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首页> 外文期刊>Academic radiology >Model-based automatic segmentation algorithm accurately assesses the whole cardiac volumetric parameters in patients with cardiac CT angiography: A validation study for evaluating the accuracy of the workstation software and establishing the reference values
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Model-based automatic segmentation algorithm accurately assesses the whole cardiac volumetric parameters in patients with cardiac CT angiography: A validation study for evaluating the accuracy of the workstation software and establishing the reference values

机译：基于模型的自动分割算法可准确评估心脏CT血管造影患者的整个心脏体积参数：一项评估工作站软件准确性并建立参考值的验证研究

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Rationale and Objectives: The cardiac chamber volumes and functions can be assessed manually and automatically using the current computed tomography (CT) workstation system. We aimed to evaluate the accuracy and precision and to establish the reference values for both segmentation methods using cardiac CT angiography (CTA). Materials and Methods: A total of 134 subjects (mean age 55.3years, 72 women) without heart disease were enrolled in the study. The cardiac four-chamber volumes, left ventricular (LV) mass, and biventricular functions were measured with manual, semiautomatic, and model-based fully automatic approaches. The accuracies of the semiautomated and fully automated approaches were validated by comparing them with manual segmentation as a reference. The precision error was determined and compared for both manual and automatic measurements. Results: No significant difference was found between the manual and semiautomatic assessments for the assessment of all functional parameters (P>.05). Using the manual method as a reference, the automatic approach provided a similar value in LV ejection fraction and left atrial volumes in both genders and right ventricular (RV) stroke volume in women (P>.05), with some underestimation of RV volume (P<.001) and overestimation of all remaining parameters (P<.05) in both genders. In addition, a significantly higher precision with a considerable association in intermeasurement (reproducibility) was observed using the automated approach. Conclusions: The model-based fully automatic segmentation algorithm can help with the assessment of the cardiac four-chamber volume and function. This may help in establishing reference values of functional parameters in patients who undergo cardiac CTA.
机译：原理和目标：使用当前的计算机断层扫描（CT）工作站系统，可以手动和自动评估心腔容积和功能。我们旨在评估准确性和精密度，并建立使用心脏CT血管造影（CTA）的两种分割方法的参考值。材料与方法：共有134名无心脏病的受试者（平均年龄55.3岁，女性72名）参加了研究。用手动，半自动和基于模型的全自动方法测量心脏四腔室容积，左心室（LV）质量和双心室功能。通过将半自动和全自动方法与手动分割作为参考进行比较，从而验证了其准确性。确定了精度误差，并进行了手动和自动测量的比较。结果：对于所有功能参数的评估，手动评估和半自动评估之间没有显着差异（P> .05）。使用手动方法作为参考，自动方法在男女的左心室射血分数和左心房容积以及女性的右心室（RV）中风容积方面具有相似的值（P> .05），但对RV容积有些低估（ P <.001），并高估了所有剩余参数（P <.05）。此外，使用自动方法可以观察到明显更高的精度，并且在测量之间具有显着的关联性（可重复性）。结论：基于模型的全自动分割算法可以帮助评估心脏四腔容积和功能。这可能有助于建立接受心脏CTA的患者功能参数的参考值。

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