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Modeling respiratory motion variations in the 4D NCAT phantom

机译：4D NCAT幻像的呼吸运动变化建模

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The current 4D NCAT phantom includes a flexible, parameterized respiratory model based on respiratory-gated CT data of a normal subject. A limitation of this model is that it is based on only one realization of the normal respiratory motion. The data upon which it was based also had a resolution lower than that offered by more advanced CT scanners and consisted of only four time frames that did not adequately cover normal tidal breathing.We further develop the 4D NCAT to more accurately model normal and abnormal states of respiration. Over two- hundred sets of 4D respiratory gated CT image data from normal and abnormal patients obtained from the Massachusetts General Hospital were used to characterize variations in the respiratory motion. Each dataset contains twenty time frames over the respiratory cycle with the patient breathing normally.With the improved resolution and better coverage of tidal breathing, this data was used to improve the respiratory model of the 4D NCAT phantom. Using automatic and semiautomatic techniques, the different respiratory structures were segmented from each time frame of each CT dataset. The time series of segmented structures were used to characterize the respiratory motion in each case. From an analysis of all normal and abnormal patient datasets, we determined the range of sizes and shapes of the right and left lungs and the range in motion (expansion in the anterior and inferior (diaphragm)directions)in the different lung regions. This analysis was used to further parameterize the general respiratory model of the 4D NCAT to more realistically model normal and abnormal variations in anatomy and in the respiratory motion. With the ability to model variations in the respiratory motion indicative of a patient population, the phantom will be a great resource to investigate the effects of respiratory motion on medical imaging and to develop compensation methods for these effects.
机译：目前的4D NCAT幻像包括基于正常对象的呼吸门CT数据的柔性参数化呼吸模型。该模型的限制是它仅基于正常呼吸运动的一个实现。它所基于它的数据也比更高级的CT扫描仪提供的分辨率低，并且仅由不充分覆盖正常潮汐呼吸的四个时间框架组成。我们进一步开发了4D NCAT，以更准确地模拟正常和异常状态呼吸。来自马萨诸塞州综合医院的正常和异常患者的两百套4D呼吸门CT图像数据用于表征呼吸运动的变化。每个数据集在呼吸周期内包含20帧，患者呼吸正常。随着改进的分辨率和更好地覆盖潮气呼吸，该数据用于改善4D NCAT幻像的呼吸模型。使用自动和半自动技术，不同的呼吸结构从每个CT数据集的每个时间帧进行分段。分段结构的时间序列用于表征每种情况下的呼吸运动。根据对所有正常和异常的患者数据集的分析，我们确定了右肺和左肺的尺寸和形状的范围，以及在不同肺部区域中的运动范围（横向和下（隔膜）的膨胀范围）。该分析用于进一步参数化4D NCAT的一般呼吸模型，以更现实地模范解剖学和呼吸运动中的正常和异常变化。通过能够模拟指示患者人群的呼吸运动中的变化，幻影将是调查呼吸运动对医学成像的影响以及为这些效果的补偿方法进行良好的资源。

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