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This paper reports on the work of the Web3D Consortium's Medical Working Group to specify and implement MedX3D – an extension to the X3D standard that will support advanced medical visualization functionality and medical data exchange. This initiative covers volume rendering, ontology support, and data import/export, for standalone applications and web-based plug-ins. It is our hypothesis that such a 3D medical standard will provide better access to data, and enable improvements in medical care. [ABSTRACT FROM AUTHOR]

Background: Depression and anxiety create a large health burden and increase the risk of premature mortality. Mental health screening is vital, but more sophisticated screening and monitoring methods are needed. The Ellipsis Health App addresses this need by using semantic information from recorded speech to screen for depression and anxiety., Objectives: The primary aim of this study is to determine the feasibility of collecting weekly voice samples for mental health screening. Additionally, we aim to demonstrate portability and improved performance of Ellipsis' machine learning models for patients of various ages., Methods: Study participants were current patients at Desert Oasis Healthcare, mean age 63 years (SD = 10.3). Two non-randomized cohorts participated: one with a documented history of depression within 24 months prior to the study (Group Positive), and the other without depression (Group Negative). Participants recorded 5-min voice samples weekly for 6 weeks via the Ellipsis Health App. They also completed PHQ-8 and GAD-7 questionnaires to assess for depression and anxiety, respectively., Results: Protocol completion rate was 61% for both groups. Use beyond protocol was 27% for Group Positive and 9% for Group Negative. The Ellipsis Health App showed an AUC of 0.82 for the combined groups when compared to the PHQ-8 and GAD-7 with a threshold score of 10. Performance was high for senior participants as well as younger age ranges. Additionally, many participants spoke longer than the required 5 min., Conclusion: The Ellipsis Health App demonstrated feasibility in using voice recordings to screen for depression and anxiety among various age groups and the machine learning models using Transformer methodology maintain performance and improve over LSTM methodology when applied to the study population., Competing Interests: All authors were employed by the company Ellipsis Health Inc. The authors declare that this study received funding from Ellipsis Health Inc. Ellipsis Health Inc. had the following involvement in the study: study design, collection, analysis, interpretation of data, the writing of this article and the decision to submit it for publication., (Copyright © 2022 Lin, Nazreen, Rutowski, Lu, Harati, Shriberg, Chlebek and Aratow.)

Adolescents and young adults (AYAs) diagnosed with cancer are an age-defined population, with studies reporting up to 45% of the population experiencing psychological distress. Although it is essential to screen and monitor for psychological distress throughout AYAs' cancer journeys, many cancer centers fail to effectively implement distress screening protocols largely due to busy clinical workflow and survey fatigue. Recent advances in mobile technology and speech science have enabled flexible and engaging methods to monitor psychological distress. However, patient-centered research focusing on these methods' feasibility and acceptability remains lacking. Therefore, in this project, we aim to evaluate the feasibility and acceptability of an artificial intelligence (AI)-enabled and speech-based mobile application to monitor psychological distress among AYAs diagnosed with cancer. We use a single-arm prospective cohort design with a stratified sampling strategy. We aim to recruit 60 AYAs diagnosed with cancer and to monitor their psychological distress using an AI-enabled speech-based distress monitoring tool over a 6 month period. The primary feasibility endpoint of this study is defined by the number of participants completing four out of six monthly distress assessments, and the acceptability endpoint is defined both quantitatively using the acceptability of intervention measure and qualitatively using semi-structured interviews.

Objective: To utilize, in an individual and institutional privacy-preserving manner, electronic health record (EHR) data from 202 hospitals by analyzing answers to COVID-19-related questions and posting these answers online., Materials and Methods: We developed a distributed, federated network of 12 health systems that harmonized their EHRs and submitted aggregate answers to consortia questions posted at https://www.covid19questions.org. Our consortium developed processes and implemented distributed algorithms to produce answers to a variety of questions. We were able to generate counts, descriptive statistics, and build a multivariate, iterative regression model without centralizing individual-level data., Results: Our public website contains answers to various clinical questions, a web form for users to ask questions in natural language, and a list of items that are currently pending responses. The results show, for example, that patients who were taking angiotensin-converting enzyme inhibitors and angiotensin II receptor blockers, within the year before admission, had lower unadjusted in-hospital mortality rates. We also showed that, when adjusted for, age, sex, and ethnicity were not significantly associated with mortality. We demonstrated that it is possible to answer questions about COVID-19 using EHR data from systems that have different policies and must follow various regulations, without moving data out of their health systems., Discussion and Conclusions: We present an alternative or a complement to centralized COVID-19 registries of EHR data. We can use multivariate distributed logistic regression on observations recorded in the process of care to generate results without transferring individual-level data outside the health systems., (© The Author(s) 2021. Published by Oxford University Press on behalf of the American Medical Informatics Association.)

In this paper we summarize the progress of the Web3D scene graph model, and associated standards, specifically Extensible 3D (X3D) in the domain of medical simulation. Historically, the Web3D nodesets have focused on the representation and rendering of point, line or surface geometry. More recently, significant progress in X3D Volume rendering has been made available through the co-operative DICOM work item, n-Dimensional Presentation States. However, here we outline the need for a standard for simulation meshes and review several related approaches. As a result, we propose preliminary requirements for a simulation mesh standard and provide several use case scenarios of how Web3D and haptic technologies can aid the fulfillment of these requirements. We conclude with an X3D proposal to describe simulation meshes for soft (deformable) bodies.

Intramuscular pressure was measured continuously in the deep compartment of the calf and anterior thigh of volunteers while their legs were cyclically moved from 0 degrees to 90 degrees back to 0 degrees (angle of knee flexion) in an anatomic continuous passive motion (CPM) device and a nonanatomic CPM device. Femoral venous flow was measured continuously using a thermodilution technique in volunteers while their legs were moved in both CPM devices, during inflation of a pneumatic stocking, and during several leg manipulations. Baseline intramuscular pressures in the deep calf and anterior thigh were 10.0 +/- 1.9 mmHg and 4.9 +/- 1.9 mmHg, respectively (mean +/- standard error). Both the anatomic and nonanatomic CPM devices produced a statistically significant maximal increase in pressure in the calf. By contrast, only a decrease in pressure occurred in the thigh with both devices. Baseline femoral vein flow measured by the thermodilution technique was 311 +/- 38 ml per minute. Significant increases in femoral vein flow were seen with both CPM devices. The maximal flow produced by the anatomic CPM was 1199 ml per minute and was approximately four times higher than baseline flow and approximately 1.4 times the maximal flow change seen with the nonanatomic CPM (836 ml per minute). The greatest net increase in flow was observed between 60 degrees and 90 degrees of knee flexion with both devices. Overall, passive straight-leg elevation produced the largest flow (1524 ml per minute), followed by the anatomic CPM and nonanatomic CPM, and then by active ankle dorsiflexion(640 ml per minute), pneumatic stocking inflation (586 ml per minute), manual calf compression (532 ml per minute), and passive dorsiflexion (385 ml per minute)(ABSTRACT TRUNCATED AT 250 WORDS)

To explore the mechanism for facial puffiness, headache, and nasal congestion associated with microgravity and cephalad fluid shifts, the postural responses of the cutaneous microcirculation in the forehead and dorsum of the foot of eight healthy men were studied by changing body position on a tilt table and measuring blood flows with a laser-Doppler flowmeter. Increasing arterial pressure in the feet by moving from a -6 degree head-down tilt to a 60 degrees head-up posture decreased foot cutaneous flow by 46.5 +/- 12.0% (mean +/- S.E.; p less than 0.05). Raising arterial pressure in the head by tilting from the 60 degree head-up to -6 degree head-down posture increased forehead cutaneous flow by 25.5 +/- 7.2% (p less than 0.05). To investigate the possibility that these opposite responses could be modified by simulated microgravity, tilt tests were repeated after 7 d of -6 degrees head-down tilt bed rest. On the 1st and 2nd days after bed rest, flows in the foot were decreased by 69.4 +/- 8.8% and 45.8 +/- 18.7%, respectively, and increased in the head by 39.3 +/- 8.6% and 15.5 +/- 5.9%, respectively. These responses were not significantly different from those recorded before bed rest. Therefore, cutaneous microcirculatory flow in the feet is well regulated to prevent edema when shifting to an upright position, whereas there is less regulation in the head microcirculation. The lack of regulation in the forehead cutaneous microcirculation increases capillary flow, and consequently increases fluid filtration. This phenomenon helps explain the facial edema associated with the stimulated or actual microgravity environment.

A full-thickness articular-cartilage defect was created in the medial femoral condyles of 32 adult rabbits. The defects were filled with demineralized bone or a composite of demineralized bone and perichondrium. Results of cartilage repair were assessed after 12 weeks of implantation. We conclude that demineralized bone matrix used as a subchondral matrix in a cartilage repair model 1) stimulates and induces subchondral bone ingrowth, 2) provides a surface on which cartilage repair can proceed, and 3) can be utilized as a platform on which perichondrium can be fixed to provide a cellular source for cartilage repair. Repair tissue that developed from perichondrium was thicker, more closely resembled normal articular cartilage, and was of a less fibrous nature than the repair tissue that developed de novo on the demineralized bone matrix.