G-ALPS: An index for evaluating cognitive decline and aging using diffusion tensor imaging.

The G-ALPS index demonstrated stronger correlation with cognitive measures compared to the standard ALPS index across multiple assessment tools.

• Improvements were observed for Mini-Mental State Examination (MMSE, 2.78% improvement), Clinical Dementia Rating (CDR, 5.13% improvement), and Functional Activities Questionnaire (FAQ, 10% improvement).
• Analysis was performed on 217 diffusion tensor imaging (DTI) samples from the Alzheimer's Disease Neuroimaging Initiative (ADNI) dataset.
• The G-ALPS index was derived using Genetic Programming applied to fiber diffusivities in DTI data.

The G-ALPS index exhibited substantially enhanced sensitivity in identifying the effects of aging compared to the ALPS index across diagnostic groups.

• Improvement in sensitivity for aging effects was 94.81% in Alzheimer's disease (AD) individuals.
• Improvement was 105% in patients with mild cognitive impairment (MCI).
• Improvement was 81.25% in normal controls.
• These findings were demonstrated using the Human Connectome Project (HCP) dataset.

The G-ALPS index showed improved sensitivity for detecting sleep-related disorders compared to the standard ALPS index.

• A 21.27% improvement in correlation with MMSE was observed in the context of sleep-related disorders.
• A 2.53% improvement in correlation with Pittsburgh Sleep Quality Index (PSQI) was found.
• These results were obtained using the Human Connectome Project (HCP) dataset.

The G-ALPS index was proposed as an indirect metric for assessing glymphatic system function or dysfunction.

• Glymphatic system dysfunction is associated with cognitive decline in neurodegenerative diseases such as Alzheimer's disease.
• The G-ALPS index is an optimized version of the Along Perivascular Space (ALPS) index.
• The index was derived using Genetic Programming applied to DTI data.
• The authors suggest G-ALPS 'may be an indirect metric for assessing the glymphatic system's function or dysfunction.'

The study analyzed DTI data from 217 samples to evaluate the G-ALPS index across different cognitive and clinical groups.

• Data were drawn from two sources: the Alzheimer's Disease Neuroimaging Initiative (ADNI) dataset and the Human Connectome Project (HCP) dataset.
• Diagnostic groups included AD individuals, MCI patients, and normal controls.
• The analysis involved fiber diffusivities measured through diffusion tensor imaging (DTI).
• Cognitive measures included MMSE, CDR, FAQ, and PSQI.