Narrow Limits Of Agreement Research Articles

P574Accuracy of wrist-worn heart rate monitors for chronotropic assessment in atrial fibrillation

Abstract Introduction Wrist-worn fitness and heart rate (HR) monitors are increasingly popular. Previous studies in healthy participants with sinus rhythm (SR) have yielded variable results depending on HR, activity levels and device tested. A paucity of data exists on their accuracy in atrial fibrillation (AF) in ambulatory patients. Purpose We sought to assess the HR accuracy of 2 commercially available smart watches (Fitbit Charge HR [FB] and Apple Watch Series 3 [AW]) compared with Holter monitoring in an ambulant patient cohort. Methods Patients aged >18 years referred for 24-hour Holter monitoring were prospectively recruited. The Holter monitor was the criterion measure. Each patient was randomly allocated to either a FB or AW along with their Holter monitor. The study protocol was approved by the institutional review board. Statistical analysis: Pearson (r) correlation coefficients and Bland-Altman comparison with 95% limits of agreement (LoA) were evaluated to assess criterion validity and agreement between the smart watch and Holter ECG-HR. Bias was the calculated mean difference between the smart watch and ECG-HR. A ± 10-beat different between Holter-HR and SW-HR was used as a clinically relevant range to establish the accuracy of HR estimation by SW. Results Across all devices, 53,288 hear rate values were recorded from 32 patients. Twenty six patients were in persistent AF and six were in SR. Twelve patients wore the FB while 20 wore the AW. In the FB arm, nice patient were in persistent AF and three in SR. In the AW arm, persistent AF was the rhythm in seventeen and SR in three. Patients in SR demonstrated overall strong agreement compared to Holter monitoring (Mean Bias <1 beat, LoA −11 to 11 beats) and a correlation coefficient of 0.87 (p<0.001). In AF, both devices underestimated HR measurements (Overall Bias −9 beats, LoA −41 to 23, r=0.60, p<0.001). The AW had lower bias and narrower LoA compared to FB (−5 beats vs −13 beats, LoA −31 to 21 beats vs −50 to 22 beats). Using a ± 10-beat range against ECG-HR for clinical accuracy, both the AW and FB performed satisfactorily in SR with 95.2% of AW and 92.2% of FB HR readings considered valid. In AF, however, the AW-HR readings were within the ± 10-beat threshold in 76.5% of the time compared with only 56.1% of FB readings. Conclusion In ambulatory patients, smart watches were accurate in HR estimation when compared to Holter monitor in SR; however tended to underestimate HR in AF. Further improvements in device technology are needed before the widespread consumer adoption of this nascent technology for chronotropic assessment in arrhythmias.

Modelling the loading mechanics of anterior cruciate ligament

Background and ObjectivesThe anterior cruciate ligament (ACL) plays a crucial role in knee stability and is the most commonly injured knee ligament. Although ACL loading patterns have been investigated previously, the interactions between knee loadings transmitted to ACL remain elusive. Understanding the loading mechanism of ACL during dynamic tasks is essential to prevent ACL injuries. Therefore, we propose a computational model that predicts the force applied to ACL in response to knee loading in three planes of motion. MethodsFirst, a three-dimensional (3D) computational model was developed and validated using available cadaveric experimental data to predict ACL force. This 3D model was then combined with a neuromusculoskeletal model of lower limb and used to estimate in vivo ACL forces during a standardised drop-landing task. The neuromusculoskeletal model utilised movement data collected from female participants during a dynamic task and calculated lower limb joint kinematics and kinetics, as well as muscle forces. ResultsThe total ACL force predicted by the 3D computational ACL force model was in good agreement with cadaveric data, as strong correlation (r2 = 0.96 and P < 0.001), minimal bias, and narrow limits of agreement were observed. The combined model further illustrated that the ACL is primarily loaded through the sagittal plane, mainly due to muscle loading. ConclusionsThe proposed computational model is the first validated model that can provide an accessible tool to develop and test knee ACL injury prevention programs for people with normal ACL. This method can be extended to study the abnormal ACL upon the availability of relevant experimental data.

Influence of RunScribe™ placement on the accuracy of spatiotemporal gait characteristics during running

This study aimed to examine the influence of RunScribe location (i.e. lace shoe vs heel shoe) on the accuracy of spatiotemporal gait characteristics during running by comparing data with a high-speed video analysis system at 1000 Hz. A total of 49 endurance runners performed a running protocol on a treadmill at comfortable velocity. Two systems were used to determine spatiotemporal parameters (i.e. contact time, flight time, step frequency, and step length) during running: high-speed video analysis at 1000 Hz and two different RunScribe placements (i.e. lace shoe vs heel shoe). The pairwise comparisons showed some between-system differences in both lace shoe (contact time: p = 0.009; step frequency: p = 0.001) and heel shoe (flight time: p = 0.006; step frequency: p = 0.010), although the effect sizes were small (effect size &lt; 0.3 in all cases). The intraclass correlation coefficients revealed an almost perfect association between systems for contact time and flight time (intraclass correlation coefficient: 0.85–0.90), and step length and step frequency (intraclass correlation coefficient: 0.96–0.97), regardless of the RunScribe placement. Bland–Altman plots revealed that the lace shoe location yielded smaller systematic bias, random errors, and narrower limits of agreement for spatiotemporal parameters during running, except for SF, which had a higher accuracy in a heel shoe location. The results suggest that RunScribe is a valid system to measure spatiotemporal parameters during running on a treadmill according to a high-speed video analysis at 1000 Hz. In addition, the data indicate that the location of the RunScribe system (lace shoe vs heel shoe) plays an important role on the accuracy of spatiotemporal parameters. The lace shoe placement showed smaller systematic bias, random errors, and narrower limits of agreement for contact time, flight time, and step length, whereas the heel shoe placement was slightly more accurate for the step frequency.

Technical note: Glucose concentration in dairy cows measured using 6 handheld meters designed for human use

The objective was to evaluate the precision and accuracy of 6 handheld glucose meters, designed for human use [Accu-Chek Aviva Plus (AC), Roche Diabetes Care, Mannheim, Germany; Aga Matrix (AM), AgaMatrix Inc., Salem, NH; Contour Next (CT), Bayer HealthCare LLC, Leverkusen, Germany; FreeStyle Precision Neo (FS), Abbott Diabetes Care Ltd., Alameda, CA; Nova Max Plus (NM), Nova Biomedical Corporation, Waltham, MA; and Precision Xtra (PX), Abbott Diabetes Care Ltd., Witney, UK] to measure blood glucose concentration in dairy cows. Blood samples from Jersey and Jersey × Holstein crossbreed cows (n = 97 for all; except CT, n = 71) were collected and analyzed in triplicate using the 6 handheld glucose meters evaluated. Plasma glucose was also measured with the laboratory reference method (hexokinase glucose-6-phosphate dehydrogenase). Based on the intra-assay coefficient of variation (CV), precision varied across handheld glucose meters: AC (2.2%), CT (4.0%), PX (4.7%), FS (5.6%), AM (6.2%), and NM (6.7%). Lin's concordance correlation coefficients between handheld glucose meters and the reference method were 0.75 for FS, 0.74 for PX, 0.62 for AC, 0.55 for CT, 0.53 for NM, and 0.48 for AM. Based on Passing-Bablok regression, the AM and PX meters showed bias in the measurements of blood glucose. Bland-Altman plots indicated a negative bias (FS = -0.25 mmol/L; CT = -0.60 mmol/L) or a positive bias (AM = 0.29 mmol/L; PX = 0.33 mmol/L; NM = 0.52 mmol/L; AC = 0.65 mmol/L) between handheld glucose meters and the reference method. All handheld glucose meters evaluated had wide limits of agreement (LoA) ranging from -0.18 to 1.47 mmol/L (AC, narrowest LoA) to -1.25 to 1.82 mmol/L (AM, widest LoA). Bias was the major contributor to the total observed error (TEobs), accounting for 81.5% of the TEobs in AC, 72.0% in CT, 64.9% in AM, 61.1% in NM, 57.8% in PX, and 56.2% in FS. Overall, although some handheld meters (AC, CT, and PX) showed satisfactory precision, none were accurate measuring glucose. Future studies should evaluate whether incorporating algorithms designed for cattle can improve accuracy and precision of handheld glucose meters.

Volumetric assessment of solid pulmonary nodules on ultralow-dose CT: a phantom study.

To reduce the radiation exposure from chest computed tomography (CT), ultralow-dose CT (ULDCT) protocols performed at sub-millisievert levels were previously tested for the evaluation of pulmonary nodules (PNs). The purpose of our study was to investigate the effect of ULDCT and iterative image reconstruction on volumetric measurements of solid PNs. CT datasets of an anthropomorphic chest phantom containing solid microspheres were obtained with a third-generation dual-source CT at standard dose, 1/8th, 1/20th and 1/70th of standard dose [CT volume dose index (CTDIvol): 0.03-2.03 mGy]. Semi-automated volumetric measurements were performed on CT datasets reconstructed with filtered back projection (FBP) and advanced modelled iterative reconstruction (ADMIRE), at strength level 3 and 5. Absolute percentage error (APE) evaluated measurement accuracy related to the effective volume. Scan repetition differences were evaluated using Bland-Altman analysis. Two-way analysis of variance (ANOVA) assessed influence of different scan parameters on APE. Proportional differences (PDs) tested the effect of dose settings and reconstruction algorithms on volumetric measurements, as compared to the standard protocol (standard dose-FBP). Bland-Altman analysis revealed small mean interscan differences of APE with narrow limits of agreement (-0.1%±4.3% to -0.3%±3.8%). Dose settings (P<0.001), reconstruction algorithms (P<0.001), nodule diameters (P<0.001) and nodule density (P=0.011) had statistically significant influence on APE. Post-hoc Bonferroni tests showed slightly higher APE when scanning with 1/70th of standard dose [mean difference: 3.4%, 95% confidence interval (CI): 2.5-4.3%; P<0.001], and for image reconstruction with ADMIRE5 (mean difference: 1.8%, 95% CI: 1.0-2.5%; P<0.001). No significant differences for scanning with 1/20th of standard dose (P=0.42), and image reconstruction with ADMIRE3 (P=0.19) were found. Scanning with 1/70th of standard dose and image reconstruction with FBP showed the widest range of PDs (-16.8% to 23.4%) compared to standard dose-FBP. Our phantom study showed no significant difference between nodule volume measurements on standard dose CT (CTDIvol: 2 mGy) and ULDCT with 1/20th of standard dose (CTDIvol: 0.10 mGy).

4D Flow versus Conventional 2D MRI for Measuring Pulmonary Flow after Tetralogy of Fallot Repair

After tetralogy of Fallot (TOF) repair, pulmonary regurgitation and right ventricular function must be monitored. Conventional (2D) cardiac magnetic resonance (CMR) is currently the clinical reference method for measuring pulmonary regurgitation. However, 4D CMR has been reported to provide a more comprehensive flow analysis than 2D CMR. We aimed to compare 4D CMR to 2D CMR for assessing pulmonary regurgitation and flow, as well as aortic flow, in children and adults after surgical repair of TOF. Retrospective analysis of patients with repaired TOF admitted for cardiac MRI with 4D flow acquisition from 2016 to 2018. Linear regression was used to assess correlations and Bland-Altman analyses were performed. The 60 included patients had a mean age of 18.2 ± 10.4 years (range, 2–54 years). Significant correlations between the two techniques were found for pulmonary regurgitant fraction (R 2 = 0.6642, P < 0.0001), net pulmonary flow (R 2 = 0.6782, P < 0.0001), forward pulmonary flow (R 2 = 0.6185, P < 0.0001), backward pulmonary flow (R 2 = 0.8192, P < 0.0001), and aortic valve flow (R 2 = 0.6494, P < 0.0001). The Bland-Altman analysis showed no significant bias, narrow limits of agreement, and few scattered points. The correlation between pulmonary and aortic flow was better with 4D CMR than with 2D CMR (R 2 = 0.8564, P < 0.0001 versus R 2 = 0.4393, P < 0,0001, respectively). Interobserver reliability was good. These results establish the feasibility and reliability of 4D CMR for assessing pulmonary flow in a large paediatric and adult population with repaired TOF. 4D CMR may be more reliable than 2D MRI for pulmonary flow assessment after TOF repair.

Full-Range Liver Fat Fraction Estimation in Magnitude MRI Using a Signal Shape Descriptor

Current methods for estimation of proton density fat fraction (PDFF) of the liver using magnitude magnetic resonance (MR) imaging face the challenge of correctly estimating it when fat is the dominant molecule; i.e., PDFF is more than 50%. Therefore, the accuracy of the methods is limited to half-range operation. We introduce a method based on neural networks for regression capable of estimating over the full range of fat fractions. We built a neural network based on the angles and distances between the data in the discrete MR signal (ADALIFE), using these as features associated with different PDFFs and as input for the network. Tests were performed using ADALIFE and Multi-interference, a state-of-the-art method to estimate PDFFs, with simulated signals at various signal-to-noise (SNR) values. Results were compared in order to verify repeatability and agreement using Bland-Altman and REC curves. Results for Multi-interference were similar to its in vivo literature, showing the relevance of a simulation. ADALIFE was able to correctly estimate fat fractions up to 100%, breaking the current paradigm for full-range estimation using only offline postprocessing. Within half range, our method outperformed Multi-interference in repeatability and agreement, with narrower limits of agreement and lower expected error at any SNR.

Toward Accurate Extraction of Respiratory Frequency From the Photoplethysmogram: Effect of Measurement Site.

Background: It is known that the respiration-modulated photoplethysmographic (PPG) signals could be used to derive respiratory frequency (RF) and that PPG signals could be measured from different body sites. However, the accuracy of RF derived from PPG signals of different body sites has not been comprehensively investigated. Objective: This study aims to investigate the difference in the accuracy of PPG-derived RFs between measurements from different body sites, respectively, for normal and deep breathing conditions. Methods: Under normal and deep breathing patterns, the PPG signals were recorded sequentially in a randomized order from six body sites [finger, wrist under (anatomically volar), wrist upper (dorsal), earlobe, and forehead] of 36 healthy subjects. Simultaneously, the reference respiratory signal was measured by a respiratory belt on the chest. Using the frequency demodulation approach, respiratory signals were extracted from PPG signals for calculating RF by power spectral density. The bias between PPG-derived and reference RFs was then analyzed statistically using analysis of variance and non-parametric tests, Bland-Altman analysis, and linear regression to investigate the difference in RF bias between different sites. Results: The RF bias was significantly influenced by the breathing pattern and measurement site (both p < 0.001). Under normal breathing, the RF bias was insignificant in the arm, forehead, and wrist under (all p > 0.05) and significant in the other sites (all p < 0.05). Significant linear relationship between PPG-derived and reference RFs existed at all the sites (p < 0.001) except the wrist upper (p > 0.05). The linearity between PPG-derived and reference RFs was highest at the forehead (slope of best-fit line: 0.90, R2: 0.64), followed by the earlobe, finger, arm, and wrist under (slope: 0.71, R2: 0.40). Under deep breathing, there was no significant RF bias in all the measurement sites (p > 0.05) except forehead (p = 0.048). The effect of measurement site on RF bias was not significant (p > 0.05). The finger had the smallest RF bias and the narrowest limits of agreement. Conclusion: This study has demonstrated that the accuracy of PPG-derived RF depends on the measurement site and breathing pattern. The best sites are the forehead and finger, respectively, for normal and deep breathing patterns.

Schiotz Scleral Intraocular Pressure Readings Predict Goldmann Applanation Readings Better Than Rebound Tonometry.

To study the agreement between scleral intraocular pressure (IOP) measurements using the Schiotz, Icare, and Icare PRO tonometers versus Goldmann applanation tonometer (GAT) in eyes with nonscarred corneas. This cross-sectional study included 83 eyes of 55 subjects. The order of IOP estimation was the corneal GAT, followed by ICare, ICare PRO, and Schiotz on the corneal and temporal sclera. The agreement between different tonometers and the 95% limits of agreement (LoA) were assessed using Bland-Altman plots. The repeated measures correlation coefficient was calculated between GAT IOP and scleral Schiotz IOP, and the 95% confidence intervals were calculated by the bootstrap method. The linear mixed effects model was used (adjusted for both eyes of the subjects) to generate an equation to predict GAT IOP from scleral Schiotz IOP. The prediction model was validated with new data from 60 eyes. Statistical analyses were performed using "R" software (version 3.3.2). Comparing the scleral IOP measurements, the mean IOP difference (95% LoA) was the lowest with Schiotz, underestimating by -1.21 mm Hg (7.32, -9.74). Both ICare and ICare PRO significantly overestimated GAT IOP: ICare, 24.6 mm Hg (53.2, -3.97); and ICare PRO, 21.56 mm Hg (52.9, -9.79). The correlation coefficient between scleral Schiotz and GAT IOP was 0.92 (95% bootstrap confidence interval: 0.89, 98). The derived predictive equation was (Equation is included in full-text article.). The mean difference between the predicted GAT IOP and the actual GAT IOP was 0.96 mm Hg with narrow LoA (+1.79, -3.71), validating the prediction model. Among the tonometers tested, the scleral IOP measurements with Schiotz had the best agreement with the GAT although LoA were wide. The predictive equation may have great potential to predict GAT IOP from scleral IOP readings in eyes with scarred/prosthetic corneas.

Characterisation of dairy processing sludge using energy dispersive X-ray fluorescence spectroscopy

The dairy processing industry generates significant volumes of dairy sludge and recycling onto land could provide a source of nutrients for crop production. This work assessed the feasibility of energy dispersive X-ray fluorescence spectroscopy (XRF) for the direct, elemental analysis for land application. XRF intensities were calibrated using fundamental parameters (FP), matching libraries (ML) and empirical (EMP) standards. For major nutrients phosphorus (P), potassium (K), magnesium (Mg), sulphur (S) and aluminium (Al) each calibration method provided an excellent fit to conventional analysis. Agreement statistics computed the Concordance Correlation Coefficient (CCC) that expresses agreement in which a value of 1 represents perfect agreement and a value of 0 represents no agreement. The CCC values for FP calibrations fell between 0.8820 and 0.9925 representing excellent agreement with ICP values, and outperformed other calibration methods in XRF. Copper (Cu), manganese (Mn), zinc (Zn) and nickel (Ni) recorded R2 between 0.8037 and 0.9868, for FP and ML calibrated values with empirical calibrations showing moderate agreement (R2 0.6510 to 0.8855). Trace elements fell within narrow limits of agreement with negligible bias with CCC values between 0.8335 to 0.9930. XRF can provide rapid and accurate analysis of dairy sludge without the need for empirical standards.

Left atrial strain reproducibility using vendor-dependent and vendor-independent software

BackgroundTwo-dimensional speckle-tracking echocardiography (2D-STE) enables objective assessment of left atrial (LA) deformation through the analysis of myocardial strain, which can be measured by different speckle-tracking software. The aim of this study was to compare the consistency of 3 different commercially available software, which include vendor-specific software for measuring left ventricle (VSSLV), vendor-independent software packages for measuring LV strain (VISLV) and vendor-independent software packages for measuring LA strain (VISLA).MethodsSixty-four subjects (mean age: 44 ± 16 years, 50% males) underwent conventional echocardiograms using a GE Vivid 9 (GE Ultrasound, Horten, Norway) cardiac ultrasound system. Standard apical 4 and 2 chamber views of the left atrium were obtained in each subject with a frame-rate range of 40–71 frames/s. LA strain during the contraction phase (Sct), conduit phase (Scd), reservoir phase (Sr = Sct + Scd) were analyzed by 2 independent observers and 3 different software.ResultsSct, Scd, Sr were, respectively, − 11.26 ± 2.45%, − 16.77 ± 7.06%, and 28.03 ± 7.58% with VSSLV, − 14.77 ± 3.59%, − 23.17 ± 10.33%, and 38.23 ± 10.99% with VISLV, and − 14.80 ± 3.88%, − 23.94 ± 10.48%, and 38.73 ± 11.56% when VISLA was used. A comparison of strain measurements between VSSLV and VIS (VISLV and VISLA) showed VIS had significantly smaller mean differences and narrower limits of agreement. Similar results were observed in the coefficient of variation (CV) for measurements between VSSLV and VIS (VISLV and VISLA). Comparison of the intra-class correlation coefficients (ICCs) indicated that measurement reliability was weaker with VSSLV (ICC < 0.6) than with VIS (VISLV and VISLA) (ICC > 0.9). For intra-observer ICCs, VISLA > VSSLV = VISLV. For inter-observer ICCs, VSSLV > VISLA > VISLV.ConclusionsSoftware measurement results of LA strain vary considerably. We recommended not measuring LA strain across vendor platforms.

Reference values for spirometric parameters in healthy children living in a Colombian city located at 2640 m altitude.

To identify the spirometric equations that are most appropriate for use in children and adolescents living in Bogota, Colombia after evaluating a set of relevant previously-developed equations, including the Global Lung Function Initiative (GLI) 2012 spirometry reference equations. Healthy children aged between 6 and 17 years that were attending two randomly-selected schools in Bogota were invited to participate in the study, from January 2017 to January 2018. All participants underwent spirometry, following the procedures recommended by the American Thoracic Society/European Respiratory Society (ATS/ERS) Task Force. To identify the model or group of models that best predict each spirometric parameter in our population, we performed extensive residuals analyses and constructed Bland-Altman plots. Three hundred twenty-six spirometric tests (149 boys, 177 girls) formed the reference data set. Knudson and GLI-2012 spirometry reference equations proved to be the most accurate in predicting the majority of spirometry parameters in both sexes and both age groups, each providing the lowest median prediction error in the residual analyses or the narrowest limits of agreement in the Bland-Altman plots in approximately one-third of the spirometry parameters analyzed. For the majority of spirometry parameters, we recommend the use of Knudson and GLI-2012 spirometry reference equations for evaluating the respiratory function of children living in Bogota, Colombia, a city located at an altitude of 2640 m. Future investigations should target additional spirometric equations from Latin American populations living at moderate to high altitude to improve the GLI-2012 equations.

Reproducibility of aortic valve calcification scoring with computed tomography – An interplatform analysis

BackgroundTo investigate whether aortic valve calcification (AVC) scoring performed with different workstation platforms generates comparable and thus software-independent results. MethodsIn this IRB-approved retrospective study, we included 100 consecutive patients with symptomatic aortic stenosis undergoing CT prior to transcatheter aortic valve implantation. Two independent observers performed AVC scoring on non-enhanced images with commercially available software platforms of four vendors (GE, Philips, Siemens, 3mensio). Gender-specific Agatston score cut-off values were applied according to current recommendations to assign patients to different likelihood categories of aortic stenosis (unlikely to very likely). Comparative analysis of Agatston scores between the four platforms were performed by using Kruskal-Wallis analysis, Spearman rank correlation, linear regression analysis, and Bland-Altman analysis. Differences in category assignment were compared using Fisher's exact test and Cohen's kappa. ResultsFor both observers, each workstation platform produced slightly different numeric AVC Agatston scores, however, without statistical significance (p = 0.96 and p = 0.98). Excellent correlation was found between platforms, with r = 0.991–0.996 (Spearman) and r2 = 0.981–0.992 (regression analysis) for both observers. Bland-Altman analyses revealed small mean differences with narrow limits of agreement between platforms (mean differences: 6 ± 128 to 100 ± 179), for inter-observer (mean differences: 1 ± 43 to 12 ± 70), and intra-observer variability (mean differences: 9 ± 42 to 20 ± 96). Observer 1 assigned 11 (kappa: 0.85–0.97) and observer 2 assigned 10 patients (kappa: 0.88–0.95) to different likelihood groups of severe aortic stenosis with at least one platform. Overall, there was no significant difference of likelihood assignment between platforms (p = 0.98 and p = 1.0, respectively). ConclusionWhile absolute values differ slightly, common commercially available software platforms produce comparable results for AVC scoring, which indicates software-independence of the method.

Accuracy of Anthropometric Equations to Estimate DXA-Derived Skeletal Muscle Mass in Professional Male Soccer Players.

Background Several anthropometric equations that estimate skeletal muscle mass (SMM) have been published, but their applicability and accuracy among athletes are still uncertain. Purpose To assess the accuracy of different anthropometric equations that estimate SMM in professional male soccer players, as compared to dual-energy X-ray absorptiometry (DXA) as the reference method. Methods In this cross-sectional study, we evaluated 179 professional male soccer players aged between 18 and 37 years. Anthropometric measurements (height, body weight, skinfold thicknesses, and girths) and a DXA whole body scan were performed the same day for each participant, and SMM was estimated with nine anthropometric equations (Heymsfield, Martin, Doupe, Kerr, Drinkwater, Lee, De Rose, and two equations published by Kuriyan). To determine differences between SMM estimated with anthropometric equations and SMM evaluated with DXA, a Kruskal-Wallis test was performed using Dunn's test as post hoc. The significance level was set at p < 0.05. We calculated the mean difference and 95% limits of agreement for the analyzed equations (Equation – DXA). Results Only Heymsfield's and Lee's equations showed no significant differences with DXA. Heymsfield's equation had the smallest mean difference (-0.17 kg), but wider limits of agreement with DXA (-6.61 to 6.94 kg). Lee's equation had a small mean difference (1.10 kg) but narrower limits of agreement with DXA (-1.83 to 4.03 kg). Conclusions In this study, the prediction equation published by Lee et al. showed the best agreement with DXA and is able to estimate SMM accurately in professional male soccer players.

Poor reliability of P-wave terminal force V1 in ischemic stroke

IntroductionSeveral ECG markers are postulated to represent underlying atrial remodelling and have been associated with ischemic stroke. P-wave terminal force in lead V1 (PTFV1) is one such marker. We examined the factors that contribute to the reliability of PTFV1 and its association with ischemic stroke. Material and methodsFour hundred and thirty-five patients that presented with an ischemic stroke or transient ischemic attack (TIA) were identified through a prospectively maintained multi-site institutional stroke database. Control group consisted of age matched patients without prior history of an ischemic stroke or TIA. All patients underwent a 12-lead ECG and 24-hour Holter monitoring during the study period to exclude atrial fibrillation. ResultsMorphology consistent with PTFV1 occurred commonly in both the stroke/TIA and control groups. There was no significant difference in the median PTFV1 value between the stroke 3.96 mV ms [Interquartile range (IQR) 2.78–5.58] and control 4.23 mV ms [IQR 2.91–5.57] groups. Measurements of PTFV1 demonstrated excellent intra-observer reliability on assessment of the same P-wave (Intra class correlation (ICC) 0.91, p < 0.001) with narrow limits of agreement 2.21 to −2.95 mV ms. A change in the P wave assessed led to a significant reduction in reliability (ICC 0.79, p < 0.001). Inter-observer, inter P-wave assessment demonstrated further reduction in reliability (ICC 0.68, p < 0.002) with wide limits of agreement 6.17 to −5.78 mV ms, indicating significant under and overestimation of PTFV1. ConclusionThe utility of PTFV1 as a clinical marker for ischemic stroke is limited by the reduction in reliability associated with inter-observer and inter P-wave measurements.

Value of PET/MRI for assessing tumor resectability in NSCLC-intra-individual comparison with PET/CT.

The purpose of this study was to compare the diagnostic accuracy of positron emission tomography (PET)/MRI with PET/CT for determining tumor resectability of non-small cell lung cancer (NSCLC). Sequential trimodality PET/CT/MRI was performed in 36 patients referred with the clinical question of resectability assessment in NSCLC. PET/CT and PET/MR images including T1 weighted sequence (T1-Dixon) and respiration gated T2 weighted sequence (T2-Propeller) were evaluated for resectability-defining factors; i.e. longest diameter of the tumor, minimal tumor distance to the carina, mediastinal invasion, invasion of the carina, pleural infiltration, pericardial infiltration, diaphragm infiltration, presence of additional nodules. There was no significant difference of maximal axial diameter measurements of the primary lung tumors and narrow limits of agreement in Bland-Altman analysis ranging from -11.1 mm to + 11.8 mm for T2-Propeller and from -14.3 mm to + 13.8 mm for T1-Dixon sequence. A high agreement of PET/MR with PET/CT for the different resectability-defining factors was observed (k from 0.769 to 1.000). There was an excellent agreement of T2-Propeller sequence and CT for additional pulmonary nodule detection (k of 0.829 and 0.833), but only a moderate and good agreement using T1-Dixon sequence (k of 0.484 and 0.722). In NSCLC the use of PET/MRI, including a dedicated pulmonary MR imaging protocol, provides a comparable diagnostic value for determination of tumor resectability compared to PET/CT. Our findings suggest that whole body PET/MRI can safely be used for the local staging of NSCLC patients. Further studies are warranted to determine whether it is feasible to integrate an imaging sequence in a whole body PET/MRI setting with the potential advantage of detection of liver or brain metastases.

Reproducibility study on myocardial strain assessment using fast-SENC cardiac magnetic resonance imaging

Myocardial strain is a well validated parameter for estimating left ventricular (LV) performance. The aim of our study was to evaluate the inter-study as well as intra- and interobserver reproducibility of fast-SENC derived myocardial strain. Eighteen subjects (11 healthy individuals and 7 patients with heart failure) underwent a cardiac MRI examination including fast-SENC acquisition for evaluating left ventricular global longitudinal (GLS) and circumferential strain (GCS) as well as left ventricular ejection fraction (LVEF). The examination was repeated after 63 [range 49‒87] days and analyzed by two experienced observers. Ten datasets were repeatedly assessed after 1 month by the same observer to test intraobserver variability. The reproducibility was measured using the intraclass correlation coefficient (ICC) and Bland-Altman analysis. Patients with heart failure demonstrated reduced GLS and GCS compared to healthy controls (−15.7 ± 3.7 vs. −20.1 ± 1.4; p = 0.002 for GLS and −15.3 ± 3.7 vs. −21.4 ± 1.1; p = 0.001 for GCS). The test-retest analysis showed excellent ICC for LVEF (0.92), GLS (0.94) and GCS (0.95). GLS exhibited excellent ICC (0.99) in both intra- and interobserver variability analysis with very narrow limits of agreement (−0.6 to 0.5 for intraobserver and −1.3 to 0.96 for interobserver agreement). Similarly, GCS showed excellent ICC (0.99) in both variability analyses with narrow limits of agreement (−1.1 to 1.2 for intraobserver and −1.7 to 1.3 for interobserver agreement), whereas LVEF showed larger limits of agreement (−14.4 to 10.1). The analysis of fast-SENC derived myocardial strain using cardiac MRI provides a highly reproducible method for assessing LV functional performance.

Minimum time required for assessing step variability during running at submaximal velocities

This study aimed to determine the minimum time required for assessing spatiotemporal variability during continuous running at different submaximal velocities and, thereby, the number of steps required. Nineteen trained endurance runners performed an incremental running protocol, with a 3-min recording period at 10, 12, 14 and 16 km/h. Spatiotemporal parameters (contact and flight times, step length and step frequency) were measured using the OptoGait system and step variability was considered for each parameter, in terms of within-participants standard deviation (SD) and coefficient of variation (CV%). Step variability was considered over six different durations at every velocity tested: 0–10 s, 0–20 s, 0–30 s, 0–60 s, 0–120 s and 0–180 s. The repeated measures ANOVA revealed no significant differences in the magnitude of the four spatiotemporal parameters between the recording intervals at each running velocity tested (p ≥ 0.05, ICC > 0.90). The post-hoc analysis confirmed no significant differences in step variability (SD and CV% of each spatiotemporal parameter at any velocity tested) between measurements. The Bland-Altman limits of agreement method showed that longer recording intervals yield smaller systematic bias, random errors, and narrower limits of agreement, regardless of running velocity. The results suggest that the duration of the recording period required to estimate spatiotemporal variability plays an important role in the accuracy of the measurement, regardless of running velocity (10–16 km/h).

Measurement of Left Ventricular Volumes and Ejection Fraction in Patients with Regional Wall Motion Abnormalities Using an Automated 3D Quantification Algorithm

Accurate and rapid left ventricular (LV) ejection fraction (EF) measurement is crucial for patients with wall motion abnormalities (WMAs). Conventional 2D echocardiographic imaging has limitations. The recently developed software HeartModel (HM, Philips Healthcare, Andover, MA, USA) has shown promise in automated 3D quantification. However, the accuracy and detailed features of HM in measurements of LV volume and EF in patients with regional WMAs have not been carefully investigated. In the present study, echocardiographic imaging (EPIQ, X5-1, Philips Healthcare) was performed in 72 patients with WMAs. The LV end-diastolic volume (EDV), end-systolic volume (ESV) and EF were measured by HM in three modes: without editing and with global and regional endocardial border editing (Auto 3D-NE, Auto 3D-GE and Auto 3D-RE, respectively). The conventional 2D Simpson's biplane method and manual 3D quantification (QLAB-3DQA software, Philips Healthcare), as the standard method, were used for comparison. Among the three HM modalities, Auto 3D-RE exhibited the best correlation with manual 3D in assessing EDV, ESV and EF (r = 0.88, 0.93 and 0.91, respectively), although it took slightly longer (67.3 ± 13.0 s). Auto 3D-RE also exhibited a small degree of bias for the measurements (EDV: 11.7mL, ESV: 8.45mL, EF: –1.57%) and narrow limits of agreement. Heterogeneity of LV wall motion was defined to indicate the dispersion degree of WMAs. It associated with the difference in EF measurement between Auto 3D-RE and manual 3D (p = 0.014, hazard ratio = 5.19). In patients with WMAs, HM with regional contour editing enables accurate and efficient evaluation of LV volume and EF.

Methods for data analysis of resting energy expenditure measured using indirect calorimetry.

The aim of this study was to test the accuracy of different methods of resting energy expenditure (REE) data analysis using indirect calorimetry (IC) during traditional (30 min) and abbreviated (10 min) protocols. Fifteen women and 15 men (21-34 y of age) completed two consecutive 30-min IC measurements. Body composition was measured using dual-energy x-ray absorptiometry. The reference method for REE analysis was 5 min in steady state (SS) during 30 min (first 5 min discarded). REE measurements were randomized to define a reference or testing method. An interval method was defined using 25, 20, and 15 min (with first 5, 10, and 15 min discarded, respectively), during 30 min, and 5 min (first 5 min discarded) during 10-min intervals. The SS method was defined using 5 min in SS (first 5 min discarded) during 30 min, 5, 4, and 3 min in SS during 10-min (first 5 min discarded) intervals. Interval methods during 30 min and SS and interval methods during 10 min demonstrated large bias with significantly high REEs compared to the reference method (78.8-109.0 kcal/d, all P < 0.001). Testing methods demonstrated large upper limits of agreement between 225.2 and 322.8 kcal/d. No mean differences (P > 0.05), small bias (14.3 kcal/d), and narrow limits of agreement (-125.8 to 154.4 kcal/d) were observed between 5-min SS during 30 min and the reference method. All interval methods and SS methods during 10 min overestimated REE. We recommend using 5-min SS during 30 min. The measurement may be repeated until all participants achieve SS.