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.

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.(1) 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 the microcapillary gel, a topical gel embedded with the anti-inflammatory drug infliximab.(38) Additionally, the use of three-dimensional bioprinting and photo-modulation for skin reconstruction following burns is a promising area for continued discovery.

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.

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.

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.

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.

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.

Real-time motion management in MRI-guided radiotherapy: Current status and AI-enabled prospects.

MRI-guided radiotherapy (MRIgRT) is a highly complex treatment modality, allowing adaptation to anatomical changes occurring from one treatment day to the other (inter-fractional), but also to motion occurring during a treatment fraction (intra-fractional). In this vision paper, we describe the different steps of intra-fractional motion management during MRIgRT, from imaging to beam adaptation, and the solutions currently available both clinically and at a research level. Furthermore, considering the latest developments in the literature, a workflow is foreseen in which motion-induced over- and/or under-dosage is compensated in 3D, with minimal impact to the radiotherapy treatment time. Considering the time constraints of real-time adaptation, a particular focus is put on artificial intelligence (AI) solutions as a fast and accurate alternative to conventional algorithms.

Genomic landscape of patients with germline RUNX1 variants and familial platelet disorder with myeloid malignancy.

ABSTRACT: Familial platelet disorder with associated myeloid malignancies (FPDMM) is caused by germline RUNX1 mutations and characterized by thrombocytopenia and increased risk of hematologic malignancies. We recently launched a longitudinal natural history study for patients with FPDMM. Among 27 families with research genomic data by the end of 2021, 26 different germline RUNX1 variants were detected. Besides missense mutations enriched in Runt homology domain and loss-of-function mutations distributed throughout the gene, splice-region mutations and large deletions were detected in 6 and 7 families, respectively. In 25 of 51 (49%) patients without hematologic malignancy, somatic mutations were detected in at least 1 of the clonal hematopoiesis of indeterminate potential (CHIP) genes or acute myeloid leukemia (AML) driver genes. BCOR was the most frequently mutated gene (in 9 patients), and multiple BCOR mutations were identified in 4 patients. Mutations in 6 other CHIP- or AML-driver genes (TET2, DNMT3A, KRAS, LRP1B, IDH1, and KMT2C) were also found in ≥2 patients without hematologic malignancy. Moreover, 3 unrelated patients (1 with myeloid malignancy) carried somatic mutations in NFE2, which regulates erythroid and megakaryocytic differentiation. Sequential sequencing data from 19 patients demonstrated dynamic changes of somatic mutations over time, and stable clones were more frequently found in older adult patients. In summary, there are diverse types of germline RUNX1 mutations and high frequency of somatic mutations related to clonal hematopoiesis in patients with FPDMM. Monitoring changes in somatic mutations and clinical manifestations prospectively may reveal mechanisms for malignant progression and inform clinical management. This trial was registered at www.clinicaltrials.gov as #NCT03854318.

Experimental comparison of linear regression and LSTM motion prediction models for MLC-tracking on an MRI-linac.

BACKGROUND: Magnetic resonance imaging (MRI)-guided radiotherapy with multileaf collimator (MLC)-tracking is a promising technique for intra-fractional motion management, achieving high dose conformality without prolonging treatment times. To improve beam-target alignment, the geometric error due to system latency should be reduced by using temporal prediction. PURPOSE: To experimentally compare linear regression (LR) and long-short-term memory (LSTM) motion prediction models for MLC-tracking on an MRI-linac using multiple patient-derived traces with different complexities. METHODS: Experiments were performed on a prototype 1.0 T MRI-linac capable of MLC-tracking. A motion phantom was programmed to move a target in superior-inferior (SI) direction according to eight lung cancer patient respiratory motion traces. Target centroid positions were localized from sagittal 2D cine MRIs acquired at 4 Hz using a template matching algorithm. The centroid positions were input to one of four motion prediction models. We used (1) a LSTM network which had been optimized in a previous study on patient data from another cohort (offline LSTM). We also used (2) the same LSTM model as a starting point for continuous re-optimization of its weights during the experiment based on recent motion (offline+online LSTM). Furthermore, we implemented (3) a continuously updated LR model, which was solely based on recent motion (online LR). Finally, we used (4) the last available target centroid without any changes as a baseline (no-predictor). The predictions of the models were used to shift the MLC aperture in real-time. An electronic portal imaging device (EPID) was used to visualize the target and MLC aperture during the experiments. Based on the EPID frames, the root-mean-square error (RMSE) between the target and the MLC aperture positions was used to assess the performance of the different motion predictors. Each combination of motion trace and prediction model was repeated twice to test stability, for a total of 64 experiments. RESULTS: The end-to-end latency of the system was measured to be (389 ± 15) ms and was successfully mitigated by both LR and LSTM models. The offline+online LSTM was found to outperform the other models for all investigated motion traces. It obtained a median RMSE over all traces of (2.8 ± 1.3) mm, compared to the (3.2 ± 1.9) mm of the offline LSTM, the (3.3 ± 1.4) mm of the online LR and the (4.4 ± 2.4) mm when using the no-predictor. According to statistical tests, differences were significant (p-value <0.05) among all models in a pair-wise comparison, but for the offline LSTM and online LR pair. The offline+online LSTM was found to be more reproducible than the offline LSTM and the online LR with a maximum deviation in RMSE between two measurements of 10%. CONCLUSIONS: This study represents the first experimental comparison of different prediction models for MRI-guided MLC-tracking using several patient-derived respiratory motion traces. We have shown that among the investigated models, continuously re-optimized LSTM networks are the most promising to account for the end-to-end system latency in MRI-guided radiotherapy with MLC-tracking.

Natural history study of patients with familial platelet disorder with associated myeloid malignancy.

ABSTRACT: Deleterious germ line RUNX1 variants cause the autosomal dominant familial platelet disorder with associated myeloid malignancy (FPDMM), characterized by thrombocytopenia, platelet dysfunction, and a predisposition to hematologic malignancies (HMs). We launched a FPDMM natural history study and, from January 2019 to December 2021, enrolled 214 participants, including 111 patients with 39 different RUNX1 variants from 45 unrelated families. Seventy of 77 patients had thrombocytopenia, 18 of 18 had abnormal platelet aggregometry, 16 of 35 had decreased platelet dense granules, and 28 of 55 had abnormal bleeding scores. Nonmalignant bone marrows showed increased numbers of megakaryocytes in 12 of 55 patients, dysmegakaryopoiesis in 42 of 55, and reduced cellularity for age in 30 of 55 adult and 17 of 21 pediatric cases. Of 111 patients, 19 were diagnosed with HMs, including myelodysplastic syndrome, acute myeloid leukemia, chronic myelomonocytic leukemia, acute lymphoblastic leukemia, and smoldering myeloma. Of those 19, 18 were relapsed or refractory to upfront therapy and referred for stem cell transplantation. In addition, 28 of 45 families had at least 1 member with HM. Moreover, 42 of 45 patients had allergic symptoms, and 24 of 30 had gastrointestinal (GI) symptoms. Our results highlight the importance of a multidisciplinary approach, early malignancy detection, and wider awareness of inherited disorders. This actively accruing, longitudinal study will genotype and phenotype more patients with FPDMM, which may lead to a better understanding of the disease pathogenesis and clinical course, which may then inform preventive and therapeutic interventions. This trial was registered at www.clinicaltrials.gov as #NCT03854318.

Irisin deficiency exacerbates diet-induced insulin resistance and cardiac dysfunction in type II diabetes in mice.

Irisin is involved in the regulation of a variety of physiological conditions, metabolism, and survival. We and others have demonstrated that irisin contributes critically to modulation of insulin resistance and the improvement of cardiac function. However, whether the deletion of irisin will regulate cardiac function and insulin sensitivity in type II diabetes remains unclear. We utilized the CRISPR/Cas-9 genome-editing system to delete irisin globally in mice and high-fat diet (HFD)-induced type II diabetes model. We found that irisin deficiency did not result in developmental abnormality during the adult stage, which illustrates normal cardiac function and insulin sensitivity assessed by glucose tolerance test in the absence of stress. The ultrastructural analysis of the transmission electronic microscope (TEM) indicated that deletion of irisin did not change the morphology of mitochondria in myocardium. Gene expression profiling showed that several key signaling pathways related to integrin signaling, extracellular matrix, and insulin-like growth factors signaling were coordinately downregulated by deletion of irisin. However, when mice were fed a high-fat diet and chow food for 16 wk, ablation of irisin in mice exposed to HFD resulted in much more severe insulin resistance, metabolic derangements, profound cardiac dysfunction, and hypertrophic response and remodeling as compared with wild-type control mice. Taken together, our results indicate that the loss of irisin exacerbates insulin resistance, metabolic disorders, and cardiac dysfunction in response to HFD and promotes myocardial remodeling and hypertrophic response. This evidence reveals the molecular evidence and the critical role of irisin in modulating insulin resistance and cardiac function in type II diabetes.NEW & NOTEWORTHY By utilizing the CRISPR/Cas-9 genome-editing system and high-fat diet (HFD)-induced type II diabetes model, our results provide direct evidence showing that the loss of irisin exacerbates cardiac dysfunction and insulin resistance while promoting myocardial remodeling and a hypertrophic response in HFD-induced diabetes. This study provides new insight into understanding the molecular evidence and the critical role of irisin in modulating insulin resistance and cardiac function in type II diabetes.

Survey of COVID-19 Vaccine Attitudes in Predominately Minority Pregnant Women.

OBJECTIVES: Despite recommendations for coronavirus disease (COVID-19) vaccination during pregnancy, some pregnant women are concerned about COVID-19 vaccines and decline to be vaccinated. This study focuses on attitudes in a sample of mostly minority pregnant Hispanic and Black women that may influence vaccine hesitancy. METHODS: This was a cross-sectional survey of 400 pregnant women. Participants were provided with a one-page information sheet on pregnancy health, COVID-19 health, and COVID-19 vaccines. They were then asked to complete a survey on attitudes about these topics. RESULTS: We found that attitudes for knowing about the health topics were in the range from agree to strongly agree, whereas attitudes for knowing about topics pertaining to COVID-19 messenger RNA (mRNA) vaccines were in a lower-level range from neutral to agree. Negative vaccine attitudes were significantly associated with decreased agreement for knowing about health attitudes, but not significantly associated with COVID-19 mRNA vaccine attitudes. CONCLUSIONS: COVID-19 vaccine mRNA technology was a lesser understood topic than attitudes for knowing about other health topics. This finding suggests the need for physician intervention and that further education about COVID-19 vaccine mRNA technology may influence patient attitudes toward acceptance of the COVID-19 mRNA vaccine in pregnancy.

Anatomically Guided Cross-Domain Repair and Screening for Ultrasound Fetal Biometry.

Ultrasound based estimation of fetal biometry is extensively used to diagnose prenatal abnormalities and to monitor fetal growth, for which accurate segmentation of the fetal anatomy is a crucial prerequisite. Although deep neural network-based models have achieved encouraging results on this task, inevitable distribution shifts in ultrasound images can still result in severe performance drop in real world deployment scenarios. In this article, we propose a complete ultrasound fetal examination system to deal with this troublesome problem by repairing and screening the anatomically implausible results. Our system consists of three main components: A routine segmentation network, a fetal anatomical key points guided repair network, and a shape-coding based selective screener. Guided by the anatomical key points, our repair network has stronger cross-domain repair capabilities, which can substantially improve the outputs of the segmentation network. By quantifying the distance between an arbitrary segmentation mask to its corresponding anatomical shape class, the proposed shape-coding based selective screener can then effectively reject the entire implausible results that cannot be fully repaired. Extensive experiments demonstrate that our proposed framework has strong anatomical guarantee and outperforms other methods in three different cross-domain scenarios.

SOX9 is a key component of RUNX2-regulated transcriptional circuitry in osteosarcoma.

BACKGROUND: The absence of prominent, actionable genetic alternations in osteosarcomas (OS) implies that transcriptional and epigenetic mechanisms significantly contribute to the progression of this life-threatening form of cancer. Therefore, the identification of potential transcriptional events that promote the survival of OS cells could be key in devising targeted therapeutic approaches for OS. We have previously shown that RUNX2 is a transcription factor (TF) essential for OS cell survival. Unfortunately, the transcriptional network or circuitry regulated by RUNX2 in OS cells is still largely unknown. METHODS: The TFs that are in the RUNX2 transcriptional circuitry were identified by analyzing RNAseq and ChIPseq datasets of RUNX2. To evaluate the effect of SOX9 knockdown on the survival of osteosarcoma cells in vitro, we employed cleaved caspase-3 immunoblotting and propidium iodide staining techniques. The impact of SOX9 and JMJD1C depletion on OS tumor growth was examined in vivo using xenografts and immunohistochemistry. Downstream targets of SOX9 were identified and dissected using RNAseq, pathway analysis, and gene set enrichment analysis. Furthermore, the interactome of SOX9 was identified using BioID and validated by PLA. RESULT: Our findings demonstrate that SOX9 is a critical TF that is induced by RUNX2. Both in vitro and in vivo experiments revealed that SOX9 plays a pivotal role in the survival of OS. RNAseq analysis revealed that SOX9 activates the transcription of MYC, a downstream target of RUNX2. Mechanistically, our results suggest a transcriptional network involving SOX9, RUNX2, and MYC, with SOX9 binding to RUNX2. Moreover, we discovered that JMJD1C, a chromatin factor, is a novel binding partner of SOX9, and depletion of JMJD1C impairs OS tumor growth. CONCLUSION: The findings of this study represent a significant advancement in our understanding of the transcriptional network present in OS cells, providing valuable insights that may contribute to the development of targeted therapies for OS.

Nano X Image Guidance in radiation therapy: feasibility study protocol for cone beam computed tomography imaging with gravity-induced motion.

BACKGROUND: This paper describes the protocol for the Nano X Image Guidance (Nano X IG) trial, a single-institution, clinical imaging study. The Nano X is a prototype fixed-beam radiotherapy system developed to investigate the feasibility of a low-cost, compact radiotherapy system to increase global access to radiation therapy. This study aims to assess the feasibility of volumetric image guidance with cone beam computed tomography (CBCT) acquired during horizontal patient rotation on the Nano X radiotherapy system. METHODS: In the Nano X IG study, we will determine whether radiotherapy image guidance can be performed with the Nano X radiotherapy system where the patient is horizontally rotated while scan projections are acquired. We will acquire both conventional CBCT scans and Nano X CBCT scans for 30 patients aged 18 and above and receiving radiotherapy for head/neck or upper abdomen cancers. For each patient, a panel of experts will assess the image quality of Nano X CBCT scans against conventional CBCT scans. Each patient will receive two Nano X CBCT scans to determine the image quality reproducibility, the extent and reproducibility of patient motion and assess patient tolerance. DISCUSSION: Fixed-beam radiotherapy systems have the potential to help ease the current shortfall and increase global access to radiotherapy treatment. Advances in image guidance could facilitate fixed-beam radiotherapy using horizontal patient rotation. The efficacy of this radiotherapy approach is dependent on our ability to image and adapt to motion due to rotation and for patients to tolerate rotation during treatment. TRIAL REGISTRATION: ClinicalTrials.gov, NCT04488224. Registered on 27 July 2020.

Distortion-corrected image reconstruction with deep learning on an MRI-Linac.

PURPOSE: MRI is increasingly utilized for image-guided radiotherapy due to its outstanding soft-tissue contrast and lack of ionizing radiation. However, geometric distortions caused by gradient nonlinearities (GNLs) limit anatomical accuracy, potentially compromising the quality of tumor treatments. In addition, slow MR acquisition and reconstruction limit the potential for effective image guidance. Here, we demonstrate a deep learning-based method that rapidly reconstructs distortion-corrected images from raw k-space data for MR-guided radiotherapy applications. METHODS: We leverage recent advances in interpretable unrolling networks to develop a Distortion-Corrected Reconstruction Network (DCReconNet) that applies convolutional neural networks (CNNs) to learn effective regularizations and nonuniform fast Fourier transforms for GNL-encoding. DCReconNet was trained on a public MR brain dataset from 11 healthy volunteers for fully sampled and accelerated techniques, including parallel imaging (PI) and compressed sensing (CS). The performance of DCReconNet was tested on phantom, brain, pelvis, and lung images acquired on a 1.0T MRI-Linac. The DCReconNet, CS-, PI-and UNet-based reconstructed image quality was measured by structural similarity (SSIM) and RMS error (RMSE) for numerical comparisons. The computation time and residual distortion for each method were also reported. RESULTS: Imaging results demonstrated that DCReconNet better preserves image structures compared to CS- and PI-based reconstruction methods. DCReconNet resulted in the highest SSIM (0.95 median value) and lowest RMSE (<0.04) on simulated brain images with four times acceleration. DCReconNet is over 10-times faster than iterative, regularized reconstruction methods. CONCLUSIONS: DCReconNet provides fast and geometrically accurate image reconstruction and has the potential for MRI-guided radiotherapy applications.

Alpha Defensin-1 Biomarker Outperforms Culture in Diagnosing Breast Implant-Related Infection: Results from a Multicenter Prospective Study.

BACKGROUND: Prompt diagnosis of breast implant infection is critical to reducing morbidity. A high incidence of false-negative microbial culture mandates superior testing modalities. Alpha defensin-1 (AD-1), an infection biomarker, has outperformed culture in diagnosing periprosthetic joint infection with sensitivity/specificity of 97%. After previously demonstrating its feasibility in breast implant-related infection (BIRI), this case-control study compares the accuracy of AD-1 to microbial culture in suspected BIRI. METHODS: An institutional review board-approved, prospective, multicenter study was conducted of adults with prior breast implant reconstruction undergoing surgery for suspected infection (cases) or prosthetic exchange/revision (controls). Demographics, perioperative characteristics, antibiotic exposure, and implant pocket fluid were collected. Fluid samples underwent microbial culture, AD-1 assay, and adjunctive markers (C-reactive protein, lactate, cell differential); diagnostic performance was assessed by means of sensitivity, specificity, and accuracy from receiver operating characteristic curve analysis, with values of P < 0.05 considered significant. RESULTS: Fifty-three implant pocket samples were included (cases, n = 20; controls, n = 33). All 20 patients with suspected BIRI exhibited cellulitis, 65% had abnormal drainage, and 55% were febrile. All suspected BIRIs were AD-1 positive (sensitivity, 100%). Microbial culture failed to grow any microorganisms in four BIRIs (sensitivity, 80%; P = 0.046); Gram stain was least accurate (sensitivity, 25%; P < 0.001). All tests demonstrated 100% specificity. Receiver operating characteristic curve analyses yielded the following areas under the curve: AD-1, 1.0; microbial culture, 0.90 ( P = 0.029); and Gram stain, 0.62 ( P < 0.001). Adjunctive markers were significantly higher among infections versus controls ( P < 0.001). CONCLUSIONS: Study findings confirm the accuracy of AD-1 in diagnosing BIRI and indicate superiority to microbial culture. Although further study is warranted, AD-1 may facilitate perioperative decision-making in BIRI management in a resource-efficient manner. CLINICAL QUESTION/LEVEL OF EVIDENCE: Diagnostic, II.

Genomic Landscape of Patients with Germline RUNX1 Variants and Familial Platelet Disorder with Myeloid Malignancy.

Germline RUNX1 mutations lead to familial platelet disorder with associated myeloid malignancies (FPDMM), which is characterized by thrombocytopenia and a life-long risk (35-45%) of hematological malignancies. We recently launched a longitudinal natural history study for patients with FPDMM at the NIH Clinical Center. Among 29 families with research genomic data, 28 different germline RUNX1 variants were detected. Besides missense mutations enriched in Runt homology domain and loss-of-function mutations distributed throughout the gene, splice-region mutations and large deletions were detected in 6 and 7 families, respectively. In 24 of 54 (44.4%) non-malignant patients, somatic mutations were detected in at least one of the clonal hematopoiesis of indeterminate potential (CHIP) genes or acute myeloid leukemia (AML) driver genes. BCOR was the most frequently mutated gene (in 9 patients), and multiple BCOR mutations were identified in 4 patients. Mutations in 7 other CHIP or AML driver genes ( DNMT3A, TET2, NRAS, SETBP1, SF3B1, KMT2C , and LRP1B ) were also found in more than one non-malignant patient. Moreover, three unrelated patients (one with myeloid malignancy) carried somatic mutations in NFE2 , which regulates erythroid and megakaryocytic differentiation. Sequential sequencing data from 19 patients demonstrated dynamic changes of somatic mutations over time, and stable clones were more frequently found in elderly patients. In summary, there are diverse types of germline RUNX1 mutations and high frequency of somatic mutations related to clonal hematopoiesis in patients with FPDMM. Monitoring dynamic changes of somatic mutations prospectively will benefit patients’ clinical management and reveal mechanisms for progression to myeloid malignancies. Key Points: Comprehensive genomic profile of patients with FPDMM with germline RUNX1 mutations. Rising clonal hematopoiesis related secondary mutations that may lead to myeloid malignancies.