An Introduction to Generative Artificial Intelligence in Mental Health Care: Considerations and Guidance.

PURPOSE OF REVIEW: This paper provides an overview of generative artificial intelligence (AI) and the possible implications in the delivery of mental health care. RECENT FINDINGS: Generative AI is a powerful technology that is changing rapidly. As psychiatrists, it is important for us to understand generative AI technology and how it may impact our patients and our practice of medicine. This paper aims to build this understanding by focusing on GPT-4 and its potential impact on mental health care delivery. We first introduce key concepts and terminology describing how the technology works and various novel uses of it. We then dive into key considerations for GPT-4 and other large language models (LLMs) and wrap up with suggested future directions and initial guidance to the field.

Methods for Navigating the Mobile Mental Health App Landscape for Clinical Use.

There are over 10,000 mental health and wellness apps on the market. Apps offer the opportunity to increase access to mental health care. However, with many apps to choose from and an app landscape that is largely unregulated, it can be difficult to incorporate this technology into clinical practice. The first step towards achieving this goal is to identify clinically relevant and appropriate apps. The purpose of this review is to discuss app evaluation, raise awareness of considerations involved in implementing mental health apps into clinical care, and provide an example of how apps can be used effectively in the clinical space. We discuss the current regulatory environment for health apps, how to evaluate apps, and implement them into clinical practice. We also showcase a digital clinic where apps are integrated into the clinical workflow and discuss barriers to app implementation. Mental health apps have the potential to increase access to care if they are clinically effective, easy to use, and protect patient privacy. Learning how to find, evaluate, and implement quality apps into practice is key in harnessing this technology for the benefit of patients.

Relationship between novel inflammatory biomarker galectin-3 and depression symptom severity in a large community-based sample.

Major depressive disorder is associated with pro-inflammatory markers, such as cytokines TNF-alpha, IL-6, IL-1ß, and C-reactive protein. Galectin-3 is a novel emerging biomarker with pro-inflammatory properties. It is a saccharide binding protein distributed throughout many tissues with varying functions and is a predictor of poor outcomes in patients with heart failure and stroke. However, its role as a predictor in depressive symptom severity remains undefined. Data from the community-based Dallas Heart Study (n = 2554) were examined using a multiple linear regression analysis to evaluate the relationship between galectin-3 and depressive symptom severity as assessed with Quick Inventory of Depressive Symptomatology Self-Report (QIDS-SR) scores. Additional covariates included age, sex, race/ethnicity, body mass index (BMI), years of education, serum creatinine, history of diabetes, and smoking history. Galectin-3 levels statistically significantly predicted QIDS-SR depressive symptom severity (ß = 0.055, p = .015). Female sex, smoking status, and BMI were found to be statistically significant positive predictors of depression severity, while age, years of education, non-Hispanic White race, and Hispanic ethnicity were negative predictors of depressive symptom severity. In this large sample, higher galectin-3 levels were associated with higher levels of depressive symptoms. The findings suggest that galectin-3 may be a new and useful inflammatory biomarker associated with depression.

Relationship between inflammatory biomarker galectin-3 and hippocampal volume in a community study.

Galectin-3 (Gal3) is expressed by microglia and performs functions including adhesion; activation of macrophages and fibroblasts, and mediates inflammatory responses in the hippocampus. The present study examined whether serum Gal3 levels predict hippocampal volume in a multi-ethnic, community-based sample. Results of a multiple linear regression (controlling for depression, serum creatinine level, age, BMI, total brain volume, MoCA score, sex, ethnicity, smoking status, history of diabetes) showed that Gal3 levels significantly predicted left (p = .027) but not right hippocampal volume. The relationship was stronger in men than women. Findings suggest this novel inflammatory biomarker is associated with human hippocampal volume.

Assessment of a noninvasive optical photoplethysmography imaging device with dynamic tissue phantom models.

Noncontact photoplethysmography (PPG) has been studied as a method to provide low-cost, noninvasive, two-dimensional blood oxygenation measurements and medical imaging for a variety of near-surface pathologies. To evaluate this technology in a laboratory setting, dynamic tissue phantoms were developed with tunable parameters that mimic physiologic properties of the skin, including blood vessel volume change, pulse wave frequency, and tissue scattering and absorption. Tissue phantoms were generated using an elastic tubing to represent a blood vessel where the luminal volume could be modulated with a pulsatile fluid flow. The blood was mimicked with a scattering and absorbing motility standard, and the tissue with a gelatin-lipid emulsion hydrogel. A noncontact PPG imaging system was then evaluated using the phantoms. Noncontact PPG imaging accurately identified pulse frequency, and PPG signals from these phantoms suggest that the phantoms can be used to evaluate noncontact PPG imaging systems. Such information may be valuable to the development of future PPG imaging systems.

Imaging Techniques for Clinical Burn Assessment with a Focus on Multispectral Imaging.

Significance: Burn assessments, including extent and severity, are some of the most critical diagnoses in burn care, and many recently developed imaging techniques may have the potential to improve the accuracy of these evaluations. Recent Advances: Optical devices, telemedicine, and high-frequency ultrasound are among the highlights in recent burn imaging advancements. We present another promising technology, multispectral imaging (MSI), which also has the potential to impact current medical practice in burn care, among a variety of other specialties. Critical Issues: At this time, it is still a matter of debate as to why there is no consensus on the use of technology to assist burn assessments in the United States. Fortunately, the availability of techniques does not appear to be a limitation. However, the selection of appropriate imaging technology to augment the provision of burn care can be difficult for clinicians to navigate. There are many technologies available, but a comprehensive review summarizing the tissue characteristics measured by each technology in light of aiding clinicians in selecting the proper device is missing. This would be especially valuable for the nonburn specialists who encounter burn injuries. Future Directions: The questions of when burn assessment devices are useful to the burn team, how the various imaging devices work, and where the various burn imaging technologies fit into the spectrum of burn care will continue to be addressed. Technologies that can image a large surface area quickly, such as thermography or laser speckle imaging, may be suitable for initial burn assessment and triage. In the setting of presurgical planning, ultrasound or optical microscopy techniques, including optical coherence tomography, may prove useful. MSI, which actually has origins in burn care, may ultimately meet a high number of requirements for burn assessment in routine clinical use.

Multispectral and Photoplethysmography Optical Imaging Techniques Identify Important Tissue Characteristics in an Animal Model of Tangential Burn Excision.

Burn excision, a difficult technique owing to the training required to identify the extent and depth of injury, will benefit from a tool that can cue the surgeon as to where and how much to resect. We explored two rapid and noninvasive optical imaging techniques in their ability to identify burn tissue from the viable wound bed using an animal model of tangential burn excision. Photoplethysmography (PPG) imaging and multispectral imaging (MSI) were used to image the initial, intermediate, and final stages of burn excision of a deep partial-thickness burn. PPG imaging maps blood flow in the skin's microcirculation, and MSI collects the tissue reflectance spectrum in visible and infrared wavelengths of light to classify tissue based on a reference library. A porcine deep partial-thickness burn model was generated and serial tangential excision accomplished with an electric dermatome set to 1.0 mm depth. Excised eschar was stained with hematoxylin and eosin to determine the extent of burn remaining at each excision depth. We confirmed that the PPG imaging device showed significantly less blood flow where burn tissue was present, and the MSI method could delineate burn tissue in the wound bed from the viable wound bed. These results were confirmed independently by a histological analysis. We found these devices can identify the proper depth of excision, and their images could cue a surgeon as to the preparedness of the wound bed for grafting. These image outputs are expected to facilitate clinical judgment in the operating room.

Surgical wound debridement sequentially characterized in a porcine burn model with multispectral imaging.

INTRODUCTION: Multispectral imaging (MSI) is an optical technique that measures specific wavelengths of light reflected from wound site tissue to determine the severity of burn wounds. A rapid MSI device to measure burn depth and guide debridement will improve clinical decision making and diagnoses. METHODOLOGY: We used a porcine burn model to study partial thickness burns of varying severity. We made eight 4 × 4 cm burns on the dorsum of one minipig. Four burns were studied intact, and four burns underwent serial tangential excision. We imaged the burn sites with 400-1000 nm wavelengths. RESULTS: Histology confirmed that we achieved various partial thickness burns. Analysis of spectral images show that MSI detects significant variations in the spectral profiles of healthy tissue, superficial partial thickness burns, and deep partial thickness burns. The absorbance spectra of 515, 542, 629, and 669 nm were the most accurate in distinguishing superficial from deep partial thickness burns, while the absorbance spectra of 972 nm was the most accurate in guiding the debridement process. CONCLUSION: The ability to distinguish between partial thickness burns of varying severity to assess whether a patient requires surgery could be improved with an MSI device in a clinical setting.