Evaluation of automatic cochlear dimension measurement using ALPACA: a comparative study.

BACKGROUND: Cochlear dimension measurements are critical in diagnosing and managing congenital sensorineural hearing loss. OBJECTIVES: To evaluate the feasibility and reliability of an automated landmark approach for measuring cochlear dimensions (A-, B- and H-values). MATERIAL AND METHODS: Cochlear parameters from 100 patients were measured by MPR, manual three-dimensional and ALPACA. We assessed intra- and inter-observer reliability as well as inter-method reliability. Statistical analyses were conducted to detect differences between the right and left ears, as well as to assess the relevance of the values obtained using ALPACA. RESULTS: All A-, B-, and H-values measured by the various methods showed a high intra-observer reliability with intra-class correlation coefficients (ICC) ranging from 0.70 to 0.99, and values gained by ALPACA reaching the highest ICC. Inter-method reliability was at a good level with ICC ranging from 0.51 to 0.86. There were no significant differences between the right and left ears' measured values. Obvious positive correlations existed among cochlear dimensions measured by ALPACA. CONCLUSIONS AND SIGNIFICANCE: The ALPACA method can be used to measure cochlear dimensions. Values obtained by the method demonstrate high reliability and consistency with a significant reduction in intra-observer variability compared to results from conventional MPR and manual 3D measurements.

A hybrid approach to sample size re-estimation in cluster randomized trials with continuous outcomes.

This study presents a hybrid (Bayesian-frequentist) approach to sample size re-estimation (SSRE) for cluster randomised trials with continuous outcome data, allowing for uncertainty in the intra-cluster correlation (ICC). In the hybrid framework, pre-trial knowledge about the ICC is captured by placing a Truncated Normal prior on it, which is then updated at an interim analysis using the study data, and used in expected power control. On average, both the hybrid and frequentist approaches mitigate against the implications of misspecifying the ICC at the trial's design stage. In addition, both frameworks lead to SSRE designs with approximate control of the type I error-rate at the desired level. It is clearly demonstrated how the hybrid approach is able to reduce the high variability in the re-estimated sample size observed within the frequentist framework, based on the informativeness of the prior. However, misspecification of a highly informative prior can cause significant power loss. In conclusion, a hybrid approach could offer advantages to cluster randomised trials using SSRE. Specifically, when there is available data or expert opinion to help guide the choice of prior for the ICC, the hybrid approach can reduce the variance of the re-estimated required sample size compared to a frequentist approach. As SSRE is unlikely to be employed when there is substantial amounts of such data available (ie, when a constructed prior is highly informative), the greatest utility of a hybrid approach to SSRE likely lies when there is low-quality evidence available to guide the choice of prior.

Partitioning variance in cortical morphometry into genetic, environmental, and subject-specific components.

The relative contributions of genetic variation and experience in shaping the morphology of the adolescent brain are not fully understood. Using longitudinal data from 11,665 subjects in the ABCD Study, we fit vertex-wise variance components including family effects, genetic effects, and subject-level effects using a computationally efficient framework. Variance in cortical thickness and surface area is largely attributable to genetic influence, whereas sulcal depth is primarily explained by subject-level effects. Our results identify areas with heterogeneous distributions of heritability estimates that have not been seen in previous work using data from cortical regions. We discuss the biological importance of subject-specific variance and its implications for environmental influences on cortical development and maturation.

Reliability and validity of the Japanese version of the Overwork Climate Scale.

This study aimed to investigate the validity and reliability of the Japanese version of the Overwork Climate Scale. Japanese workers were invited to participate in online surveys at baseline and 1-month follow-up. The Overwork Climate Scale was translated into Japanese, according to international guidelines. Reliability was assessed using Cronbach's alpha and the intra-class correlation coefficient (ICC), while structural validity was evaluated through confirmatory factor analysis (CFA). Psychological job demands, work engagement, psychological safety, and workaholism were assessed for convergent validity. The number of respondents was 302 at baseline and 169 at follow-up. Results indicated robust Cronbach's alpha values of 0.86 (for overwork endorsement) and 0.80 (for lacking overwork reward) at baseline, complemented by ICC of 0.89 and 0.82, respectively. CFA confirmed the suitability of the two-factor model. Moreover, the Japanese Overwork Climate Scale exhibited significant correlations with anticipated constructs. Structural equation modeling revealed a consistent association between overwork climate and both workaholism and work engagement, similar to the original version. In conclusion, the Japanese version of the Overwork Climate Scale demonstrates acceptable levels of reliability and validity, warranting its potential adoption among Japanese workers.

Survival among children under-five in India: a parametric multilevel survival approach.

BACKGROUND: Many studies have been conducted on under-five mortality in India and most of them focused on the associations between individual-level factors and under-five mortality risks. On the contrary, only a scarce number of literatures talked about contextual level effect on under-five mortality. Hence, it is very important to have thorough study of under-five mortality at various levels. This can be done by applying multilevel analysis, a method that assesses both fixed and random effects in a single model. The multilevel analysis allows extracting the influence of individual and community characteristics on under-five mortality. Hence, this study would contribute substantially in understanding the under-five mortality from a different perspective. METHOD: The study used data from the Demographic and Health Survey (DHS) acquired in India, i.e., the fourth round of National Family and Health Survey (2015-16). It is a nationally representative repeated cross-sectional data. Multilevel Parametric Survival Model (MPSM) was employed to assess the influence of contextual correlates on the outcome. The assumption behind this study is that 'individuals' (i.e., level-1) are nested within 'districts' (i.e., level-2), and districts are enclosed within 'states' (i.e., level-3). This suggests that people have varying health conditions, residing in dissimilar communities with different characteristics. RESULTS: Highest under-five mortality i.e., 3.85% are happening among those women whose birth interval is less than two years. In case of parity, around 4% under-five mortality is among women with Third and above order parity. Further, findings from the full model is that ICC values of 1.17 and 0.65% are the correlation of the likelihood of having under-five mortality risk among people residing in the state and district communities, respectively. Besides, the risk of dying was increased alarmingly in the first year of life and slowly to aged 3 years and then it remains steady. CONCLUSION: This study has revealed that both aspects viz. individual and contextual effect of the community are necessary to address the importance variations in under-five mortality in India. In order to ensure substantial reduction in under-five mortality, findings of the study support some policy initiatives that involves the need to think beyond individual level effects and considering contextual characteristics.

Characterization of nickel levels considering seasonal and intra-individual variation using three biological matrices.

Nickel compounds are classified as group 1 carcinogens by the International Agency for Research on Cancer. However, only a few exposure assessment studies have been conducted on such compounds to date. In this study, we investigated the distribution of nickel in three biological types of samples (blood, serum, and urine) and its temporal variability through repeated measurements. From 2020 to 2021, blood and urine samples were collected for four times from 50 healthy participants. Nickel concentrations were determined using inductively coupled plasma mass spectrometry, and inter-individual correlation was calculated from linear mixed model. The overall geometric mean of nickel was 1.028 µg/L in blood, 0.687 µg/L in serum, and 1.464 µg/L in urine. Blood nickel was the highest in November (blood: 1.197 µg/L), and the geometric mean of nickel concentrations in the serum and urine were the highest in March (serum: 1.146 µg/L; urine: 1.893 µg/L). This matched seasonal trends for fine particulate matter concentrations from 2020 to 2021. Thus, seasonal effects significantly affect nickel levels in blood, serum, and urine. The inter-individual correlations were low as 0.081 for blood and 0.064 for urine. In addition, the correlation of nickel levels between each biological sample was low. It was also found that age, gender, commuting time, and different matrices affect concentrations. Blood and serum nickel levels were high in this study compared to other nationwide data, with urinary nickel ranking the second highest among the six countries examined. Therefore, biomonitoring study in the general population should be conducted, and finding a suitable matrix that can reflect nickel exposure to set exposure guideline levels is imperative.

Correlational analyses of biomarkers that are harmonized through a bridging study due to measurement errors.

Evaluating correlations between disease biomarkers and clinical outcomes is crucial in biomedical research. During the early stages of many chronic diseases, changes in biomarkers and clinical outcomes are often subtle. A major challenge to detecting subtle correlations is that studies with large sample sizes are usually needed to achieve sufficient statistical power. This challenge is even greater when biofluid and imaging biomarker data are used because the required procedures are burdensome, perceived as invasive, and/or expensive, limiting sample sizes in individual studies. Combining data across multiple studies may increase statistical power, but biomarker data may be generated using different assay platforms, scanner types, or processing protocols, which may affect measured biomarker values. Therefore, harmonizing biomarker data is essential to combining data across studies. Bridging studies involve re-processing of a subset of samples or imaging scans to evaluate how biomarker values vary by studies. This presents an analytic challenge on how to best harmonize biomarker data across studies to allow unbiased and optimal estimates of their correlations with standardized clinical outcomes. We conceptualize that a latent biomarker underlies the observed biomarkers across studies, and propose a novel approach that integrates the data in the bridging study with the study-specific biomarker data for estimating the biological correlations between biomarkers and clinical outcomes. Through extensive simulations, we compare our method to several alternative methods/algorithms often used to estimate the correlations. Finally, we demonstrate the application of this methodology to a real-world multi-center Alzheimer's disease biomarker study to correlate cerebrospinal fluid biomarker concentrations with cognitive outcomes.

Characterizing the spatiotemporal features of functional connectivity across the white matter and gray matter during the naturalistic condition.

Introduction: The naturalistic stimuli due to its ease of operability has attracted many researchers in recent years. However, the influence of the naturalistic stimuli for whole-brain functions compared with the resting state is still unclear. Methods: In this study, we clustered gray matter (GM) and white matter (WM) masks both at the ROI- and network-levels. Functional connectivity (FC) and inter-subject functional connectivity (ISFC) were calculated in GM, WM, and between GM and WM under the movie-watching and the resting-state conditions. Furthermore, intra-class correlation coefficients (ICC) of FC and ISFC were estimated on different runs of fMRI data to denote the reliability of them during the two conditions. In addition, static and dynamic connectivity indices were calculated with Pearson correlation coefficient to demonstrate the associations between the movie-watching and the resting-state. Results: As the results, we found that the movie-watching significantly affected FC in whole-brain compared with the resting-state, but ISFC did not show significant connectivity induced by the naturalistic condition. ICC of FC and ISFC was generally higher during movie-watching compared with the resting-state, demonstrating that naturalistic stimuli could promote the reliability of connectivity. The associations between static and dynamic ISFC were weakly negative correlations in the naturalistic stimuli while there is no correlation between them under resting-state condition. Discussion: Our findings confirmed that compared to resting-state condition, the connectivity indices under the naturalistic stimuli were more reliable and stable to investigate the normal functional activities of the human brain, and might promote the applications of FC in the cerebral dysfunction in various mental disorders.

Validation of the Cantonese version of the Traditional Chinese Medicine (TCM) Body constitution Questionnaire in elderly people.

BACKGROUND: The Traditional Chinese Medicine (TCM) Body Constitution Questionnaire (For Elderly People) (TCMECQ) is a patient-reported outcome questionnaire developed in Mandarin in 2013 to differentiate the body constitutions of the elderly aged 65 and above. Considering the cultural and linguistic differences between Mainland China and Hong Kong (HK) Special Administrative Region, the TCMECQ was translated into Cantonese following "back translation" policy and validated in proper process. METHODS: Ten Chinese Medicine Practitioners (CMPs) and 30 senior citizens aged 65 or above were recruited to evaluate the first version of the Traditional Chinese Medicine Body Constitution Questionnaire (For Elderly People) (Cantonese version) (TCMECQ-C). Based on their comments, the second version was developed and discussed in the panel meeting to form the third version, validated the third version on 270 recruited seniors. Based on the validation results, a panel of 5 experts finalized the Questionnaire as the final version. The TCMECQ-C developers finalized the Questionnaire as the validated endorsed third version (i.e. final version). RESULTS: The item-level content validity index of most items of the TCMECQ-C (First Version) were ranging from 0.80 to 1.00 in terms of clarity, relevance and appropriateness. Factor loadings of Qi-deficiency Constitution ranging from 0.37 to 0.71, Yang-deficiency Constitution ranging from 0.36 to 0.65, Yin-deficiency Constitution ranging from 0.36 to 0.65, and Stagnant Qi Constitution ranging from 0.68 to 0.82. The chi-squared degree-of-freedom ratio was 2.13 (928.63/436), Goodness-of-Fit Index (0.83), Adjusted Goodness-of-Fit Index (0.79), Normed Fit Index (0.66), Comparative Fit Index (0.78), Incremental Fit Index (0.78), Relative Fit Index (0.61) and Tucker-Lewis Index (0.75), and Root Mean Square Error of Approximation (0.07) and Standardized Root Mean Square Residual (0.07), implied acceptable Confirmatory Factor Analysis model fit of the overall scale. A Pearson correlation coefficient (r) showed the sufficient convergent validity for excessive subscales (Phlegm-dampness Constitution and Dampness-heat Constitution with r = 0.35, p < 0.01). Cronbach's alpha coefficient ranged from 0.56 to 0.89, including Qi-deficiency Constitution (0.67), Yang-deficiency Constitution (0.84), Yin-deficiency Constitution (0.59), Stagnant Blood Constitution (0.56), Stagnant Qi Constitution (0.89), Inherited Special Constitution (0.76) and Balanced Constitution (0.73), indicating acceptable internal consistency for subscales. The intra-class correlation coefficients of the TCMECQ-C ranged from 0.70 to 0.87 (p < 0.001), indicating moderate to good test-retest reliability. CONCLUSION: TCMECQ-C is a valid and reliable questionnaire for assessing the body constitution in Cantonese elderly.

Reliability Associated with the Measurement of Continuous Variables in Veterinary Medicine: What the Different Possible Indicators Tell, and How to Use and Report Them.

Reliable indicators of health status (heart rate, rectal temperature, blood marker, etc.) are of cornerstone importance in the daily practice of veterinary medicine. The reliability of a measurement assesses the variability that is associated with the variable to be measured itself vs. other sources of variation (measurement device, person performing the measurement, etc.). Quantitative and continuous indicators are numerous in practice and the determination of their reliability is a complex issue. In the absence of a gold standard approach, several indicators of reliability have been described and can be used depending on several assumptions, study design, and type of measurement. The aim of this manuscript is, therefore, to determine the applicability of commonly described reliability indicators. After a description of the different sources of errors of a measurement, a review of the different indicators that are commonly used in the veterinary field as well as their applicability, limitations, and interpretations is performed.

Interpartner Agreement on Intimate Partner Violence Reports: Evidence From a Community Sample of Different-Sex Couples.

An accurate assessment of intimate partner violence (IPV) is crucial to guide public policy and intervention. The Conflict Tactic Scales Revised (CTS-2) is one of the most widely used instruments to do so. Despite its good psychometric properties, research on interpartner agreement has pointed to low-to-moderate estimates, which generated some concerns about the validity of the results obtained through single-partner reports. This cross-sectional study introduces indexes that have not previously been used to assess interpartner agreement. Both partners' reports on perpetration and victimization were analyzed in a community sample of 268 different-sex couples. Our results generally pointed to better agreement levels on IPV occurrence than frequency, suggesting that the proxy method (i.e., using a single-partner report) could be a reliable method for assessing IPV occurrence but not its frequency in this population. Findings are discussed as well as the advantages and constraints of different IPV assessment practices.

Effect of humeral rotation on the reliability of radiographic measurements for proximal humerus fractures.

BACKGROUND: There are concerns as to the reliability of proximal humerus radiographic measurements, particularly regarding the rotational position of the humerus when obtaining radiographs. METHODS: Twenty-four patients with proximal humerus fractures fixed surgically with locked plates received postoperative anteroposterior radiographs with the humerus in neutral rotation and in 30° of internal and external rotation. Radiographic measurements for head shaft angle, humeral offset and humeral head height were performed in each humeral rotation position. Intra-class correlation coefficient was used to assess inter-rater and intra-rater reliability. Mean differences (md) in measurements between humeral positions was evaluated using one-way ANOVA. RESULTS: Head shaft angle demonstrated good-to-excellent reliability; the highest estimates for inter-rater reliability (ICC: 0.85; 95% CI: 0.76, 0.94) and intra-rater reliability (ICC: 0.96; 95% CI: 0.93, 0.98) were achieved in neutral rotation. There were significant differences in measurement values between each rotational position, with mean head shaft angle of 133.1° in external rotation, and increasingly valgus measurements in neutral (md: 7.6°; 95% CI: 5.0, 10.3°; p < 0.001) and internal rotation (md: 26.4°; 95% CI: 21.8, 30.9°; p < 0.001). Humeral head height and humeral offset showed good-to-excellent reliability in neutral and external rotation, but poor inter-rater reliability in internal rotation. Humeral head height was significantly greater using internal compared to external rotation (md: 4.5 mm; 95% CI: 1.7, 7.3 mm; p = 0.002). Humeral offset was significantly greater in external compared to internal rotation (md: 4.6 mm; 95% CI: 2.6, 6.6 mm; p < 0.001). CONCLUSIONS: Views of the humerus in neutral rotation and 30° of external rotation displayed superior reliability. Differences in radiographic measurement values, depending on humeral rotation views, can make for problematic correlations with patient outcome measures. Studies assessing radiographic outcomes following proximal humerus fractures should ensure standardized humeral rotation for obtaining anteroposterior shoulder radiographs, with neutral rotation and external rotation views likely yielding the most reliable results. LEVEL OF EVIDENCE: Level IV.

Test-Retest Reliability of Resting Brain Small-World Network Properties across Different Data Processing and Modeling Strategies.

Resting-state functional magnetic resonance imaging (fMRI) with graph theoretical modeling has been increasingly applied for assessing whole brain network topological organization, yet its reproducibility remains controversial. In this study, we acquired three repeated resting-state fMRI scans from 16 healthy controls during a strictly controlled in-laboratory study and examined the test-retest reliability of seven global and three nodal brain network metrics using different data processing and modeling strategies. Among the global network metrics, the characteristic path length exhibited the highest reliability, whereas the network small-worldness performed the poorest. Nodal efficiency was the most reliable nodal metric, whereas betweenness centrality showed the lowest reliability. Weighted global network metrics provided better reliability than binary metrics, and reliability from the AAL90 atlas outweighed those from the Power264 parcellation. Although global signal regression had no consistent effects on the reliability of global network metrics, it slightly impaired the reliability of nodal metrics. These findings provide important implications for the future utility of graph theoretical modeling in brain network analyses.

Determination of subset models for predicting vertical centre of mass position during front crawl in male swimmers.

We attempted to find a subset model that would allow robust prediction of a swimmer's vertical body position during front crawl with fewer markers, which can reduce extra drag and time-consuming measurements. Thirteen male swimmers performed a 15-metre front crawl either with three different lung-volume levels or various speeds, or both, without taking a breath with 36 reflective markers. The vertical positions of the centre of mass (CoM) and four representative landmarks in the trunk segment over a stroke cycle were calculated using an underwater motion-capture system. We obtained 212 stroke cycles across trials and analysed the vertical position derived from 15 patterns as candidates for the subset models. Unconstrained optimisation minimises the root-mean-square error between the vertical CoM position and each subset model. The performance evaluated from the intra-class correlation coefficient (ICC) and weight parameters of each subset model were detected from the mean values across five-fold cross-validation. The subset model with four markers attached to the trunk segment showed good reliability (ICC: 0.776 ± 0.019). This result indicates that the subset model with few markers can robustly predict a male swimmer's vertical CoM position during front crawl under a wide range of speeds from 0.66 to 1.66 m · s-1.

Inter-device concordance of Veggie Meter-A reflection spectroscopy to measure skin carotenoids.

The Veggie Meter® (VM) is a refraction spectrometer that detects skin carotenoids. We tested the variability of the two modes (single-scan and averaging modes) of four VMs of three different versions (VM-1, 2, 3, 4) with 92 healthy volunteers. Both the modes exhibited a high intra-class correlation coefficient (ICC); however, the averaging mode had a significantly lower coefficient of variance than the single-scan mode. The Bland-Altman analysis showed a systematic error between VM-1 and other three VMs. The actual errors between the VM-1 and the other three VMs in the averaging mode were 7.4%, 10.4%, and 11.8% of the median of VM scores, but the errors could be reduced to 2.8%, 6.3%, and 7.0% by compensating VM scores using the regression equations. Averaging mode had higher accuracy than single-scan mode. The reliability of the VMs was validated by the small coefficient of variation and high ICC. The error was improved using linear regression compensation.

Intra-cluster correlations in socio-demographic variables and their implications: An analysis based on large-scale surveys in India.

Individuals who share similar socio-economic and cultural characteristics also share similar health outcomes. Consequently, they have a propensity to cluster together, which results in positive intra-class correlation coefficients (ICCs) in their socio-demographic and behavioural characteristics. In this study, using data from four rounds of the National Family Health Survey (NFHS), we estimated the ICC for selected socio-demographic and behavioural characteristics in rural and urban areas of six states namely Assam, Gujarat, Kerala, Punjab, Uttar Pradesh, and West Bengal. The socio-demographic and behavioural characteristics included religion & caste of the household head, use of contraception & prevalence of anaemia among currently married women and coverage of full immunization services among children aged 12-23 months. ICC was computed at the level ofPrimary Sampling Units (PSUs), that is, villages in rural areas and census enumeration blocks in urban areas. Our research highlights high clustering in terms of religion and caste within PSUs in India. In NFHS-4, the ICCs for religion ranged from the lowest of 0.19 in rural areas of Kerala to the highest of 0.67 in urban areas of West Bengal. For the caste of the household head, the ICCs ranged from the lowest of 0.12 in the urban areas of Punjab to the highest of 0.46 in the rural areas of Assam. In most of the states selected for the study, the values of ICC were higher for the use of family planning methods than for full immunization. The value of ICC for use of contraception was highest for rural areas of Assam (0.15) followed by rural areas of Gujarat (0.13). A higher value of ICC has considerable implications for determining an effective sample size for large-scale surveys. Our findings agree with the fact that for a given cluster size, the higher the value of ICC, the higher is the loss in precision of the estimate. Knowing and taking into account ICCs can be extremely helpful in determining an effective sample size when designing a large-scale demographic and health survey to arrive at estimates of parameters with the desired precision.

A hybrid approach to comparing parallel-group and stepped-wedge cluster-randomized trials with a continuous primary outcome when there is uncertainty in the intra-cluster correlation.

BACKGROUND/AIMS: To evaluate how uncertainty in the intra-cluster correlation impacts whether a parallel-group or stepped-wedge cluster-randomized trial design is more efficient in terms of the required sample size, in the case of cross-sectional stepped-wedge cluster-randomized trials and continuous outcome data. METHODS: We motivate our work by reviewing how the intra-cluster correlation and standard deviation were justified in 54 health technology assessment reports on cluster-randomized trials. To enable uncertainty at the design stage to be incorporated into the design specification, we then describe how sample size calculation can be performed for cluster- randomized trials in the 'hybrid' framework, which places priors on design parameters and controls the expected power in place of the conventional frequentist power. Comparison of the parallel-group and stepped-wedge cluster-randomized trial designs is conducted by placing Beta and truncated Normal priors on the intra-cluster correlation, and a Gamma prior on the standard deviation. RESULTS: Many Health Technology Assessment reports did not adhere to the Consolidated Standards of Reporting Trials guideline of indicating the uncertainty around the assumed intra-cluster correlation, while others did not justify the assumed intra-cluster correlation or standard deviation. Even for a prior intra-cluster correlation distribution with a small mode, moderate prior densities on high intra-cluster correlation values can lead to a stepped-wedge cluster-randomized trial being more efficient because of the degree to which a stepped-wedge cluster-randomized trial is more efficient for high intra-cluster correlations. With careful specification of the priors, the designs in the hybrid framework can become more robust to, for example, an unexpectedly large value of the outcome variance. CONCLUSION: When there is difficulty obtaining a reliable value for the intra-cluster correlation to assume at the design stage, the proposed methodology offers an appealing approach to sample size calculation. Often, uncertainty in the intra-cluster correlation will mean a stepped-wedge cluster-randomized trial is more efficient than a parallel-group cluster-randomized trial design.

Imaging biomarkers to stratify lymph node metastases in abdominal CT - Is radiomics superior to dual-energy material decomposition?

Purpose: To assess the potential of radiomic features in comparison to dual-energy CT (DECT) material decomposition to objectively stratify abdominal lymph node metastases. Materials and methods: In this retrospective study, we included 81 patients (m, 57; median age, 65 (interquartile range, 58.7-73.3) years) with either lymph node metastases (n = 36) or benign lymph nodes (n = 45) who underwent contrast-enhanced abdominal DECT between 06/2015-07/2019. All malignant lymph nodes were classified as unequivocal according to RECIST criteria and confirmed by histopathology, PET-CT or follow-up imaging. Three investigators segmented lymph nodes to extract DECT and radiomics features. Intra-class correlation analysis was applied to stratify a robust feature subset with further feature reduction by Pearson correlation analysis and LASSO. Independent training and testing datasets were applied on four different machine learning models. We calculated the performance metrics and permutation-based feature importance values to increase interpretability of the models. DeLong test was used to compare the top performing models. Results: Distance matrices and t-SNE plots revealed clearer clusters using a combination of DECT and radiomic features compared to DECT features only. Feature reduction by LASSO excluded all DECT features of the combined feature cohort. The top performing radiomic features model (AUC = 1.000; F1 = 1.000; precision = 1.000; Random Forest) was significantly superior to the top performing DECT features model (AUC = 0.942; F1 = 0.762; precision = 0.800; Stochastic Gradient Boosting) (DeLong < 0.001). Conclusion: Imaging biomarkers have the potential to stratify unequivocal lymph node metastases. Radiomics models were superior to DECT material decomposition and may serve as a support tool to facilitate stratification of abdominal lymph node metastases.

Are inter-subject functional correlations consistent across different movies?

Movie fMRI has been increasingly used in investigations of human brain function. Inter-subject functional correlation (ISFC), which evaluates stimulus-dependent inter-regional synchrony between brains exposed to the same stimulus, is emerging as an influencing measure for movie fMRI data analyses. Before the wide application of ISFC analyses, it will be useful to investigate the degree to which they are similar and different across different movies. Based on the four movie fMRI runs of 178 subjects included in the "human connectome project (HCP) S1200 Release", we evaluated ISFCs throughout the brain and analyzed their consistency across different movies using intra-class correlation (ICC). We also investigated the generalizability of ISFC-based predictive models, which is closely related to their consistency, with sex classification and grip strength prediction used as test cases. The results showed that the intensity of ISFCs was generally weak (0.047). Except a few within-network ones (e.g., ICC of ISFC in the PON was 0.402), ISFCs throughout the brain exhibited low consistency, as indicated by a mean ICC of 0.130. The accuracies for inter-run predictions (60.7-72.8% for sex classification, and R = 0.122-0.275 for grip strength prediction) were much lower than those for intra-run predictions (73.2-83.0% for sex classification, and R = 0.325-0.403 for grip strength prediction), and this indicates poor generalizability of predictive models based on ISFCs. According to these findings, ISFC analyses capture aspects of brain function that are specific to each individual movie, and this specificity should be taken into account (in some cases might be especially useful) in future naturalistic studies.

A new circle method for measuring humeral torsion on MRI-scans less sensitive to Hill-Sachs lesions.

Objectives: The literature on humeral torsion angles (retrotorsion) reveals great inconsistencies between methodology and values. Decreased retrotorsion was suspected to correlate with instability, but evidence is contradictory. The measurement according to the gold standard method of Bernageau and Godefroy (B&G) can be challenging especially in the presence of Hill-Sachs-lesions. Therefore, we have developed and evaluated a new measurement method for the humeral torsion angle on MRI-scans. Materials and Methods: Three investigators have measured 67 patients (35 with shoulder instability, 32 healthy) on axial MRIs with 603 measurements used for reliability calculation. The new Circle-method determines the retrotorsion by overlaying two circles on the transversal section of the humeral head. The first circle is adjusted congruent with the margin of the humeral head, whereas the second circle is adjusted to the greater tubercle. The line bisecting the centres of these circles is defined as the humeral head axis. This method was compared to B&G. Results: The mean retrotorsion angle of all patients was 25°± 25° (mean ± SD) with B&G, and 24° ± 27° with the Circle-method. Neither method revealed a significant difference between stable and unstable shoulders (p = 0.47). Of the 35 patients with unstable shoulders 21 (60%) presented Hill-Sachs lesions. No significant differences between patients with or without Hill-Sachs lesions (Circle-method: p = 0.61; B&G: p = 0.67). The reliability parameters for both methods were similar. Conclusions: The new Circle-method is as precise as the method of B&G. It may yield more consistent values in cases with substantial Hill-Sachs-lesions. Our data do not suggest retrotorsion as a predictor of instability.