Validated respiratory drug deposition predictions from 2D and 3D medical images with statistical shape models and convolutional neural networks.

For the one billion sufferers of respiratory disease, managing their disease with inhalers crucially influences their quality of life. Generic treatment plans could be improved with the aid of computational models that account for patient-specific features such as breathing pattern, lung pathology and morphology. Therefore, we aim to develop and validate an automated computational framework for patient-specific deposition modelling. To that end, an image processing approach is proposed that could produce 3D patient respiratory geometries from 2D chest X-rays and 3D CT images. We evaluated the airway and lung morphology produced by our image processing framework, and assessed deposition compared to in vivo data. The 2D-to-3D image processing reproduces airway diameter to 9% median error compared to ground truth segmentations, but is sensitive to outliers of up to 33% due to lung outline noise. Predicted regional deposition gave 5% median error compared to in vivo measurements. The proposed framework is capable of providing patient-specific deposition measurements for varying treatments, to determine which treatment would best satisfy the needs imposed by each patient (such as disease and lung/airway morphology). Integration of patient-specific modelling into clinical practice as an additional decision-making tool could optimise treatment plans and lower the burden of respiratory diseases.

Influenza vaccination coverage among persons ages six months and older in the Vaccine Safety Datalink in the 2017-18 through 2022-23 influenza seasons.

BACKGROUND: In the United States, annual vaccination against seasonal influenza is recommended for all people ages ≥ 6 months. Vaccination coverage assessments can identify populations less protected from influenza morbidity and mortality and help to tailor vaccination efforts. Within the Vaccine Safety Datalink population ages ≥ 6 months, we report influenza vaccination coverage for the 2017-18 through 2022-23 seasons. METHODS: Across eight health systems, we identified influenza vaccines administered from August 1 through March 31 for each season using electronic health records linked to immunization registries. Crude vaccination coverage was described for each season, overall and by self-reported sex; age group; self-reported race and ethnicity; and number of separate categories of diagnoses associated with increased risk of severe illness and complications from influenza (hereafter referred to as high-risk conditions). High-risk conditions were assessed using ICD-10-CM diagnosis codes assigned in the year preceding each influenza season. RESULTS: Among individual cohorts of more than 12 million individuals each season, overall influenza vaccination coverage increased from 41.9 % in the 2017-18 season to a peak of 46.2 % in 2019-20, prior to declaration of the COVID-19 pandemic. Coverage declined over the next three seasons, coincident with widespread SARS-CoV-2 circulation, to a low of 40.3 % in the 2022-23 season. In each of the six seasons, coverage was lowest among males, 18-49-year-olds, non-Hispanic Black people, and those with no high-risk conditions. While decreases in coverage were present in all age groups, the declines were most substantial among children: 2022-23 season coverage for children ages six months through 8 years and 9-17 years was 24.5 % and 22.4 % (14 and 10 absolute percentage points), respectively, less than peak coverage achieved in the 2019-20 season. CONCLUSIONS: Crude influenza vaccination coverage increased from 2017 to 18 through 2019-20, then decreased to the lowest level in the 2022-23 season. In this insured population, we identified persistent disparities in influenza vaccination coverage by sex, age, and race and ethnicity. The overall low coverage, disparities in coverage, and recent decreases in coverage are significant public health concerns.

Effect of patient inhalation profile and airway structure on drug deposition in image-based models with particle-particle interactions.

For many of the one billion sufferers of respiratory diseases worldwide, managing their disease with inhalers improves their ability to breathe. Poor disease management and rising pollution can trigger exacerbations that require urgent relief. Higher drug deposition in the throat instead of the lungs limits the impact on patient symptoms. To optimise delivery to the lung, patient-specific computational studies of aerosol inhalation can be used. However in many studies, inhalation modelling does not represent situations when the breathing is impaired, such as in recovery from an exacerbation, where the patient's inhalation is much faster and shorter. Here we compare differences in deposition of inhaler particles (10, 4 µm) in the airways of three patients. We aimed to evaluate deposition differences between healthy and impaired breathing with image-based healthy and diseased patient models. We found that the ratio of drug in the lower to upper lobes was 35% larger with a healthy inhalation. For smaller particles the upper airway deposition was similar in all patients, but local deposition hotspots differed in size, location and intensity. Our results identify that image-based airways must be used in respiratory modelling. Various inhalation profiles should be tested for optimal prediction of inhaler deposition.

Accuracy of the Actigraph wGT3x-BT for step counting during inpatient spinal cord rehabilitation.

STUDY DESIGN: Cross-sectional. OBJECTIVES: (1) Assess the accuracy of the Actigraph wGT3x-BT accelerometer to count steps taken by inpatients with incomplete spinal cord injury (iSCI) in physical therapy (PT) sessions and self-directed activities, and (2) compare the number of steps/min taken in PT sessions to that in self-directed activities during inpatient rehabilitation. SETTING: Inpatient spinal cord injury rehabilitation. METHODS: Seventeen individuals with subacute motor iSCI were observed for up to 45-min of both PT and self-directed activities, during which steps were simultaneously tracked by the Actigraph wGT3x-BT and a researcher using a hand tally counter. Accuracy was evaluated with an intraclass correlation coefficient (ICC) for the entire PT session and self-directed activities, as well as for periods of walking. RESULTS: There was excellent agreement between the Actigraph wGT3x-BT and manually counted steps for entire PT sessions (ICC = 0.86) and walking periods (PT walking, ICC = 0.99; self-directed walking, ICC = 0.99). There was poor agreement for entire self-directed sessions (ICC = 0.15). Visual analysis of Bland-Altman plots supported these findings. Participants took more steps/min in PT sessions compared to self-directed activities (p = 0.023). CONCLUSION: The Actigraph wGT3x-BT accurately counts steps during PT sessions and walking periods in individuals with subacute motor iSCI. Clinically, this may enable physical therapists to track walking repetitions during inpatient rehabilitation more effortlessly.

Consequences of wear interruption for discomfort with contact lenses.

PURPOSE: To establish whether increased end-of-day discomfort during soft contact lens wear is associated with short-term changes occurring to the lens itself. METHODS: Twenty-seven subjects wore hydrogel lenses (Focus Dailies; Alcon) bilaterally for 10 hours on two separate days. Comfort was reported using 1-100 numerical rating scales (1 = intolerable discomfort, 100 = lens cannot be felt). Day 1 ratings were taken before lens insertion and at 0.05, 5, and 10 hours post-insertion. Day 2 ratings occurred at similar times, but lenses were removed after the 5-hour assessment and either reinserted (n = 14) or newly replaced (n = 12). An additional rating was taken 5 minutes after re-insertion. Wear then continued to the 10-hour point. In a separate study, 24 different subjects repeated these procedures using a silicone hydrogel lens (AirOptix Aqua; Alcon) with wear taking place on 3 days to permit lens replacement to be with existing as well as new lenses in all subjects. RESULTS: For hydrogel lenses, comfort scores (mean ± 95% CI) reported after 10 hours were 79.4 ± 8.3 when lenses were worn un-replaced, compared with 73.2 ± 9.2 for replacement with the existing lens. When replacement was with a brand new lens, the corresponding values were 72.9 ± 10.9 (un-replaced) versus 69.2 ± 12.8 (new lens replacement). For silicone hydrogel lenses, 10-hour comfort was 90.3 ± 3.2 (un-replaced) versus 92.2 ± 2.9 (replacement with existing lens) versus 90.0 ± 3.3 (replacement with new lens). Differences between replacement conditions were not significant in any case (analysis of variance, p > 0.05). CONCLUSIONS: Final comfort was not influenced by replacing lenses midway through the wearing period. Comfort decrements experienced by users of these daily contact lenses towards the later part of the wearing period are not caused by changes occurring to the lenses on this time scale. Possible alternative etiological factors include a fatigue-like response in one or more ocular tissues or stimulation of ocular surface nociceptors induced by the presence of the contact lens.

STRIVE: Stress Resilience In Virtual Environments: a pre-deployment VR system for training emotional coping skills and assessing chronic and acute stress responses.

The incidence of posttraumatic stress disorder (PTSD) in returning OEF/OIF military personnel is creating a significant healthcare challenge. This has served to motivate research on how to better develop and disseminate evidence-based treatments for PTSD. One emerging form of treatment for combat-related PTSD that has shown promise involves the delivery of exposure therapy using immersive Virtual Reality (VR). Initial outcomes from open clinical trials have been positive and fully randomized controlled trials are currently in progress to further validate this approach. Based on our research group's initial positive outcomes using VR to emotionally engage and successfully treat persons undergoing exposure therapy for PTSD, we have begun development in a similar VR-based approach to deliver stress resilience training with military service members prior to their initial deployment. The Stress Resilience In Virtual Environments (STRIVE) project aims to create a set of combat simulations (derived from our existing Virtual Iraq/Afghanistan exposure therapy system) that are part of a multi-episode narrative experience. Users can be immersed within challenging combat contexts and interact with virtual characters within these episodes as part of an experiential learning approach for training a range of psychoeducational and cognitive-behavioral emotional coping strategies believed to enhance stress resilience. The STRIVE project aims to present this approach to service members prior to deployment as part of a program designed to better prepare military personnel for the types of emotional challenges that are inherent in the combat environment. During these virtual training experiences users are monitored physiologically as part of a larger investigation into the biomarkers of the stress response. One such construct, Allostatic Load, is being directly investigated via physiological and neuro-hormonal analysis from specimen collections taken immediately before and after engagement in the STRIVE virtual experience.

Virtual reality goes to war: a brief review of the future of military behavioral healthcare.

Numerous reports indicate that the incidence of posttraumatic stress disorder (PTSD) in returning OEF/OIF military personnel is creating a significant healthcare challenge. These findings have served to motivate research on how to better develop and disseminate evidence-based treatments for PTSD. Virtual Reality delivered exposure therapy for PTSD has been previously used with reports of positive outcomes. This article details how virtual reality applications are being designed and implemented across various points in the military deployment cycle to prevent, identify and treat combat-related PTSD in OIF/OEF Service Members and Veterans. The summarized projects in these areas have been developed at the University of Southern California Institute for Creative Technologies, a U.S. Army University Affiliated Research Center, and this paper will detail efforts to use virtual reality to deliver exposure therapy, assess PTSD and cognitive function and provide stress resilience training prior to deployment.

An intelligent virtual human system for providing healthcare information and support.

Over the last 15 years, a virtual revolution has taken place in the use of Virtual Reality simulation technology for clinical purposes. Shifts in the social and scientific landscape have now set the stage for the next major movement in Clinical Virtual Reality with the "birth" of intelligent virtual humans. Seminal research and development has appeared in the creation of highly interactive, artificially intelligent and natural language capable virtual human agents that can engage real human users in a credible fashion. No longer at the level of a prop to add context or minimal faux interaction in a virtual world, virtual humans can be designed to perceive and act in a 3D virtual world, engage in spoken dialogues with real users and can be capable of exhibiting human-like emotional reactions. This paper will present an overview of the SimCoach project that aims to develop virtual human support agents to serve as online guides for promoting access to psychological healthcare information and for assisting military personnel and family members in breaking down barriers to initiating care. The SimCoach experience is being designed to attract and engage military Service Members, Veterans and their significant others who might not otherwise seek help with a live healthcare provider. It is expected that this experience will motivate users to take the first step--to empower themselves to seek advice and information regarding their healthcare and general personal welfare and encourage them to take the next step towards seeking more formal resources if needed.

Development of a data management tool for investigating multivariate space and free will experiences in virtual reality.

Virtual reality (VR) has become mature enough to be successfully used in clinical applications such as exposure therapy, pain distraction, and neuropsychological assessment. However, we now need to go beyond the outcome data from this research and conduct the detailed scientific investigations required to better understand what factors influence why VR works (or doesn't) in these types of clinical applications. This knowledge is required to guide the development of VR applications in the key areas of education, training, and rehabilitation and to further evolve existing VR approaches. One of the primary assets obtained with the use of VR is the ability to simulate the complexity of real world environments, within which human performance can be tested and trained. But this asset comes with a price in terms of the capture, quantification and analysis of large, multivariate and concurrent data sources that reflect the naturalistic behavioral interaction that is afforded in a virtual world. As well, while achieving realism has been a main goal in making convincing VR environments, just what constitutes realism and how much is needed is still an open question situated firmly in the research domain. Just as in real "reality," such factors in virtual reality are complex and multivariate, and the understanding of this complexity presents exceptional challenges to the VR researcher. For certain research questions, good behavioral science often requires consistent delivery of stimuli within tightly controlled lab-based experimental conditions. However, for other important research questions we do not want to constrain naturalistic behavior and limit VR's ability to replicate real world conditions, simply because it is easier to study human performance with traditional lab-based methodologies. By doing so we may compromise the very qualities that comprise VR's unique capacity to mimic the experiences and challenges that exist in everyday life. What is really needed to address scientific questions that require natural exploration of a simulated environment are more usable and robust tools to instrument, organize, and visualize the complex data generated by measurements of participant behaviors within a virtual world. This paper briefly describes the rationale and methodology of an initial study in an ongoing research program that aims to investigate human performance within a virtual environment where unconstrained "free will" exploratory behavior is essential to research questions that involve the relationships between physiology, emotion, and memory. After a discussion of the research protocol and the types of data that were collected, we describe a novel tool that was borne from our need to more efficiently capture, manage, and explore the complex data that was generated in this research. An example of a research participant's annotated display from this data management and visualization tool is then presented. It is our view that this tool provides the capacity to better visualize and understand the complex data relationships that may arise in VR research that investigates naturalistic free will behavior and its impact on other human performance variables.