A Pilot Clinical and Technical Validation of an Immersive Virtual Reality Platform for 3D Anatomical Modeling and Contouring in Support of Surgical and Radiation Oncology Treatment Planning.

The aim of this study was to validate a novel medical virtual reality (VR) platform used for medical image segmentation and contouring in radiation oncology and 3D anatomical modeling and simulation for planning medical interventions, including surgery. The first step of the validation was to verify quantitatively and qualitatively that the VR platform can produce substantially equivalent 3D anatomical models, image contours, and measurements to those generated with existing commercial platforms. To achieve this, a total of eight image sets and 18 structures were segmented using both VR and reference commercial platforms. The image sets were chosen to cover a broad range of scanner manufacturers, modalities, and voxel dimensions. The second step consisted of evaluating whether the VR platform could provide efficiency improvements for target delineation in radiation oncology planning. To assess this, the image sets for five pediatric patients with resected standard-risk medulloblastoma were used to contour target volumes in support of treatment planning of craniospinal irradiation, requiring complete inclusion of the entire cerebral-spinal volume. Structures generated in the VR and the commercial platforms were found to have a high degree of similarity, with dice similarity coefficient ranging from 0.963 to 0.985 for high-resolution images and 0.920 to 0.990 for lower resolution images. Volume, cross-sectional area, and length measurements were also found to be in agreement with reference values derived from a commercial system, with length measurements having a maximum difference of 0.22 mm, angle measurements having a maximum difference of 0.04°, and cross-sectional area measurements having a maximum difference of 0.16 mm2. The VR platform was also found to yield significant efficiency improvements, reducing the time required to delineate complex cranial and spinal target volumes by an average of 50% or 29 min.

Interventions that have potential to help older adults living with social frailty: a systematic scoping review.

BACKGROUND: The impact of social frailty on older adults is profound including mortality risk, functional decline, falls, and disability. However, effective strategies that respond to the needs of socially frail older adults are lacking and few studies have unpacked how social determinants operate or how interventions can be adapted during periods requiring social distancing and isolation such as the COVID-19 pandemic. To address these gaps, we conducted a scoping review using JBI methodology to identify interventions that have the best potential to help socially frail older adults (age ≥65 years). METHODS: We searched MEDLINE, CINAHL (EPSCO), EMBASE and COVID-19 databases and the grey literature. Eligibility criteria were developed using the PICOS framework. Our results were summarized descriptively according to study, patient, intervention and outcome characteristics. Data synthesis involved charting and categorizing identified interventions using a social frailty framework.  RESULTS: Of 263 included studies, we identified 495 interventions involving ~124,498 older adults who were mostly female. The largest proportion of older adults (40.5%) had a mean age range of 70-79 years. The 495 interventions were spread across four social frailty domains: social resource (40%), self-management (32%), social behavioural activity (28%), and general resource (0.4%). Of these, 189 interventions were effective for improving loneliness, social and health and wellbeing outcomes across psychological self-management, self-management education, leisure activity, physical activity, Information Communication Technology and socially assistive robot interventions. Sixty-three interventions were identified as feasible to be adapted during infectious disease outbreaks (e.g., COVID-19, flu) to help socially frail older adults. CONCLUSIONS: Our scoping review identified promising interventions with the best potential to help older adults living with social frailty.

Evaluation of an online arts-based platform to support the health and well-being of older adults during the COVID-19 pandemic: a cross-sectional survey.

OBJECTIVES: The objective of this study was to conduct a formative evaluation of the Art Your Service (AYS) arts-based program to determine the program's potential for improving the social and physical well-being of older adults during the COVID-19 pandemic. DESIGN, SETTINGS AND PARTICIPANTS: An online questionnaire was administered to the AYS members who consented to be invited to participate in the study. Questionnaire items consisted of a Likert scale and open-ended questions delivered using an online platform (SurveyMonkey). Participants provided feedback on their perceptions and experiences of the AYS program, such as its impact on their health and well-being during the COVID-19 pandemic, the benefits and challenges of participating, and any suggestions for program improvement. OUTCOME MEASURES AND ANALYSIS: Quantitative data were analyzed using descriptive statistics (frequencies, means with standard deviations), and open-ended questions (qualitative data) were analyzed using content analysis. Outcomes included participant demographics, perceptions about the program, usability (System Usability Scale [SUS]), eHealth literacy (eHealth Literacy Scale), and social isolation (Lubben Social Network Scale; LSNS-6). RESULTS: Program participants revealed consistent patterns of their perceptions and experiences about the program, including a high satisfaction rate (95%) and a perceived positive impact on participants' health and well-being. The program sessions were perceived to be a well-organized, convenient, and safe way to engage with one another socially during the COVID-19 pandemic. The program usability was also perceived to be high (SUS mean score 86.2). Participants felt a sense of connectedness and had reduced feelings of social isolation. Most participants (75%) reported that the program improved their physical health. CONCLUSIONS: Findings from this formative evaluation study identified key strengths and opportunities to improve the Art Your Service arts-based program, which can be used to help enhance the program's functioning and long-term sustainability potential.

A scoping review reveals candidate quality indicators of knowledge translation and implementation science practice tools.

OBJECTIVES: To identify candidate quality indicators from existing tools that provide guidance on how to practice knowledge translation and implemenation science (KT practice tools) across KT domains (dissemination, implementation, sustainability, and scalability). STUDY DESIGN AND SETTING: We conducted a scoping review using the Joanna Briggs Institute Manual for Evidence Synthesis. We systematically searched multiple electronic databases and the gray literature. Documents were independently screened, selected, and extracted by pairs of reviewers. Data about the included articles, KT practice tools, and candidate quality indicators were analyzed, categorized, and summarized descriptively. RESULTS: Of 43,060 titles and abstracts that were screened from electronic databases and gray literature, 850 potentially relevant full-text articles were identified, and 253 articles were included in the scoping review. Of these, we identified 232 unique KT practice tools from which 27 unique candidate quality indicators were generated. The identified candidate quality indicators were categorized according to the development (n = 17), evaluation (n = 5) and adaptation (n = 3) of the tools, and engagement of knowledge users (n = 2). No tools were identified that appraised the quality of KT practice tools. CONCLUSIONS: The development of a quality appraisal instrument of KT practice tools is needed. The results will be further refined and finalized in order to develop a quality appraisal instrument for KT practice tools.

Predicting VMAT patient-specific QA results using a support vector classifier trained on treatment plan characteristics and linac QC metrics.

The use of treatment plan characteristics to predict patient-specific quality assurance (QA) measurement results has recently been reported as a strategy to help facilitate automated pre-treatment verification workflows or to provide a virtual assessment of delivery quality. The goal of this work is to investigate the potential of using treatment plan characteristics and linac performance metrics (i.e. quality control test results) in combination with machine learning techniques to predict the results of VMAT patient-specific QA measurements. Using features that describe treatment plan complexity and linac performance metrics, we trained a linear support vector classifier (SVC) to classify the results of VMAT patient-specific QA measurements. The 'targets' in this model were simple classes representing median dose difference between measured and expected dose distributions-'hot' if the median dose deviation was >1%, 'cold' if it was <-1%, and 'normal' if it was within ±1%. A total of 1620 unique patient-specific QA measurements were available for model development and testing. 75% of the data were used to develop and cross-validate the model, and the remaining 25% were used for an independent assessment of model performance. For the model development phase, a recursive feature elimination (RFE) cross-validation technique was used to eliminate unimportant features. Model performance was assessed using receiver operator characteristic (ROC) curve metrics. Of the ten features found to be most predictive of patient-specific QA measurement results, half were derived from treatment plan characteristics and half from quality control (QC) metrics characterizing linac performance. The model achieved a micro-averaged area under the ROC curve of 0.93, and a macro-averaged area under the ROC curve of 0.88. This work demonstrates the potential of using both treatment plan characteristics and routine linac QC results in the development of machine learning models for VMAT patient-specific QA measurements.

Applying Modern Virtual and Augmented Reality Technologies to Medical Images and Models.

Recent technological innovations have created new opportunities for the increased adoption of virtual reality (VR) and augmented reality (AR) applications in medicine. While medical applications of VR have historically seen greater adoption from patient-as-user applications, the new era of VR/AR technology has created the conditions for wider adoption of clinician-as-user applications. Historically, adoption to clinical use has been limited in part by the ability of the technology to achieve a sufficient quality of experience. This article reviews the definitions of virtual and augmented reality and briefly covers the history of their development. Currently available options for consumer-level virtual and augmented reality systems are presented, along with a discussion of technical considerations for their adoption in the clinical environment. Finally, a brief review of the literature of medical VR/AR applications is presented prior to introducing a comprehensive conceptual framework for the viewing and manipulation of medical images in virtual and augmented reality. Using this framework, we outline considerations for placing these methods directly into a radiology-based workflow and show how it can be applied to a variety of clinical scenarios.

Impact of blending for direct potable reuse on premise plumbing microbial ecology and regrowth of opportunistic pathogens and antibiotic resistant bacteria.

Little is known about how introducing recycled water intended for direct potable reuse (DPR) into distribution systems and premise plumbing will affect water quality at the point of use, particularly with respect to effects on microbial communities and regrowth. The examination of potential growth of opportunistic pathogens (OPs) and spread of antibiotic resistance genes (ARGs), each representing serious and growing public health concerns, by introducing DPR water has not previously been evaluated. In this study, the impact of blending purified DPR water with traditional drinking water sources was investigated with respect to treatment techniques, blending location, and blending ratio. Water from four U.S. utility partners was treated in bench- and pilot-scale treatment trains to simulate DPR with blending. Water was incubated in simulated premise plumbing rigs made of PVC pipe containing brass coupons to measure regrowth of total bacteria (16S rRNA genes, heterotrophic plate count), OPs (Legionella spp., Mycobacterium spp., Pseudomonas aeruginosa), ARGs (qnrA, vanA), and an indicator of horizontal gene transfer and multi-drug resistance (intI1). The microbial community composition was profiled and the resistome (i.e., all ARGs present) was characterized in select samples using next generation sequencing. While regrowth of total bacteria (16S rRNA genes) from the start of the incubation through week eight consistently occurred across tested scenarios (Wilcoxon, p ≤ 0.0001), total bacteria were not more abundant in the water or biofilm of any DPR scenario than in the corresponding conventional potable condition (p ≥ 0.0748). Regrowth of OP marker genes, qnrA, vanA, and intI1 were not significantly greater in water or biofilm for any DPR blends treated with advanced oxidation compared to corresponding potable water (p ≥ 0.1047). This study of initial bacteria colonizing pipes after introduction of blended DPR water revealed little evidence (i.e., one target in one water type) of exacerbated regrowth of total bacteria, OPs, or ARGs in premise plumbing.