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

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

Assessing the impact of nodule features and software algorithm on pulmonary nodule measurement uncertainty for nodules sized 20 mm or less.

Background: Measurements are not exact, so that if a measurement is repeated, one would get a different value each time. The spread of these values is the measurement uncertainty. Understanding measurement uncertainty of pulmonary nodules is important for proper interpretation of size and growth measurements. Larger amounts of measurement uncertainty may require longer follow-up intervals to be confident that any observed growth is due to actual growth rather than measurement uncertainty. We examined the influence of nodule features and software algorithm on measurement uncertainty of small, solid pulmonary nodules. Methods: Volumes of 107 nodules were measured on 4-6 repeated computed tomography (CT) scans (Siemens Somatom AS, 100 kVp, 120 mA, 1.0 mm slice thickness reconstruction) prospectively obtained during CT-guided fine needle aspiration biopsy between 2015-2021 at Department of Diagnostic, Molecular, and Interventional Radiology in Icahn School of Medicine at Mount Sinai, using two different automated volumetric algorithms. For each, the coefficient of variation (standard deviation divided by the mean) of nodule volume measurements was determined. The following features were considered: diameter, location, vessel and pleural attachments, nodule surface area, and extent of the nodule in the three acquisition dimensions of the scanner. Results: Median volume of 107 nodules was 515.23 and 535.53 mm3 for algorithm #1 and #2, respectively with excellent agreement (intraclass correlation coefficient =0.98). Median coefficient of variation of nodule volume was low for the two algorithms, but significantly different (4.6% vs. 8.7%, P<0.001). Both algorithms had a trend of decreasing coefficient of variation of nodule volume with increasing nodule diameter, though only significant for algorithm #2. Coefficient of variation of nodule volume was significantly associated with nodule volume (P=0.02), attachment to blood vessels (P=0.02), and nodule surface area (P=0.001) for algorithm #2 using a multiple linear regression model. Correlation between the coefficient of variation (CoV) of nodule volume and the CoV of the x, y, z measurements for algorithm #1 were 0.29 (P=0.0021), 0.25 (P=0.009), and 0.80 (P<0.001) respectively, and for algorithm #2, 0.46 (P<0.001), 0.52 (P<0.001), and 0.58 (P<0.001), respectively. Conclusions: Even in the best-case scenario represented in this study, using the same measurement algorithm, scanner, and scanning protocol, considerable measurement uncertainty exists in nodule volume measurement for nodules sized 20 mm or less. We found that measurement uncertainty was affected by interactions between nodule volume, algorithm, and shape complexity.

The variability in nociceptive flexion reflex threshold measurement is mostly caused by probabilistic effects of the estimation algorithms: a simulation study.

OBJECTIVES: The nociceptive flexion reflex (NFR) and its threshold are frequently used to investigate spinal nociception in humans. Since this threshold (NFRT) is a probabilistic measure, specific algorithms are used for NFRT estimation based on the stochastic occurrence of reflexes at different stimulus intensities. We used a validated simulation model of the NFR to investigate the amount of NFRT measurement variability induced by different estimation algorithms in a steady setting of reduced external influences. METHODS: We simulated the behavior of different estimation algorithms in subjects with an artificially steady baseline NFRT variability (standard deviation: 0 mA) or low baseline NFRT variability (standard deviation: 0.156 mA), equaling a quiet experimental setting. The obtained data were analyzed for NFRT measurement variability caused by the algorithms compared to the baseline variability reflecting other physiological influences. RESULTS: The standard deviation of the NFRT estimated by the different algorithms ranged between 0.381 and 3.464 mA with 96.8% to 99.6% of the measurement variability attributed to the algorithm used. Out of the investigated algorithms the dynamic staircase algorithm was most precise. CONCLUSION: The NFRT measurement variability observed during quiet and steady experimental sessions is mostly caused by the properties of the estimation algorithms, due to the probabilistic nature of the reflex occurrence. Our results give reference for choosing the optimal estimation algorithm to improve measurement precision.

Differences in nasalance scores obtained with different Nasometer headsets.

The goal of the present research study was to investigate possible differences in nasalance scores between different Nasometer headgears. Frequency response characteristics of microphone pairs in a Nasometer model 6200, a model 6450 and two model 6500 headsets were compared using long-term average spectra of white noise and multi-speaker babble signals. Prerecorded sound files from a male and a female speaker were used to record nasalance scores with the four Nasometer headsets and to calculate cumulative absolute differences within and between the headsets. The main outcome measures were the cumulative absolute differences between the decibel (dB) values in the frequency bins from 300 to 750 Hz for the nasal and oral channels of each microphone pair. Cumulative absolute differences between nasalance scores of repeated stimuli within and across Nasometer headsets were tabulated. Results showed that cumulative absolute differences for the frequency range 300-750 Hz were between 6.58 and 7.68 dB. Within headsets, 95.6% to 100% of measurements of all four Nasometer headsets were within 3 nasalance points, although test-retest differences of up to 6 nasalance points were found. Between headsets, 56.1% to 98.9% of measurements were within 3 nasalance points, with the single largest difference of 8 nasalance points. In conclusion, differences between repeated nasalance scores obtained with the same and different headsets were noted. Clinicians should allow a margin of error of ±6 to 8 nasalance points when interpreting scores from different Nasometer headsets.

Population data-based federated machine learning improves automated echocardiographic quantification of cardiac structure and function: the Automatisierte Vermessung der Echokardiographie project.

Aims: Machine-learning (ML)-based automated measurement of echocardiography images emerges as an option to reduce observer variability. The objective of the study is to improve the accuracy of a pre-existing automated reading tool ('original detector') by federated ML-based re-training. Methods and results: Automatisierte Vermessung der Echokardiographie was based on the echocardiography images of n = 4965 participants of the population-based Characteristics and Course of Heart Failure Stages A-B and Determinants of Progression Cohort Study. We implemented federated ML: echocardiography images were read by the Academic Core Lab Ultrasound-based Cardiovascular Imaging at the University Hospital Würzburg (UKW). A random algorithm selected 3226 participants for re-training of the original detector. According to data protection rules, the generation of ground truth and ML training cycles took place within the UKW network. Only non-personal training weights were exchanged with the external cooperation partner for the refinement of ML algorithms. Both the original detectors as the re-trained detector were then applied to the echocardiograms of n = 563 participants not used for training. With regard to the human referent, the re-trained detector revealed (i) superior accuracy when contrasted with the original detector's performance as it arrived at significantly smaller mean differences in all but one parameter, and a (ii) smaller absolute difference between measurements when compared with a group of different human observers. Conclusion: Population data-based ML in a federated ML set-up was feasible. The re-trained detector exhibited a much lower measurement variability than human readers. This gain in accuracy and precision strengthens the confidence in automated echocardiographic readings, which carries large potential for applications in various settings.

Sensitivity and Uncertainty Analysis of Micro-Flow Imaging for Sub-Visible Particle Measurements Using Artificial Neural Network.

PURPOSE: During biopharmaceutical drug manufacturing, storage, and distribution, proteins in both liquid and solid dosage forms go through various processes that could lead to protein aggregation. The extent of aggregation in the sub-micron range can be measured by analyzing a liquid or post-reconstituted powder sample using Micro-Flow Imaging (MFI) technique. MFI is widely used in biopharmaceutical industries due to its high sensitivity in detecting and analyzing particle size distribution. However, the MFI's sensitivity to various factors makes accurate measurement challenging. Therefore, in light of the inherent variability of the method, this work aims to explore the capabilities of an adopted coupled sensitivity analysis and machine learning algorithm to quantify the influencing factors on the formed sub-visible particles and method variability. METHODS: The proposed algorithm consists of two interconnected components, namely a surrogate model with a neural network and a sensitivity analyzer. A machine learning tool based on artificial neural networks (ANN) is constructed with MFI data. The best fit with an optimized configuration is found. Sensitivity and uncertainty analysis is performed using this network as the surrogate model to understand the impacts of input parameters on MFI data. RESULTS: Results reveal the most impactful reconstitution preparation factors and others that are masked by the instrument variabilities. It is shown that instrument inaccuracy is a function of size category, with higher variabilities associated with larger size ranges. CONCLUSION: Utilizing this tool while assessing the sensitivity of outputs to various parameters, measurement variabilities for analytical characterization tests can be quantified.

Why the majority of on-site repeat donor deferrals are completely unwarranted .

BACKGROUND: On-site deferral for low hemoglobin (Hb) is common in most countries and deferral rates commonly vary between 1% and 20%. Blood banks continuously strive to reduce deferral rates as these imply an immediate loss of products, a waste of materials, a waste of staff and donor time, and potential loss of donors. Despite many efforts, the main cause of donor deferral-the variability in hemoglobin measurement outcomes-remains largely unaddressed. STUDY DESIGN AND METHODS: Repeated hemoglobin measurements obtained at donor intake were used to estimate the variability in measurement outcomes (measurement variability). This information is incorporated in a new algorithm for donor deferral where the mean hemoglobin level of a donor is used to determine both donor eligibility and the deviance of individual measurement outcomes. The algorithm was tested on a cohort of new Dutch donors that started between 2012 and 2022 to evaluate its impact on the donor deferral rate. RESULTS: Historical data from 439,376 new donors with a deferral rate of 5.3% were analyzed by applying the new donor deferral algorithm. It was found that 92% of all deferrals were unnecessary as Hb levels were within the range of expected measurement variability. Contrarily, it appeared that 460 donors (0.10%) made 704 donations (0.06%) whilst not complying with donor eligibility criteria. DISCUSSION: Not accounting for measurement variability can be shown to not only result in unnecessary on-site deferrals but also results in donations by donors that can be shown not to comply with the legally required minimum Hb levels.

Measuring the margin distance in pulmonary wedge resection.

BACKGROUND: Margin distance contributes to survival and recurrence during wedge resections for early-stage non-small cell lung cancer. The Initiative for Early Lung Cancer Research on Treatment sought to standardize a surgeon-measured margin intraoperatively. METHODS: Lung cancer patients who underwent wedge resection were reviewed. Margins were measured by the surgeon twice as per a standardized protocol. Intraobserver variability as well as surgeon-pathologist variability were compared. RESULTS: Forty-five patients underwent wedge resection. Same-surgeon measurement analysis indicated good reliability with a small mean difference and narrow limit of agreement for the two measures. The median surgeon-measured margin was 18.0 mm, median pathologist-measured margin was 16.0 mm and the median difference between the surgeon-pathologist margin was -1.0 mm, ranging from -18.0 to 12.0 mm. Bland-Altman analysis for margin measurements demonstrated a mean difference of 0.65 mm. The limit of agreement for the two approaches were wide, with the difference lying between -16.25 and 14.96 mm. CONCLUSIONS: A novel protocol of surgeon-measured margin was evaluated and compared with pathologist-measured margin. High intraobserver agreement for repeat surgeon measurements yet low-to-moderate correlation or directionality between surgeon and pathologic measurements were found. DISCUSSION: A standardized protocol may reduce variability in pathologic assessment. These findings have critical implications considering the impact of margin distance on outcomes.

Quantification and reduction of cross-vendor variation in multicenter DWI MR imaging: results of the Cancer Core Europe imaging task force.

OBJECTIVES: In the Cancer Core Europe Consortium (CCE), standardized biomarkers are required for therapy monitoring oncologic multicenter clinical trials. Multiparametric functional MRI and particularly diffusion-weighted MRI offer evident advantages for noninvasive characterization of tumor viability compared to CT and RECIST. A quantification of the inter- and intraindividual variation occurring in this setting using different hardware is missing. In this study, the MRI protocol including DWI was standardized and the residual variability of measurement parameters quantified. METHODS: Phantom and volunteer measurements (single-shot T2w and DW-EPI) were performed at the seven CCE sites using the MR hardware produced by three different vendors. Repeated measurements were performed at the sites and across the sites including a traveling volunteer, comparing qualitative and quantitative ROI-based results including an explorative radiomics analysis. RESULTS: For DWI/ADC phantom measurements using a central post-processing algorithm, the maximum deviation could be decreased to 2%. However, there is no significant difference compared to a decentralized ADC value calculation at the respective MRI devices. In volunteers, the measurement variation in 2 repeated scans did not exceed 11% for ADC and is below 20% for single-shot T2w in systematic liver ROIs. The measurement variation between sites amounted to 20% for ADC and < 25% for single-shot T2w. Explorative radiomics classification experiments yield better results for ADC than for single-shot T2w. CONCLUSION: Harmonization of MR acquisition and post-processing parameters results in acceptable standard deviations for MR/DW imaging. MRI could be the tool in oncologic multicenter trials to overcome the limitations of RECIST-based response evaluation. KEY POINTS: • Harmonizing acquisition parameters and post-processing homogenization, standardized protocols result in acceptable standard deviations for multicenter MR-DWI studies. • Total measurement variation does not to exceed 11% for ADC in repeated measurements in repeated MR acquisitions, and below 20% for an identical volunteer travelling between sites. • Radiomic classification experiments were able to identify stable features allowing for reliable discrimination of different physiological tissue samples, even when using heterogeneous imaging data.

Understanding and managing uncertainty and variability for wastewater monitoring beyond the pandemic: Lessons learned from the United Kingdom national COVID-19 surveillance programmes.

The COVID-19 pandemic has put unprecedented pressure on public health resources around the world. From adversity, opportunities have arisen to measure the state and dynamics of human disease at a scale not seen before. In the United Kingdom, the evidence that wastewater could be used to monitor the SARS-CoV-2 virus prompted the development of National wastewater surveillance programmes. The scale and pace of this work has proven to be unique in monitoring of virus dynamics at a national level, demonstrating the importance of wastewater-based epidemiology (WBE) for public health protection. Beyond COVID-19, it can provide additional value for monitoring and informing on a range of biological and chemical markers of human health. A discussion of measurement uncertainty associated with surveillance of wastewater, focusing on lessons-learned from the UK programmes monitoring COVID-19 is presented, showing that sources of uncertainty impacting measurement quality and interpretation of data for public health decision-making, are varied and complex. While some factors remain poorly understood, we present approaches taken by the UK programmes to manage and mitigate the more tractable sources of uncertainty. This work provides a platform to integrate uncertainty management into WBE activities as part of global One Health initiatives beyond the pandemic.

A critical review of the literature on comfort of hearing protection devices: analysis of the comfort measurement variability.

Objective. This article proposes a comprehensive literature review of past works addressing hearing protection device (HPD) comfort with the aim of identifying the main sources of variability in comfort evaluation. Methods. A literature review of study samples was performed: documents were hand searched and Internet searched using PubMed, Web of Science, Google Scholar, ProQuest Dissertations and Theses Professional, Scopus or Google search engines. While comfort constructs and measurement methods are reviewed for both earplugs and earmuff HPD types, results and analyses are provided for earplugs only. Results. The literature shows that the multiple sources of the perceived comfort measurement variability are related to the complexity of the concept of comfort and to the various physical and psychosocial characteristics of the triad 'environment/person/earplug', which differ from one study to the other. Conclusions. Considering the current state of knowledge and in order to decrease comfort measurements variability, it is advised to: (a) use a multidimensional construct of comfort and derive a comfort index for each comfort dimension;, (b) use exhaustive and valid questionnaires; (c) quantify as many triad characteristics as possible and use them as independent or control variables; (d) assess the quality of the earplug fitting and the attenuation efficiency.

Carotid Doppler Measurement Variability in Functional Hemodynamic Monitoring: An Analysis of 17,822 Cardiac Cycles.

Carotid Doppler ultrasound is used as a measure of fluid responsiveness, however, assessing change with statistical confidence requires an adequate beat sample size. The coefficient of variation helps quantify the number of cardiac cycles needed to adequately detect change during functional hemodynamic monitoring. DESIGN: Prospective, observational, human model of hemorrhage and resuscitation. SETTING: Human physiology laboratory at Mayo Clinic. SUBJECTS: Healthy volunteers. INTERVENTIONS: Lower body negative pressure. MEASUREMENTS AND MAIN RESULTS: We measured the coefficient of variation of the carotid artery velocity time integral and corrected flow time during significant cardiac preload changes. Seventeen-thousand eight-hundred twenty-two cardiac cycles were analyzed. The median coefficient of variation of the carotid velocity time integral was 8.7% at baseline and 11.9% during lowest-tolerated lower body negative pressure stage. These values were 3.6% and 4.6%, respectively, for the corrected flow time. CONCLUSIONS: The median coefficient of variation values measured in this large dataset indicates that at least 6 cardiac cycles should be averaged before and after an intervention when using the carotid artery as a functional hemodynamic measure.

Comparison of Dialysis Unit and Home Blood Pressures: An Observational Cohort Study.

RATIONALE & OBJECTIVE: Prior studies of patients receiving maintenance hemodialysis have shown that, on average, blood pressure (BP) measured predialysis is higher than BP measured at home. We hypothesized that a subset of hemodialysis patients has BP that is higher when measured at home than when measured predialysis and this subgroup of patients has a higher prevalence of left ventricular hypertrophy. STUDY DESIGN: Prospective cohort. SETTING & PARTICIPANTS: 97 hypertensive hemodialysis patients enrolled in the Blood Pressure in Dialysis Study (BID), a randomized trial of comparing target predialysis BP ≤140/90 to 155-165/90 mm Hg. EXPOSURE: Differences between predialysis and next-day home systolic BP measured ≥6 times over 1 year. OUTCOME: Left ventricular mass index (LVMI) by cardiac magnetic resonance imaging. ANALYTICAL APPROACH: A hierarchical clustering analysis divided patients into 3 clusters based on the average and variability of differences in systolic predialysis and home BP. Clusters were compared with respect to clinical factors and LVMI. RESULTS: Mean differences between predialysis and home systolic BP were 19.1 (95% CI, 17.0 to 21.1) mm Hg for cluster 1 ("home lower"), 3.7 (95% CI, 1.6 to 5.8) mm Hg for cluster 2 ("home and predialysis similar"), and -9.7 (95% CI, -12.0 to -7.4) mm Hg for cluster 3 ("home higher"). Systolic BP declined during dialysis in clusters 1 and 2 but increased in cluster 3. Interdialytic weight gains did not differ. After adjusting for sex and treatment arm, LVMI was higher in cluster 3 than in clusters 1 and 2: differences in means of 10.6 ± 4.96 (SE) g/m2 (P = 0.04) and 12.0 ± 5.08 g/m2 (P = 0.02), respectively. LIMITATIONS: Limited statistical power. CONCLUSIONS: Nearly one-third of participants had home BPs higher than predialysis BPs. These patients had LVMI higher than those with similar or lower BPs at home, indicating that their BP may have been undertreated.

Exploring the Interobserver Agreement in Computer-Aided Radiologic Tumor Measurement and Evaluation of Tumor Response.

The accurate, objective, and reproducible evaluation of tumor response to therapy is indispensable in clinical trials. This study aimed at investigating the reliability and reproducibility of a computer-aided contouring (CAC) tool in tumor measurements and its impact on evaluation of tumor response in terms of RECIST 1.1 criteria. A total of 200 cancer patients were retrospectively collected in this study, which were randomly divided into two sets of 100 patients for experiential learning and testing. A total of 744 target lesions were identified by a senior radiologist in distinctive body parts, of which 278 lesions were in data set 1 (learning set) and 466 lesions were in data set 2 (testing set). Five image analysts were respectively instructed to measure lesion diameter using manual and CAC tools in data set 1 and subsequently tested in data set 2. The interobserver variability of tumor measurements was validated by using the coefficient of variance (CV), the Pearson correlation coefficient (PCC), and the interobserver correlation coefficient (ICC). We verified that the mean CV of manual measurement remained constant between the learning and testing data sets (0.33 vs. 0.32, p = 0.490), whereas it decreased for the CAC measurements after learning (0.24 vs. 0.19, p < 0.001). The interobserver measurements with good agreement (CV < 0.20) were 29.9% (manual) vs. 49.0% (CAC) in the learning set (p < 0.001) and 30.9% (manual) vs. 64.4% (CAC) in the testing set (p < 0.001). The mean PCCs were 0.56 ± 0.11 mm (manual) vs. 0.69 ± 0.10 mm (CAC) in the learning set (p = 0.013) and 0.73 ± 0.07 mm (manual) vs. 0.84 ± 0.03 mm (CAC) in the testing set (p < 0.001). ICCs were 0.633 (manual) vs. 0.698 (CAC) in the learning set (p < 0.001) and 0.716 (manual) vs. 0.824 (CAC) in the testing set (p < 0.001). The Fleiss' kappa analysis revealed that the overall agreement was 58.7% (manual) vs. 58.9% (CAC) in the learning set and 62.9% (manual) vs. 74.5% (CAC) in the testing set. The 80% agreement of tumor response evaluation was 55.0% (manual) vs. 66.0% in the learning set and 60.6% (manual) vs. 79.7% (CAC) in the testing set. In conclusion, CAC can reduce the interobserver variability of radiological tumor measurements and thus improve the agreement of imaging evaluation of tumor response.

Variability of glenohumeral positioning and bone-to-tendon marker length measurements in repaired rotator cuffs from longitudinal computed tomographic imaging.

BACKGROUND: To address the need for more objective and quantitative measures of tendon healing in research studies, we intend to use computed tomography (CT) with implanted radiopaque markers on the repaired tendon to measure tendon retraction following rotator cuff repair. In our small prior study, retraction at 1-year follow-up averaged 16.1± 5.3 mm and exceeded 10.0 mm in 12 of 13 patients, and thus tendon retraction appears to be a common clinical phenomenon. This study's objectives were to assess, using 5 longitudinal CT scans obtained over 1 year following rotator cuff repair, the variability in glenohumeral positioning because of pragmatic variations in achieving perfect arm repositioning and to estimate the associated measurement variability in bone-to-tendon marker length measurements. METHODS: Forty-eight patients underwent rotator cuff repair with intraoperative placement of radiopaque tendon markers at the repair site. All patients had a CT scan with their arms at the side on the day of surgery and at 3, 12, 26, and 52 weeks postoperatively. Glenohumeral position (defined by the orientation and distance of the humerus with respect to the scapula) and bone-to-tendon marker lengths were measured from each scan. Within-patient variation in glenohumeral position measurements was described by their pooled within-patient standard deviations (SDs), and variation in bone-to-tendon marker lengths by their standard errors of measurement (SEMs) and 95% confidence level minimally detectable distances (MDD95) and changes (MDC95). RESULTS: The mean glenohumeral orientation from the 5 longitudinal CT scans averaged across the 48 patients was 12.6° abduction, 0.4° flexion, and -0.1° internal rotation. Within-patient SDs (95% confidence intervals) of glenohumeral orientation were 3.0° (2.7°-3.4°) in extension/flexion, 5.2° (4.6°-5.8°) in abduction/adduction, and 8.2° (7.3°-9.2°) in internal/external rotation. The SDs of glenohumeral distances were less than 1 mm in any direction. The estimated SEMs of bone-to-tendon lengths were consistent with a common value of 2.4 mm for any of the tendon markers placed across the repair, with MDD95 of 4.7 mm and MDC95 of 6.7 mm. CONCLUSION: Apparent tendon retraction of 5 mm or more, when measured as the distance from a tendon marker's day of surgery location to its new location on a volumetrically registered longitudinal CT scan, may be considered above the usual range of measurement variation. Tendon retraction measured using implanted radiopaque tendon markers offers an objective and sufficiently reliable means for quantifying the commonly expected changes in structural healing following rotator cuff repair.

Evaluation of the smartphone for measurement of femoral rotational deformity.

BACKGROUND: A novel measurement technique has been designed to assess femoral rotation deformation. The purpose of this study was to evaluate smartphone-aided measurement, including measurement software, intra-observer differences and the occurrence frequency of the unacceptable outliers. METHODS: Five positions (intact bone, external and internal rotations of 20° and 40° of the distal blocks after dividing the femoral shafts using a saw) were used in each of the five artificial femora. Guide wires were separately inserted into the proximal and distal ends of the model femora with a navigation system and the intersection angles between the guide wires were measured with a smartphone. The values obtained by two measurement software packages (Smart Tools and Super Swiss Army Knife) were compared with that measured on the overlapped computed tomography images. RESULTS: There were no significant differences between the intersection angles measured by smartphone and that measured on the overlapped images (P = 0.24). The mean absolute difference between pairs of measurements of the two software packages for all guide wire angles was 2.33 ± 2.34°, without statistically significant difference (P = 0.33). There was a significant correlation (r = 0.99) between the first and second (1 week apart) measurements with the same measurement tool. The values of offset capability index of the Smart Tools and the Super Swiss Army Knife measurement tools were 1.62 and 1.13, respectively. CONCLUSION: Smartphone-aided measurement technique could reliably assess femoral rotation deformation with more accurate angle measurement for software with zero calibration function.

Within- and Between-Body-Site Agreement of Skin Autofluorescence Measurements in People With and Without Diabetes-Related Foot Disease.

BACKGROUND: Skin autofluorescence has been used to assess longer term glycemic control and risk of complications. There is however no agreed site at which autofluorescence should be measured. This study evaluated the within- and between-site agreement in measurement of skin autofluorescence using a noninvasive advanced glycation end product (AGE) reader. METHODS: Overall, 132 participants were included: 16 with diabetes-related foot ulcers (DFU), 63 with diabetes but without foot ulcers (DMC), 53 without diabetes or foot ulcers (HC). Skin autofluorescence was measured using the AGE Reader (DiagnOptics technologies BV, the Netherlands). Three consecutive skin autofluorescence measurements were each performed at six different body sites: the volar surfaces of both forearms (arms), dorsal surfaces of both calves (legs), and plantar surfaces of both feet (feet). Within- and between-site agreements were analyzed with concordance correlation coefficients (CCC) and 95% confidence intervals (95% CI), absolute mean differences (±standard deviation), and Bland-Altman limits of agreement. RESULTS: The agreement between repeat assessments at the same site was almost perfect (CCC [95% CI] ranging from 0.94 [0.91-0.96] for assessments in the right foot to 0.99 [0.99-0.99] for assessments in the left arm). The limits of agreement were narrow within ±0.5 arbitrary units for all sites. The between-site agreement in measurements was poor (CCC < 0.65) with large maximum absolute mean differences (±SD) in arbitrary units (DFU = 3.40 [±2.04]; DMC = 3.15 [±2.45]; HC = 2.72 [±1.83]) and wide limits of agreement. CONCLUSIONS: Skin autofluorescence measurements can be repeated at the same site with adequate repeatability but measurements at different sites in the same patient have marked differences. The reason for this variation across sites and whether this has any role in diabetes-related complications needs further investigation.

Development of an algorithm for evaluating the impact of measurement variability on response categorization in oncology trials.

BACKGROUND: Radiologic assessments of baseline and post-treatment tumor burden are subject to measurement variability, but the impact of this variability on the objective response rate (ORR) and progression rate in specific trials has been unpredictable on a practical level. In this study, we aimed to develop an algorithm for evaluating the quantitative impact of measurement variability on the ORR and progression rate. METHODS: First, we devised a hierarchical model for estimating the distribution of measurement variability using a clinical trial dataset of computed tomography scans. Next, a simulation method was used to calculate the probability representing the effect of measurement errors on categorical diagnoses in various scenarios using the estimated distribution. Based on the probabilities derived from the simulation, we developed an algorithm to evaluate the reliability of an ORR (or progression rate) (i.e., the variation in the assessed rate) by generating a 95% central range of ORR (or progression rate) results if a reassessment was performed. Finally, we performed validation using an external dataset. In the validation of the estimated distribution of measurement variability, the coverage level was calculated as the proportion of the 95% central ranges of hypothetical second readings that covered the actual burden sizes. In the validation of the evaluation algorithm, for 100 resampled datasets, the coverage level was calculated as the proportion of the 95% central ranges of ORR results that covered the ORR from a real second assessment. RESULTS: We built a web tool for implementing the algorithm (publicly available at http://studyanalysis2017.pythonanywhere.com/ ). In the validation of the estimated distribution and the algorithm, the coverage levels were 93 and 100%, respectively. CONCLUSIONS: The validation exercise using an external dataset demonstrated the adequacy of the statistical model and the utility of the developed algorithm. Quantification of variation in the ORR and progression rate due to potential measurement variability is essential and will help inform decisions made on the basis of trial data.

Systematic analysis of measurement variability in lung cancer with multidetector computed tomography.

OBJECTIVE: To systematically analyze the nature of measurement variability in lung cancer with multidetector computed tomography (CT) scans. METHODS: Multidetector CT scans of 67 lung cancer patients were analyzed. Unidimensional (Response Evaluation Criteria in Solid Tumor criteria), bidimensional (World Health Organization criteria), and volumetric measurements were performed independently by ten radiologists and were repeated after at least 5 months. Repeatability and reproducibility measurement variations were estimated by analyzing reliability, agreement, variation coefficient, and misclassification statistically. The relationship of measurement variability with various sources was also analyzed. RESULTS: Analyses of 69 lung tumors with an average size of 1.1-12.1 cm (mean 4.3 cm) indicated that volumetric technique had the minimum measurement variability compared to the unidimensional or bidimensional technique. Tumor characteristics (object effect) could be the primary factor to influence measurement variability while the effect of raters (subjective effect) was faint. Segmentation and size in tumor characteristics were associated with measurement variability, and some mathematical function was established between the volumetric variability and tumor size. CONCLUSION: Volumetric technique has the minimum variability in measuring lung cancer, and measurement variability is associated with tumor size by nonlinear mathematical function.

Quantifying Variability in Longitudinal Peripapillary RNFL and Choroidal Layer Thickness Using Surface Based Registration of OCT Images.

PURPOSE: To assess within-subject variability of retinal nerve fiber layer (RNFL) and choroidal layer thickness in longitudinal repeat optical coherence tomography (OCT) images with point-to-point measurement comparison made using nonrigid surface registration. METHODS: Nine repeat peripapillary OCT images were acquired over 3 weeks from 12 eyes of 6 young, healthy subjects using a 1060-nm prototype swept-source device. The RNFL, choroid and the Bruch's membrane opening (BMO) were segmented, and point-wise layer thicknesses and BMO dimensions were measured. For each eye, the layer surfaces of eight follow-up images were registered to those of the baseline image, first by rigid alignment using blood vessel projections and axial height and tilt correction, followed by nonrigid registration of currents-based diffeomorphisms algorithms. This mapped all follow-up measurements point-wise to the common baseline coordinate system, allowing for point-wise statistical analysis. Measurement variability was evaluated point-wise for layer thicknesses and BMO dimensions by time-standard deviation (tSD). RESULTS: The intraclass correlation coefficients (ICCs) of BMO area and eccentricity were 0.993 and 0.972, respectively. Time-mean and tSD were computed point-wise for RNFL and choroidal thickness and color-mapped on the baseline surfaces. tSD was less than two coherence lengths of the system 2ℓ = 12 µm at most vertices. High RNFL thickness variability corresponded to the locations of retinal vessels, and choroidal thickness varied more than RNFL thickness. CONCLUSIONS: Our registration-based end-to-end pipeline produced point-wise correspondence among time-series retinal and choroidal surfaces with high measurement repeatability (low variability). Blood vessels were found to be the main sources contributing to the normal variability of the RNFL thickness measure. The computational pipeline with a measurement of normal variability can be used in future longitudinal studies to identify changes that are above the threshold of normal point-wise variability and track localized changes in retinal layers in high spatial resolution. TRANSLATIONAL RELEVANCE: Using the registration-based approach presented in this study, longitudinal changes in retinal and choroidal layers can be detected with higher sensitivity and spatial precision.