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Automated spinopelvic measurements on radiographs with artificial intelligence: a multi-reader study
No full textPurpose
To develop an artificial intelligence (AI) algorithm for automated measurements of spinopelvic parameters on lateral radiographs and compare its performance to multiple experienced radiologists and surgeons.
Methods
On lateral full-spine radiographs of 295 consecutive patients, a two-staged region-based convolutional neural network (R-CNN) was trained to detect anatomical landmarks and calculate thoracic kyphosis (TK), lumbar lordosis (LL), sacral slope (SS), and sagittal vertical axis (SVA). Performance was evaluated on 65 radiographs not used for training, which were measured independently by 6 readers (3 radiologists, 3 surgeons), and the median per measurement was set as the reference standard. Intraclass correlation coefficient (ICC), mean absolute error (MAE), and standard deviation (SD) were used for statistical analysis; while, ANOVA was used to search for significant differences between the AI and human readers.
Results
Automatic measurements (AI) showed excellent correlation with the reference standard, with all ICCs within the range of the readers (TK: 0.92 [AI] vs. 0.85–0.96 [readers]; LL: 0.95 vs. 0.87–0.98; SS: 0.93 vs. 0.89–0.98; SVA: 1.00 vs. 0.99–1.00; all p 0.05). Human reading time was on average 139 s per case (range: 86–231 s).
Conclusion
Our AI algorithm provides spinopelvic measurements accurate within the variability of experienced readers, but with the potential to save time and increase reproducibility
Multivariable prognostic prediction of efficacy and safety outcomes and response to fingolimod in people with relapsing-remitting multiple sclerosis
Get PDFBackground: The individual treatment response in people with relapsing-remitting multiple sclerosis (RRMS) remain unpredictable. In order to support medical decisions, we aimed to predict response to fingolimod compared to placebo, by developing and validating prognostic multivariable models.
Methods: We included two-year follow-up from intention-to-treat populations of two multi-country placebo-controlled randomized controlled trials (RCT) of daily fingolimod 0.5 mg. The data was accessed via ClinicalStudyDataRequest.com (Proposal Number: 11223) The RCTs were in adult RRMS patients with active disease. We used four Cox proportional hazards based penalized (elastic net and grouped lasso) and tree methods (transformation tree and forest) to predict time-to relapse and other relevant efficacy and safety endpoints in data from the RCT FREEDOMS. Treatment arm, 80 baseline variables and their interaction with treatment were considered as candidate predictors in the models. A nested cross-validation scheme ensured independent tuning parameter optimization and internal model performance evaluation. The generalizability of the models with the highest cross-validated time-dependent area under the receiver operating curve (AUC) was further evaluated in terms of discrimination (AUC), calibration (plots, intercept, slope), clinical utility (decision curve analysis), and treatment response plots by external validation in data from the RCT FREEDOMS II.
Results: The best performing model predicting relapse risk (331 events) in the development sample (n=843) was an elastic net regression with main terms for four predictors alongside treatment: EDSS score, volume of Gadolinium enhanced T1 lesions, number of relapses in the last 2 years, and number of prior MS treatments. In external validation (n=713), it had an AUC of 0.68 (95% CI 0.63-0.72), but the predictions were overestimating the actual risk (358 events) with a calibration-in-the-large of -0.17 (-0.3 - -0.04) and a slope of 1.06 (0.78-1.35). Almost no heterogeneity (variability 0.001) was detected in the predicted relapse risk change in response to fingolimod. FREEDOMS II participants were predicted to have 0.21 to 0.31 absolute relapse risk reduction with fingolimod compared to placebo. The selected model predicting new or enlarging T2 magnetic resonance imaging (MRI) lesions had an AUC of 0.74 (0.70-0.78), moderate calibration, but no treatment response variability. The final model predicting confirmed disability progression had an AUC of 0.59 (0.54-0.64) and the predicted treatment response heterogeneity was not significant. The overall safety outcome could not be predicted with sufficient discrimination. However, the final model predicting infections or neoplasms had an AUC of 0.69 (0.63-0.74) and non-significant treatment response heterogeneity. For the efficacy outcomes, important predictors were related to (para)clinical disease activity or disability. Unexpected influential predictors included concomitant disorders.
Conclusion: Relapse and new or enlarging T2 MRI lesions were moderately predictable in an independent sample with the developed prognostic models. Fingolimod was expected to decrease the risk of these events for all patients, with no predictable heterogeneity. Disability and safety outcomes could not be well-predicted and it is yet unresolved whether the change in their risk as response to fingolimod is heterogeneous or not
An atypical atherogenic chemokine that promotes advanced atherosclerosis and hepatic lipogenesis
Get PDFAtherosclerosis is the underlying cause of myocardial infarction and ischemic stroke. It is a lipid-triggered and cytokine/chemokine-driven arterial inflammatory condition. We identify D-dopachrome tautomerase/macrophage migration-inhibitory factor-2 (MIF-2), a paralog of the cytokine MIF, as an atypical chemokine promoting both atherosclerosis and hepatic lipid accumulation. In hyperlipidemic Apoe–/– mice, Mif-2-deficiency and pharmacological MIF-2-blockade protect against lesion formation and vascular inflammation in early and advanced atherogenesis. MIF-2 promotes leukocyte migration, endothelial arrest, and foam-cell formation, and we identify CXCR4 as a receptor for MIF-2. Mif-2-deficiency in Apoe–/– mice leads to decreased plasma lipid levels and suppressed hepatic lipid accumulation, characterized by reductions in lipogenesis-related pathways, tri-/diacylglycerides, and cholesterol-esters, as revealed by hepatic transcriptomics/lipidomics. Hepatocyte cultures and FLIM-FRET-microscopy suggest that MIF-2 activates SREBP-driven lipogenic genes, mechanistically involving MIF-2-inducible CD74/CXCR4 complexes and PI3K/AKT but not AMPK signaling. MIF-2 is upregulated in unstable carotid plaques from atherosclerotic patients and its plasma concentration correlates with disease severity in patients with coronary artery disease. These findings establish MIF-2 as an atypical chemokine linking vascular inflammation to metabolic dysfunction in atherosclerosis
Long-term exposure to air pollution and greenness in association with respiratory emergency room visits and hospitalizations: The Life-GAP project
Get PDFBackground
Air pollution has been linked to respiratory diseases, while the effects of greenness remain inconclusive.
Objective
We investigated the associations between exposure to particulate matter (PM2.5 and PM10), black carbon (BC), nitrogen dioxide (NO2), ozone (O3), and greenness (normalized difference vegetation index, NDVI) with respiratory emergency room visits and hospitalizations across seven Northern European centers in the European Community Respiratory Health Survey (ECRHS) study.
Methods
We used modified mixed-effects Poisson regression to analyze associations of exposure in 1990, 2000 and mean exposure 1990–2000 with respiratory outcomes recorded duing ECRHS phases II and III. We assessed interactions of air pollution and greenness, and of atopic status (defined by nasal allergies and hay fever status) and greenness, on these outcomes.
Results
The analysis included 1675 participants, resulting in 119 emergency visits and 48 hospitalizations. Increased PM2.5 by 5 μg/m³ was associated with higher relative risk (RR) of emergency visits (1990: RR 1.16, 95% CI: 1.00–1.35; 2000: RR 1.24, 95% CI: 0.98–1.57; 1990–2000: RR 1.17, 95% CI: 0.97–1.41) and hospitalizations (1990: RR 1.42, 95% CI: 1.00–2.01; 2000: RR 2.20, 95% CI: 1.43–3.38; 1990–2000: RR 1.44, 95% CI: 1.04–2.00). Similar trends were observed for PM10, BC, and NO2, with only PM10 showing significant associations with hospitalizations across all periods. No associations were found for O3. Greenness exposure was linked to more emergency visits in 2000 but to fewer hospitalizations in 1990. Significant interactions were observed between greenness and atopic status for emergency visits, and between NDVI with O3 and BC for some time windows.
Conclusion
Long-term exposure to particulate matter was associated with increased emergency room visits and hospitalizations. Significant associations were observed for BC and NO2 with hospitalizations. No link was found with O3. Greenness indicated a lower risk of hospitalizations, but increased risks for emergency visits for those with atopic status
Association of chronic stress during studies with depressive symptoms 10 years later
Get PDFThe long-tern implications of stress during university for individuals’ mental health are not well understood so far. Hence, we aimed to examine the potential effect of stress while studying at university on depression in later life. We analysed data from two waves of the longitudinal Study on Occupational Allergy Risks. Using the ‘work overload’ and ‘proving oneself’ scales of the Trier Inventory for Chronic Stress and the Patient Health Questionnaire-2 (PHQ-2), participants reported chronic stress during university (2007–2009, mean age 22.2 years, T1) and depressive symptoms ten years later (2017–2018, mean age 31.6 years, T2). We performed linear regression analyses to explore the association between stress during university (T1) and later depressive symptoms (T2). Participants (N = 548, 59% female) indicated rather low levels of stress and depression (PHQ-2 mean score: 1.14 (range: 0–6)). We observed evidence for a linear association between overload at T1 and depression at T2 (regression coefficient (B) = 0.270; 95% confidence interval (CI) = 0.131 to 0.409; standardised regression coefficient (β) = 0.170). Our analyses yielded evidence for an association between chronic stress while studying and risk of depressive symptoms later in life. This finding underlines the importance of implementing sustainable preventive measures against stress among students
Integration of highly sensitive large-area graphene-based biosensors in an automated sensing platform
Get PDFGraphene-based biosensors, featuring exceptional electronic, mechanical, and surface properties, have emerged as frontrunners in advanced sensing technologies. However, to achieve widespread industrial adoption, advancements in the fabrication and integration of large-area graphene devices are essential. Critical parameters such as enhanced sensitivity, scalable production methods, economic viability, integration capabilities, and consistent uniformity must be meticulously addressed. In this work, we demonstrate that our ultra-clean, chemical wet transfer protocol of large-area graphene enables a scalable, smooth integration of graphene into an established assay platform for transporter protein drug discovery. Furthermore, we demonstrate sensitive detection of electrolytic buffers, varying pH, bovine serum albumin (BSA) and single-stranded DNA (ssDNA) adsorption, using our large-area graphene solution-gated field-effect transistor (SGFET) sensors, thereby proving their robust and reliable performance. The sensors’ biocompatibility and ion sensitivity, down to the picomolar range, substantiate their suitability for the investigation of electroactive transport in ion channels and membrane transporters
Transcatheter aortic valve implantation and its impact on endothelial function in patients with aortic stenosis
Get PDFVascular function is impaired in patients with aortic valve stenosis (AS). The impact of transcatheter aortic valve implantation (TAVI) on endothelial function is inconclusive so far. Therefore, we sought to assess the short-term influence of TAVI on endothelial dysfunction in patients with AS.
We recruited 47 patients (76.6 % male, 80.04 years old) with AS scheduled for TAVI. Endothelial function was assessed by fingertip reactive hyperemia peripheral arterial tonometry (RH-PAT). Measurements were conducted one day before and three days after TAVI. Patients were grouped according to RH-PAT change after TAVI.
Overall, RH-PAT measurements did not significantly improve after TAVI (Reactive Hyperemia Index: 1.5 vs 1.6, p = 0.883; logarithm of the Reactive Hyperemia Index: 0.44 vs. 0.49, p = 0.523). Interestingly, patients with no RH-PAT improvement after TAVI displayed a more severe AS and had lower blood pressure after TAVI. This might be due to a more disturbed blood flow in patients with a smaller aortic valve area and higher peak aortic valve velocity.
The relationship between AS severity, endothelial dysfunction and TAVI has to be investigated in future research that apply longitudinal study designs
The effectiveness of game-based literacy app learning in preschool children from diverse backgrounds
Get PDFFamily background factors like socio-economic status (SES) and migration background, along with child characteristics such as gender and intelligence, significantly influence early childhood competencies. Children from families with low SES and/or migration background often show weaker literacy outcomes than their peers. Game-based learning via apps can support children's competency development, but its effects may depend on children's app usage and how it interacts with child and family characteristics. We examined the effects of specifically developed literacy apps with N = 500 preschoolers (MAge = 60.96 months). The intervention was successful: Children who used our literacy apps obtained greater literacy competencies compared to a control group, even after accounting for family and child characteristics. Longer app usage time was associated with literacy gains, independent of SES and migration background, with a U-shaped relation, but only among girls. Consequently, game-based learning via apps can be successful; however, individual differences should be considered
Reference intervals of two-dimensional speckle tracking–derived endocardial global longitudinal strain analysis in 132 healthy cats
Get PDFIntroduction
The assessment of left ventricular myocardial deformation and function by two-dimensional speckle tracking–derived strain analysis is an established method in human cardiology. It also progressively gains recognition in veterinary cardiology in both dogs and cats.
Objectives
The objectives of this study were to create reference intervals for two-dimensional speckle tracking echocardiography (STE)–derived endocardial global longitudinal strain (GLS) in a population of healthy adult cats of different breeds. Influences of heart rate, body weight, and age were investigated.
Animals
A total of 132 healthy, adult cats were included in this study.
Materials and Methods
Left apical two-, three-, and four-chamber views were obtained prospectively for GLS measurements using two-dimensional speckle tracking performed with cardiac performance analysis. Potential influence of body weight, heart rate, and age was analyzed, and the interobserver and intra-observer variability of the measurements was determined.
Results
Endocardial GLS values were not significantly influenced by body weight (P=0.102), heart rate (P=0.144), or age (P=0.075). A reference interval for GLS of −21.18% to −37.50% (±4.12) was determined. The interobserver and intra-observer variability showed excellent agreement.
Discussion and Conclusions
Two-dimensional STE is a feasible technique for the evaluation of cardiac myocardial deformation and systolic function in cats. Showing an excellent interobserver and intra-observer agreement, two-dimensional STE is a promising method for clinical analysis of cardiac deformation in cats
Toward open science in marketing research
Get PDFThe open science paradigm has gained prominence in marketing as researchers seek to enhance the validity, reliability, and transparency of research methods and findings. Journals and institutions increasingly encourage or require open science practices, and many authors have started to adapt to and meet these new research and publishing expectations. We provide guidance for effectively implementing open science practices in empirical marketing research. Our recommendations, are tailored to the unique methodological approaches and challenges of each subdiscipline and their specific research contexts. Successful integration of these practices into academic marketing research will require concerted and collaborative efforts among authors, journals, institutions, and funding agencies. We argue that the gradual, thoughtful adoption of these principles and practices will improve the quality and efficiency of scientific discovery