心肌最大壁厚和左室流出道解剖学参数评估肥厚型心肌病心肌纤维化的对照研究
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作者单位:南京医科大学第一附属医院放射科

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国家自然科学基金项目(面上项目,重点项目,重大项目)


A comparative study of maximal wall thickness and anatomical parameters of left ventricular outflow tract for evaluating myocardial fibrosis in hypertrophic cardiomyopathy
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Department of Radiology,the First Affiliated Hospital with Nanjing Medical University,Jiangsu Nanjing,210029

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Natural Science Foundation of China

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    摘要:

    [摘要] 目的:探讨并对比心脏磁共振(cardiac magnetic resonance,CMR)左室舒张末期最大心肌壁厚(maximal wall thickness,MWT)和左室流出道(left ventricular outflow tract,LVOT)解剖学参数在评估肥厚型心肌病(hypertrophic cardiomyopathy,HCM)心肌纤维化中的预测价值,并建立预测模型。方法:回顾性分析77例行CMR检查的HCM患者,所需测量的参数包括部分二尖瓣前叶长度、总二尖瓣前叶长度、舒张末期和收缩末期的LVOT直径和基底前间隔厚度、左室舒张末期MWT以及心肌延迟强化负荷(percentage of late gadolinium enhancement, LGE%)等,其中以LGE%来评估心肌纤维化。利用统计软件随机选择70%的样本分配至建模组,通过单因素及多因素回归分析,建立LGE%的预测模型;剩余30%的样本为内部验证组,所有患者的超声心动图参数作为外部验证,评估预测模型的准确性。绘制受试者工作特征曲线,通过计算曲线下面积来确定预测模型的预测效能,评估预测模型的敏感性及特异性。结果:在建模组中,多因素线性回归分析提示,MWT是LGE%的独立预测因子,线性公式为LGE%=-10.009+0.832×WMT(r=0.466,P<0.001),而LVOT解剖学参数均与LGE%无线性相关性。在验证组中,超声MWT与心脏磁共振MWT无统计学差异,且内部验证和外部验证的预测值均与LGE%无统计学差异;当心脏磁共振MWT≥30mm或超声MWT≥25mm时,其预测LGE%≥15%的准确率分别为82.6%和81.7%。结论:在评估HCM心肌纤维化时,MWT比LVOT解剖学参数更有预测价值。

    Abstract:

    [Abstract] Objective: To comparatively explore the value of left ventricular end-diastolic maximal wall thickness (MWT) and anatomical parameters of left ventricular outflow tract (LVOT) for evaluating myocardial fibrosis in hypertrophic cardiomyopathy (HCM) by cardiac magnetic resonance (CMR) and propose a prediction model. Methods: Seventy-seven HCM patients who underwent CMR examination were retrospectively analyzed. CMR data included partial anterior mitral leaflet length and total anterior mitral leaflet length. During end-diastole and end-systole, the diameter of LVOT and the thickness of basal anteroseptal were measured. Additionally, left ventricular end-diastolic MWT was collected and the percentage of late gadolinium enhancement (LGE%) was analyzed. LGE% was used to assess myocardial fibrosis. Seventy percent of the samples selected randomly by statistical software were assigned to the derivation cohort for establishing a prediction model of LGE% through univariable and multivariable analysis. The remaining thirty percent of the samples served as the internal validation cohort, and parameters of echocardiogram of all patients were used for external validation to assess the accuracy of the prediction model. Receiver operating characteristic curves were plotted, and the predictive efficacy of the prediction model was determined by calculating the area under the curve. The sensitivity and specificity of the prediction model were also evaluated. Results: In the derivation cohort, multivariable analysis indicated that MWT was an independent predictor of LGE% with the linear equation LGE% = -10.009 + 0.832 × MWT (r = 0.466, P < 0.001), while no anatomical parameters of LVOT were correlated with LGE%. In the validation cohort, there was no statistical difference between MWT measured by echocardiogram and MWT measured by CMR. Additionally, the predicted values from both internal and external validations showed no statistical difference from LGE%. The accuracy of predicting LGE%≥15% were 82.6% with a cutoff of 30mm for MWT measured by CMR and 81.7% with a cutoff of 25mm for MWT measured by echocardiogram respectively. Conclusion: When evaluating myocardial fibrosis in HCM, MWT has more predictive value than anatomical parameters of LVOT.

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  • 收稿日期:2025-02-23
  • 最后修改日期:2025-06-04
  • 录用日期:2025-08-25
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