Citations

Lung transplantation presents numerous intraoperative challenges, particularly related to pulmonary artery and vein anastomotic integrity and hemodynamic stability. We present 3 cases where intraoperative transesophageal echocardiography (TEE) provided real-time diagnostic insights that directly altered surgical decision-making. Case 1 highlights pulmonary vein flow acceleration initially concerning for ostial stenosis, ultimately diagnosed as external compression from a retractor. Case 2 demonstrates true right pulmonary vein stenosis requiring immediate revision. Case 3 illustrates severe right pulmonary artery narrowing, detected by TEE and corrected intraoperatively to prevent early graft dysfunction. These cases underscore the critical role of intraoperative TEE in detecting subtle anastomotic abnormalities, distinguishing functional from structural stenosis, and guiding timely surgical correction. Incorporating comprehensive 2D and 3D TEE evaluation into routine lung transplant protocols enhances diagnostic accuracy, reduces postoperative complications, and contributes to improved long-term allograft function. Intraoperative 3D TEE should be considered an essential imaging modality in cardiothoracic transplantation and an invaluable educational tool for perioperative teams.

ABSTRACT Background The optimal timing for basal insulin initiation in diabetic ketoacidosis (DKA) remains unclear. British guidelines endorse early basal insulin (EBI), while the American Diabetes Association emphasises overlap duration with intravenous insulin, without mention of timing. This meta‐analysis evaluates whether EBI administration of basal insulin improves clinical outcomes in adults with DKA. Methods A systematic review and meta‐analysis were performed according to the PRISMA guidelines. Databases searched included MEDLINE, Embase, Scopus, Web of Science and the Cochrane Central Register of Controlled Trials through December 11, 2024. Inclusion criteria included articles in the English‐language randomised controlled trials (RCTs) or observational studies evaluating EBI in adult DKA patients. Non‐human studies, conference abstracts, and case reports were excluded. The primary outcome for this study was hospital length of stay (LOS). Additional outcomes included intensive care unit (ICU) LOS, time to DKA resolution, hypoglycemia, and rebound hyperglycemia between EBI and usual care. Risk of bias was assessed using the Cochrane and Newcastle‐Ottawa tools. Grading of Recommendations Assessment, Development, and Evaluation was performed to evaluate the quality of evidence. Results From 1214 identified studies, eight (4 RCTs, 4 observational) met inclusion criteria for a total of 247 patients in the EBI group and 552 patients in the control group. No significant difference in hospital LOS was found (mean difference −11.17 h; 95% CI: −29.91 to 7.56). ICU LOS, time to DKA resolution, incidence of hypoglycemia, and rebound hyperglycemia also did not demonstrate any significant differences between groups. Significant heterogeneity existed across studies for most outcomes. All studies had a high risk of bias, and the quality of evidence was very low. Conclusion EBI did not result in significant differences in hospital LOS, ICU LOS, or time to DKA resolution; however, there were no increased adverse events with EBI. Current studies of early EBI have significant limitations. Future research should focus on developing high‐quality RCTs.

Abstract Categorical variants, or sets of genomic alterations constrained by shared properties, are pervasive across clinical, regulatory, and research domains in the biomedical ecosystem, yet their inconsistent and non-computable representation hinders data interoperability and clinical interpretation. We surveyed genomic knowledgebases spanning regulatory approvals and the biomedical literature and found that categorical variants underpin a substantial proportion of clinical genomics knowledge, but are largely described using incompatible bespoke models. To address this, we developed the GA4GH Categorical Variation Representation Specification (Cat-VRS), a constraint-based framework that provides a unified computable representation for both precise and intentionally broad categories across molecular and systemic variant domains. Cat-VRS enables harmonization of genomic knowledgebases, computable category-based search, and automated matching between assayed variants and categorical entities in clinical and research contexts. By providing a principled, extensible model for categorical variation, Cat-VRS enables computable reasoning over genomic variant categories and establishes a foundation for the standardized representation and exchange of genomic knowledge.

Abstract Background Computed tomography (CT) is an essential imaging modality for disease diagnosis, treatment efficacy, and image‐based guidance of various medical procedures. The locally deposited radiation dose in tissues, as estimated by the computed tomography dose index (CTDI), can vary considerably across exposures delivered by CT scanners from different vendors, even if the scans are performed using similar technique factors, such as tube potential and tube current. The volumetric CTDI (CTDI vol ) is a common dose metric that reports an average radiation dose (in mGy) delivered to a specific volume within a test phantom. The CTDI vol is important in dosimetry applications as the organ absorbed dose within the patient has been shown to scale in near‐linear proportion, creating a basis for comparing organ doses across different scan protocols and scanner models. Purpose To develop a database of tube current‐time product (mAs) normalized CTDI vol values for currently utilized CT scanner models for each of the four primary CT vendors for use in the MIRDct organ dosimetry software available at MIRDsoft.org. This data forms the basis of the MIRDct code, which reports organ doses across a range of computational phantoms based upon axial organ dose coefficient libraries generated through Monte Carlo radiation transport for a reference CT scanner. Organ doses delivered by alternate CT scanner vendors and models may then be reported using ratios of normalized CTDI vol values under similar technique factors. Methods Scanners were selected from four major CT manufacturers: Philips Healthcare, GE Healthcare, Canon Medical Systems, and Siemens Healthineers. Technique parameters were also selected for each scanner that closely matched values used in the generation of an equivalent CT source term (small to large bowtie filters; 80–140‐kVp tube voltage; and 10‐mm to 40‐mm beam collimation). For each scanner chosen, the appropriate technique factors and protocols were selected, and the console‐reported CTDI vol values were recorded and normalized to a set value of 100 mAs. The normalized CTDI vol data collected for use within the MIRDct code were analyzed for noticeable patterns, features, and trends, and were compared to similar normalized CTDI vol datasets used within the National Cancer Institute NCICT software and the Virtual Phantoms, Inc. VirtualDose software. Results For all given CT scanner and technique factor combinations, there was strong agreement in normalized CTDI vol values across all three codes: between 0% and 12% difference for the compared scanners. Ratios of CTDI vol values for various CT scanner vendors and models to the corresponding CTDI vol values for the MIRDct reference scanner (Cannon Aquilion One Genesis) were also compared on the basis of either the 16‐cm head PMMA phantom or the 32‐cm body PMMA phantom. The mean quotient of these normalized CTDI vol ratios (head ratios to body ratios) was found to be approximately 1.06, and thus either ratio may be applied in reporting patient organ dose by MIRDct. Conclusions A database of normalized CTDI vol (mGy/100 mAs) was created for 17 models of CT scanners from four manufacturers at varying tube potentials, collimations, x‐ray bowtie filters, and phantom sizes for use in the MIRDct software.

Background: Colorectal cancer (CRC) is the second leading cause of cancer-related mortality worldwide, accounting for approximately 10% of all cancer cases. Despite the proven effectiveness of conventional screening modalities such as colonoscopy and fecal immunochemical testing (FIT), their invasive nature, high cost, and limited patient compliance hinder widespread adoption. Recent advancements in artificial intelligence (AI) and bowel sound-based signal processing have enabled non-invasive approaches for gastrointestinal diagnostics. Among these, bowel sound analysis—historically considered subjective—has reemerged as a promising biomarker using digital auscultation and machine learning. Objective: This review explores the potential of AI-powered bowel sound analytics for early detection, screening, and characterization of colorectal cancer. It aims to assess current methodologies, summarize reported performance metrics, and highlight translational opportunities and challenges in clinical implementation. Methods: A narrative review was conducted across PubMed, Scopus, Embase, and Cochrane databases using the terms colorectal cancer, bowel sounds, phonoenterography, artificial intelligence, and non-invasive diagnosis. Eligible studies involving human bowel sound-based recordings, AI-based sound analysis, or machine learning applications in gastrointestinal pathology were reviewed for study design, signal acquisition methods, AI model architecture, and diagnostic accuracy. Results: Across studies using convolutional neural networks (CNNs), gradient boosting, and transformer-based models, reported diagnostic accuracies ranged from 88% to 96%. Area under the curve (AUC) values were ≥0.83, with F1 scores between 0.71 and 0.85 for bowel sound classification. In CRC-specific frameworks such as BowelRCNN, AI models successfully differentiate abnormal bowel sound intervals and spectral patterns associated with tumor-related motility disturbances and partial obstruction. Distinct bowel sound-based signatures—such as prolonged sound-to-sound intervals and high-pitched “tinkling” proximal to lesions—demonstrate the physiological basis for CRC detection through bowel sound-based biomarkers. Conclusions: AI-driven bowel sound analysis represents an emerging, exploratory research direction rather than a validated colorectal cancer screening modality. While early studies demonstrate physiological plausibility and technical feasibility, no large-scale, CRC-specific validation studies currently establish sensitivity, specificity, PPV, or NPV for cancer detection. Accordingly, bowel sound analytics should be viewed as hypothesis-generating and potentially complementary to established screening tools, rather than a near-term alternative to validated modalities such as FIT, multitarget stool DNA testing, or colonoscopy.

Objectives Ultrasound‐guided percutaneous needle fenestration (UPNF) and percutaneous needle tenotomy (UPNT) are minimally invasive procedures commonly used to treat chronic tendinopathies. However, these techniques can be painful, potentially limiting patient tolerance, satisfaction, and procedural feasibility. Although local anesthetics (LAs) provide analgesia, their potential inhibitory effects on tenocyte activity and the efficacy of orthobiologics raise concerns regarding their impact on tendon healing. The objectives of this study is to propose a practical, anatomy‐based approach for the use of ultrasound‐guided peripheral nerve blocks (USG‐PNBs) as a strategy to reduce pain and improve patient comfort during UPNF and UPNT, with or without orthobiologic adjuncts. Methods We reviewed commonly affected anatomical sites in chronic tendinopathies and identified corresponding peripheral nerve targets that can be reliably and safely blocked under ultrasound guidance. For each condition, we outline appropriate nerve block techniques, anatomical landmarks, and recommended patient positioning to optimize procedural analgesia. Results A set of targeted USG‐PNBs was defined for commonly treated tendinopathies, including supraspinatus tendinopathy, lateral and medial epicondylitis, gluteus medius and/or minimus tendinopathy, patellar tendinopathy, Achilles tendinopathy, and plantar fasciopathy. Conclusion Ultrasound‐guided peripheral nerve blocks represent a practical and effective approach to manage pain during percutaneous procedures for chronic tendinopathies. By reducing procedural discomfort and avoiding the potential drawbacks of peritendinous LAs, these techniques may enhance patient tolerance, procedural success, and overall clinical outcomes.