A risk prediction model of post-stroke cognitive impairment based on magnetic resonance spectroscopy imaging.

Published on Mar 30, 2021in Neurological Research2.401
· DOI :10.1080/01616412.2021.1908659
Objective: To explore the clinical value of a risk prediction model of post-stroke cognitive impairment (PSCI) based on proton magnetic resonance spectroscopy (1H-MRS).Methods:A retrospective analysis was conducted on 376 stroke patients hospitalized between March 2016 and March 2019. Their relevant clinical baseline data were collected at admission. After the patients' condition was stabilized, 1H-MRS was performed to detect the related indices of the bilateral prefrontal lobe, thalamus, basal ganglia, hippocampus, precuneus, and angular gyrus. Within 12 months of the onset of stroke, cognitive impairment tests were performed monthly. Based on score results, stroke patients were divided into two groups: PSCI and post-stroke non-PSCI (N-PSCI). Thirty-four characteristic parameters of baseline and imaging data were extracted from the PSCI and N-PSCI groups. The least absolute shrinkage and selection operator (LASSO) regression was used for optimal feature selection, and a nomogram prediction model was established. The predictive ability of the model was validated by a calibration plot and the area under the curve (AUC) of the receiver operating characteristic curve.Results: Six risk factors were identified from clinical baseline data and MRS indices based on screening by LASSO dimensionality reduction. The consistency test of the correction curve showed that the prediction probability of the PSCI nomogram had good correlation with actual diagnosis. The AUCs of internal and external validation were 0.8935 and 0.8523, respectively.Discussion: A PSCI risk prediction model based on MRS serves to assist clinicians in estimating the risk of cognitive impairment after stroke.
#1Jing Sun (WMU: Wenzhou Medical College)H-Index: 12
#2Xinhuang Lv (First Affiliated Hospital of Wenzhou Medical University)H-Index: 1
Last. Suzhi Liu (WMU: Wenzhou Medical College)H-Index: 3
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Post-stroke cognitive impairment (PSCI) is a severe complication of stroke. Predicting PSCI is difficult because some risk factors for stroke, such as blood glucose level and blood pressure, are affected by many other elements. Although recent studies have shown that high serum uric acid (UA) levels are associated with cognitive dysfunction and may be a risk factor for PSCI, its impact remains unclear. Accordingly, the present study aimed to explore the association between serum UA level and PSC...
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#1Yu-Qin Li (Lanzhou University)H-Index: 1
#2Ji-Xiang Chen (Lanzhou University)H-Index: 1
Last. Zhao-Hui Xie (Lanzhou University)H-Index: 1
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Post-stroke cognitive impairment (PSCI) severely affects the quality of a survivor's life, but its neurophysiological basis remains unknown. Neuroinflammation has been considered as an important contributor to PSCI, which could be induced or exacerbated by system inflammation. NACHT-LRR- and pyrin-domain-containing protein 3 (NLRP3) inflammasome is the most widely studied in the initiation of inflammation. Here, using a mouse model of photothrombotic stroke, we demonstrated that NLRP3 activation...
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Several investigations have revealed the utility of magnetic resonance spectroscopy (MRS) as an adjunct in the evaluation of lesions of the head and neck. This technique remains a challenge in the head and neck because of its low signal-to-noise ratio and long acquisition times. In this review article, the basics of image acquisition technique and reported clinical utilities of head and neck MRS are presented.
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#2Rubo SuiH-Index: 1
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