Investigating Sea-Level Brain Predictors for Acute Mountain Sickness: A Multimodal MRI Study before and after...

Area of Science:

• Neuroimaging
• Altitude Medicine
• Predictive Diagnostics

Background:

• Acute mountain sickness (AMS) presents with brain-centered symptoms during rapid high-altitude ascent.
• Predicting AMS is critical for safeguarding individuals undertaking such journeys.
• Current prediction methods lack accuracy, necessitating novel approaches.

Purpose of the Study:

• To assess the feasibility of predicting AMS using multimodal brain MRI features acquired at sea level.
• To identify specific sea-level neuroimaging markers that correlate with AMS development.
• To validate these predictors using high-altitude MRI data.

Main Methods:

• Recruited 45 healthy sea-level residents ascending to 3650 m.
• Acquired T1-weighted structural MRI, resting-state fMRI, and ASL perfusion MRI at sea level and high altitude.
• Diagnosed AMS using Lake Louise Scoring and employed logistic regression with LASSO for prediction modeling.

Main Results:

• High AMS incidence (80.0%) observed.
• A predictive model using sea-level fMRI features (fALFF, degree centrality in somatomotor network) achieved 86.4% AUC.
• Lower sea-level fALFF in the somatomotor network correlated with higher AMS severity and fatigue at high altitude.

Conclusions:

• Somatomotor network function, assessed via sea-level resting-state fMRI, is a key predictor of AMS.
• This finding offers a potential pre-exposure screening tool for individuals at risk of AMS.
• The study provides insights into the pathophysiological mechanisms underlying AMS.