Citations

In this study, we propose a new mathematical model able to quantify C-peptide secretion and β-cell responsivity in response to a glucagon bolus in individuals without and with type 2 diabetes. We show that individuals with type 2 diabetes exhibit reduced β-cell responsivity to glucagon.

Introduction: Hypertrophic cardiomyopathy (HCM) is a disease characterized by genotypic and phenotypic heterogeneity. Correct classification of genetic variation is critical for clinical interpretation. Herein, variants of uncertain significance (VUS) pose a dilemma in clinical practice, limiting physicians’ decision making and causing anguish to patients and family members. Furthermore, with increasing knowledge and changing guidelines, continuous reassessment is crucial to maintain usefulness in practice. This study sought to assess contemporary variant classification in a large cohort of patients with HCM. Methods: Retrospective analysis of all patients with HCM seen at Mayo Clinic and all patients with a variant in one of 8 genes with strong disease association for HCM were included. Genetic test reports were obtained from electronic health records along with their original variant classification assigned by either a commercial or research laboratory. Reassessment of variant pathogenicity was performed using the 2015 ACMG guideline criteria. Population frequency was obtained using Gnomad. Co-segregation presence or absence was determined by family history and co-segregation studies. Combined Annotation Dependent Depletion (CADD) was used as computational evidence of genetic deleterious effects for single nucleotide variants. Results: Between 2003 to 2019, a total of 1,782 patients underwent laboratory or commercial HCM genetic testing. Of these, 787 (44%) had positive genetic test with a variant at least 1 of the 8 genes. The original pathogenic classification was obtained for 754 patients. Of those, 430 (57%) variants where within the gene MYBPC3, 244 (32%) within MYH7 and 80 (11%) within either ACTC1, MYL2, MYL3, TINNI3, TNNT2 or TPM1. Overall, 222 patients (29%) originally had one or more variants classified as a VUS. Upon reassessment, 120 (54%) were reclassified as either pathogenic (33%), likely pathogenic (58%), benign (5%) or likely benign (3%). Conclusion: Periodic reassessment for HCM genetic variants, especially VUS, is critical for adequate patient care and management. Cascade screening could decrease patients’ uncertainty regarding their prognosis and management.

Abstract Hypertrophic Cardiomyopathy (HCM) is an inheritable heart disease with the highest rate of sudden cardiac death (SCD) in young adults. Implantable Cardioverter Defibrillator (ICD) therapy is recommended for HCM patients at high risk for SCD. Reviewing the recent clinical literature revealed the potential to improve the selection of candidates for ICD implantation. The current study uses information extracted from echocardiography reports to evaluate HCM patients with ICD and aims to provide a comparative insight into patients who benefited the most from the device therapy, including shock and anti-tachycardia pacing (ATP). The proposed interpretable machine learning approach has used the XGboost algorithm. The model’s performance was considered satisfactory, as evidenced by an accuracy score of 81% and an area under the receiver operating characteristic curve (AUC) value of 69% and SHapley Additive exPlanations (SHAP) identified common properties of HCM patients in each category and provided high-level reasoning and foundation for a clinical decision support tool.

Autologous mesenchymal stem/stromal cells (MSCs) have demonstrated important therapeutic effects in several diseases. Cardiovascular risk factors may impair MSC mitochondrial structure and function, but the underlying mechanisms remain unknown. We hypothesized that metabolic syndrome (MetS) induces epigenetic alterations in mitochondria-related genes in swine MSCs. Pigs were fed a Lean or MetS diet (n = 6 each) for 16 weeks. MSCs were collected from subcutaneous abdominal fat, and DNA hydroxymethylation (5 hmC) profiles of mitochondria-related genes (MitoCarta-2.0) were analyzed by hydroxymethylated DNA immunoprecipitation and next-generation sequencing (hMeDIP-seq) in Lean- and MetS-MSCs untreated or treated with the epigenetic modulator vitamin (Vit)-C (n = 3 each). Functional analysis of genes with differential 5 hmC regions was performed using DAVID6.8. Mitochondrial structure (electron microscopy), oxidative stress, and membrane potential were assessed. hMeDIP-seq identified 172 peaks (associated with 103 mitochondrial genes) with higher and 416 peaks (associated with 165 mitochondrial genes) with lower 5 hmC levels in MetS-MSCs versus Lean-MSCs (≥2-fold, p < 0.05). Genes with higher 5 hmC levels in MetS + MSCs were primarily implicated in fatty acid metabolism, whereas those with lower 5 hmC levels were associated with electron transport chain activity. Vit-C increased 5 hmC levels in mitochondrial antioxidant genes, improved mitochondrial structure and membrane potential, and decreased oxidative stress. MetS alters 5 hmC levels of mitochondria-related genes in swine MSCs. Vit-C modulated 5 hmC levels in these genes and preserved mitochondrial structure and function in MetS-MSCs. These observations may contribute to development of strategies to overcome the deleterious effects of MetS on MSCs.

AbstractThis report reviews the image acquisition and reconstruction characteristics of C‐arm Cone Beam Computed Tomography (C‐arm CBCT) systems and provides guidance on quality control of C‐arm systems with this volumetric imaging capability. The concepts of 3D image reconstruction, geometric calibration, image quality, and dosimetry covered in this report are also pertinent to CBCT for Image‐Guided Radiation Therapy (IGRT). However, IGRT systems introduce a number of additional considerations, such as geometric alignment of the imaging at treatment isocenter, which are beyond the scope of the charge to the task group and the report.Section 1 provides an introduction to C‐arm CBCT systems and reviews a variety of clinical applications. Section 2 briefly presents nomenclature specific or unique to these systems. A short review of C‐arm fluoroscopy quality control (QC) in relation to 3D C‐arm imaging is given in Section 3. Section 4 discusses system calibration, including geometric calibration and uniformity calibration. A review of the unique approaches and challenges to 3D reconstruction of data sets acquired by C‐arm CBCT systems is give in Section 5. Sections 6 and 7 go in greater depth to address the performance assessment of C‐arm CBCT units. First, Section 6 describes testing approaches and phantoms that may be used to evaluate image quality (spatial resolution and image noise and artifacts) and identifies several factors that affect image quality. Section 7 describes both free‐in‐air and in‐phantom approaches to evaluating radiation dose indices.The methodologies described for assessing image quality and radiation dose may be used for annual constancy assessment and comparisons among different systems to help medical physicists determine when a system is not operating as expected. Baseline measurements taken either at installation or after a full preventative maintenance service call can also provide valuable data to help determine whether the performance of the system is acceptable. Collecting image quality and radiation dose data on existing phantoms used for CT image quality and radiation dose assessment, or on newly developed phantoms, will inform the development of performance criteria and standards. Phantom images are also useful for identifying and evaluating artifacts. In particular, comparing baseline data with those from current phantom images can reveal the need for system calibration before image artifacts are detected in clinical practice. Examples of artifacts are provided in Sections 4, 5, and 6.

Data from transgenic rodent models suggest that glucagon acts as an insulin secretagogue by signaling through the glucagon-like peptide 1 receptor (GLP-1R) present on β-cells. However, its net contribution to physiologic insulin secretion in humans is unknown. To address this question, we studied individuals without diabetes in two separate experiments. Each subject was studied on two occasions in random order. In the first experiment, during a hyperglycemic clamp, glucagon was infused at 0.4 ng/kg/min, increasing by 0.2 ng/kg/min every hour for 5 h. On one day, exendin-9,39 (300 pmol/kg/min) was infused to block GLP-1R, while on the other, saline was infused. The insulin secretion rate (ISR) was calculated by nonparametric deconvolution from plasma concentrations of C-peptide. Endogenous glucose production and glucose disappearance were measured using the tracer-dilution technique. Glucagon concentrations, by design, did not differ between study days. Integrated ISR was lower during exendin-9,39 infusion (213 ± 26 vs. 191 ± 22 nmol/5 h, saline vs. exendin-9,39, respectively; P = 0.02). In the separate experiment, exendin-9,39 infusion, compared with saline infusion, also decreased the β-cell secretory response to a 1-mg glucagon bolus. These data show that, in humans without diabetes, glucagon partially stimulates the β-cell through GLP-1R.

The analysis and interpretation of cardiac magnetic resonance (CMR) images are often time-consuming. The automated segmentation of cardiac structures can reduce the time required for image analysis. Spatial similarities between different CMR image types were leveraged to jointly segment multiple sequences using a segmentation model termed a multi-image type UNet (MI-UNet). This model was developed from 72 exams (46% female, mean age 63 ± 11 years) performed on patients with hypertrophic cardiomyopathy. The MI-UNet for steady-state free precession (SSFP) images achieved a superior Dice similarity coefficient (DSC) of 0.92 ± 0.06 compared to 0.87 ± 0.08 for a single-image type UNet (p < 0.001). The MI-UNet for late gadolinium enhancement (LGE) images also had a superior DSC of 0.86 ± 0.11 compared to 0.78 ± 0.11 for a single-image type UNet (p = 0.001). The difference across image types was most evident for the left ventricular myocardium in SSFP images and for both the left ventricular cavity and the left ventricular myocardium in LGE images. For the right ventricle, there were no differences in DCS when comparing the MI-UNet with single-image type UNets. The joint segmentation of multiple image types increases segmentation accuracy for CMR images of the left ventricle compared to single-image models. In clinical practice, the MI-UNet model may expedite the analysis and interpretation of CMR images of multiple types.

Abstract According to the 2020 report of the American Heart Association’s Heart & Stroke Statistics report, nearly 1,000 people are dying daily because of sudden out-of-hospital cardiac arrests and unfortunately, their survival rate is as low as 10%. Hypertrophic Cardiomyopathy (HCM), a relatively rare genetic heart disease is one of these diseases but finding the right patient for the implantation of ICD is still a research question. Implantation of cardioverter-defibrillator (ICD) can save the life of some of these patients. Due to the complexity of the identification of HCM patients, financial burdens, and the clinical risks involved in the ICD implantation procedure, HCM patients will go into a monitoring state before reaching the implantation trigger. Our study cohort shows about 82% of HCM deaths, did not have an ICD, which highlights the need to improve the pre-screening algorithms. In the current paper, we have proposed a new deep learning-based unsupervised clustering technique to facilitate the prioritization of patients to undergo ICD device implantation. This model uses over 900 echocardiographic measurements to find patients who benefit more from the ICD implantation procedure. Our model was trained and tested over 6 years of echo reports collected at Mayo Clinic. This model can be used as a decision support assistant for cardiologists in finding the right HCM patient when decision-making is hard.