Association of Choroid Plexus Dysfunction and Cognitive Decline in Preeclampsia: Using <scp>T1WI</scp> Imaging, Quantitative Susceptibility Mapping and Deep‐Learning‐Based Segmentation

Preeclampsia is a severe pregnancy complication that can cause brain injury, yet early detection of related cognitive deficits remains challenging. Therefore, in order to investigate alterations in choroid plexus volume (CPV) and susceptibility values of the choroid plexus (ChP) obtained from quantitative susceptibility mapping (QSM) in preeclampsia patients, we enrolled 281 participants, comprising 98 nonpregnant healthy controls (NPHC), 85 pregnant healthy controls (PHC), and 98 patients with preeclampsia. All participants were scanned on a 1.5 T MR scanner. The results of clinical characteristics and cognitive tests were collected from all the participants. One-way ANOVA tests were used to analyze the differences in CPV and susceptibility values of ChP among the three groups. Multiple linear regression analysis was used to find the factors that influenced CPV and its susceptibility values, as well as cognitive decline. Additionally, receiver operating characteristic (ROC) analysis was employed to evaluate the diagnostic performance of the two imaging measures. Preeclampsia patients exhibited smaller CPV and higher susceptibility values compared to the other groups (p < 0.001; p < 0.001). Significant negative correlations were observed between body mass index (BMI), mean arterial pressure and CPV/eTIV (β = -0.100, 95% CI = -0.158 ~ -0.042, p = 0.001; β = -0.022, 95% CI = -0.033 ~ -0.011, p < 0.001). Additionally, significant positive correlations were observed between BMI (β = 0.455, 95% CI = 0.125 ~ 0.786, p = 0.007), mean arterial pressure (β = 0.170, 95% CI = 0.107 ~ 0.232, p < 0.001), hemoglobin (β = 0.152, 95% CI = 0.051 ~ 0.254, p = 0.003) and susceptibility values of ChP. Furthermore, CPV/eTIV and susceptibility values of ChP could be independent contributing factors of scores of TMT. The combination of CPV, susceptibility values of ChP, BMI and gestational week could distinguish preeclampsia from pregnant groups (AUC = 0.787, 95% CI = 0.722-0.853, p < 0.001) as well as distinguish individuals with cognitive decline from preeclampsia patients (AUC = 0.737, 95% CI = 0.621-0.844, p < 0.001). These findings indicate that smaller CPV and higher susceptibility values characterize preeclampsia and may serve as auxiliary indices for its diagnosis and related cognitive decline.

Authors

Institutions

Publication Details

Journal
Human Brain Mapping
Published
2025-11-01
DOI
https://doi.org/10.1002/hbm.70397
Citations
1
Primary Topic
Pregnancy and preeclampsia studies
Type
article
Field-Weighted Citation Impact
2.06

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Association of Choroid Plexus Dysfunction and Cognitive Decline in Preeclampsia: Using T1WI Imaging, Quantitative Susceptibility Mapping and Deep‐Learning‐Based Segmentation

Tao Chen, Lingfei Guo, Yiwen Chen, Zhenyu Cheng et al.
1 citations
Human Brain Mapping
Pregnancy and preeclampsia studies
2.06
article

Association of Choroid Plexus Dysfunction and Cognitive Decline in Preeclampsia: Using T1WI Imaging, Quantitative Susceptibility Mapping and Deep‐Learning‐Based Segmentation

Tao Chen, Lingfei Guo, Yiwen Chen, Zhenyu Cheng, Fushuai Zhang, Linfeng Yang, Meng Li, Pengcheng Liang, Qihao Zhang, Xinxin Huo, Boyao Chen
article en
1 citations

Abstract

Preeclampsia is a severe pregnancy complication that can cause brain injury, yet early detection of related cognitive deficits remains challenging. Therefore, in order to investigate alterations in choroid plexus volume (CPV) and susceptibility values of the choroid plexus (ChP) obtained from quantitative susceptibility mapping (QSM) in preeclampsia patients, we enrolled 281 participants, comprising 98 nonpregnant healthy controls (NPHC), 85 pregnant healthy controls (PHC), and 98 patients with preeclampsia. All participants were scanned on a 1.5 T MR scanner. The results of clinical characteristics and cognitive tests were collected from all the participants. One-way ANOVA tests were used to analyze the differences in CPV and susceptibility values of ChP among the three groups. Multiple linear regression analysis was used to find the factors that influenced CPV and its susceptibility values, as well as cognitive decline. Additionally, receiver operating characteristic (ROC) analysis was employed to evaluate the diagnostic performance of the two imaging measures. Preeclampsia patients exhibited smaller CPV and higher susceptibility values compared to the other groups (p < 0.001; p < 0.001). Significant negative correlations were observed between body mass index (BMI), mean arterial pressure and CPV/eTIV (β = -0.100, 95% CI = -0.158 ~ -0.042, p = 0.001; β = -0.022, 95% CI = -0.033 ~ -0.011, p < 0.001). Additionally, significant positive correlations were observed between BMI (β = 0.455, 95% CI = 0.125 ~ 0.786, p = 0.007), mean arterial pressure (β = 0.170, 95% CI = 0.107 ~ 0.232, p < 0.001), hemoglobin (β = 0.152, 95% CI = 0.051 ~ 0.254, p = 0.003) and susceptibility values of ChP. Furthermore, CPV/eTIV and susceptibility values of ChP could be independent contributing factors of scores of TMT. The combination of CPV, susceptibility values of ChP, BMI and gestational week could distinguish preeclampsia from pregnant groups (AUC = 0.787, 95% CI = 0.722-0.853, p < 0.001) as well as distinguish individuals with cognitive decline from preeclampsia patients (AUC = 0.737, 95% CI = 0.621-0.844, p < 0.001). These findings indicate that smaller CPV and higher susceptibility values characterize preeclampsia and may serve as auxiliary indices for its diagnosis and related cognitive decline.

Human Brain MappingVol. 46(16)
Binzhou Medical University (CN), Shandong University of Aeronautics (CN), Cornell University (US), Jinan Maternity And Care Hospital (CN), Shandong Provincial Hospital (CN), Jena University Hospital (DE), Shandong Maternal and Child Health Hospital (CN), Shandong First Medical University (CN)
National Natural Science Foundation of China, Natural Science Foundation of Shandong Province, Medical and Health Science and Technology Development Project of Shandong Province
Openalex Percentile: Top 11%
Pregnancy and preeclampsia studies
2.06
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.