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Published on: March 11, 2021
Regional myocardial motion in patients with mild cognitive impairment: a pilot study
Heng Ma1,2, Jun Yang1, Haizhu Xie1
1Department of Radiology, Yuhuangding Hospital, Qingdao University School of Medicine, 20 E Yuhuangding Rd, Yantai, 264000, Shandong, China.
Background:
Cardiovascular disease (CVD) is a risk factor for cognitive impairment in the elderly. Manifestations of subclinical CVDs can be found in patients with cognitive impairment. The aim of the present study was to test the hypothesis that patients with mild cognitive impairment (MCI) have different magnetic resonance imaging (MRI)-derived regional myocardial motion indices compared with healthy controls.
Methods:
Eleven MCI patients (age, 65.5 years ±5.9; range, 55-81 years old) and 11 sex-/age-matched healthy volunteers were enrolled. All of the participants underwent a head MRI and cardiac MRI. Global cortical atrophy (GCA) was graded on the head MRI. The left ventricular ejection fraction (LVEF) and regional strain, strain rate, displacement and velocity were measured on cine images. The GCA scores, global cardiac function and regional myocardial motion indices were compared between MCI patients and healthy controls using the t-test.
Results:
MCI patients had a higher GCA score than healthy controls (p = 0.048). However, there was no significant difference in LVEF between MCI patients and controls. Compared to healthy controls, MCI patients had a lower peak radial strain (29.1% ± 24.1% vs. 46.4% ± 43.4%, p < 0.001), lower peak diastolic radial strain rate (3.2 ± 2.4 s- 1 vs. 6.0 ± 3.0 s- 1, p < 0.001), lower peak diastolic circumferential strain rate (2.5 ± 2.1 s- 1 vs. 3.2 ± 2.1 s- 1, p = 0.002), lower peak systolic radial displacement (4.2 ± 2.2 mm vs. 5.2 ± 3.3 mm, p = 0.002), lower peak diastolic radial velocity (31 ± 18 mm/s vs. 45 ± 33 mm/s, p < 0.001), and lower peak diastolic circumferential velocity (178 ± 124 degree/s vs. 217 ± 131 degree/s, p = 0.005).
Conclusion:
MRI-derived regional myocardial strain, strain rate and velocity were found to be different between MCI patients and healthy controls. Regional myocardial motion indices have the potential to become novel quantitative imaging biomarkers for representing the risk of neurodegenerative disorders, such as Alzheimer's disease (AD).
Insights
Individuals with mild cognitive impairment (MCI) exhibit altered heart muscle motion detected by cardiac MRI. These cardiac MRI findings may serve as early indicators for neurodegenerative diseases like Alzheimer's disease.
Area of Science:
- Cardiology
- Neurology
- Radiology
Background:
- Cardiovascular disease (CVD) is a known risk factor for cognitive impairment in the elderly.
- Subclinical CVD manifestations are observed in patients with cognitive impairment.
- This study investigated differences in cardiac MRI-derived myocardial motion between MCI patients and healthy controls.
Purpose of the Study:
- To test the hypothesis that patients with mild cognitive impairment (MCI) exhibit distinct magnetic resonance imaging (MRI)-derived regional myocardial motion indices compared to healthy controls.
- To explore the potential of cardiac MRI parameters as biomarkers for neurodegenerative disorders.
Main Methods:
- Eleven MCI patients and 11 age-/sex-matched healthy controls underwent head and cardiac MRI.
- Global cortical atrophy (GCA) was assessed from head MRI.
- Cardiac MRI measured left ventricular ejection fraction (LVEF), regional strain, strain rate, displacement, and velocity.
- Statistical comparison using t-tests was performed between groups.
Main Results:
- MCI patients showed higher GCA scores (p=0.048) but similar LVEF compared to controls.
- Significantly lower peak radial strain, peak diastolic radial and circumferential strain rates, peak systolic radial displacement, and peak diastolic radial and circumferential velocities were observed in MCI patients (all p<0.005).
Conclusions:
- Cardiac MRI-derived regional myocardial motion indices differ significantly between MCI patients and healthy controls.
- These quantitative imaging biomarkers hold potential for identifying individuals at risk for neurodegenerative diseases like Alzheimer's disease.
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