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Research ArticleUltra-High-Field MRI/Imaging of Epilepsy/Demyelinating Diseases/Inflammation/Infection

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

Wei Zhang, Jie Feng, Wenjia Liu, Shiyu Zhang, Xiao Yu, Jie Liu, Baoci Shan and Lin Ma
American Journal of Neuroradiology June 2024, 45 (6) 809-818; DOI: https://doi.org/10.3174/ajnr.A8206
Wei Zhang
aFrom the Beijing Engineering Research Center of Radiographic Techniques and Equipment (W.Z., B.S.), Institute of High Energy Physics, Chinese Academy of Sciences, Beijing, China
bSchool of Nuclear Science and Technology (W.Z., B.S.), University of Chinese Academy of Sciences, Beijing, China
hCognitive Neuroimaging Centre (W.Z.), Nanyang Technological University, Singapore
iLee Kong Chian School of Medicine (W.Z.), Nanyang Technological University, Singapore
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Jie Feng
cThe Graduate School (J.F., X.Y., L.M.), Medical School of Chinese People’s Liberation Army, Beijing, China
dDepartment of Radiology (J.F., W.L., S.Z., X.Y., L.M.), The First Medical Center of Chinese People’s Liberation Army General Hospital, Beijing, China
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Wenjia Liu
dDepartment of Radiology (J.F., W.L., S.Z., X.Y., L.M.), The First Medical Center of Chinese People’s Liberation Army General Hospital, Beijing, China
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Shiyu Zhang
dDepartment of Radiology (J.F., W.L., S.Z., X.Y., L.M.), The First Medical Center of Chinese People’s Liberation Army General Hospital, Beijing, China
eDepartment of Radiology (S.Z.), Capital Medical University Affiliated Beijing Friendship Hospital, Beijing, China
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Xiao Yu
cThe Graduate School (J.F., X.Y., L.M.), Medical School of Chinese People’s Liberation Army, Beijing, China
dDepartment of Radiology (J.F., W.L., S.Z., X.Y., L.M.), The First Medical Center of Chinese People’s Liberation Army General Hospital, Beijing, China
fDepartment of Radiology (X.Y.), Beijing Jingmei Group General Hospital, Beijing, China
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Jie Liu
gDepartment of Radiology (J.L.), General Hospital of Tibet Military Region, Tibet, China
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Baoci Shan
aFrom the Beijing Engineering Research Center of Radiographic Techniques and Equipment (W.Z., B.S.), Institute of High Energy Physics, Chinese Academy of Sciences, Beijing, China
bSchool of Nuclear Science and Technology (W.Z., B.S.), University of Chinese Academy of Sciences, Beijing, China
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Lin Ma
cThe Graduate School (J.F., X.Y., L.M.), Medical School of Chinese People’s Liberation Army, Beijing, China
dDepartment of Radiology (J.F., W.L., S.Z., X.Y., L.M.), The First Medical Center of Chinese People’s Liberation Army General Hospital, Beijing, China
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Abstract

BACKGROUND AND PURPOSE: Acute mountain sickness is a series of brain-centered symptoms that occur when rapidly ascending to high altitude. Predicting acute mountain sickness before high-altitude exposure is crucial for protecting susceptible individuals. The present study aimed to evaluate the feasibility of predicting acute mountain sickness after high-altitude exposure by using multimodal brain MR imaging features measured at sea level.

MATERIALS AND METHODS: We recruited 45 healthy sea-level residents who flew to the Qinghai-Tibet Plateau (3650 m). We conducted T1-weighted structural MR imaging, resting-state fMRI, and arterial spin-labeling perfusion MR imaging both at sea level and high altitude. Acute mountain sickness was diagnosed for 5 days using Lake Louise Scoring. Logistic regression with Least Absolute Shrinkage and Selection Operator logistic regression was performed for predicting acute mountain sickness using sea-level MR imaging features. We also validated the predictors by using MR images obtained at high altitude.

RESULTS: The incidence rate of acute mountain sickness was 80.0%. The model achieved an area under the receiver operating characteristic curve of 86.4% (sensitivity = 77.8%, specificity = 100.0%, and P < .001) in predicting acute mountain sickness At sea level, valid predictors included fractional amplitude of low-frequency fluctuations (fALFF) and degree centrality from resting-state fMRI, mainly distributed in the somatomotor network. We further learned that the acute mountain sickness group had lower levels of fALFF in the somatomotor network at high altitude, associated with smaller changes in CSF volume and higher Lake Louise Scoring, specifically relating to fatigue and clinical function.

CONCLUSIONS: Our study found that the somatomotor network function detected by sea-level resting-state fMRI was a crucial predictor for acute mountain sickness and further validated its pathophysiologic impact at high altitude. These findings show promise for pre-exposure prediction, particularly for individuals in need of rapid ascent, and they offer insight into the potential mechanism of acute mountain sickness.

ABBREVIATIONS:

AMS
acute mountain sickness
ASL
arterial spin-labeling
AUC
area under the curve
DC
degree centrality
fALFF
fractional amplitude of low-frequency fluctuations
LASSO-LR
Least Absolute Shrinkage and Selection Operator logistic regression
LLS
Lake Louise Score
rs-fMRI
resting-state fMRI
ROC
receiver operating characteristic
SMN
somatomotor network
SpO2
saturation of pulse oxygen
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American Journal of Neuroradiology: 45 (6)
American Journal of Neuroradiology
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Cite this article
Wei Zhang, Jie Feng, Wenjia Liu, Shiyu Zhang, Xiao Yu, Jie Liu, Baoci Shan, Lin Ma
Investigating Sea-Level Brain Predictors for Acute Mountain Sickness: A Multimodal MRI Study before and after High-Altitude Exposure
American Journal of Neuroradiology Jun 2024, 45 (6) 809-818; DOI: 10.3174/ajnr.A8206

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Sea-Level Brain Predictors of Mountain Sickness
Wei Zhang, Jie Feng, Wenjia Liu, Shiyu Zhang, Xiao Yu, Jie Liu, Baoci Shan, Lin Ma
American Journal of Neuroradiology Jun 2024, 45 (6) 809-818; DOI: 10.3174/ajnr.A8206
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