Search

Surveillance imaging at 45 to 90 days after transcatheter left atrial appendage occlusion device implantation with transesophageal echocardiography (TEE) or cardiac computed tomography (CT) is recommended to assess device position and the presence of device-related complications such as device-related thrombus (DRT) or peridevice leak. Detection of DRT is associated with a significantly increased risk of a stroke or systemic embolization event within 6 months of detection. Nonetheless, there is significant variability in detection of DRT as a result of timing, frequency, and imaging modality used for surveillance. The process of DRT formation vs benign device endothelization is not known. Here we highlight the spectrum of imaging findings seen on TEE and CT and emphasize the need for unified definitions and standardized reporting of imaging findings., Competing Interests: Dr Alkhouli has served on Advisory board for Boston Scientific and Abbott. All other authors have reported that they have no relationships relevant to the contents of this paper to disclose., (© 2024 The Authors.)

The management of pulmonary embolus and intracardiac masses is rapidly evolving with the availability of transcatheter aspiration devices. We describe the utility of a transcatheter aspiration device in management of a patient with pulmonary embolus and a right atrial mass in transit after spinal surgery where a topical hemostatic agent was used to control intraoperative bleeding., Competing Interests: The authors have reported that they have no relationships relevant to the contents of this paper to disclose., (© 2024 The Authors.)

Background: Loneliness and social isolation are associated with poor health outcomes such as an increased risk of cardiovascular diseases., Objectives: The authors aimed to explore the association between social isolation with biological aging which was determined by artificial intelligence-enabled electrocardiography (AI-ECG) as well as the risk of all-cause mortality., Methods: The study included adults aged ≥18 years seen at Mayo Clinic from 2019 to 2022 who respond to a survey for social isolation assessment and had a 12-lead ECG within 1 year of completing the questionnaire. Biological age was determined from ECGs using a previously developed and validated convolutional neural network (AI-ECG age). Age-Gap was defined as AI-ECG age minus chronological age, where positive values reflect an older-than-expected age. The status of social isolation was measured by the previously validated multiple-choice questions based on Social Network Index (SNI) with score ranges between 0 (most isolated) and 4 (least isolated)., Results: A total of 280,324 subjects were included (chronological age 59.8 ± 16.4 years, 50.9% female). The mean Age-Gap was -0.2 ± 9.16 years. A higher SNI was associated with a lower Age-Gap (β of SNI = 4 was -0.11; 95% CI: -0.22 to -0.01; P  < 0.001, adjusted to covariates). Cox proportional hazard analysis revealed the association between social connection and all-cause mortality (HR for SNI = 4, 0.47; 95% CI: 0.43-0.5; P  < 0.001)., Conclusions: Social isolation is associated with accelerating biological aging and all-cause mortality independent of conventional cardiovascular risk factors. This observation underscores the need to address social connection as a health care determinant., Competing Interests: Drs Friedman, Lopez-Jimenez, and Attia are coinvestigators of the AI-ECG age algorithm, which has been licensed to Alumana, Mayo Clinic. All other authors have reported that they have no relationships relevant to the contents of this paper to disclose., (© 2024 The Authors.)

Transapical puncture for transcatheter treatment of mitral-paravalvular leak (PVL) is associated with increased risks even when the apical tract is closed with vascular plugs. A novel technique that leverages back wall support from the right or left atrium can be used to facilitate transcatheter closure of mitral PVL through an antegrade approach. ( Level of Difficulty: Advanced. )., Competing Interests: The authors have reported that they have no relationships relevant to the contents of this paper to disclose., (© 2023 The Authors.)

Spontaneous coronary artery dissection of the septal arteries is rare and may be overlooked on coronary angiogram. Additionally, dedicated intracoronary imaging may not be feasible due to artery size. Cardiac magnetic resonance imaging has an emerging role in diagnosis, which is critical because management changes significantly if spontaneous coronary artery dissection is diagnosed. ( Level of Difficulty: Beginner. )., Competing Interests: Dr Tweet is supported by funding from the National Institutes of Health (1K23HL155506-01A1). All other authors have reported that they have no relationships relevant to the contents of this paper to disclose., (© 2023 The Authors.)

Objective: To investigate the association of voice analysis with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection., Patients and Methods: A vocal biomarker, a unitless scalar with a value between 0 and 1, was developed based on 434 voice samples. The biomarker training was followed by a prospective, multicenter, observational study. All subjects were tested for SARS-CoV-2, had their voice recorded to a smartphone application, and gave their informed consent to participate in the study. The association of SARS-CoV-2 infection with the vocal biomarker was evaluated., Results: The final study population included 80 subjects with a median age of 29 [range, 23 to 36] years, of whom 68% were men. Forty patients were positive for SARS-CoV-2. Infected patients were 12 times more likely to report at least one symptom (odds ratio, 11.8; P <.001). The vocal biomarker was significantly higher among infected patients (OR, 0.11; 95% CI, 0.06 to 0.17 vs OR, 0.19; 95% CI, 0.12 to 0.3; P =.001). The area under the receiver operating characteristic curve evaluating the association of the vocal biomarker with SARS-CoV-2 status was 72%. With a biomarker threshold of 0.115, the results translated to a sensitivity and specificity of 85% (95% CI, 70% to 94%) and 53% (95% CI, 36% to 69%), respectively. When added to a self-reported symptom classifier, the area under the curve significantly improved from 0.775 to 0.85., Conclusion: Voice analysis is associated with SARS-CoV-2 status and holds the potential to improve the accuracy of self-reported symptom-based screening tools. This pilot study suggests a possible role for vocal biomarkers in screening for SARS-CoV-2-infected subjects., (© 2021 The Authors.)

Background: Adoption of the Digital Imaging and Communications in Medicine (DICOM) standard for whole slide images (WSIs) has been slow, despite significant time and effort by standards curators. One reason for the lack of adoption is that there are few tools which exist that can meet the requirements of WSIs, given an evolving ecosystem of best practices for implementation. Eventually, vendors will conform to the specification to ensure enterprise interoperability, but what about archived slides? Millions of slides have been scanned in various proprietary formats, many with examples of rare histologies. Our hypothesis is that if users and developers had access to easy to use tools for migrating proprietary formats to the open DICOM standard, then more tools would be developed as DICOM first implementations., Methods: The technology we present here is dicom&#95;wsi, a Python based toolkit for converting any slide capable of being read by the OpenSlide library into DICOM conformant and validated implementations. Moreover, additional postprocessing such as background removal, digital transformations (e.g., ink removal), and annotation storage are also described. dicom&#95;wsi is a free and open source implementation that anyone can use or modify to meet their specific purposes., Results: We compare the output of dicom&#95;wsi to two other existing implementations of WSI to DICOM converters and also validate the images using DICOM capable image viewers., Conclusion: dicom&#95;wsi represents the first step in a long process of DICOM adoption for WSI. It is the first open source implementation released in the developer friendly Python programming language and can be freely downloaded at ., Competing Interests: There are no conflicts of interest., (Copyright: © 2021 Journal of Pathology Informatics.)

Whole-slide images (WSIs) are a rich new source of biomedical imaging data. The use of automated systems to classify and segment WSIs has recently come to forefront of the pathology research community. While digital slides have obvious educational and clinical uses, their most exciting potential lies in the application of quantitative computational tools to automate search tasks, assist in classic diagnostic classification tasks, and improve prognosis and theranostics. An essential step in enabling these advancements is to apply advances in machine learning and artificial intelligence from other fields to previously inaccessible pathology datasets, thereby enabling the application of new technologies to solve persistent diagnostic challenges in pathology. Here, we applied convolutional neural networks to differentiate between two forms of melanocytic lesions (Spitz and conventional). Classification accuracy at the patch level was 99.0%-2% when applied to WSI. Importantly, when the model was trained without careful image curation by a pathologist, the training took significantly longer and had lower overall performance. These results highlight the utility of augmented human intelligence in digital pathology applications, and the critical role pathologists will play in the evolution of computational pathology algorithms., Competing Interests: There are no conflicts of interest.