Domestic and International Cosmetic Tourism Complications Presenting to a U.S. Tertiary Hospital.

BACKGROUND: Cosmetic surgery tourism has become a significant global industry. Oftentimes, patients who develop postoperative complications present for care in their home U.S. state. OBJECTIVES: This study evaluated patients who either traveled abroad or to other states within the United States for cosmetic surgeries and returned with complications treated in the authors' center. We sought to compare rates of complications between patients that underwent cosmetic surgery internationally and domestically. METHODS: This retrospective cross-sectional study reviewed patients who presented from June 2014 to June 2022 with concerns related to cosmetic surgeries performed in another state or abroad. Binary logistic regressions were performed to assess differences in outcomes between domestic and international cases, including complications, interventions, and admissions. RESULTS: One-hundred twenty-three patients (97.6% female, me an age 34.0 ± 8.7 years, range 16-62 years) comprised 159 emergency department consultations. The most common procedures included abdominoplasty (n=72) and liposuction (n=56). Complications included wound dehiscence (n=39), infection (n=38), and seroma (n=34). Over one-half of patients required intervention. Twenty-nine patients (23.6%) required hospital admission. On multivariate regression analyses, incidence of seroma (p=0.025) and oral (p=0.036) and intravenous antibiotic prescriptions (p=0.045) were significantly greater among the international cohort compared to domestic, whereas all other complication variables were non-significant. There were no other significant differences in operative interventions or hospital admissions between international and domestic cohorts. CONCLUSIONS: Compared to domestic tourism cases, international tourism cases were associated with significantly higher rates of seroma formation and antibiotic use. There were no significant differences otherwise in overall complications including infections, operative interventions, or hospital admissions.

Super-resolution neural networks improve the spatiotemporal resolution of adaptive MRI-guided radiation therapy.

BACKGROUND: Magnetic resonance imaging (MRI) offers superb non-invasive, soft tissue imaging of the human body. However, extensive data sampling requirements severely restrict the spatiotemporal resolution achievable with MRI. This limits the modality's utility in real-time guidance applications, particularly for the rapidly growing MRI-guided radiation therapy approach to cancer treatment. Recent advances in artificial intelligence (AI) could reduce the trade-off between the spatial and the temporal resolution of MRI, thus increasing the clinical utility of the imaging modality. METHODS: We trained deep learning-based super-resolution neural networks to increase the spatial resolution of real-time MRI. We developed a framework to integrate neural networks directly onto a 1.0 T MRI-linac enabling real-time super-resolution imaging. We integrated this framework with the targeting system of the MRI-linac to demonstrate real-time beam adaptation with super-resolution-based imaging. We tested the integrated system using large publicly available datasets, healthy volunteer imaging, phantom imaging, and beam tracking experiments using bicubic interpolation as a baseline comparison. RESULTS: Deep learning-based super-resolution increases the spatial resolution of real-time MRI across a variety of experiments, offering measured performance benefits compared to bicubic interpolation. The temporal resolution is not compromised as measured by a real-time adaptation latency experiment. These two effects, an increase in the spatial resolution with a negligible decrease in the temporal resolution, leads to a net increase in the spatiotemporal resolution. CONCLUSIONS: Deployed super-resolution neural networks can increase the spatiotemporal resolution of real-time MRI. This has applications to domains such as MRI-guided radiation therapy and interventional procedures.

Magnetic resonance imaging (MRI) is a medical imaging modality that is used to image organs such as the brain, lungs, and liver as well as diseases such as cancer. MRI scans taken at high resolution are of overly long duration. This time constraint limits the accuracy of MRI-guided cancer radiation therapy, where imaging must be fast to adapt treatment to tumour motion. Here, we deployed artificial intelligence (AI) models to achieve fast and high detail MRI. We additionally validated our AI models across various scenarios. These AI-based models could potentially enable people with cancer to be treated with higher accuracy and precision.

Boosting Your Context by Dual Similarity Checkup for In-Context Learning Medical Image Segmentation.

The recent advent of in-context learning (ICL) capabilities in large pre-trained models has yielded significant advancements in the generalization of segmentation models. By supplying domain-specific image-mask pairs, the ICL model can be effectively guided to produce optimal segmentation outcomes, eliminating the necessity for model fine-tuning or interactive prompting. However, current existing ICL-based segmentation models exhibit significant limitations when applied to medical segmentation datasets with substantial diversity. To address this issue, we propose a dual similarity checkup approach to guarantee the effectiveness of selected in-context samples so that their guidance can be maximally leveraged during inference. We first employ large pre-trained vision models for extracting strong semantic representations from input images and constructing a feature embedding memory bank for semantic similarity checkup during inference. Assuring the similarity in the input semantic space, we then minimize the discrepancy in the mask appearance distribution between the support set and the estimated mask appearance prior through similarity-weighted sampling and augmentation. We validate our proposed dual similarity checkup approach on eight publicly available medical segmentation datasets, and extensive experimental results demonstrate that our proposed method significantly improves the performance metrics of existing ICL-based segmentation models, particularly when applied to medical image datasets characterized by substantial diversity.

The Impact of a Centralized Plastic Surgery Research Infrastructure on Scholarly Productivity and Output.

Although research and innovation is a key within the field of plastic and reconstructive surgery, the impact of team structure, interpersonal dynamics, and/or standardized infrastructure on scholarly output has been infrequently studied. In this work, we present the formation and implementation of a novel plastic surgery research program that aims to unite previously disparate clinical and translational research efforts at our institution to facilitate critical inquiry. From July 2022 to June 2023, our department launched a pilot research program based on three pillars: (1) formalization of a research curriculum (monthly research meetings for agenda setting and discussion for project honing, formal research leadership for meeting facilitation and workflow regulation), (2) development of a centralized database to compile ongoing research (Google Drive repository to house all ongoing research documents, facilitate real-time editing, and provide resources/templates for assisting in the research process), and (3) bolstering of a core research identity built on mentorship and collaboration (more frequent interactions to shift previously siloed faculty-student mentorship into a robust milieu of intercollaboration). During the first year, we saw an increased number of publications and presentations, as well as robust participation and contribution from faculty, residents, and medical students. Future directions will focus on addressing resource limitation, such as project idea availability and funding, to sustain the success and growth of this novel research infrastructure.

Alpha Defensin-1 Level Correlates with Periprosthetic Infection Severity following Implant-based Breast Reconstruction.

Background: Accurate diagnosis of periprosthetic infections following breast reconstructions is paramount to reduce morbidity. Alpha defensin-1 (AD-1) is an antimicrobial peptide released by neutrophils. This study evaluates the relationship between quantitative AD-1 levels and infection severity in patients with suspected periprosthetic infection. Methods: Retrospective review was conducted of patients with prior breast implant reconstruction undergoing surgery for either suspected infection or prosthesis exchange and revision. The AD-1 level in periprosthetic fluid was sent for quantitative analysis. Association between AD-1 levels with outcomes, management, systemic markers of infection, and overall infection severity was evaluated. Results: Thirty-eight breasts were included. Infected breasts had higher AD-1 levels (3.91 versus 0.14, P < 0.01), greater odds of erythema [odds ratio (OR) 2.98 (1.53-5.82), P = 0.01], purulence [OR 2.84 (1.51-5.35), P = 0.01], fever [OR 1.84 (1.15-2.93), P = 0.01], threatened implant exposure [OR 2.97 (1.48-5.95), P < 0.01], and true implant exposure [OR 1.79 (1.04-3.08), P = 0.04]. Increasing AD-1 was an independent risk factor for washout (P < 0.01), and explant [OR 2.48 (1.47-4.2), P < 0.01]. AD-1 positively correlated with white blood cell count (ß = 1.81 cells/µL, P < 0.01), and serum lactate (ß = 0.19 meq/L, P < 0.04). Increasing AD-1 level was an independent predictor of infection severity (χ² = 22.77, P < 0.01). Conclusions: AD-1 levels correlate with infection severity, highlighting its potential both when clinical examination is ambiguous and when treatment response is being monitored. Although further evaluation is warranted, AD-1 may demonstrate utility in novel breast implant salvage algorithms.

Field-Scale Testing of a High-Efficiency Membrane Reactor (MR)-Adsorptive Reactor (AR) Process for H2 Generation and Pre-Combustion CO2 Capture.

The study objective was to field-validate the technical feasibility of a membrane- and adsorption-enhanced water gas shift reaction process employing a carbon molecular sieve membrane (CMSM)-based membrane reactor (MR) followed by an adsorptive reactor (AR) for pre-combustion CO2 capture. The project was carried out in two different phases. In Phase I, the field-scale experimental MR-AR system was designed and constructed, the membranes, and adsorbents were prepared, and the unit was tested with simulated syngas to validate functionality. In Phase II, the unit was installed at the test site, field-tested using real syngas, and a technoeconomic analysis (TEA) of the technology was completed. All project milestones were met. Specifically, (i) high-performance CMSMs were prepared meeting the target H2 permeance (>1 m3/(m2.hbar) and H2/CO selectivity of >80 at temperatures of up to 300 °C and pressures of up to 25 bar with a <10% performance decline over the testing period; (ii) pelletized adsorbents were prepared for use in relevant conditions (250 °C < T < 450 °C, pressures up to 25 bar) with a working capacity of >2.5 wt.% and an attrition rate of <0.2; (iii) TEA showed that the MR-AR technology met the CO2 capture goals of 95% CO2 purity at a cost of electricity (COE) 30% less than baseline approaches.

Open-source hardware and software for the measurement, characterization, reporting, and correction of geometric distortion in MRI.

BACKGROUND: Geometric distortion is a serious problem in MRI, particularly in MRI guided therapy. A lack of affordable and adaptable tools in this area limits research progress and harmonized quality assurance. PURPOSE: To develop and test a suite of open-source hardware and software tools for the measurement, characterization, reporting, and correction of geometric distortion in MRI. METHODS: An open-source python library was developed, comprising modules for parametric phantom design, data processing, spherical harmonics, distortion correction, and interactive reporting. The code was used to design and manufacture a distortion phantom consisting of 618 oil filled markers covering a sphere of radius 150 mm. This phantom was imaged on a CT scanner and a novel split-bore 1.0 T MRI magnet. The CT images provide distortion-free dataset. These data were used to test all modules of the open-source software. RESULTS: All markers were successfully extracted from all images. The distorted MRI markers were mapped to undistorted CT data using an iterative search approach. Spherical harmonics reconstructed the fitted gradient data to 1.0 ± 0.6% of the input data. High resolution data were reconstructed via spherical harmonics and used to generate an interactive report. Finally, distortion correction on an independent data set reduced distortion inside the DSV from 5.5 ± 3.1 to 1.6 ± 0.8 mm. CONCLUSION: Open-source hardware and software for the measurement, characterization, reporting, and correction of geometric distortion in MRI have been developed. The utility of these tools has been demonstrated via their application on a novel 1.0 T split bore magnet.

Systematic Review of Prophylactic Plastic Surgery Closure to Prevent Postoperative Wound Complications Following Spine Surgery.

Spinal surgeries are increasingly performed in the United States, but complication rates can be unacceptably high at up to 26%. Consequently, plastic surgeons (PS) are sometimes recruited by spine surgeons (SS) for intraoperative assistance with soft tissue closures. An electronic multidatabase literature search was systematically conducted to determine whether spinal wound closure performed by PS minimizes postoperative wound healing complications when compared to closure by SS (neurosurgical or orthopedic), with the hypothesis that closures by PS minimizes incidence of complications. All published studies involving patients who underwent posterior spinal surgery with closure by PS or SS at index spine surgery were identified. Filtering by exclusion criteria identified 10 studies, 4 of which were comparative in nature and included both closures by PS and SS. Of these 4, none reported significant differences in postoperative outcomes between the groups. Across all studies, PS were involved in cases with higher baseline risk for wound complications and greater comorbidity burden. Closures by PS were significantly more likely to have had prior chemotherapy in 2 of the 4 (50%) studies (P = 0.014, P < 0.001) and radiation in 3 of the 4 (75%) studies (P < 0.001, P < 0.01, P < 0.001). In conclusion, closures by PS are frequently performed in higher risk cases, and use of PS in these closures may normalize the risk of wound complications to that of the normal risk cohort, though the overall level of evidence of the published literature is low.

Management of Acute Wounds-Expert Panel Consensus Statement.

Significance: The Wound Healing Foundation recognized the need for consensus-based unbiased recommendations for the treatment of wounds. As a first step, a consensus on the treatment of chronic wounds was developed and published in 2022. The current publication on acute wounds represents the second step in this process. Acute wounds may result from any number of conditions, including burns, military and combat operations, and trauma to specific areas of the body. The management of acute wounds requires timely and evidence-driven intervention to achieve optimal clinical outcomes. This consensus statement provides the clinician with the necessary foundational approaches to the causes, diagnosis, and therapeutic management of acute wounds. Presented in a structured format, this is a useful guide for clinicians and learners in all patient care settings. Recent Advances: Recent advances in the management of acute wounds have centered on stabilization and treatment in the military and combat environment. Specifically, advancements in hemostasis, resuscitation, and the mitigation of infection risk through timely initiation of antibiotics and avoidance of high-pressure irrigation in contaminated soft tissue injury. Critical Issues: Critical issues include infection control, pain management, and the unique considerations for the management of acute wounds in pediatric patients. Future Directions: Future directions include new approaches to preventing the progression and conversion of burns through the use of specific gel formulations. Additionally, the use of three-dimensional bioprinting and photo-modulation for reconstruction is a promising area for continued discovery.