德国国家队列(NAKO)的心脏磁共振成像:短轴电影图像的自动分割和后处理质量控制。

IF 6.1 1区 医学 Q1 CARDIAC & CARDIOVASCULAR SYSTEMS
Peter M Full, Robin T Schirrmeister, Manuel Hein, Maximilian F Russe, Marco Reisert, Clemens Ammann, Karin Halina Greiser, Thoralf Niendorf, Tobias Pischon, Jeanette Schulz-Menger, Klaus H Maier-Hein, Fabian Bamberg, Susanne Rospleszcz, Christopher L Schlett, Christopher Schuppert
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引用次数: 0

摘要

背景:前瞻性,多中心德国国家队列(NAKO)提供了心脏磁共振(CMR)电影图像的独特数据集。有效地处理这些图像需要一个强大的分割和质量控制管道。方法:基于nnU-Net架构的语义分割深度学习模型应用于29,908名基线参与者的全周期短轴电影图像。主要目的是确定两个心室(左室、右室)的结构和功能数据,包括舒张末期体积(EDV)、收缩末期体积(ESV)和左室心肌质量。质量控制措施包括对形态功能参数、室内外相位差和时间-体积曲线(TVC)的异常值进行视觉评估。这些都是用五分制评定的,从五分(优秀)到一分(非诊断性),三分或更低的评分被排除在外。使用受试者工作特征分析评估纳入和排除异常值标准的预测价值。结果:分割模型生成完整数据29,609例(1.0%不完整),其中5,082例(17.0%)进行了视觉评估。质量保证产生了26,899个(90.8%)质量优秀或良好的参与者样本,排除了由于图像质量问题而导致的1,875个参与者和由于分割质量问题而导致的835个参与者。TVC是入选和未入选受试者之间最强的单一鉴别因子(AUC: 0.684)。在两类组合中,TVC和相位的配对比单独TVC提供了最大的改进(AUC差:0.044)p结论:所实现的管道促进了广泛的CMR数据集的自动分割,整合了质量控制措施。这种方法确保了随后的定量分析是在减少偏倚风险的情况下进行的。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Cardiac Magnetic Resonance Imaging in the German National Cohort (NAKO): Automated Segmentation of Short-Axis Cine Images and Post-Processing Quality Control.

Background: The prospective, multicenter German National Cohort (NAKO) provides a unique dataset of cardiac magnetic resonance (CMR) cine images. Effective processing of these images requires a robust segmentation and quality control pipeline.

Methods: A deep learning model for semantic segmentation, based on the nnU-Net architecture, was applied to full-cycle short-axis cine images from 29,908 baseline participants. The primary objective was to determine data on structure and function for both ventricles (LV, RV), including end-diastolic volumes (EDV), end-systolic volumes (ESV), and LV myocardial mass. Quality control measures included a visual assessment of outliers in morphofunctional parameters, inter- and intra-ventricular phase differences, and time-volume curves (TVC). These were adjudicated using a five-point rating scale, ranging from five (excellent) to one (non-diagnostic), with ratings of three or lower subject to exclusion. The predictive value of outlier criteria for inclusion and exclusion was evaluated using receiver operating characteristics analysis.

Results: The segmentation model generated complete data for 29,609 participants (incomplete in 1.0%), of which 5,082 cases (17.0%) underwent visual assessment. Quality assurance yielded a sample of 26,899 (90.8%) participants with excellent or good quality, excluding 1,875 participants due to image quality issues and 835 participants due to segmentation quality issues. TVC was the strongest single discriminator between included and excluded participants (AUC: 0.684). Of the two-category combinations, the pairing of TVC and phases provided the greatest improvement over TVC alone (AUC difference: 0.044; p<0.001). The best performance was observed when all three categories were combined (AUC: 0.748). By extending the quality-controlled sample to include mid-level 'acceptable' quality ratings, a total of 28,413 (96.0%) participants could be included.

Conclusion: The implemented pipeline facilitated the automated segmentation of an extensive CMR dataset, integrating quality control measures. This methodology ensures that ensuing quantitative analyses are conducted with a diminished risk of bias.

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来源期刊
CiteScore
10.90
自引率
12.50%
发文量
61
审稿时长
6-12 weeks
期刊介绍: Journal of Cardiovascular Magnetic Resonance (JCMR) publishes high-quality articles on all aspects of basic, translational and clinical research on the design, development, manufacture, and evaluation of cardiovascular magnetic resonance (CMR) methods applied to the cardiovascular system. Topical areas include, but are not limited to: New applications of magnetic resonance to improve the diagnostic strategies, risk stratification, characterization and management of diseases affecting the cardiovascular system. New methods to enhance or accelerate image acquisition and data analysis. Results of multicenter, or larger single-center studies that provide insight into the utility of CMR. Basic biological perceptions derived by CMR methods.
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