A General Bayesian Functional Spatial Partitioning Method for Multiple Region Discovery Applied to Prostate Cancer MRI.

Current protocols to estimate the number, size, and location of cancerous lesions in the prostate using multiparametric magnetic resonance imaging (mpMRI) are highly dependent on reader experience and expertise. Automatic voxel-wise cancer classifiers do not directly provide estimates of number, location, and size of cancerous lesions that are clinically important. Existing spatial partitioning methods estimate linear or piecewise-linear boundaries separating regions of local stationarity in spatially registered data and are inadequate for the application of lesion detection. Frequentist segmentation and clustering methods often require pre-specification of the number of clusters and do not quantify uncertainty. Previously, we developed a novel Bayesian functional spatial partitioning method to estimate the boundary surrounding a single cancerous lesion using data derived from mpMRI. We propose a Bayesian functional spatial partitioning method for multiple lesion detection with an unknown number of lesions. Our method utilizes functional estimation to model the smooth boundary curves surrounding each cancerous lesion. In a Reversible Jump Markov Chain Monte Carlo (RJ-MCMC) framework, we develop novel jump steps to jointly estimate and quantify uncertainty in the number of lesions, their boundaries, and the spatial parameters in each lesion. Through simulation we show that our method is robust to the shape of the lesions, number of lesions, and region-specific spatial processes. We illustrate our method through the detection of prostate cancer lesions using MRI.

What is it that you say you do here? Advocating for the critical role of data scientists in research infrastructure.

Clinical and academic research continues to become more complex as our knowledge and technology advance. A substantial and growing number of specialists in biostatistics, data science, and library sciences are needed to support these research systems and promote high-caliber research. However, that support is often marginalized as optional rather than a fundamental component of research infrastructure. By building research infrastructure, an institution harnesses access to tools and support/service centers that host skilled experts who approach research with best practices in mind and domain-specific knowledge at hand. We outline the potential roles of data scientists and statisticians in research infrastructure and recommend guidelines for advocating for the institutional resources needed to support these roles in a sustainable and efficient manner for the long-term success of the institution. We provide these guidelines in terms of resource efficiency, monetary efficiency, and long-term sustainability. We hope this work contributes to-and provides shared language for-a conversation on a broader framework beyond metrics that can be used to advocate for needed resources.

A Comparison and Evaluation of Two Commercially Available Metal Artifact Reduction Applications.

Objective: The angiography systems A (A) and B (B), both incorporated at our hospital, are equipped with metal artifact reduction (MAR) applications. In clinical practice, it is crucial to understand the characteristics of MAR in both systems given that endovascular treatments are occasionally administered with both. In this study, we compared the artifact reduction effects of MAR on equipment A and B and clarified the differences between the two systems. Methods: An artifact evaluation phantom was created using a cylindrical water phantom and an iodine contrast medium. The phantom was imaged, MAR processing was performed on the obtained images, and an isotropic quantitative evaluation of artifacts was performed by extreme value statistical analysis using the Gumbel distribution. Results: The MAR reduction effects were approximately 45% and 40% for equipment A and B at concentrations of 8300 and 6000, respectively. The MAR reduction effect in both devices exhibited different trends depending on the concentration. Conclusion: In clinical procedures that make use of absorbents in medium concentrations of approximately 3000-5000, such as n-butyl-2-cyanoacrylate and Onyx, it is necessary to understand the MAR characteristics of both devices and consider the use of alternative devices as an option.

XAI-Based Assessment of the AMURA Model for Detecting Amyloid-ß and Tau Microstructural Signatures in Alzheimer's Disease.

Brain microstructural changes already occur in the earliest phases of Alzheimer's disease (AD) as evidenced in diffusion magnetic resonance imaging (dMRI) literature. This study investigates the potential of the novel dMRI Apparent Measures Using Reduced Acquisitions (AMURA) as imaging markers for capturing such tissue modifications.Tract-based spatial statistics (TBSS) and support vector machines (SVMs) based on different measures were exploited to distinguish between amyloid-beta/tau negative (A[Formula: see text]-/tau-) and A[Formula: see text]+/tau+ or A[Formula: see text]+/tau- subjects. Moreover, eXplainable Artificial Intelligence (XAI) was used to highlight the most influential features in the SVMs classifications and to validate the results by seeing the explanations' recurrence across different methods.TBSS analysis revealed significant differences between A[Formula: see text]-/tau- and other groups in line with the literature. The best SVM classification performance reached an accuracy of 0.73 by using advanced measures compared to more standard ones. Moreover, the explainability analysis suggested the results' stability and the central role of the cingulum to show early sign of AD.By relying on SVM classification and XAI interpretation of the outcomes, AMURA indices can be considered viable markers for amyloid and tau pathology. Clinical impact: This pre-clinical research revealed AMURA indices as viable imaging markers for timely AD diagnosis by acquiring clinically feasible dMR images, with advantages compared to more invasive methods employed nowadays.

Application of multivariate binary logistic regression grouped outlier statistics and geospatial logistic model to identify villages having unusual health-seeking habits for childhood malaria in Malawi.

BACKGROUND: Early diagnosis and prompt treatment of malaria in young children are crucial for preventing the serious stages of the disease. If delayed treatment-seeking habits are observed in certain areas, targeted campaigns and interventions can be implemented to improve the situation. METHODS: This study applied multivariate binary logistic regression model diagnostics and geospatial logistic model to identify traditional authorities in Malawi where caregivers have unusual health-seeking behaviour for childhood malaria. The data from the 2021 Malawi Malaria Indicator Survey were analysed using R software version 4.3.0 for regressions and STATA version 17 for data cleaning. RESULTS: Both models showed significant variability in treatment-seeking habits of caregivers between villages. The mixed-effects logit model residual identified Vuso Jere, Kampingo Sibande, Ngabu, and Dzoole as outliers in the model. Despite characteristics that promote late reporting of malaria at clinics, most mothers in these traditional authorities sought treatment within twenty-four hours of the onset of malaria symptoms in their children. On the other hand, the geospatial logit model showed that late seeking of malaria treatment was prevalent in most areas of the country, except a few traditional authorities such as Mwakaboko, Mwenemisuku, Mwabulambya, Mmbelwa, Mwadzama, Zulu, Amidu, Kasisi, and Mabuka. CONCLUSIONS: These findings suggest that using a combination of multivariate regression model residuals and geospatial statistics can help in identifying communities with distinct treatment-seeking patterns for childhood malaria within a population. Health policymakers could benefit from consulting traditional authorities who demonstrated early reporting for care in this study. This could help in understanding the best practices followed by mothers in those areas which can be replicated in regions where seeking care is delayed.

Estimation of time-varying kernel densities and chronology of the impact of COVID-19 on financial markets.

The time-varying kernel density estimation relies on two free parameters: the bandwidth and the discount factor. We propose to select these parameters so as to minimize a criterion consistent with the traditional requirements of the validation of a probability density forecast. These requirements are both the uniformity and the independence of the so-called probability integral transforms, which are the forecast time-varying cumulated distributions applied to the observations. We thus build a new numerical criterion incorporating both the uniformity and independence properties by the mean of an adapted Kolmogorov-Smirnov statistic. We apply this method to financial markets during the onset of the COVID-19 crisis. We determine the time-varying density of daily price returns of several stock indices and, using various divergence statistics, we are able to describe the chronology of the crisis as well as regional disparities. For instance, we observe a more limited impact of COVID-19 on financial markets in China, a strong impact in the US, and a slow recovery in Europe.

[The actual issues of detection of risk factors and prevention of myocardium infarction in sailors].

In Russia, increases morbidity of myocardial infarction. The statistics of recent years demonstrate failure in meeting target indicators of national programs on reducing number of deaths from this disease. At that, able-bodied population is in high risk zone and their professional activity is under influence of large combination of risk factors of myocardial infarction. This risk area covers profession of seafarer that is characterized by irregular work schedule, high levels of stress and mental tension, low physical activity or, contrariwise, increased working loads, unbalanced diet, isotherm stress and interaction with harmful substances. Besides that, situation is aggravated by limited set of first medical aid measures at exacerbation of disease in view of remoteness from hospitalization centers. Thus, considering high mortality rate from myocardial infarction, it is extremely important for ship crews to have full and timely information about diagnostic, symptomatic and prevention of this disease. The article examines statistics data of morbidity and mortality of myocardial infarction in population of the Russian Federation on the basis of Rosstat data and target indicators of the National project "Health Care". The risk factors of myocardial infarction established by INTERHEART studies are analyzed. The specifics of work conditions of crew members of marine vessels are established. The collection of professional modifying risk factors was selected. The recommendations for their correction were developed to enhance efficiency of primary preventive measures and to decrease morbidity and mortality among seafarers.

Characterizing the Adoption and Experiences of Users of Artificial Intelligence-Generated Health Information in the United States: Cross-Sectional Questionnaire Study.

BACKGROUND: OpenAI's ChatGPT is a source of advanced online health information (OHI) that may be integrated into individuals' health information-seeking routines. However, concerns have been raised about its factual accuracy and impact on health outcomes. To forecast implications for medical practice and public health, more information is needed on who uses the tool, how often, and for what. OBJECTIVE: This study aims to characterize the reasons for and types of ChatGPT OHI use and describe the users most likely to engage with the platform. METHODS: In this cross-sectional survey, patients received invitations to participate via the ResearchMatch platform, a nonprofit affiliate of the National Institutes of Health. A web-based survey measured demographic characteristics, use of ChatGPT and other sources of OHI, experience characterization, and resultant health behaviors. Descriptive statistics were used to summarize the data. Both 2-tailed t tests and Pearson chi-square tests were used to compare users of ChatGPT OHI to nonusers. RESULTS: Of 2406 respondents, 21.5% (n=517) respondents reported using ChatGPT for OHI. ChatGPT users were younger than nonusers (32.8 vs 39.1 years, P<.001) with lower advanced degree attainment (BA or higher; 49.9% vs 67%, P<.001) and greater use of transient health care (ED and urgent care; P<.001). ChatGPT users were more avid consumers of general non-ChatGPT OHI (percentage of weekly or greater OHI seeking frequency in past 6 months, 28.2% vs 22.8%, P<.001). Around 39.3% (n=206) respondents endorsed using the platform for OHI 2-3 times weekly or more, and most sought the tool to determine if a consultation was required (47.4%, n=245) or to explore alternative treatment (46.2%, n=239). Use characterization was favorable as many believed ChatGPT to be just as or more useful than other OHIs (87.7%, n=429) and their doctor (81%, n=407). About one-third of respondents requested a referral (35.6%, n=184) or changed medications (31%, n=160) based on the information received from ChatGPT. As many users reported skepticism regarding the ChatGPT output (67.9%, n=336), most turned to their physicians (67.5%, n=349). CONCLUSIONS: This study underscores the significant role of AI-generated OHI in shaping health-seeking behaviors and the potential evolution of patient-provider interactions. Given the proclivity of these users to enact health behavior changes based on AI-generated content, there is an opportunity for physicians to guide ChatGPT OHI users on an informed and examined use of the technology.

The geometry of admixture in population genetics: the blessing of dimensionality.

We present a geometry-based interpretation of the f-statistics framework, commonly used in population genetics to estimate phylogenetic relationships from genomic data. The focus is on the determination of the mixing coefficients in population admixture events subject to post-admixture drift. The interpretation takes advantage of the high dimension of the dataset and analyzes the problem as a dimensional reduction issue. We show that it is possible to think of the f-statistics technique as an implicit transformation of the genomic data from a phase space into a subspace where the mapped data structure is more similar to the ancestral admixture configuration. The two-way mixing coefficient is, as a matter of fact, carried out implicitly in this subspace. In addition, we propose the admixture test to be evaluated in the subspace because the comparison with the conventional one provides an important assessment of the admixture model. The overarching geometric framework provides slightly more general formulas than the f-formalism by using a different rationale as a starting point. Explicitly addressed are two-way and three-way admixtures. The mixture proportions are provided by suitable linear fits, in two or three dimensions, that can be easily visualized. The difficulties encountered with introgression and gene flow are also addressed. The developments and findings are illustrated with numerical simulations and real-world cases.

A Mixed Method Study in Young Children Participating in Clinical Research During A Kidney Transplantation Trajectory.

INTRODUCTION: Regulations designed to protect children participating in clinical research often restrict the availability of research data necessary for the development of age-specific therapies and drug dosing. Few data exist on how children experience participation in clinical research, and studies investigating young children undergoing an intensive medical treatment are lacking. METHODS: Mixed methods with semi-structured interviews and DISCO-RC questionnaires were used to explore young children's and their parents' experiences in clinical research participation during a kidney transplantation trajectory. FINDINGS: Nine children and their parents were interviewed. Children's median age at kidney transplantation was 4 years (IQR 4,7); age at interview was 7 years (IQR 6,9). Thematic content analysis of interviews revealed that most children were unaware of having participated in a study. Both children and their parents frequently were unaware whether procedures were standard care or research related. The additional burden attributed to study participation varied from not at all to heavy in combination with intensive medical treatment. Positive experiences included kind healthcare professionals, effective distraction techniques, educational aspects, contributing to science and extra check-ups. Most reported negative experiences were conflicting communication, spending much time in the hospital, missing school and suboptimal planning. Venous puncture was stressful for all children, whereas the discomfort of other procedures varied. CONCLUSION: Pediatric clinical research design should focus on education and fun during research procedures, smart planning, consistent communication, close collaboration between clinical and research team and age appropriate distraction techniques.

Building and validating trend-based multiple sclerosis case definitions: a population-based cohort study for Manitoba, Canada.

OBJECTIVE: This study aims to (1) build and validate model-based case definitions for multiple sclerosis (MS) that use trends (ie, trend-based case definitions) and (2) to apply dynamic classification to identify the average number of data years needed for classification (ie, average trend needed). DESIGN: Retrospective cohort study design. PARTICIPANTS: 608 MS cases and 59 620 MS non-cases. SETTING: Data from 1 April 2004 to 31 March 2022 were obtained from the Manitoba Population Research Data Repository. MS case status was ascertained from homecare records and linked to health data. Trend-based case definitions were constructed using multivariate generalised linear mixed models applied to annual numbers of general and specialist physician visits, hospitalisations and MS healthcare contacts or medication dispensations. Dynamic classification, which ascertains cases and non-cases annually, was used to estimate mean classification time. Classification accuracy performance measures, including sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), proportion correctly classified (PCC) and F1-scores, were compared for trend-based case definitions and a deterministic case definition of 3+MS healthcare contacts or medication dispensations. RESULTS: When applied to the full study period, classification accuracy performance measure estimates for all case definitions exceeded 0.90, except sensitivity and PPV for the trend-based dynamic case definition (0.88, 0.64, respectively). PCC was high for all case definitions (0.94-0.99); F1-scores were lower for the trend-based case definitions compared with the deterministic case definition (0.74-0.93 vs 0.96). Dynamic classification identified 5 years as the average trend needed. When applied to the average trend windows, accuracy estimates for trend-based case definitions were lower than the estimates from the full study period (sensitivity: 0.77-0.89; specificity: 0.90-0.97; PPV: 0.54-0.81; NPV: 0.97-0.99; F1-score: 0.64-0.84). Accuracy estimates for the deterministic case definition remained high, except sensitivity (0.42-0.80). F1-score was variable (0.59-0.89). CONCLUSIONS: Trend-based and deterministic case definitions classifications were similar to a population-based clinician assessment reference standard for multiple measures of classification accuracy. However, accuracy estimates for both trend-based and deterministic case definitions varied as the years of data used for classification were reduced. Dynamic classification appears to be a viable option for identifying the average trend needed for trend-based case definitions.

Effects of Statistical Practices for Longitudinal Group Comparison of the Penetration-Aspiration Scale on Power and Effect Size Estimation: A Monte Carlo Simulation Study.

Multiple bolus trials are administered during clinical and research swallowing assessments to comprehensively capture an individual's swallowing function. Despite valuable information obtained from these boluses, it remains common practice to use a single bolus (e.g., the worst score) to describe the degree of dysfunction. Researchers also often collapse continuous or ordinal swallowing measures into categories, potentially exacerbating information loss. These practices may adversely affect statistical power to detect and estimate smaller, yet potentially meaningful, treatment effects. This study sought to examine the impact of aggregating and categorizing penetration-aspiration scale (PAS) scores on statistical power and effect size estimates. We used a Monte Carlo approach to simulate three hypothetical within-subject treatment studies in Parkinson's disease and head and neck cancer across a range of data characteristics (e.g., sample size, number of bolus trials, variability). Different statistical models (aggregated or multilevel) as well as various PAS reduction approaches (i.e., types of categorizations) were performed to examine their impact on power and the accuracy of effect size estimates. Across all scenarios, multilevel models demonstrated higher statistical power to detect group-level longitudinal change and more accurate estimates compared to aggregated (worst score) models. Categorizing PAS scores also reduced power and biased effect size estimates compared to an ordinal approach, though this depended on the type of categorization and baseline PAS distribution. Multilevel models should be considered as a more robust approach for the statistical analysis of multiple boluses administered in standardized swallowing protocols due to its high sensitivity and accuracy to compare group-level changes in swallowing function. Importantly, this finding appears to be consistent across patient populations with distinct pathophysiology (i.e., PD and HNC) and patterns of airway invasion. The decision to categorize a continuous or ordinal outcome should be grounded in the clinical or research question with recognition that scale reduction may negatively affect the quality of statistical inferences in certain scenarios.

Ultrasound normalized cumulative residual entropy imaging: Theory, methodology, and application.

BACKGROUND AND OBJECTIVE: Ultrasound information entropy imaging is an emerging quantitative ultrasound technique for characterizing local tissue scatterer concentrations and arrangements. However, the commonly used ultrasound Shannon entropy imaging based on histogram-derived discrete probability estimation suffers from the drawbacks of histogram settings dependence and unknown estimator performance. In this paper, we introduced the information-theoretic cumulative residual entropy (CRE) defined in a continuous distribution of cumulative distribution functions as a new entropy measure of ultrasound backscatter envelope uncertainty or complexity, and proposed ultrasound CRE imaging for tissue characterization. METHODS: We theoretically analyzed the CRE for Rayleigh and Nakagami distributions and proposed a normalized CRE for characterizing scatterer distribution patterns. We proposed a method based on an empirical cumulative distribution function estimator and a trapezoidal numerical integration for estimating the normalized CRE from ultrasound backscatter envelope signals. We presented an ultrasound normalized CRE imaging scheme based on the normalized CRE estimator and the parallel computation technique. We also conducted theoretical analysis of the differential entropy which is an extension of the Shannon entropy to a continuous distribution, and introduced a method for ultrasound differential entropy estimation and imaging. Monte-Carlo simulation experiments were performed to evaluate the estimation accuracy of the normalized CRE and differential entropy estimators. Phantom simulation and clinical experiments were conducted to evaluate the performance of the proposed normalized CRE imaging in characterizing scatterer concentrations and hepatic steatosis (n = 204), respectively. RESULTS: The theoretical normalized CRE for the Rayleigh distribution was π/4, corresponding to the case where there were ≥10 randomly distributed scatterers within the resolution cell of an ultrasound transducer. The theoretical normalized CRE for the Nakagami distribution decreased as the Nakagami parameter m increased, corresponding to that the ultrasound backscattered statistics varied from pre-Rayleigh to Rayleigh and to post-Rayleigh distributions. Monte-Carlo simulation experiments showed that the proposed normalized CRE and differential entropy estimators can produce a satisfying estimation accuracy even when the size of the test samples is small. Phantom simulation experiments showed that the proposed normalized CRE and differential entropy imaging can characterize scatterer concentrations. Clinical experiments showed that the proposed ultrasound normalized CRE imaging is capable to quantitatively characterize hepatic steatosis, outperforming ultrasound differential entropy imaging and being comparable to ultrasound Shannon entropy and Nakagami imaging. CONCLUSION: This study sheds light on the theory and methodology of ultrasound normalized CRE. The proposed ultrasound normalized CRE can serve as a new, flexible quantitative ultrasound envelope statistics parameter. The proposed ultrasound normalized CRE imaging may find applications in quantified characterization of biological tissues. Our code will be made available publicly at https://github.com/zhouzhuhuang.

Rapid measurement of soluble xylo-oligomers using near-infrared spectroscopy (NIRS) and multivariate statistics: calibration model development and practical approaches to model optimization.

BACKGROUND: Rapid monitoring of biomass conversion processes using techniques such as near-infrared (NIR) spectroscopy can be substantially quicker and less labor-, resource-, and energy-intensive than conventional measurement techniques such as gas or liquid chromatography (GC or LC) due to the lack of solvents and preparation methods, as well as removing the need to transfer samples to an external lab for analytical evaluation. The purpose of this study was to determine the feasibility of rapid monitoring of a biomass conversion process using NIR spectroscopy combined with multivariate statistical modeling, and to examine the impact of (1) subsetting the samples in the original dataset by process location and (2) reducing the spectral range used in the calibration model on model performance. RESULTS: We develop multivariate calibration models for the concentrations of soluble xylo-oligosaccharides (XOS), monomeric xylose, and total solids at multiple points in a biomass conversion process which produces and then purifies XOS compounds from sugar cane bagasse. A single model using samples from multiple locations in the process stream showed acceptable performance as measured by standard statistical measures. However, compared to the single model, we show that separate models built by segregating the calibration samples according to process location show improved performance. We also show that combining an understanding of the sample spectra with simple multivariate analysis tools can result in a calibration model with a substantially smaller spectral range that provides essentially equal performance to the full-range model. CONCLUSIONS: We demonstrate that real-time monitoring of soluble xylo-oligosaccharides (XOS), monomeric xylose, and total solids concentration at multiple points in a process stream using NIR spectroscopy coupled with multivariate statistics is feasible. Segregation of sample populations by process location improves model performance. Models using a reduced spectral range containing the most relevant spectral signatures show very similar performance to the full-range model, reinforcing the importance of performing robust exploratory data analysis before beginning multivariate modeling.

Suicide in the USA: A Decadal Study From the 1930s to the 2020s.

This study provides a decadal analysis of national suicide data over 90 years, offering a comprehensive view of long-term trends and current levels in the United States. We analyzed mean decadal suicide numbers, rates, and confidence intervals from the 1930s to the early 2020s across demographic categories including sex, race, and age. Our findings reveal that suicide rates in the 2020s are the highest since the 1930s. The data indicate significant variations across groups; the 2020s show the highest suicide rates for both Whites and Nonwhites, and individuals under 44 years of age. Conversely, men's suicide rates were slightly lower than those in the 1930s, whereas rates for women and older adults peaked during the 1930s. The results underscore the need for ongoing surveillance of suicide trends and proactive suicide prevention measures by governmental and other relevant organizations.

Statistical design for health monitoring in laboratory animal facilities using sentinel animals.

Regular health monitoring is crucial in laboratory animal facilities to determine the presence or absence of specific pathogens. One common approach to monitoring involves the use of sentinel animals, which are periodically exposed to biological material from the cages being monitored. At a certain point, some of these sentinel animals are tested for pathogens. This article discusses designing an effective sampling scheme to meet desired quality standards. It addresses questions such as the number of sentinel animals required, the frequency of sampling biological material, the selection of cages based on facility set-up, and the optimal frequency and quantity of sentinel animal tests. While existing design formulas are available for simple random sampling, no quantitative recommendation exists for using sentinel animals to the best of our knowledge. We propose a Monte Carlo simulation-based approach in this article to address this. Our algorithm has been implemented in a publicly accessible web page at http://nolan.cnb.csic.es/sentinelcagesmanager.

Trends in Surgical and Nonsurgical Aesthetic Procedures: A 14-Year Analysis of the International Society of Aesthetic Plastic Surgery-ISAPS.

INTRODUCTION: As part of the International Society of Aesthetic Plastic Surgery, we present an analysis of our global aesthetic statistics, fulfilling the role of a worldwide organization of plastic surgeons with a clear mission to disseminate aesthetic education worldwide, promote patient safety, protect high ethical standards, and communicate. MATERIAL AND METHODS: A retrospective analysis of the ISAPS Global Aesthetic Statistics was conducted annually from 2010 to 2023. The design and analysis of each survey was carefully developed and validated by Industry Insights, Inc. prior to distribution. Participants were recruited using an anonymous online questionnaire that focused primarily on the number of surgical and nonsurgical procedures performed in the previous year, as well as questions related to surgeon demographics and the prevalence of medical tourism. ISAPS invited all physicians in their data base who were board-certified plastic surgeons or equivalent and suggested National Societies to encourage their members to participate. RESULTS: The latest survey reported a global increase in 3.4%, including 34.9 million surgical and nonsurgical aesthetic procedures performed by plastic surgeons in 2023. More than 15.8 million surgical procedures and more than 19.1 million nonsurgical procedures were performed worldwide. During the past decade, a steady increase in aesthetic procedures has been observed, which has been more pronounced since 2021. In the last 4 years, the overall increase in procedures was 40%. SURGICAL PROCEDURES: The top five surgical procedures were liposuction, breast augmentation, eyelid surgery, abdominoplasty, and rhinoplasty. This trend has been stable for 14 years, with the exception of 2022, when breast lift surgery temporarily replaced rhinoplasty. FACE AND HEAD PROCEDURES: These procedures continue to be the most popular. This group included brow lift, ear surgery, eyelid surgery, facelift, facial bone contouring, facial fat grafting, lip augmentation or frontal surgery, neck lift, and rhinoplasty. BODY AND EXTREMITIES PROCEDURES: This group included abdominoplasty, buttock augmentation, buttock lift, liposuction, lower body lift, thigh lift, arm lift, upper body lift, labiaplasty, and vaginal rejuvenation. Over the past 14 years, body and extremity procedures have increased, with more than 5.1 million procedures in 2023 compared to 2.6 million in 2009. NONSURGICAL PROCEDURES: The five most popular nonsurgical procedures are botulinum toxin, hyaluronic acid, hair removal, chemical peels, and nonsurgical fat reduction. In 2022, chemical peels will replace nonsurgical skin tightening in the top five. MALE AESTHETIC SURGERY: Procedures performed on men continue to grow, with minimally invasive procedures dominating. The most recent survey reported that they represented 14.5% of the total. The top five surgical procedures were eyelid surgery, gynecomastia, liposuction, rhinoplasty, and facial fat grafting. The most popular nonsurgical procedures for men were botulinum toxin, hyaluronic acid, hair removal, nonsurgical skin tightening, and nonsurgical fat reduction. This trend has held steady for more than a decade. DISCUSSION: This study analyzes the most recent data and experience of board-certified aesthetic plastic surgeons in surgical and nonsurgical procedures worldwide over 14 years and provides insight into future trends. More than 60 years have passed since the introduction of liposuction, being one of the most performed aesthetic procedures worldwide over the past 14 years and currently number one procedure performed by plastic surgeons. New trends and technologies have evolved over the years, however, plastic surgeons must be cautious, as history has shown that risks increase when new technologies are introduced. With the popularity of liposuction, other body contouring procedures began to gain interest, and in 2015, gluteal lipoinjections were added to the ISAPS global aesthetic statistics and with them complications arise. In 2018 and 2019, the major patient safety societies, ISAPS, ASERF, ASPS, and ASAPS, began a systematic educational campaign to inform their members about the inherent risks of performing gluteal fat transfer surgery and what techniques or equipment can be used to minimize risks. Another procedure added to the ISAPS statistics in 2010 was vaginal aesthetic surgery. With the new trend of vaginal aesthetics, many believed that they were just changing the appearance of the area, but today it is clear that they are here for much more, to truly empower women with their sexuality. Breast augmentation showed a decline for the first-time last year. However, breast augmentation and liposuction have been the most performed procedures by plastic surgeons worldwide for more than a decade. On the other hand, implant removal has been the fastest growing procedure since 2015, with an overall increase in 46.3% over the past 5 years. In relation to male aesthetic surgery, the number of men undergoing aesthetic procedures has remained stable in recent years at around 14%. Male aesthetics is certainly a growing trend, and our practices should be more inclusive. Another prominent field is regenerative medicine. In relation to plastic surgery, regenerative surgery strategies often involve adipose tissue with stem cells and preadipocytes, alone or in combination with scaffolds. In terms of prevention, regenerative medicine aims to improve the quality of the skin by improving our outcomes and would make it possible to avoid the need for facelifts in the future. Finally, given the increasing popularity of medical procedures abroad ("medical tourism") and the fact that safety regulations and guidelines vary widely from place to place, we encourage patients to choose a board-certified, specialized, trained and experienced plastic surgeon for their procedure and an accredited surgical facility to ensure the procedure in done under the highest patient safety standards. CONCLUSIONS: Despite the obvious cultural and social differences from country to country that make certain procedures more desirable in some geographic areas and less so in other parts of the world, the results of this study show a significant overall increase in all surgical and nonsurgical procedures aimed at improving the aesthetic appearance of the body during14 years. As plastic surgeons, we are open to new possibilities in aesthetic procedures and are responsible for patient safety protocols and procedures. LEVEL OF EVIDENCE III: This journal requires that authors assign a level of evidence to each article. For a full description of these Evidence-Based Medicine ratings, please refer to the Table of Contents or the online Instructions to Authors www.springer.com/00266 .

A dependent circular-linear model for multivariate biomechanical data: Ilizarov ring fixator study.

Biomechanical and orthopaedic studies frequently encounter complex datasets that encompass both circular and linear variables. In most cases (i) the circular and linear variables are considered in isolation with dependency between variables neglected and (ii) the cyclicity of the circular variables is disregarded resulting in erroneous decision making. Given the inherent characteristics of circular variables, it is imperative to adopt methods that integrate directional statistics to achieve precise modelling. This paper is motivated by the modelling of biomechanical data, that is, the fracture displacements, that is used as a measure in external fixator comparisons. We focus on a dataset, based on an Ilizarov ring fixator, comprising of six variables. A modelling framework applicable to the six-dimensional joint distribution of circular-linear data based on vine copulas is proposed. The pair-copula decomposition concept of vine copulas represents the dependence structure as a combination of circular-linear, circular-circular and linear-linear pairs modelled by their respective copulas. This framework allows us to assess the dependencies in the joint distribution as well as account for the cyclicity of the circular variables. Thus, a new approach for accurate modelling of mechanical behaviour for Ilizarov ring fixators and other data of this nature is imparted.