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DOI 10.1080/10255842.2016.1139093

Медицинская библиотека · Computer methods in biomechanics and biomedical engineering · 2016

Left ventricular diastolic dysfunction in type 2 diabetes patients: a novel 2D strain analysis based on cardiac magnetic resonance imaging.

Chen Qiang, Gan Yan, Li Zhi-Yong

СтатьяПеревод пока не подготовлен

Аннотация

OBJECTIVE

This study was to develop a strain analysis method to evaluate the left ventricular (LV) functions in type 2 diabetic patients with an asymptomatic LV diastolic dysfunction.

METHODS

Two groups (10 asymptomatic type 2 diabetic subjects and 10 control ones) were considered. All of the subjects had normal ejection fraction values but impaired diastolic functions assessed by the transmitral blood flow velocity. For each subject, based on cardiac MRI, global indexes including LV volume, LV myocardial mass, cardiac index (CI), and transmitral peak velocity, were measured, and regional indexes (i.e., LV deformation, strain and strain rate) were calculated through an image-registration technology.

RESULTS

Most of the global indexes did not differentiate between the two groups, except for the CI, LV myocardial mass and transmitral peak velocity. While for the regional indexes, the global LV diastolic dysfunction of the diabetic indicated an increased strain (0.08 ± 0.044 vs. -0.031 ± 0.077, p = 0.001) and a reduced strain rate (1.834 ± 0.909 vs. 3.791 ± 2.394, p = 0.033) compared to the controls, moreover, the local LV diastolic dysfunction reflected by the strain and strain rate varied, and the degree of dysfunction gradually decreased from the basal level to the apical level.

CONCLUSIONS

The results showed that the strain and strain rates are effective to capture the subtle alterations of the LV functions, and the proposed method can be used to estimate the LV myocardial function based on cardiac MRI.

Для цитирования: Chen Qiang, Gan Yan, Li Zhi-Yong. Left ventricular diastolic dysfunction in type 2 diabetes patients: a novel 2D strain analysis based on cardiac magnetic resonance imaging.. Computer methods in biomechanics and biomedical engineering. 2016. DOI: 10.1080/10255842.2016.1139093.

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