Impact of Automated Prognostication on Traumatic Brain Injury Care: A Focus Group Study.

BACKGROUND: Prognosticating outcomes for traumatic brain injury (TBI) patients is challenging due to the required specialized skills and variability among clinicians. Recent attempts to standardize TBI prognosis have leveraged machine learning (ML) methodologies. This study evaluates the necessity and influence of ML-assisted TBI prognostication through healthcare professionals' perspectives via focus group discussions. METHODS: Two virtual focus groups included ten key TBI care stakeholders (one neurosurgeon, two emergency clinicians, one internist, two radiologists, one registered nurse, two researchers in ML and healthcare and one patient representative). They answered six open-ended questions about their perceptions and potential ML use in TBI prognostication. Transcribed focus group discussions were thematically analyzed using qualitative data analysis software. RESULTS: The study captured diverse perceptions and interests in TBI prognostication across clinical specialties. Notably, certain clinicians who currently do not prognosticate expressed an interest in doing so independently provided they had access to ML support. Concerns included ML's accuracy and the need for proficient ML researchers in clinical settings. The consensus suggested using ML as a secondary consultation tool and promoting collaboration with internal or external research resources. Participants believed ML prognostication could enhance disposition planning and standardize care regardless of clinician expertise or injury severity. There was no evidence of perceived bias or interference during the discussions. CONCLUSION: Our findings revealed an overall positive attitude toward ML-based prognostication. Despite raising multiple concerns, the focus group discussions were particularly valuable in underscoring the potential of ML in democratizing and standardizing TBI prognosis practices.

Approaches and Limitations of Machine Learning for Synthetic Ultrasound Generation: A Scoping Review.

This scoping review examines the emerging field of synthetic ultrasound generation using machine learning (ML) models in radiology. Nineteen studies were analyzed, revealing three primary methodological strategies: unconditional generation, conditional generation, and domain translation. Synthetic ultrasound is mainly used to augment training datasets and as training material for radiologists. Blind expert assessment and Fréchet Inception Distance are common evaluation methods. Current limitations include the need for large training datasets, manual annotations for controllable generation, and insufficient research on incorporating new domain knowledge. While generative ultrasound models show promise, further work is required for clinical implementation.

External Validation of O-RADS US Risk Stratification and Management System.

Background The Ovarian-Adnexal Reporting and Data System (O-RADS) US risk stratification and management system (O-RADS US) was designed to improve risk assessment and management of ovarian and adnexal lesions. Validation studies including both surgical and nonsurgical treatment as the reference standard remain lacking. Purpose To externally validate O-RADS US in women who underwent either surgical or nonsurgical treatment and to determine if incorporating acoustic shadowing as a benign finding improves diagnostic performance. Materials and Methods This retrospective study included consecutive women who underwent pelvic US between August 2015 and April 2017 at a tertiary referral oncology center. Two independent readers blinded to clinical and histologic outcome assigned an O-RADS risk category and an International Ovarian Tumor Analysis (IOTA) Assessment of Different NEoplasias in the adneXa (ADNEX) model risk of malignancy score to assessable lesions. Reference standards were surgical histopathology or 2-year imaging follow-up. Receiver operating characteristic (ROC) curve analysis was used to evaluate performance of the O-RADS US, ADNEX, and modified O-RADS models incorporating acoustic shadowing. Results In total, 227 women (mean age, 52 years ± 16 [SD]) with 262 ovarian or adnexal lesions were evaluated. Of these lesions, 187 (71%) were benign and 75 (29%) were malignant. The proportion of malignancy was 0% (0 of 100) for O-RADS 2, 3% (one of 32) for O-RADS 3, 35% (22 of 63) for O-RADS 4, and 78% (52 of 67) for O-RADS 5. The area under the ROC curve (AUC) for O-RADS and ADNEX was 0.91 (95% CI: 0.88, 0.94) and 0.95 (95% CI: 0.92, 0.97; P = .01), respectively. The addition of acoustic shadowing as a benign finding improved O-RADS AUC to 0.94 (95% CI: 0.91, 0.96; P = .01). Use of O-RADS 4 as a threshold yielded a sensitivity of 99% (74 of 75; 95% CI: 96, 100) and a specificity of 70% (131 of 187; 95% CI: 64, 77). Conclusion In a tertiary referral oncology center, the Ovarian-Adnexal Reporting and Data System US risk stratification and management system enabled accurate distinction of benign from malignant ovarian and adnexal lesions. Adding acoustic shadowing as a benign finding improved its diagnostic performance. © RSNA, 2022 See also the editorial by Levine in this issue.

Effect of Caffeine on Endurance Performance in Athletes May Depend on HTR2A and CYP1A2 Genotypes.

ABSTRACT: Guest, NS, Corey, P, Tyrrell, PN, and El-Sohemy, A. Effect of caffeine on endurance performance in athletes may depend on HTR2A and CYP1A2 genotypes. J Strength Cond Res 36(9): 2486-2492, 2022-This investigation determined whether variation in the HTR2A (serotonin receptor) gene modifies the ergogenic effects of caffeine on endurance and further modifies performance by the CYP1A2 genotype. Male athletes ( n = 100; 25 ± 4 years) completed 10-km cycling time trials under 3 conditions as follows: 0, 2, or 4 mg of caffeine per kg body mass. Using a randomized, double-blinded, placebo-controlled design, data were analyzed using analysis of covariance to compare changes in cycling time between placebo (0 mg·kg -1 ) and each caffeine dose and adjusted for the placebo trial and order of treatment. A significance of ρ ≤ 0.05 was used. Subjects were genotyped for HTR2A (rs6313) and CYP1A2 (rs762551). A significant caffeine- HTR2A interaction ( p = 0.003) was observed; however, after adjustment for placebo trials, the interaction was no longer significant ( p = 0.37). Because of the strong caffeine- CYP1A2 interaction ( p < 0.0001) previously reported in these subjects, where the 4-mg dose resulted in divergent effects (slower and faster) on the 10-km cycling time, we conducted a simplified model to examine these same factors by the HTR2A genotype. The post hoc analysis excluded HTR2A CT heterozygotes and 2-mg·kg -1 caffeine trials. Among CYP1A2 fast metabolizers alone, a significant difference (1.7 minutes; p = 0.006) was observed when comparing (4- vs. 0-mg·kg -1 caffeine trials) between the HTR2A CC ( n = 16; 2.4 minutes) and TT ( n = 7; 0.7 minutes) genotypes. Our results show that 4-mg·kg -1 caffeine improves performance in individuals with the HTR2A CC genotype but only in those who are also CYP1A2 AA fast metabolizers. This study was registered with clinicaltrials.gov (NCT02109783).

Caffeine, genetic variation and anaerobic performance in male athletes: a randomized controlled trial.

PURPOSE: The effect of caffeine on anaerobic performance is unclear and may differ depending on an individual's genetics. The goal of this study was to determine whether caffeine influences anaerobic performance in a 30 s Wingate test, and if 14 single nucleotide polymorphisms (SNPs) in nine genes, associated with caffeine metabolism or response, modify caffeine's effects. METHODS: Competitive male athletes (N = 100; 25 ± 4 years) completed the Wingate under three conditions: 0, 2, or 4 mg of caffeine per kg of body mass (mg kg-1), using a double-blinded, placebo-controlled design. Using saliva samples, participants were genotyped for the 14 SNPs. The outcomes were peak power (Watts [W]), average power (Watts [W]), and fatigue index (%). RESULTS: There was no main effect of caffeine on Wingate outcomes. One significant caffeine-gene interaction was observed for CYP1A2 (rs762551, p = 0.004) on average power. However, post hoc analysis showed no difference in caffeine's effects within CYP1A2 genotypes for average power performance. No significant caffeine-gene interactions were observed for the remaining SNPs on peak power, average power and fatigue index. CONCLUSION: Caffeine had no effect on anaerobic performance and variations in several genes did not modify any effects of caffeine. TRIAL REGISTRATION: This study was registered with clinicaltrials.gov (NCT02109783).

Distribution of Iliac Artery Calcification on Unenhanced Computed Tomography Scans Performed on Potential Recipients Prior to Renal Transplantation.

PURPOSE: To investigate whether a significant difference exists between the calcification of the common iliac arteries (CIAs) and the external iliac arteries (EIAs) and test for associations between clinical factors and the distribution of calcification. METHODS: A retrospective review of renal transplant candidates who underwent a routine preoperative unenhanced computed tomography yielded 214 patients. Agatston scores for the patients' left CIA, left EIA, right CIA, and right EIA were assigned. A retrospective search of patient records screened for 5 clinical factors (diabetes, hypertension, coronary artery disease [CAD], smoking, and dialysis). Data were assessed using a 2-sided t test, odds ratio, and a multivariate linear regression calculated through generalized estimating equation (GEE). RESULTS: The log-transformed Agatston scores in the CIA were found to be significantly greater than that in the EIA (t = 9.57, P < .0001), with a mean difference of 1.5078 (95% confidence interval: 1.1962-1.8194), indicating relative EIA sparing. There were no significant differences in calcification between the right and left sides. Generalized estimating equation found that CAD and smoking demonstrated independent positive associations with EIA sparing (GEE = 2.6464 [P = .0197] and 1.9092 [P = .0470], respectively). Age was also significantly associated and indicated that EIA sparing remained relatively constant throughout patients' lives (GEE = 1.0711 [P < .0001]). CONCLUSION: This study has demonstrated statistically significant EIA sparing in end-stage renal disease patients and identified CAD and smoking as associated factors. This phenomenon warrants further investigation into its biological mechanisms and the impact of EIA sparing on outcomes following transplants.

Mechanical thrombectomy in patients with proximal occlusions and low NIHSS: Results from a large prospective registry.

BACKGROUND: Mechanical thrombectomy is now standard of care for treatment of acute ischemic stroke secondary to large vessel occlusion in the setting of high NIHSS. We analysed a large nationwide registry focusing on patients with large vessel occlusion and low NIHSS on admission to evaluate the efficacy and safety of thrombectomy in this patient population METHODS: 2826 patients treated with mechanical thrombectomy were included in a multicentre registry from January 1, 2011 to December 31, 2015. We included patients with large vessel occlusion and NIHSS ≤ 6 on admission. Baseline characteristics, imaging, clinical outcome, procedure adverse events and positive and negative outcome predictors were analysed. RESULTS: 134 patients were included. 90/134 had an anterior circulation and 44 a posterior circulation stroke. One patient died before treatment. Successful revascularization (mTICI 2b-3) was achieved in 73.7% (98/133) of the patients. Intraprocedural adverse event was observed in 3% (4/133) of cases. Symptomatic intracranial haemorrhage rate was 5.3% (7/133). At three months, 70.9% (95/134) of the patients had mRS score 0-2, 15.7% (21/134) mRS 3-5 and 13.4% (18/134) mRS 6. Age and successful recanalization were significant predictors of a good clinical outcome on both univariate (p= 0.005 and p=0.007) and multivariable (p=0.0018 and p=0.009 [nat log]) analysis. Absence of vessel recanalization and symptomatic intracranial hemorrhage were independent predictors of poor outcome (p=0.021) . CONCLUSIONS: Our study suggests that patients with large vessel occlusion and low NIHSS score on admission can benefit from mechanical thrombectomy. Randomized trials are warranted.

Effectiveness of Electronic Medication Packaging Devices on Medication Adherence: A Scoping Review.

Poor adherence to complex medication regimens is a global problem that affects the treatment of chronic diseases, which involves polypharmacy and requires long-term administration of medications. The most significant barrier to medication adherence in older adults is patient-related factors. The purpose of this study was to find evidence from the current literature to evaluate the effectiveness of electronic medication packaging (EMP) devices on improving medication adherence in older patients. MEDLINE and EMBASE databases were searched based on inclusion/exclusion criteria, focusing on medication adherence and EMP devices with specific technological features. Search results included studies with experiences of patients with four different devices and various medical conditions. Study results indicated that EMP devices may improve medication adherence in older patients. However, due to insufficient evidence that supports their effectiveness specifically in the aging population, further clinical validation in older adults is recommended to draw strong conclusions. [Journal of Gerontological Nursing, 46(3), 27-36.].

Serum cytokine and chemokine levels in patients with eosinophilic granulomatosis with polyangiitis, hypereosinophilic syndrome, or eosinophilic asthma.

OBJECTIVES: The pathogenesis of eosinophilic granulomatosis with polyangiitis (EGPA) remains poorly understood, and may overlap with eosinophilic asthma and primary hypereosinophilic syndrome (HES). The aim of this study was to analyse a panel of serum cytokines and chemokines as markers of disease activity in patients with these conditions. METHODS: The levels of 54 cytokines and chemokines were measured in the sera of 40 patients with active EGPA, 10 of these patients during inactive disease, 6 patients with HES, 8 with asthma, and 10 healthy controls. Serum cytokine/chemokines measured included interleukin (IL)-1α, 1ß, 3, 4, 5, 6, 8, 13, 15, 17A, 17E(25), 18, 23 and 33, soluble IL-2 receptor alpha, eotaxin-1 (CCL11), -2 (CCL24) and -3 (CCL26), macrophage-derived chemokine (MDC/CCL22), macrophage inflammatory protein (MIP)-1a and -1b, and tumour necrosis factor (TNF)-α. Results were compared between disease and control groups using regression analysis, with Bonferroni correction for multiple comparisons (significant p value ≤0.00093). RESULTS: Significant differences were observed only in serum levels of MDC, IL-8, MIP-1a and -1b, TNF-α, each of which were lower in patients with active EGPA than in healthy controls (p<0.0001). Differences between patients with active disease and other disease groups did not reach significance. Paired comparisons between sera from patients with active or inactive EGPA showed no significant difference for any of the studied cytokines or chemokines. CONCLUSIONS: No clear difference in the serum levels of measured cytokines and chemokines helped distinguish between active EGPA or inactive EGPA, or other disease or control groups.

Sample-Size Determination Methodologies for Machine Learning in Medical Imaging Research: A Systematic Review.

PURPOSE: The required training sample size for a particular machine learning (ML) model applied to medical imaging data is often unknown. The purpose of this study was to provide a descriptive review of current sample-size determination methodologies in ML applied to medical imaging and to propose recommendations for future work in the field. METHODS: We conducted a systematic literature search of articles using Medline and Embase with keywords including "machine learning," "image," and "sample size." The search included articles published between 1946 and 2018. Data regarding the ML task, sample size, and train-test pipeline were collected. RESULTS: A total of 167 articles were identified, of which 22 were included for qualitative analysis. There were only 4 studies that discussed sample-size determination methodologies, and 18 that tested the effect of sample size on model performance as part of an exploratory analysis. The observed methods could be categorized as pre hoc model-based approaches, which relied on features of the algorithm, or post hoc curve-fitting approaches requiring empirical testing to model and extrapolate algorithm performance as a function of sample size. Between studies, we observed great variability in performance testing procedures used for curve-fitting, model assessment methods, and reporting of confidence in sample sizes. CONCLUSIONS: Our study highlights the scarcity of research in training set size determination methodologies applied to ML in medical imaging, emphasizes the need to standardize current reporting practices, and guides future work in development and streamlining of pre hoc and post hoc sample size approaches.

Sharing De-identified Medical Images Electronically for Research: A Survey of Patients' Opinion Regarding Data Management.

PURPOSE: Secondary usage of patient data has recently become of increasing interest for the development and application of computer analytic techniques. Strict oversight of these data is required and the individual patients themselves are integral to providing guidance. We sought to understand patients' attitudes to sharing their imaging data for research purposes. These images could provide a great wealth of information for researchers. METHODS: Patients from the Greater Toronto Area attending Sunnybrook Health Sciences Centre for imaging (magnetic resonance imagining, computed tomography, or ultrasound) examination areas were invited to participate in an electronic survey. RESULTS: Of the 1083 patients who were approached (computed tomography 609, ultrasound 314, and magnetic resonance imaging 160), 798 (74%) agreed to take the survey. Overall median age was 60 (interquartile range = 18, Q1 = 52, Q3 = 70), 52% were women, 42% had a university degree, and 7% had no high school diploma. In terms of willingness to share de-identified medical images for research, 76% were willing (agreed and strongly agreed), while 7% refused. Most participants gave their family physicians (73%) and other physicians (57%) unconditional data access. Participants chose hospitals/research institutions to regulate electronic images databases (70%), 89% wanted safeguards against unauthorized access to their data, and over 70% wanted control over who will be permitted, for how long, and the ability to revoke that permission. CONCLUSIONS: Our study found that people are willing to share their clinically acquired de-identified medical images for research studies provided that they have control over permissions and duration of access.

A Systematic Review of Fatigue in Radiology: Is It a Problem?

OBJECTIVE: The purpose of this study was to review current literature regarding radiologist fatigue. MATERIALS AND METHODS: A literature search was performed using PubMed. Key words and Medical Subject Heading terms were used to generate refined queries with inclusion and exclusion criteria, focusing on fatigue and error. Results were selected according to these criteria: examined radiologist fatigue and radiologic error stemming from fatigue; experimental results measured as accuracy, error, or performance; and peer-reviewed publication. The risk of bias was addressed by including both quantitative and qualitative studies. RESULTS: Twenty-seven articles were included, mainly primary research articles. Common outcome measures included subjective self-reports and tests to measure eyestrain. Reaction time was also recorded, accounting for variables such as age and experience. One group recommended that guidelines should be implemented regarding number of hours worked. Most recommended ergonomic interventions, proposing the implementation of tools to measure and standardize fatigue and optimize workflow, in conjunction with considering radiologists individually. Education in appropriate viewing habits and breaks were also suggested. Only one study with seven participants recommended that radiologists should sleep well to improve their performance and overall well-being, despite the undeniable evidence that radiologists are fatigued. CONCLUSION: Fatigue is present in radiology and affects diagnostic accuracy.

Age-Specific Sex Differences in Magnetic Resonance Imaging-Depicted Carotid Intraplaque Hemorrhage.

BACKGROUND AND PURPOSE: Stroke rates are higher in men compared with women in the fourth through seventh decades of life, and higher rates may result from differences in carotid intraplaque hemorrhage (IPH), an unstable atherosclerotic plaque component. We report age-specific sex differences in the presence of magnetic resonance imaging-depicted carotid IPH. METHODS: Patients (n=1115) underwent magnetic resonance imaging for carotid IPH between 2005 and 2014. Low-grade carotid stenosis patients (n=906) without prior endarterectomy were eligible for this cross-sectional study. RESULTS: Of the 906 patients included (mean age±SD in years, 66.98±15.15), 63 (6.95%) had carotid IPH. In men and women, carotid IPH was present in 11.43% (48 of 420) and 3.09% (15 of 486), respectively (P<0.0001). Multivariable logistic regression analysis confirmed greater odds of carotid IPH in men for all ages: 45 to 54 (odds ratio=45.45; 95% confidence interval, 3.43-500), 55 to 64 years (odds ratio=21.74; 95% confidence interval, 3.21-142.86), 65 to 74 years (odds ratio=10.42; 95% confidence interval, 2.91-37.04), and ≥75 years (odds ratio=5.00; 95% confidence interval, 2.31-10.75). Male sex modified the effect of age on the presence of carotid IPH (ß=0.074; SE=0.036; P=0.0411). CONCLUSIONS: Men have greater age-specific odds of magnetic resonance imaging-depicted carotid IPH compared with women. With increasing age post-menopause, the odds of carotid IPH in women becomes closer to that of men. Delayed onset of carotid IPH in women, an unstable plaque component, may partly explain differential stroke rates between sexes, and further studies are warranted.

Diagnostic criteria for cryopyrin-associated periodic syndrome (CAPS).

Cryopyrin-associated periodic syndrome (CAPS) is a rare, heterogeneous disease entity associated with NLRP3 gene mutations and increased interleukin-1 (IL-1) secretion. Early diagnosis and rapid initiation of IL-1 inhibition prevent organ damage. The aim of the study was to develop and validate diagnostic criteria for CAPS. An innovative process was followed including interdisciplinary team building, item generation: review of CAPS registries, systematic literature review, expert surveys, consensus conferences for item refinement, item reduction and weighting using 1000Minds decision software. Resulting CAPS criteria were tested in large cohorts of CAPS cases and controls using correspondence analysis. Diagnostic models were explored using sensitivity analyses. The international team included 16 experts. Systematic literature and registry review identified 33 CAPS-typical items; the consensus conferences reduced these to 14. 1000Minds exercises ranked variables based on importance for the diagnosis. Correspondence analysis determined variables consistently associated with the diagnosis of CAPS using 284 cases and 837 controls. Seven variables were significantly associated with CAPS (p<0.001). The best diagnosis model included: Raised inflammatory markers (C-reactive protein/serum amyloid A) plus ≥two of six CAPS-typical symptoms: urticaria-like rash, cold-triggered episodes, sensorineural hearing loss, musculoskeletal symptoms, chronic aseptic meningitis and skeletal abnormalities. Sensitivity was 81%, specificity 94%. It performed well for all CAPS subtypes and regardless of NLRP3 mutation. The novel approach integrated traditional methods of evidence synthesis with expert consensus, web-based decision tools and innovative statistical methods and may serve as model for other rare diseases. These criteria will enable a rapid diagnosis for children and adults with CAPS.

Countermeasures against methotrexate intolerance in juvenile idiopathic arthritis instituted by parents show no effect.

Objectives: A high proportion of children with JIA will develop intolerance to MTX with anticipatory and associative gastrointestinal adverse effects. Parents and physicians frequently try to alleviate these symptoms with a variety of countermeasures. The objective of this study was to investigate the course of MTX intolerance within a 6 month period, and the effects of countermeasures on MTX intolerance severity. Methods: We performed a prospective study of 196 consecutive JIA patients treated with MTX. Intolerance was determined using the Methotrexate Intolerance Severity Score (MISS) questionnaire. MISS and countermeasures instituted by parents or physicians were determined at four time points, each 2 months apart. Countermeasures, classified into four types (antiemetic drugs, covert dosing, taste masking and complementary medicine), were analysed using non-parametric statistics and mixed linear modelling, adjusted by propensity scoring for use of countermeasures. Results: Ninety patients (46%) showed MTX intolerance, with 58 (64%) using countermeasures at time of inclusion. Median MISS at inclusion was 11 (interquartile range = 8.0-14.25), and did not change significantly over time. No significant difference in MISS score was observed between patients receiving countermeasures and those who did not. For specific countermeasures, MISS did not change significantly after introduction. Sensitivity analysis adjusting for propensity score indicated no significant association of MISS severity on parents' decision to implement any countermeasures. Conclusion: MTX intolerance was present in many children with JIA and symptoms decreased little in the short term. Various modalities used as countermeasures against nausea by parents showed no discernible effect.

Departmental h-Index: Evidence for Publishing Less?

PURPOSE: The h-index is an established method for determining an individual faculty member's impact on the scientific literature. The purpose of this study was to measure and describe over time the combined h-index of a large university medical imaging department. MATERIALS AND METHODS: All faculty members from the Department of Medical Imaging, University of Toronto, were identified from administrative records for 6 separate years between 2000-2014. Individual members' and the departmental h-index were calculated using citation data from the Scopus database. Descriptive univariate statistics were reported. Factors contributing to the change in departmental h-index over time were assessed using linear regression analysis. RESULTS: The number of faculty members increased from 117 in 2000 to 186 in 2014. The departmental h-index increased from 48 in 2000 to 142 in 2014. During this time period, the median h-index for faculty members increased from 4 (interquartile range 2-8) to 10 (interquartile range 5-19). Regression analysis revealed that for every additional staff member, the departmental h-index increased by 1.4 (standard error = 0.1, P < .01), whereas, by increasing the median h-index of members by 1 the departmental h-index increased by 15.7 (standard error = 0.6, P < .01). CONCLUSION: Our study suggests that to increase a department's h-index, it is important to foster impactful research from within the faculty ranks of the department. The h-index of academic radiology departments is a meaningful tool that allows for evaluation from within and against other academic centres.

Presentation and outcome of paediatric membranous non-proliferative lupus nephritis.

BACKGROUND: Studies of paediatric patients with membranous lupus nephritis (MLN) have yielded variable results, mostly due to the inclusion of mixed, i.e. proliferative nephritis. The aim of this study was to describe clinical and laboratory findings at the diagnosis of paediatric non-proliferative MLN, report the outcome and identify predictors of remission. METHODS: A single-center cohort study of consecutive children diagnosed with non-proliferative MLN was performed. Clinical and laboratory measures and treatment regimens were obtained in prospective standardized assessments. Renal outcome was measured by renal parameters and steroid requirement. Predictors for remission and time to remission were determined. RESULTS: A total of 30 children were identified with a median follow-up time 4.1 years. Of 21 patients followed for more than 2 years, 19 (90 %) achieved clinical remission, and 16 (76 %) achieved a state of maintained clinical remission on low-dose prednisone. Three patients developed proliferative nephritis on subsequent renal biopsy. Lower albumin at the time of biopsy was correlated with a lower rate of remission and longer time to remission. CONCLUSIONS: Among our paediatric patient cohort the outcome of non-proliferative MLN in systemic lupus erythematosus was good. The majority of patients did not require aggressive immunosuppressive treatment to reach a stable disease state on low-dose steroid treatment.

Using diffusion models to generate synthetic labeled data for medical image segmentation.

PURPOSE: Medical image analysis has become a prominent area where machine learning has been applied. However, high-quality, publicly available data are limited either due to patient privacy laws or the time and cost required for experts to annotate images. In this retrospective study, we designed and evaluated a pipeline to generate synthetic labeled polyp images for augmenting medical image segmentation models with the aim of reducing this data scarcity. METHODS: We trained diffusion models on the HyperKvasir dataset, comprising 1000 images of polyps in the human GI tract from 2008 to 2016. Qualitative expert review, Fréchet Inception Distance (FID), and Multi-Scale Structural Similarity (MS-SSIM) were tested for evaluation. Additionally, various segmentation models were trained with the generated data and evaluated using Dice score (DS) and Intersection over Union (IoU). RESULTS: Our pipeline produced images more akin to real polyp images based on FID scores. Segmentation model performance also showed improvements over GAN methods when trained entirely, or partially, with synthetic data, despite requiring less compute for training. Moreover, the improvement persists when tested on different datasets, showcasing the transferability of the generated images. CONCLUSIONS: The proposed pipeline produced realistic image and mask pairs which could reduce the need for manual data annotation when performing a machine learning task. We support this use case by showing that the methods proposed in this study enhanced segmentation model performance, as measured by Dice and IoU scores, when trained fully or partially on synthetic data.

Increased Prevalence of the Electrocardiographic Early Repolarization Pattern in Young Patients With Vagally Mediated Syncope: A Case-Control Study.

Background: Electrocardiographic early repolarization (EER) is linked with idiopathic ventricular fibrillation in adults. It is frequently seen in children, with poorly understood significance. Some evidence suggests that it could be a vagally mediated phenomenon. A retrospective case-control study was undertaken to test the hypothesis that EER is more common among children with typical vasovagal syncope (VVS) than among their peers with nonvagal syncope (NVS) or with no syncope. Methods: Patients aged 4-18 years with syncope were identified by a single-centre database search followed by a review of history for features of VVS (n = 150) or NVS (n = 84). The first available electrocardiogram (ECG) for VVS or for NVS was retrieved. Age- and sex-matched children with no known syncope or heart disease were then identified (n = 216). ECGs were assessed separately for EER based on published criteria by 2 observers blinded to patients' clinical status. Results: Mean age was 12.3 ± 3.2 years, and heart rate was 74.2 ± 16.5 beats/min. EER was more prevalent in VVS (33.3%) than among patients with NVS (19.1%; odds ratio: 2.29; confidence interval: 1.32-5.50) or among those with no syncope (12.5%; odds ratio: 3.14; confidence interval: 1.81-5.46). Heart rates were significantly lower in VVS and NVS (heart rate: 70.1 ± 13.8 and 70.7 ± 12.4 beats/min, respectively) compared with children with no syncope (heart rate: 78.2 ± 18.0 beats/min), both P < 0.001. Conclusions: EER is more common in paediatric patients with VVS than those with NVS or without syncope, consistent with a possible vagal contribution to the ECG finding.

Contexte: La repolarisation précoce (RP) à l'électrocardiogramme (ECG) est liée à une fibrillation ventriculaire idiopathique chez les adultes. Fréquente chez les enfants, sa signification est toutefois nébuleuse. Certaines données laissent penser qu'il pourrait s'agir d'un phénomène d'origine vagale. Une étude rétrospective cas-témoins a donc été réalisée dans le but de vérifier l'hypothèse selon laquelle la RP à l'ECG est plus courante chez les enfants atteints de syncope vasovagale (SVV) typique que chez leurs pairs atteints de syncope non vagale (SNV) ou non atteints de syncope. Méthodologie: Des patients de 4 à 18 ans atteints de syncope ont été recensés au moyen d'une recherche dans la base de données d'un centre, suivie d'un examen des antécédents visant à retracer des manifestations de SVV (n = 150) ou de SNV (n = 84). Le premier ECG disponible traduisant une SVV ou une SNV a été récupéré. Un appariement selon l'âge et le sexe entre les sujets atteints et des enfants qui n'étaient pas atteints de syncope ni de maladie cardiaque (n = 216) a ensuite été effectué. Deux observateurs qui ne connaissaient pas l'état clinique des enfants ont évalué les ECG séparément, à la recherche d'une RP, en se basant sur les critères publiés. Résultats: L'âge moyen des sujets était de 12,3 ± 3,2 ans et la fréquence cardiaque moyenne, de 74,2 ± 16,5 battements/minute. La prévalence de la RP à l'ECG était plus élevée chez les patients atteints de SVV (33,3 %) que chez les patients atteints de SNV (19,1 %; rapport de cotes [RC] : 2,29; intervalle de confiance [IC] : 1,32-5,50) ou les enfants non atteints de syncope (12,5 %; RC : 3,14; IC : 1,81-5,46). La fréquence cardiaque (FC) était significativement plus faible chez les sujets atteints de SVV ou de SNV (FC : 70,1 ± 13,8 et 70,7 ± 12,4 battements/minute, respectivement), en comparaison des enfants non atteints de syncope (FC : 78,2 ± 18,0 battements/minute); p < 0,001 dans les deux cas. Conclusion: La repolarisation précoce à l'ECG est plus courante chez les enfants atteints de syncope vasovagale que chez les enfants atteints de syncope non vagale ou non atteints de syncope, ce qui concorde avec une possible composante vagale dans le tracé de l'ECG.

Causal Forest Machine Learning Analysis of Parkinson's Disease in Resting-State Functional Magnetic Resonance Imaging.

In recent years, Artificial Intelligence has been used to assist healthcare professionals in detecting and diagnosing neurodegenerative diseases. In this study, we propose a methodology to analyze functional Magnetic Resonance Imaging signals and perform classification between Parkinson's disease patients and healthy participants using Machine Learning algorithms. In addition, the proposed approach provides insights into the brain regions affected by the disease. The functional Magnetic Resonance Imaging from the PPMI and 1000-FCP datasets were pre-processed to extract time series from 200 brain regions per participant, resulting in 11,600 features. Causal Forest and Wrapper Feature Subset Selection algorithms were used for dimensionality reduction, resulting in a subset of features based on their heterogeneity and association with the disease. We utilized Logistic Regression and XGBoost algorithms to perform PD detection, achieving 97.6% accuracy, 97.5% F1 score, 97.9% precision, and 97.7%recall by analyzing sets with fewer than 300 features in a population including men and women. Finally, Multiple Correspondence Analysis was employed to visualize the relationships between brain regions and each group (women with Parkinson, female controls, men with Parkinson, male controls). Associations between the Unified Parkinson's Disease Rating Scale questionnaire results and affected brain regions in different groups were also obtained to show another use case of the methodology. This work proposes a methodology to (1) classify patients and controls with Machine Learning and Causal Forest algorithm and (2) visualize associations between brain regions and groups, providing high-accuracy classification and enhanced interpretability of the correlation between specific brain regions and the disease across different groups.