameter between the photogrammetry and 3D Kinect’s methods. Agreement between the two observers varied from 0.999 Sn-Me to 1 with the rest of linear measurements. CONCLUSION: Measurements done using 3D Images obtained from Kinect device indicate that it may be an accurate and reliable imaging method for use in orthodontics. It also provides an easy low-cost 3D imaging technique that has become increasingly popular in clinical settings, offering advantages for surgical planning and outcome evaluation.

Is Machine Learning-derived Low-Density Lipoprotein Cholesterol estimation more reliable than standard closed form equations? Insights from a laboratory database by comparison with a direct homogeneous assay

BackgroundThere is no consensus on the best method to estimate Low Density Lipoprotein-Cholesterol (LDL-C) in routine laboratories. MethodsWe conducted a retrospective study to compare the performances of a Machine Learning (ML) algorithm using the K-Nearest Neighbors (LDL-KNN) method with that of the Friedewald formula (LDL-F), the Martin-Hopkins equation (LDL-NF), the de Cordova equation (LDL-CO) and the Sampson equation (LDL-SA) against direct homogeneous LDL-C assay (LDL-D) in patients who presented to the Laboratories of Hôtel Dieu de France university hospital in Beirut, Lebanon, from September 2017 to July 2020. Agreements between methods were analyzed using Intraclass Correlation Coefficients (ICC) and the Bland-Altman method of agreement. Results31,922 observations from 19,279 subjects were included, with a mean age of 52 ± 18 years and 10,075 (52.3%) females. All methods except LDL-F and LDL-CO exhibited an overall ICC beyond the 0.9 cut-off. LDL-SA, LDL-NF and LDL-KNN were less susceptible to triglyceridemia than LDL-F and LDL-CO, with LDL-KNN resulting in the lesser fraction of points beyond the Bland-Altman limits of agreement. ConclusionAn ML algorithm using LDL-KNN is promising for the estimation of LDL-C as it agrees better with LDL-D than closed form equations, especially in mild and severe hypertriglyceridemia.

Reliability of Performing Multiparametric Ultrasound in Adult Livers.

The aim of the study was to test inter-observer and intra-observer reliability of measuring multiparametric ultrasound in adult livers. We prospectively measured shear wave velocity (SWV, m/s), shear wave dispersion slope (SWD, m/s/kHz), attenuation coefficient (ATI, dB/cm/MHz), normalized local variance (NLV), and echo intensity ratio of liver to kidney (L/K ratio) in 21 adults who underwent liver magnetic resonance imaging-proton density fat fraction (MRI-PDFF). Intraclass correlation coefficient and 95% Bland-Altman limits of agreement (95% LOA) were used to analyze intra- and inter-observer reproducibility. Based on liver MRI-PDFF, 21 participants (8 men and 13 women, mean age 55 years) were divided into group 1 (11 normal livers, MRI-PDFF <5%) and group 2 (10 steatotic livers, MRI-PDFF ≥5%). ICCs for intra-observer repeatability and inter-observer reproducibility in measuring multiple ultrasound parameters in both normal and steatotic livers were above 0.75. However, 95% confidence interval for measuring SWD in all livers and L/K ratio in normal livers was 0.38-0.90 and 0.47-0.91, respectively. Differences in SWV, SWD, ATI, NLV, L/K ratio, and MRI-PDFF between participants with and without hepatic steatosis were significant (p < .05), whereas serum biomarkers and body mass index were not (p > .05), based on a two-tailed t-test. The results suggest that the repeatability and reproducibility for measuring liver SWV, ATI, and NLV are moderate to excellent, while those for SWD and L/K ratio are poor. Standardized machine settings, scanning protocols, and operator training are suggested in performing multiparametric ultrasound of the liver.

Repeatability of Quantitative 18F-FET PET in Glioblastoma

Purpose: O-(2-[18F]fluoroethyl)-L-tyrosine (FET), a PET radiotracer of amino acid uptake, has shown potential for diagnosis and treatment planning in patients with glioblastoma (GBM). To improve quantitative assessment of FET PET imaging, we evaluated the repeatability of uptake of this tracer in patients with GBM. Methods: Test-retest FET PET imaging was performed on 8 patients with histologically confirmed GBM, who previously underwent surgical resection of the tumour. Data were acquired according to the protocol of a prospective clinical trial validating FET PET as a clinical tool in GBM. SUVmean, SUVmax and SUV98% metrics were extracted for both test and retest images and used to calculate 95% Bland-Altman limits of agreement (LoA) on lesion-level, as well as on volumes of varying sizes. Impact of healthy brain normalization on repeatability of lesion SUV metrics was evaluated. Results: Tumour LoA were [0.72, 1.46] for SUVmean and SUVtotal, [0.79,1.23] for SUVmax, and [0.80,1.18] for SUV98%. Healthy brain LoA were [0.80,1.25] for SUVmean, [0.80,1.25] for SUVmax, and [0.81,1.23] for SUV98%. Voxel-level SUV LoA were [0.76, 1.32] for tumour volumes and [0.80, 1.25] for healthy brain. When sampled over maximum volume, SUV LoA were [0.90,1.12] for tumour and [0.92,1.08] for healthy brain. Normalization of uptake using healthy brain volumes was found to improve repeatability, but not after normalization volume size of about 15 cm3. Conclusions Advances in Knowledge and Implications for Patient Care: Repeatability of FET PET is comparable to existing tracers such as FDG and FLT. Healthy brain uptake is slightly more repeatable than uptake of tumour volumes. Repeatability was found to increase with sampled volume. SUV normalization between scans using healthy brain uptake should be performed using volumes at least 15 cm3 in size to ensure best imaging repeatability.

Cerebral autoregulation assessed by near-infrared spectroscopy: validation using transcranial Doppler in patients with controlled hypertension, cognitive impairment and controls

PurposeCerebral autoregulation (CA) aims to attenuate the effects of blood pressure variation on cerebral blood flow. This study assessed the criterion validity of CA derived from near-infrared spectroscopy (NIRS) as an alternative for Transcranial Doppler (TCD).MethodsMeasurements of continuous blood pressure (BP), oxygenated hemoglobin (O2Hb) using NIRS and cerebral blood flow velocity (CBFV) using TCD (gold standard) were performed in 82 controls, 27 patients with hypertension and 94 cognitively impaired patients during supine rest (all individuals) and repeated sit to stand transitions (cognitively impaired patients). The BP-CBFV and BP-O2Hb transfer function phase shifts (TFφ) were computed as CA measures. Spearman correlations (ρ) and Bland Altman limits of agreement (BAloa) between NIRS- and TCD-derived CA measures were computed. BAloa separation < 50° was considered a high absolute agreement.ResultsNIRS- and TCD-derived CA estimates were significantly correlated during supine rest (ρ = 0.22–0.30, N = 111–120) and repeated sit-to-stand transitions (ρ = 0.46–0.61, N = 19–32). BAloa separation ranged between 87° and 112° (supine rest) and 65°–77° (repeated sit to stand transitions).ConclusionCriterion validity of NIRS-derived CA measures allows for comparison between groups but was insufficient for clinical application in individuals.

Utility of venous blood gases for the assessment of traumatic shock: a prospective observational study

BackgroundABG samples are often obtained in trauma patients to assess shock severity. Venous blood gas (VBG) sampling, which is less invasive, has been widely used to assess other forms of...

Deep neural network-based detection and segmentation of intracranial aneurysms on 3D rotational DSA.

Accurate diagnosis and measurement of intracranial aneurysms are challenging. This study aimed to develop a 3D convolutional neural network (CNN) model to detect and segment intracranial aneurysms (IA) on 3D rotational DSA (3D-RA) images. 3D-RA images were collected and annotated by 5 neuroradiologists. The annotated images were then divided into three datasets: training, validation, and test. A 3D Dense-UNet-like CNN (3D-Dense-UNet) segmentation algorithm was constructed and trained using the training dataset. Diagnostic performance to detect aneurysms and segmentation accuracy was assessed for the final model on the test dataset using the free-response receiver operating characteristic (FROC). Finally, the CNN-inferred maximum diameter was compared against expert measurements by Pearson's correlation and Bland-Altman limits of agreement (LOA). A total of 451 patients with 3D-RA images were split into n = 347/41/63 training/validation/test datasets, respectively. For aneurysm detection, observed FROC analysis showed that the model managed to attain a sensitivity of 0.710 at 0.159 false positives (FP)/case, and 0.986 at 1.49 FP/case. The proposed method had good agreement with reference manual aneurysmal maximum diameter measurements (8.3 ± 4.3 mm vs. 7.8 ± 4.8 mm), with a correlation coefficient r = 0.77, small bias of 0.24 mm, and LOA of -6.2 to 5.71 mm. 37.0% and 77% of diameter measurements were within ±1 mm and ±2.5 mm of expert measurements. A 3D-Dense-UNet model can detect and segment aneurysms with relatively high accuracy using 3D-RA images. The automatically measured maximum diameter has potential clinical application value.

A 4D continuous representation of myocardial velocity fields from tissue phase mapping magnetic resonance imaging.

Myocardial velocities carry important diagnostic information in a range of cardiac diseases, and play an important role in diagnosing and grading left ventricular diastolic dysfunction. Tissue Phase Mapping (TPM) Magnetic Resonance Imaging (MRI) enables discrete sampling of the myocardium’s underlying smooth and continuous velocity field. This paper presents a post-processing framework for constructing a spatially and temporally smooth and continuous representation of the myocardium’s velocity field from TPM data. In the proposed scheme, the velocity field is represented through either linear or cubic B-spline basis functions. The framework facilitates both interpolation and noise reducing approximation. As a proof-of-concept, the framework was evaluated using artificially noisy (i.e., synthetic) velocity fields created by adding different levels of noise to an original TPM data. The framework’s ability to restore the original velocity field was investigated using Bland-Altman statistics. Moreover, we calculated myocardial material point trajectories through temporal integration of the original and synthetic fields. The effect of noise reduction on the calculated trajectories was investigated by assessing the distance between the start and end position of material points after one complete cardiac cycle (end point error). We found that the Bland-Altman limits of agreement between the original and the synthetic velocity fields were reduced after application of the framework. Furthermore, the integrated trajectories exhibited consistently lower end point error. These results suggest that the proposed method generates a realistic continuous representation of myocardial velocity fields from noisy and discrete TPM data. Linear B-splines resulted in narrower limits of agreement between the original and synthetic fields, compared to Cubic B-splines. The end point errors were also consistently lower for Linear B-splines than for cubic. Linear B-splines therefore appear to be more suitable for TPM data.

A Scalable Approach to Determine Intracardiac Pressure From Mechanical Circulatory Support Device Signals.

Effective mechanical circulatory support (MCS) relies on cardiac function measures to guide titration. Left ventricular end diastolic pressure (LVEDP) is a useful measure that is indirectly estimated using pulmonary artery catheters (PACs). PACs require additional intervention and provide intermittent and unreliable estimations. MCS device signals can estimate LVEDP but are prone to inter-device variability and require rigorous specialized characterization. We present a scalable and implementable approach to calculate LVEDP continuously using device signals. LVEDP was calculated from MCS device measured aortic pressure and motor current, which approximates the pressure head between the aorta and left ventricle. This motor current-pressure head relationship is device-specific but approximated using existing flow calibration and assumed physiologic relationships. Performance was evaluated with comparison from direct measurement of LVEDP in a series of acute animal models. LVEDP measures (n = 178,279) from 18 animals had good correlation (r = 0.84) and calibration (Bland-Altman limits of agreement -7.77 to 7.63 mmHg; mean bias -0.07 ± 0.02 mmHg). The total mean error prediction interval was -3.42 to 3.32 mmHg and RMS error was 3.85 mmHg. LVEDP can be continuously calculated using device signals without specialized characterization. Calculated LVEDP values improved upon PAC estimations and were found using a scalable and manufacturer-accessible method. This method improves upon existing LVEDP measures without the need for rigorous characterization, external calibration, or additional intervention; this allows widescale deployment of continuous LVEDP measurement for patients on MCS and demonstrates key considerations necessary to translate research-grade technologies.

A contactless method to measure real-time finger motion using depth-based pose estimation

BackgroundFinger mobility plays a crucial role in everyday living and is a leading indicator during hand rehabilitation and assistance tasks. Depth-based hand pose estimation is a potentially low-cost solution for the clinical and home-based measurement of symptoms of limited human finger motion. ObjectiveThe purpose of this study was to achieve the contactless measurement of finger motion based on depth-based hand pose estimation using Azure Kinect depth cameras and transfer learning, and to evaluate the accuracy in comparison with a three-dimensional motion analysis (3DMA) system. MethodsThirty participants performed a series of tasks during which their hand motions were measured concurrently using the Azure Kinect and 3DMA systems. We propose a simple and effective approach to achieving real-time hand pose estimations from single depth images using ensemble convolutional neural networks trained by a transfer learning strategy. Algorithms to calculate the finger joint motion angles are presented by tracking the locations of the 24 hand joints. To demonstrate their potential, the Azure-Kinect-based 3D finger motion measurement system and algorithms are experimentally verified through comparison with a camera-based 3DMA system, which is the gold standard. ResultsOur results revealed that the Azure-Kinect-based hand pose estimation system produced highly correlated measurements of hand joint coordinates. Our method achieved excellent performance in terms of the fraction of good frames ( >80%) when the error thresholds were larger than approximately 2 cm, and the range of mean error distance was 0.23−−1.05 cm. For joint angles, the Azure Kinect and 3DMA systems had comparable inter-trial reliability (ICC2,1 ranging from 0.89 to 0.97) and excellent concurrent validity, with Pearsons r-values >0.90 for most measurements (range: 0.88−−0.97). The 95% BlandAltman limits of agreement were narrow enough for the Azure Kinect to be considered a valid tool for the measurement of all reported joint angles of the index finger and thumb in pinching. Moreover, our method runs in real time at over 45 fps. ConclusionThe results of this study suggest that the proposed method has the capacity to measure the performance of fine motor skills.

A comparison of 2- and 3-dimensional mandibular superimposition techniques against Björk's structural superimposition method

The purpose of this research was to compare mandibular growth rotation relative to the cranial base in different vertical facial patterns on the basis of multiple 2-dimensional (2D) and 3-dimensional (3D) superimposition methods. Cone-beam computed tomography (CBCT) images taken at a mean interval of 54.8±16.8months were assessed from a sample of 70 growing patients. Three mandibular superimposition methods were compared against Björk's structural method: (1) a 2D landmark method (2D-M1), (2) a voxel-based 3D method based on a previously reported method (3D-M1), and (3) a voxel-based 3D method incorporating symphyseal structures as references (3D-M2). After superimposition, the relative change in cranial base lines as depicted in sagittal views were measured for true mandibular rotation. Agreement between methods was assessed with Lin's concordance correlation coefficient, Bland-Altman's limits of agreement, and the Bradley-Blackwood test. Lin's concordance correlation coefficients ranged between 0.924 for the 2D-M1 method, 0.695 for the 3D-M1 method, and 0.965 for the 3D-M2 method. Bland-Altman limits of agreement were wide for all but the 3D-M2 method. Finally, the Bradley-Blackwood test of equality of means and variances was significant in all except the 3D-M2 method. For time intervals between CBCT volume acquisitions>3years, the use of the 2D-M1 and 3D-M1 methods is not recommended. There was a high concordance between the 3D-M2 method and Björk's structural method when assessing mandibular growth rotation using relative changes in cranial base lines. The high concordance was displayed across all vertical facial types and for all time differences between first and second CBCT data acquisitions.

CNN color-coded difference maps accurately display longitudinal changes in liver MRI-PDFF.

To assess the feasibility of a CNN-based liver registration algorithm to generate difference maps for visual display of spatiotemporal changes in liver PDFF, without needing manual annotations. This retrospective exploratory study included 25 patients with suspected or confirmed NAFLD, who underwent PDFF-MRI at two time points at our institution. PDFF difference maps were generated by applying a CNN-based liver registration algorithm, then subtracting follow-up from baseline PDFF maps. The difference maps were post-processed by smoothing (5 cm2 round kernel) and applying a categorical color scale. Two fellowship-trained abdominal radiologists and one radiology resident independently reviewed difference maps to visually determine segmental PDFF change. Their visual assessment was compared with manual ROI-based measurements of each Couinaud segment and whole liver PDFF using intraclass correlation (ICC) and Bland-Altman analysis. Inter-reader agreement for visual assessment was calculated (ICC). The mean patient age was 49 years (12 males). Baseline and follow-up PDFF ranged from 2.0 to 35.3% and 3.5 to 32.0%, respectively. PDFF changes ranged from - 20.4 to 14.1%. ICCs against the manual reference exceeded 0.95 for each reader, except for segment 2 (2 readers ICC = 0.86-0.91) and segment 4a (reader 3 ICC = 0.94). Bland-Altman limits of agreement were within 5% across all three readers. Inter-reader agreement for visually assessed PDFF change (whole liver and segmental) was excellent (ICCs > 0.96), except for segment 2 (ICC = 0.93). Visual assessment of liver segmental PDFF changes using a CNN-generated difference map strongly agreed with manual estimates performed by an expert reader and yielded high inter-reader agreement. • Visual assessment of longitudinal changes in quantitative liver MRI can be performed using a CNN-generated difference map and yields strong agreement with manual estimates performed by expert readers.

Concurrent Validity and Reliability of the Load-Velocity Relationship to Predict the One-Repetition Maximum during Three Weightlifting Derivatives

The study investigated the concurrent validity and reliability of the load-velocity relationship to predict the one-repetition maximum (1RM) of the power clean from the knee (PCK), high pull from the knee (HPK), and mid-thigh clean pull (MTCP). For each exercise, 12 participants performed two 1RM sessions tests and two sessions to measure the barbell’s load-velocity relationship at 30, 45, 60, 75, and 90% of 1RM. The velocity recorded at each load was used to establish the linear regression equation and, consequently, to predict 1RM value. A low validity between the 1RM direct test and predicted 1RM was observed for PCK (typical error [TE]=3.96 to 4.50 kg, coefficient of variation [CV]=4.68 to 5.27%, effect size [ES]=-0.76 to -0.58, Bland-Altman bias [BAB]=9.83 to 11.19 kg), HPK (TE=4.58 to 5.82 kg, CV=6.44 to 8.14%, ES=-0.40 to -0.39, BAB=3.52 to 4.17 kg), and MTCP (TE=6.33 to 8.08 kg, CV=4.78 to 6.16%, ES=-0.29 to -0.19, BAB=3.98 to 6.17 kg). Adequate reliability was observed for the 1RM direct test and for the predicted 1RM. However, based on Bland-Altman limits of agreement, lower measurement errors were obtained for the 1RM direct test in comparison to the predicted 1RM for all the exercises. In conclusion, the load-velocity relationship was not able to predict 1RM values with high accuracy in the PCK, HPK, and MTCP. Moreover, the 1RM direct test was the most reliable for PCK, HPK and MTCP.

Imaging-Based Uveitis Surveillance in Juvenile Idiopathic Arthritis: Feasibility, Acceptability, and Diagnostic Performance.

Children with juvenile idiopathic arthritis (JIA) need regular examinations for uveitis to avoid visual morbidity from the most common extraarticular manifestation of disease. This study was undertaken to investigate the feasibility, acceptability, and performance of optical coherence tomography (OCT) imaging-based diagnosis of uveitis. This observational cross-sectional study included children with and those without uveitis. The children underwent routine clinical examinations and anterior segment OCT scanning of intraocular inflammatory cells. Acceptability of image acquisition was assessed using a visual analog scale and length of time needed to acquire images. Interobserver and intraobserver variability of manual counting of acquired images (Bland-Altman limits of agreement), correlation between imaging and routine assessment, and sensitivity and specificity of anterior segment OCT detection of active inflammation were assessed. Of the 26 children ages 3-15 years (median age 8 years) who underwent imaging, 12 had active inflammation. All patients rated the acceptability of image acquisition as at least 8.5 on a scale of 0-10. Time taken to acquire images ranged from 1.5 minutes to 22 minutes (median time 8 minutes). There was good positive correlation between clinical assessment and image-based cell quantification (R2 = 0.63, P = 0.002). Sensitivity of anterior segment OCT manual image cell count for diagnosis of active inflammation was 92% (95% confidence interval [95% CI] 62-99%), specificity was 86% (95% CI 58-98%), and negative predictive value (ruling out uveitis) was 92% (95% CI 65-99%). Non-contact, high-resolution imaging for JIA uveitis surveillance is feasible, acceptable to patients, and holds the promise of transforming pediatric practice. Further work is needed to determine the analytic and clinical validity of anterior segment OCT quantification of active inflammation, and the clinical utility and cost-effectiveness of imaging-based disease monitoring.

The Validity and Reliability of the Microsoft Kinect for Measuring Trunk Compensation during Reaching.

Compensatory movements at the trunk are commonly utilized during reaching by persons with motor impairments due to neurological injury such as stroke. Recent low-cost motion sensors may be able to measure trunk compensation, but their validity and reliability for this application are unknown. The purpose of this study was to compare the first (K1) and second (K2) generations of the Microsoft Kinect to a video motion capture system (VMC) for measuring trunk compensation during reaching. Healthy participants (n = 5) performed reaching movements designed to simulate trunk compensation in three different directions and on two different days while being measured by all three sensors simultaneously. Kinematic variables related to reaching range of motion (ROM), planar reach distance, trunk flexion and lateral flexion, shoulder flexion and lateral flexion, and elbow flexion were calculated. Validity and reliability were analyzed using repeated-measures ANOVA, paired t-tests, Pearson’s correlations, and Bland-Altman limits of agreement. Results show that the K2 was closer in magnitude to the VMC, more valid, and more reliable for measuring trunk flexion and lateral flexion during extended reaches than the K1. Both sensors were highly valid and reliable for reaching ROM, planar reach distance, and elbow flexion for all conditions. Results for shoulder flexion and abduction were mixed. The K2 was more valid and reliable for measuring trunk compensation during reaching and therefore might be prioritized for future development applications. Future analyses should include a more heterogeneous clinical population such as persons with chronic hemiparetic stroke.

Three-dimensional (3D) magnetic resonance volume assessment and loco-regional failure in anal cancer: early evaluation case-control study

BackgroundThe primary aim was to test the hypothesis that deriving pre-treatment 3D magnetic resonance tumour volume (mrTV) quantification improves performance characteristics for the prediction of loco-regional failure compared with standard maximal tumour diameter (1D) assessment in patients with squamous cell carcinoma of the anus undergoing chemoradiotherapy.MethodsWe performed an early evaluation case-control study at two UK centres (2007–2014) in 39 patients with loco-regional failure (cases), and 41 patients disease-free at 3 years (controls). mrTV was determined using the summation of areas method (Volsum). Reproducibility was assessed using intraclass concordance correlation (ICC) and Bland-Altman limits of agreements. We derived receiver operating curves using logistic regression models and expressed accuracy as area under the curve (ROCAUC).ResultsThe median time per patient for Volsum quantification was 7.00 (inter-quartile range, IQR: 0.57–12.48) minutes. Intra and inter-observer reproducibilities were generally good (ICCs from 0.79 to 0.89) but with wide limits of agreement (intra-observer: − 28 to 31%; inter-observer: − 28 to 46%). Median mrTVs were greater for cases (32.6 IQR: 21.5–53.1 cm3) than controls (9.9 IQR: 5.7–18.1 cm3, p < 0.0001). The ROCAUC for mrT-size predicting loco-regional failure was 0.74 (95% CI: 0.63–0.85) improving to 0.82 (95% CI: 0.72–0.92) when replaced with mrTV (test for ROC differences, p = 0.024).ConclusionPreliminary results suggest that the replacement of mrTV for mrT-size improves prediction of loco-regional failure after chemoradiotherapy for squamous cell carcinoma of the anus. However, mrTV calculation is time consuming and variation in its reproducibility are drawbacks with the current technology.