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左心室心肌致密化不全的心血管磁共振决定因素。

Cardiovascular magnetic resonance determinants of left ventricular noncompaction.

机构信息

Cardiovascular Medicine Research Unit, University of Aberdeen, Aberdeen, United Kingdom.

Cardiovascular Medicine Research Unit, University of Aberdeen, Aberdeen, United Kingdom.

出版信息

Am J Cardiol. 2014 Aug 1;114(3):456-62. doi: 10.1016/j.amjcard.2014.05.017. Epub 2014 May 17.

Abstract

Insufficient precision remains in accurately identifying left ventricular noncompaction (LVNC) from the healthy normal morphologic spectrum. We aim to provide a better distinction between normal left ventricular trabeculations and LVNC. We used a previously well-defined cohort of 120 healthy volunteers for normal reference values of the trabecular/compacted ratio derived from a consistent selection of short-axis cardiovascular magnetic resonance images. We performed forward selection of logistic regression models, selecting the best model that was subsequently assessed for discrimination and calibration, validated, and converted into a clinical diagnostic chart to benchmark the boundaries of detection from a cohort of 30 patients considered to have LVNC. We showed that 3 combinations of a maximal end-diastolic trabecular/compacted ratio (≥1 [apex], >1.8 [midcavity]), (>2 [apex], ≥0.6 [midcavity]), or (>0.5 [base], >1.8 [midcavity]) separate the cohorts with the highest accuracy (C statistic [95% confidence interval] of 0.9749 (0.9748 to 0.9751) for the diagnostic chart). Quantitative cardiovascular magnetic resonance also shows that patients considered to have LVNC have a significantly reduced ejection fraction compared with normal volunteers. At midcavity and apical level, it is difficult to identify papillary muscles that are replaced by a dense trabecular meshwork. In conclusion, we developed a new, refined, diagnostic tool for identifying LVNC, based on an a priori assessment of the trabecular architecture in healthy volunteers.

摘要

从健康正常形态学谱中准确识别左心室心肌致密化不全(LVNC)仍然存在精度不足的问题。我们旨在更好地区分正常左心室小梁和 LVNC。我们使用了先前定义良好的 120 名健康志愿者队列,以获得从一致选择的短轴心血管磁共振图像中得出的小梁/致密化比值的正常参考值。我们进行了逻辑回归模型的前向选择,选择了最佳模型,然后对其进行区分和校准评估、验证,并转换为临床诊断图表,以从 30 名被认为患有 LVNC 的患者队列中确定检测的边界。我们表明,3 种最大舒张末期小梁/致密化比值(≥1[顶点]、>1.8[中腔])、(>2[顶点]、≥0.6[中腔])或(>0.5[基底]、>1.8[中腔])的组合以最高的准确性(诊断图表的 C 统计量[95%置信区间]为 0.9749(0.9748 至 0.9751))分离了队列。定量心血管磁共振还表明,与健康志愿者相比,被认为患有 LVNC 的患者的射血分数明显降低。在心腔中部和心尖水平,很难识别被密集小梁网格替代的乳头肌。总之,我们基于对健康志愿者小梁结构的预先评估,开发了一种新的、经过改进的 LVNC 识别诊断工具。

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