Correction: Use of Virtual Reality and Augmented Reality Technologies to Support Resilience and Skill-Building in Caregivers of Persons With Dementia: A Scoping Review.

[This corrects the article DOI: 10.7759/cureus.64082.

Treating Lower Phantom Limb Pain in the Postoperative Acute Care Setting Using Virtual Reality: Protocol for a 4-Phase Development and Feasibility Trial.

Background: Phantom limb pain (PLP) affects most people living with lower limb amputations (LLAs). Nonpharmacological interventions, such as graded motor imagery (GMI), have demonstrated promise as PLP treatments. However, GMI access is limited by low patient buy-in and long public outpatient wait times.

Use of Virtual Reality and Augmented Reality Technologies to Support Resilience and Skill-Building in Caregivers of Persons With Dementia: A Scoping Review.

Dementia presents a growing public health challenge with most affected individuals living at home, placing significant responsibility on their caregivers. Various interventions, from traditional support groups and education programs to emerging technologies, and more specifically virtual reality (VR) and augmented reality (AR), aim to enhance caregiver skills. While VR/AR shows promise in educating and fostering empathy among caregivers and healthcare professionals, its overall effectiveness and practicality in older adults and dementia care warrant further exploration.

An Immersive Virtual Reality Intervention for Preoperative Anxiety and Distress Among Adults Undergoing Oncological Surgery: Protocol for a 3-Phase Development and Feasibility Trial.

Background: Preoperative state anxiety (PSA) is distress and anxiety directly associated with perioperative events. PSA is associated with negative postoperative outcomes such as longer hospital length of stay, increased pain and opioid use, and higher rates of rehospitalization. Psychological prehabilitation, such as education, exposure to hospital environments, and relaxation strategies, has been shown to mitigate PSA; however, there are limited skilled personnel to deliver such interventions in clinical practice.

Preoperative Virtual Reality to Expose Patients With Breast Cancer to the Operating Room Environment: Feasibility and Pilot Case Series Study.

Background: Clinically elevated preoperative distress and anxiety are common among patients undergoing cancer surgery. Preoperative interventions have been developed to mitigate this distress and anxiety but are inconsistent in efficacy and feasibility for broad implementation.

Objective: This preliminary pilot study aims to assess the feasibility and utility of a newly developed virtual reality (VR) intervention to expose patients awaiting breast cancer surgery to the operating room environment and a simulation of anesthetic induction.

An Immersive and Interactive Platform for Cognitive Assessment and Rehabilitation (bWell): Design and Iterative Development Process.

Background: Immersive technologies like virtual reality can enable clinical care that meaningfully aligns with real-world deficits in cognitive functioning. However, options in immersive 3D environments are limited, partly because of the unique challenges presented by the development of a clinical care platform. These challenges include selecting clinically relevant features, enabling tasks that capture the full breadth of deficits, ensuring longevity in a rapidly changing technology landscape, and performing the extensive technical and clinical validation required for digital interventions.

Fractal dimension and directional analysis of elastic and collagen fiber arrangement in unsectioned arterial tissues affected by atherosclerosis and aging.

Structural proteins like collagen and elastin are major constituents of the extracellular matrix (ECM). ECM degradation and remodeling in diseases significantly impact the microorganization of these structural proteins. Therefore, tracking the changes of collagen and elastin fiber morphological features within ECM impacted by disease progression could provide valuable insight into pathological processes such as tissue fibrosis and atherosclerosis.

Evaluation of texture parameters for the quantitative description of multimodal nonlinear optical images from atherosclerotic rabbit arteries.

The composition and structure of atherosclerotic lesions can be directly related to the risk they pose to the patient. Multimodal nonlinear optical (NLO) microscopy provides a powerful means to visualize the major extracellular components of the plaque that critically determine its structure. Textural features extracted from NLO images were investigated for their utility in providing quantitative descriptors of structural and compositional changes associated with plaque development.

Differentiating atherosclerotic plaque burden in arterial tissues using femtosecond CARS-based multimodal nonlinear optical imaging.

A femtosecond CARS-based nonlinear optical microscope was used to simultaneously image extracellular structural proteins and lipid-rich structures within intact aortic tissue obtained from myocardial infarction-prone Watanabe heritable hyperlipidemic rabbits (WHHLMI). Clear differences in the NLO microscopic images were observed between healthy arterial tissue and regions dominated by atherosclerotic lesions. In the current ex-vivo study, we present a single parameter based on intensity changes derived from multi-channel NLO image to classify plaque burden within the vessel.

Multimodal nonlinear optical imaging of atherosclerotic plaque development in myocardial infarction-prone rabbits.

Label-free imaging of bulk arterial tissue is demonstrated using a multimodal nonlinear optical microscope based on a photonic crystal fiber and a single femtosecond oscillator operating at 800 nm. Colocalized imaging of extracellular elastin fibers, fibrillar collagen, and lipid-rich structures within aortic tissue obtained from atherosclerosis-prone myocardial infarction-prone Watanabe heritable hyperlipidemic (WHHLMI) rabbits is demonstrated through two-photon excited fluorescence, second harmonic generation, and coherent anti-Stokes Raman scattering, respectively. These images are shown to differentiate healthy arterial wall, early atherosclerotic lesions, and advanced plaques.

Semi-parametric estimation in the compositional modeling of multicomponent systems from Raman spectroscopic data.

Identification and quantification of molecular species are central applications of molecular spectroscopy. In complex multicomponent systems like tissue samples, linear parametric models are often used to estimate the relative concentrations of the biochemical components of the sample. In situations where not all of the components of the sample are known or modeled, such parametric models can suffer from omitted variable bias and result in skewed estimates of component concentrations.