Citations

Objectives: The practice parameter was revised collaboratively by the American College of Radiology (ACR), the American Brachytherapy Society (ABS), the American College of Nuclear Medicine (ACNM), the American Radium Society (ARS), the Society of Interventional Radiology (SIR), and the Society of Nuclear Medicine and Molecular Imaging (SNMMI). This document summarizes current evidence-based guidelines for the administration of Yttrium radioembolic therapy to the liver, including training requirements, evidence-based guidelines for administration, and safe practice for administration. Methods: This practice parameter was revised according to the process described under the heading The Process for Developing ACR Practice Parameters and Technical Standards on the ACR website (https://www.acr.org/ClinicalResources/Practice-Parameters-and-Technical-Standards) by the Committee on Practice Parameters—Interventional and Cardiovascular Radiology of the ACR Commission on Interventional and Cardiovascular, Committee on Practice Parameters and Technical Standards—Nuclear Medicine and Molecular Imaging of the ACR Commission on Nuclear Medicine and Molecular Imaging and the Committee on Practice Parameters—Radiation Oncology of the ACR Commission on Radiation Oncology in collaboration with the ABS, the ACNM, the ARS, the SIR, and the SNMMI. Results: This review seeks not to be a comprehensive discussion of radiotherapy to the liver, but rather, seeks to provide a parameter for safe and effective therapy. We discuss the qualifications of physicians involved in this therapy, basic indications, contraindications, procedural work-up, safe-handling, and regulatory requirement for the administration of selective internal radiation therapy to patients that are likely to benefit. The goal of this document is not to define which patients are best treated by these therapies, as this is best determined for individual patients after multidisciplinary review. A consistent and evidence-based approach to therapy, however, would benefit all patients who are offered this therapy. This document seeks to provide a framework for current best practices for the administration of the 2 currently available radioembolization devices. Conclusions: As Yttrium-90 radiotherapy to the liver occupies a growing role in the treatment of primary and metastatic liver cancer, this review seeks to assist clinicians of all involved specialties to optimize the efficacy and safety of these procedures.

While anatomic total shoulder arthroplasty is a successful procedure that provides reliable pain relief and restoration of function in most patients, its success has been limited by glenoid component loosening. While series reporting the outcomes of inlay glenoid components have demonstrated excellent clinical outcomes with low rates of component loosening and need for revision, surgeons have been hesitant to adopt these implants due to concerns of inadequate pain relief secondary to the remaining glenoid rim contacting the humeral head implant. The inset glenoid component, a variant of the traditional inlay components, has gained interest because its design aims to achieve similar stability to traditional inlay components through implantation within strong subchondral bone, reduce the amount of glenoid vault removed compared to inlay components, and has a glenoid face designed to limit the rocking-horse phenomenon. In limited series, the inset glenoid component has demonstrated superior biomechanical and clinical performance compared to traditional onlay glenoid components. Although there have been minimal clinical studies investigating the inset glenoid in comparison to onlay and inlay components to date, a subset of case series with short-term follow-up have demonstrated favorable outcomes. The purpose of this article was to review the design rationale, biomechanical evidence, and clinical performance of the inset glenoid component.

Abstract Clinical question What are the benefits and harms of medications for adults with type 2 diabetes at varied risks of cardiovascular and kidney related complications? Context Emerging clinical trials of novel medications have demonstrated benefits on cardiovascular, kidney, and weight related outcomes in people with type 2 diabetes. Dynamically updated practice guidelines adhering to standards of trustworthiness are necessary in response to a rapidly evolving evidence base and the availability of multiple medication alternatives. This living practice guideline incorporates the latest available medications and evidence and provides recommendations stratified by risks of cardiovascular and kidney complications to inform diabetes management. Recommendations The panel issued risk-stratified recommendations regarding four prioritised medications for adults with type 2 diabetes (SGLT-2 inhibitors, GLP-1 receptor agonists, finerenone and tirzepatide): • Lower risk (three or fewer cardiovascular risk factors without established cardiovascular disease (CVD) or chronic kidney disease (CKD)): weak recommendation against SGLT-2 inhibitors or GLP-1 receptor agonists. • Moderate risk (more than three cardiovascular risk factors without established CVD or CKD; or established CVD and/or CKD at lower risk of complications): weak recommendation in favour of SGLT-2 inhibitors or GLP-1 receptor agonists; and a weak recommendation against finerenone in adults with CKD. • Higher risk (established CVD and/or CKD at higher risk of complications, or established heart failure): strong recommendation in favour of SGLT-2 inhibitors or GLP-1 receptor agonists; and a weak recommendation in favour of finerenone in adults with CKD. • Across risk strata: weak recommendation in favour of tirzepatide in adults with obesity. About this guideline and how it was created An international panel including two patient partners, clinicians, and methodologists produced these recommendations. The panel followed standards for trustworthy guidelines and used the GRADE approach, explicitly considering the balance of benefits, harms and burdens of treatment from an individual patient perspective. Recommendations were informed by a linked living systematic review and network meta-analysis evaluating relative benefits and harms updated to 31 July 2024; and by linked systematic reviews addressing risk prediction models and values and preferences of adults with type 2 diabetes. Candidate therapeutics are prioritised based on availability of sufficient randomised trial data, relevance to a global audience and likelihood of changing practice. This is the first version of the living guideline. The guideline is part of the BMJ Rapid Recommendations series. MAGICapp displays the most recent version of the guideline and full content including evidence summaries and decision aids; major updates will be published in The BMJ . We encourage re-use, adaptation and translation of these living guidelines, and recognise that the lack of availability or high costs of some medications may be prohibitive and will impact on how these recommendations are implemented across different health care systems.

Abstract The aim of this international meta-analysis was to quantify the predictive value of BMI for incident fracture and relationship of this risk with age, sex, follow-up time, and BMD. A total of 1 667 922 men and women from 32 countries (63 cohorts), followed for a total of 16.0 million person-years were studied. 293 325 had FN BMD measured (2.2 million person-years follow-up). An extended Poisson model in each cohort was used to investigate relationships between WHO-defined BMI categories (Underweight: <18.5 kg/m2; Normal: 18.5-24.9 kg/m2; Overweight: 25.0-29.9 kg/m2; Obese I: 30.0-34.9 kg/m2; Obese II: ≥35.0 kg/m2) and risk of incident osteoporotic, major osteoporotic and hip fracture (HF). Inverse-variance weighted β-coefficients were used to merge the cohort-specific results. For the subset with BMD available, in models adjusted for age and follow-up time, the hazard ratio (95% CI) for HF comparing underweight with normal weight was 2.35 (2.10-2.60) in women and for men was 2.45 (1.90-3.17). Hip fracture risk was lower in overweight and obese categories compared to normal weight [obese II vs normal: women 0.66 (0.55-0.80); men 0.91 (0.66-1.26)]. Further adjustment for FN BMD T-score attenuated the increased risk associated with underweight [underweight vs normal: women 1.69 (1.47-1.96); men 1.46 (1.00-2.13)]. In these models, the protective effects of overweight and obesity were attenuated, and in both sexes, the direction of association reversed to higher fracture risk in Obese II category [Obese II vs Normal: women 1.24 (0.97-1.58); men 1.70 (1.06-2.75)]. Results were similar for other fracture outcomes. Underweight is a risk factor for fracture in both men and women regardless of adjustment for BMD. However, while overweight/obesity appeared protective in base models, they became risk factors after additional adjustment for FN BMD, particularly in the Obese II category. This effect in the highest BMI categories was of greater magnitude in men than women. These results will inform the second iteration of FRAX®.

Pharmacogenomics (PGx) has the potential to improve prescribing practices. In 2012, our institution developed a multidisciplinary program to implement PGx-CDS to support the clinical practice. CDS has been implemented for 45 drug-gene interactions, in 42,000 patients with PGx tests results, and in 2023, approximately 9281 CDS interventions have triggered at the time of prescribing. The program has been successful.

Accurate diagnosis of gastrointestinal (GI) diseases typically requires invasive procedures or imaging studies that pose the risk of various post-procedural complications or involve radiation exposure. Bowel sounds (BSs), though typically described during a GI-focused physical exam, are highly inaccurate and variable, with low clinical value in diagnosis. Interpretation of the acoustic characteristics of BSs, i.e., using a phonoenterogram (PEG), may aid in diagnosing various GI conditions non-invasively. Use of artificial intelligence (AI) and improvements in computational analysis can enhance the use of PEGs in different GI diseases and lead to a non-invasive, cost-effective diagnostic modality that has not been explored before. The purpose of this work was to develop an automated AI model, You Only Listen Once (YOLO), to detect prominent bowel sounds that can enable real-time analysis for future GI disease detection and diagnosis. A total of 110 2-minute PEGs sampled at 44.1 kHz were recorded using the Eko DUO® stethoscope from eight healthy volunteers at two locations, namely, left upper quadrant (LUQ) and right lower quadrant (RLQ) after IRB approval. The datasets were annotated by trained physicians, categorizing BSs as prominent or obscure using version 1.7 of Label Studio Software®. Each BS recording was split up into 375 ms segments with 200 ms overlap for real-time BS detection. Each segment was binned based on whether it contained a prominent BS, resulting in a dataset of 36,149 non-prominent segments and 6435 prominent segments. Our dataset was divided into training, validation, and test sets (60/20/20% split). A 1D-CNN augmented transformer was trained to classify these segments via the input of Mel-frequency cepstral coefficients. The developed AI model achieved area under the receiver operating curve (ROC) of 0.92, accuracy of 86.6%, precision of 86.85%, and recall of 86.08%. This shows that the 1D-CNN augmented transformer with Mel-frequency cepstral coefficients achieved creditable performance metrics, signifying the YOLO model’s capability to classify prominent bowel sounds that can be further analyzed for various GI diseases. This proof-of-concept study in healthy volunteers demonstrates that automated BS detection can pave the way for developing more intuitive and efficient AI-PEG devices that can be trained and utilized to diagnose various GI conditions. To ensure the robustness and generalizability of these findings, further investigations encompassing a broader cohort, inclusive of both healthy and disease states are needed.

Background Eosinophilic oesophagitis (EoE) is a food allergen-induced inflammatory disorder characterised by interleukin (IL)-13-mediated oesophageal inflammation and epithelial basal cell hyperplasia (BCH). The role of mitochondria in EoE pathogenesis remains elusive. Design Prompted by single cell transcriptomics data, we interrogated the role of mitochondria in EoE pathobiology using patient biopsies, EoE-mouse models and oesophageal epithelial cells grown in monolayer and three-dimensional (3D) organoid cultures treated with EoE-relevant cytokines. 3D organoids and EoE-bearing mice were treated with omeprazole—a proton-pump inhibitor used as first-line EoE therapy. We performed CRISPR (Clustered Regularly Interspaced Short Palindromic Repeats) interference in mouse organoids to identify the key mitochondrial regulatory genes whose depletion may lead to BCH. We analysed mitochondrial membrane potential, mass and superoxide production by flow cytometry, cellular oxygen consumption by respirometry, mitochondrial structures and perturbation of cellular energy homeostasis by immunoblotting. Results Mitochondrial dysfunction appeared to be a hallmark of EoE-related BCH where mitochondrial structural damage was associated with impaired oxidative respiratory capacity, elevation of mitochondrial superoxide and decreased adenosine triphosphate (ATP) production, as corroborated by activation of the adenosine monophosphate (AMP) -activated protein kinase and suppression of mammalian target-of-rapamycin signalling. Depletion of PGC1A, the master regulator of mitochondria biogenesis, recapitulated EoE-related BCH, suggesting that mitochondrial dysfunction drives BCH. Further, omeprazole alleviated mitochondrial damage and dysfunction in EoE-related BCH modelled in mice and patient-derived organoids. Conclusion Mitochondrial dysfunction is tightly linked to perturbation of redox homeostasis in EoE-related BCH, which is promoted by IL-13 and reversible with omeprazole treatment.

Accurate analysis of medical videos remains a major challenge in deep learning (DL) due to the need for effective spatiotemporal feature mapping that captures both spatial detail and temporal dynamics. Despite advances in DL, most existing models in medical AI focus on static images, overlooking critical temporal cues present in video data. To bridge this gap, a novel DL-based framework is proposed for spatiotemporal feature extraction from medical video sequences. As a feasibility use case, this study focuses on gastrointestinal (GI) endoscopic video classification. A 3D convolutional neural network (CNN) is developed to classify upper and lower GI endoscopic videos using the hyperKvasir dataset, which contains 314 lower and 60 upper GI videos. To address data imbalance, 60 matched pairs of videos are randomly selected across 20 experimental runs. Videos are resized to 224 × 224, and the 3D CNN captures spatiotemporal information. A 3D version of the parallel spatial and channel squeeze-and-excitation (P-scSE) is implemented, and a new block called the residual with parallel attention (RPA) block is proposed by combining P-scSE3D with a residual block. To reduce computational complexity, a (2 + 1)D convolution is used in place of full 3D convolution. The model achieves an average accuracy of 0.933, precision of 0.932, recall of 0.944, F1-score of 0.935, and AUC of 0.933. It is also observed that the integration of P-scSE3D increased the F1-score by 7%. This preliminary work opens avenues for exploring various GI endoscopic video-based prospective studies.