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Biomechanical Patient-Specific Model of the Respiratory System Based on 4D CT Scans and Controlled by Personalized Physiological Compliance

机译:基于4D CT扫描的呼吸系统呼吸系统的生物力学患者特异性模型,由个性化生理合规性控制

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In this paper, we present a dynamic patient-specific model of the respiratory system for a whole respiratory cycle, based on 4D CT scans, personalized physiological compliance (pressure-volume curves), as well as an automatic tuning algorithm to determine lung pressure and diaphragm force parameters. The amplitude of the lung pressure and diaphragm forces are specific, and differs from one patient to another and depends on geometrical and physiological characteristics of the patient. To determine these parameters at different respiratory states and for each patient, an inverse finite element (FE) analysis has been implemented to match the experimental data issued directly from 4D CT images, to the FE simulation results, by minimizing the lungs volume variations. We have evaluated the model accuracy on five selected patients, from DIR-Lab Dataset, with small and large breathing amplitudes, by comparing the FE simulation results on 75 landmarks, at end inspiration (EI), end expiration (EE) states, and at each intermediate respiratory state. We have also evaluated the tumor motion identified in 4D CT scan images and compared it with the trajectory obtained by FE simulation, during one complete breathing cycle. The results demonstrate the good quantitative results of our physic-based model and we believe that our model, despite of others takes into account the challenging problem of the respiratory variabilities.
机译:在本文中,我们介绍了一种全呼吸系统的动态患者特异性模型,用于整个呼吸周期,基于4D CT扫描,个性化生理符合性(压力体积曲线),以及自动调谐算法来确定肺压力和隔膜力参数。肺部压力和隔膜力的幅度是特异性的,并且与一个患者不同,并且取决于患者的几何和生理特性。为了确定不同呼吸状态和每位患者的这些参数,已经实施了逆有限元(FE)分析以使FE模拟结果直接从4D CT图像发出的实验数据匹配,以通过最小化肺部体积变化。我们通过比较了75个地标在75个地标,最终启发(EI),最终到期(EE)状态和AT的情况下,从DIR-LAB数据集中评估了五个选定患者的模型准确性每个中间呼吸状态。我们还评估了在4D CT扫描图像中识别的肿瘤运动,并在一个完全呼吸循环期间将其与通过FE模拟获得的轨迹进行比较。结果证明了我们基于物理的模型的良好定量结果,我们认为,尽管其他人考虑了呼吸变量的具有挑战性问题,我们认为我们的模式。

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