Eye-tracking paradigms for the assessment of mild cognitive impairment: a systematic review

Integrating Biomarkers From Virtual Reality and Magnetic Resonance Imaging for the Early Detection of Mild Cognitive Impairment Using a Multimodal Learning Approach: Validation Study

BACKGROUND

Early detection of mild cognitive impairment (MCI), a transitional stage between normal aging and Alzheimer disease, is crucial for preventing the progression of dementia. Virtual reality (VR) biomarkers have proven to be effective in capturing behaviors associated with subtle deficits in instrumental activities of daily living, such as challenges in using a food-ordering kiosk, for early detection of MCI. On the other hand, magnetic resonance imaging (MRI) biomarkers have demonstrated their efficacy in quantifying observable structural brain changes that can aid in early MCI detection. Nevertheless, the relationship between VR-derived and MRI biomarkers remains an open question. In this context, we explored the integration of VR-derived and MRI biomarkers to enhance early MCI detection through a multimodal learning approach.

OBJECTIVE

We aimed to evaluate and compare the efficacy of VR-derived and MRI biomarkers in the classification of MCI while also examining the strengths and weaknesses of each approach. Furthermore, we focused on improving early MCI detection by leveraging multimodal learning to integrate VR-derived and MRI biomarkers.

METHODS

The study encompassed a total of 54 participants, comprising 22 (41%) healthy controls and 32 (59%) patients with MCI. Participants completed a virtual kiosk test to collect 4 VR-derived biomarkers (hand movement speed, scanpath length, time to completion, and the number of errors), and T1-weighted MRI scans were performed to collect 22 MRI biomarkers from both hemispheres. Analyses of covariance were used to compare these biomarkers between healthy controls and patients with MCI, with age considered as a covariate. Subsequently, the biomarkers that exhibited significant differences between the 2 groups were used to train and validate a multimodal learning model aimed at early screening for patients with MCI among healthy controls.

RESULTS

The support vector machine (SVM) using only VR-derived biomarkers achieved a sensitivity of 87.5% and specificity of 90%, whereas the MRI biomarkers showed a sensitivity of 90.9% and specificity of 71.4%. Moreover, a correlation analysis revealed a significant association between MRI-observed brain atrophy and impaired performance in instrumental activities of daily living in the VR environment. Notably, the integration of both VR-derived and MRI biomarkers into a multimodal SVM model yielded superior results compared to unimodal SVM models, achieving higher accuracy (94.4%), sensitivity (100%), specificity (90.9%), precision (87.5%), and F1-score (93.3%).

CONCLUSIONS

The results indicate that VR-derived biomarkers, characterized by their high specificity, can be valuable as a robust, early screening tool for MCI in a broader older adult population. On the other hand, MRI biomarkers, known for their high sensitivity, excel at confirming the presence of MCI. Moreover, the multimodal learning approach introduced in our study provides valuable insights into the improvement of early MCI detection by integrating a diverse set of biomarkers.

Return to Play Following Concussion: Role for Imaging?

This review surveys concussion management, focusing on the use of neuroimaging techniques in return to play (RTP) decisions. Clinical assessments traditionally were the foundation of concussion diagnoses. However, their subjective nature prompted an exploration of neuroimaging modalities to enhance diagnosis and management. Magnetic resonance spectroscopy provides information about metabolic changes and alterations in the absence of structural abnormalities. Diffusion tensor imaging uncovers microstructural changes in white matter. Functional magnetic resonance imaging assesses neuronal activity to reveal changes in cognitive and sensorimotor functions. Positron emission tomography can assess metabolic disturbances using radiotracers, offering insight into the long-term effects of concussions. Vestibulo-ocular dysfunction screening and eye tracking assess vestibular and oculomotor function. Although these neuroimaging techniques demonstrate promise, continued research and standardization are needed before they can be integrated into the clinical setting. This review emphasizes the potential for neuroimaging in enhancing the accuracy of concussion diagnosis and guiding RTP decisions.

Changes in cognitive ability and serum microRNA levels during aging in mice

Mild cognitive impairment (MCI) is an early stage that can result in dementia. MCI can be reversed, and diagnosis at an early stage is crucial to control the progression to dementia. Dementia is currently diagnosed based on interviews and screening tests; however, novel biomarkers must be identified to allow early MCI detection. Therefore, the present study aimed to identify novel biomarkers in the form of blood microRNAs (miRNAs/miRs) for the diagnosis of MCI or early dementia. Blood samples were collected from C57BL/6NJcl male mice at four time points, including 4-week-old (4W), 8-week-old (8W), 36-week-old (36W) and 58-week-old (58W), and serum was isolated. Body weight and blood total cholesterol levels were increased, and blood alkaline phosphatase was decreased with aging. The 8W mice exhibited the highest cognitive ability in the Morris water maze test, whereas the 58W mice demonstrated decreased cognitive ability. The serum RNA concentrations of the 4W, 8W, 36W and 58W mice demonstrated no significant differences. Furthermore, small RNA levels were detected in the serum of all mice. miRNA microarray analysis revealed a >1.5-fold increase in the serum expression of two miRNAs (miR-21a-5p and miR-92a-3p) and a >1.5-fold decrease in the serum expression of two other miRNAs (miR-6769b-5p and miR-709) in 58W mice compared with those in 8W mice. In the future, we aim to further analyze aged mice to discover novel MCI biomarkers.

Eye-Tracking Technology in Dentistry: A Review of Literature

This narrative review explores the integration of eye-tracking technology in dentistry, aiming to provide a comprehensive overview of its current applications and potential benefits. The review begins by elucidating the fundamental principles of eye tracking, encompassing the various eye-tracking methods and devices commonly used in dental research. It then delves into the role of eye tracking in dental education, where the technology offers a unique perspective on students' visual attention during training and skill acquisition. Moreover, the review examines how eye tracking can aid in assessing and improving dental practitioners' clinical performance, shedding light on areas of improvement and expertise. In patient care, the application of eye-tracking technology offers significant potential. By analyzing patients' gaze patterns and visual focus during dental procedures, clinicians can gain valuable insights into their experiences, identifying sources of anxiety and discomfort. This newfound understanding can pave the way for more patient-centric care and optimized treatment plans. The review also explores the application of eye-tracking technology in designing and evaluating dental interfaces and equipment. By assessing visual ergonomics and usability, researchers can develop user-friendly instruments that enhance dental professionals' workflow and efficiency. However, despite its promise, integrating eye tracking in dentistry is not without challenges. Technical limitations, data analysis complexities, and ethical considerations require careful attention to ensure this technology's ethical and responsible use. In conclusion, this narrative review highlights the growing significance of eye-tracking technology in dentistry. Its applications span dental education, clinical practice, and patient care, holding immense potential to revolutionize how dental procedures are conducted, evaluated, and experienced. Nevertheless, further research and collaboration between dental professionals and eye-tracking experts are necessary to unlock the technology's benefits and ensure its seamless integration into dental practices.

Cognition and saccadic eye movement performance are impaired in chronic rhinosinusitis

BACKGROUND

Patients with chronic rhinosinusitis (CRS) can experience cognitive dysfunction. The literature on this topic mostly reflects patient-reported measurements. Our goal was to assess cognitive function in patients with CRS using objective measures, including saccadic eye movements-a behavioral response reflecting cognitive and sensory information integration that is often compromised in conditions with impaired cognition.

METHODS

Participants (N = 24 with CRS, N = 23 non-CRS healthy controls) enrolled from rhinology clinic underwent sinonasal evaluation, quality of life assessment (Sino-nasal Outcome Test 22 [SNOT-22]), and cognitive assessment with the Neuro-QOL Cognitive Function-Short Form, the Montreal Cognitive Assessment (MoCA), and recording of eye movements using video-oculography.

RESULTS

Participants with CRS were more likely to report cognitive dysfunction (Neuro-QOL; 45.8% vs. 8.7%; p = 0.005) and demonstrate mild or greater cognitive impairment (MoCA; 41.7% vs. 8.7%; p = 0.005) than controls. Additionally, participants with CRS performed worse on the MoCA overall and within the executive functioning and memory domains (all p < 0.05) and on the anti-saccade (p = 0.014) and delay saccade (p = 0.044) eye movement tasks. Poorer performance on the MoCA (r = -0.422; p = 0.003) and the anti-saccade (r = -0.347; p = 0.017) and delay saccade (r = -0.419; p = 0.004) eye movement tasks correlated with worse CRS severity according to SNOT-22 scores.

CONCLUSION

This study is the first to utilize objective eye movement assessments in addition to researcher-administered cognitive testing in patients with CRS. These patients demonstrated a high prevalence of cognitive dysfunction, most notably within executive functioning and memory domains, with the degree of dysfunction correlating with the severity of CRS.