Nichols Kenneth J, Van Tosh Andrew, Wang Yi, De Bondt Pieter, Palestro Christopher J, Reichek Nathaniel
Division of Nuclear Medicine and Molecular Imaging, North Shore-Long Island Jewish Health System, Manhasset and New Hyde Park, NY 11040, USA.
Nucl Med Commun. 2010 Oct;31(10):881-8. doi: 10.1097/MNM.0b013e32833d82ff.
The ability to detect left ventricular (LV) apical dyskinesis, the hallmark of an aneurysm, is an important requirement of diagnostic cardiac imaging modalities that perform wall motion analysis. Our investigation assessed the ability of gated blood pool single-photon emission-computed tomography (GBPS) to automatically detect LV dyskinesis, using cardiac magnetic resonance (CMR) as the reference standard.
GBPS data were analyzed for 41 patients with congestive heart failure or cardiomyopathy and compared with ECG-gated TrueFISP CMR evaluations. An experienced nuclear cardiologist without the knowledge of quantitative GBPS or CMR results graded visual impressions of regional wall motion while examining cinematic playbacks of GBPS images. GBPS algorithms automatically isolated LV counts and computed regional phase (phi) values in each of 17 conventional American Heart Association LV segments. LV asynchrony was quantified by the two local measures: maximum apical phi difference (Deltaalpha), and standard deviation among apical phases (sigmaalpha), and by the five global measures: varphi histogram bandwidth (BWHistogram), phi histogram standard deviation (sigmaHistogram), Z-scores, Entropy, and Synchrony. For CMR data, an expert manually drew endocardial LV outlines to measure regional wall motion in 17 LV segments.
Apical dyskinesis was present in nine patients. Among GBPS measurements, the method with the greatest accuracy for detecting dyskinesis was Deltaalpha (receiver operating characteristic area=95%). The only method with a sufficiently high kappa statistic to represent 'very good agreement' with CMR was Deltaalpha, with kappa=0.81. Deltaalpha was more sensitive in detecting dyskinesis than visual analysis (100 vs. 33%, P=0.01).
Automatic GBPS computations accurately identified patients with LV dyskinesis, and detected dyskinesis more successfully than did visual analysis.
检测左心室（LV）心尖运动障碍（动脉瘤的标志）的能力是进行壁运动分析的诊断性心脏成像模态的一项重要要求。我们的研究使用心脏磁共振成像（CMR）作为参考标准，评估了门控血池单光子发射计算机断层扫描（GBPS）自动检测左心室运动障碍的能力。
对41例充血性心力衰竭或心肌病患者的GBPS数据进行分析，并与心电图门控TrueFISP CMR评估结果进行比较。一位不了解GBPS定量结果或CMR结果的经验丰富的核心脏病专家在查看GBPS图像的动态回放时，对局部壁运动的视觉印象进行分级。GBPS算法自动分离左心室计数，并计算17个传统美国心脏协会左心室节段中每个节段的局部相位（phi）值。通过两种局部测量方法对左心室不同步进行量化：最大心尖phi差值（Deltaalpha）和心尖相位之间的标准差（sigmaalpha），以及通过五种全局测量方法：phi直方图带宽（BWHistogram）、phi直方图标准差（sigmaHistogram）、Z分数、熵和同步性。对于CMR数据，一位专家手动绘制左心室心内膜轮廓，以测量17个左心室节段的局部壁运动。
9例患者存在心尖运动障碍。在GBPS测量中，检测运动障碍准确性最高的方法是Deltaalpha（受试者操作特征面积=95%）。唯一具有足够高kappa统计量以表示与CMR“非常好的一致性”的方法是Deltaalpha，kappa=0.81。Deltaalpha在检测运动障碍方面比视觉分析更敏感（100%对33%，P=0.01）。
GBPS自动计算能够准确识别左心室运动障碍患者，并且比视觉分析更成功地检测到运动障碍。
