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Background:
Mild cognitive impairment (MCI) is an intermediate stage between cognitively unimpaired (CU) and dementia, often considered a critical phase for early detection. Mini-Mental State Examination (MMSE) and Hippocampal volume (HV) are commonly used to evaluate cognitive impairment. However, the sensitivity of these methods for detecting early MCI remains relatively low. Montreal Cognitive Assessment (MoCA) is more sensitive than MMSE in detecting MCI but is also more time-consuming and complex, requiring greater examiner expertise. There is an unmet need for a screening tool quicker and more convenient than MoCA while being more sensitive than HV. The Virtual Reality Eye-tracking Cognitive Assessment (VECA) represents a novel approach that integrates virtual reality, eye-tracking technology, and machine learning to evaluate multiple cognitive domains efficiently. This study aims to explore cognitive decline patterns across MCI subgroups using VECA and compare its diagnostic performance to HV.
Methods:
A total of 125 MCI patients and 190 CU individuals from the Shenzhen multi-modal Aging Research (STAR) cohort underwent neuropsychological assessments, VECA, and 3D-T1WI MRI. MCI patients were divided into four subgroups (Q1-MCI to Q4-MCI) based on their MoCA and MMSE scores. Statistical analyses were performed using SPSS 27.0. The performances were compared using the DeLong test in MedCalc.
Results:
In the Q1-MCI subgroup, functions of abstraction, calculation, execution, memory, and recall consistently performed best. In the Q2-MCI and Q3-MCI subgroups, abstraction, calculation, execution, and memory functions consistently performed best. In the Q4-MCI subgroup, calculation, execution, and memory functions consistently performed best. No significant differences in attention function were observed among the four groups, with AUC values consistently demonstrating lower scores than other cognitive functions (p < 0.05). Besides, VECA (Total Score) demonstrated higher AUC values (0.746 for Q1-MCI subgroup, 0.845-0.964 for Q2-MCI to Q4-MCI subgroup) than HV in all subgroups (p < 0.05).
Conclusion:
VECA demonstrates strong potential as a rapid and efficient screening tool, requiring only 5 minutes to administer and consistently outperforming HV in differentiating MCI across all stages. VECA findings indicate that attention remains relatively preserved during MCI, while impairments in calculation, execution, and memory become progressively more pronounced in later stages.
Insights
The Virtual Reality Eye-tracking Cognitive Assessment (VECA) is a novel tool that effectively screens for mild cognitive impairment (MCI) and outperforms traditional methods like Hippocampal volume (HV). VECA shows that attention is preserved in MCI, while calculation, execution, and memory decline with disease progression.
Area of Science:
- Neuroscience
- Gerontology
- Medical Technology
Background:
- Mild cognitive impairment (MCI) is a critical transitional stage between cognitive unimpaired (CU) and dementia, necessitating sensitive early detection methods.
- Current screening tools like Mini-Mental State Examination (MMSE) and Hippocampal volume (HV) have limitations in sensitivity for early MCI detection.
- Montreal Cognitive Assessment (MoCA) is more sensitive but complex and time-consuming, highlighting the need for a more efficient screening tool.
Purpose of the Study:
- To explore cognitive decline patterns across different Mild Cognitive Impairment (MCI) subgroups using the novel Virtual Reality Eye-tracking Cognitive Assessment (VECA).
- To compare the diagnostic performance of VECA against traditional methods, specifically Hippocampal volume (HV), in identifying MCI.
- To assess the efficiency and sensitivity of VECA as a rapid screening tool for cognitive impairment.
Main Methods:
- A cohort of 125 MCI patients and 190 cognitively unimpaired (CU) individuals from the Shenzhen multi-modal Aging Research (STAR) cohort were recruited.
- Participants underwent neuropsychological assessments, including the Virtual Reality Eye-tracking Cognitive Assessment (VECA), and 3D-T1WI MRI for Hippocampal volume (HV) measurement.
- MCI patients were stratified into four subgroups (Q1-MCI to Q4-MCI) based on Montreal Cognitive Assessment (MoCA) and Mini-Mental State Examination (MMSE) scores, with statistical comparisons performed using DeLong tests.
Main Results:
- VECA demonstrated superior diagnostic performance compared to HV across all MCI subgroups, with higher Area Under the Curve (AUC) values.
- Specific cognitive functions showed varying patterns of decline: abstraction, calculation, execution, and memory were consistently impaired, particularly in later MCI stages (Q4-MCI).
- Attention function showed no significant differences across MCI subgroups, with consistently lower AUC values compared to other cognitive domains.
Conclusions:
- The Virtual Reality Eye-tracking Cognitive Assessment (VECA) shows significant promise as a rapid (5-minute administration) and efficient screening tool for mild cognitive impairment (MCI).
- VECA consistently outperformed Hippocampal volume (HV) in differentiating MCI across all stages, offering a more sensitive diagnostic approach.
- Findings suggest that while attention remains relatively preserved, impairments in calculation, execution, and memory progressively worsen in later stages of MCI.
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