IEEE Trans Med Imaging. 2021 Jan;40(1):297-309. doi: 10.1109/TMI.2020.3025467. Epub 2020 Dec 29.
Measures of vascular tortuosity-how curved and twisted a vessel is-are associated with a variety of vascular diseases. Consequently, measurements of vessel tortuosity that are accurate and comparable across modality, resolution, and size are greatly needed. Yet in practice, precise and consistent measurements are problematic-mismeasurements, inability to calculate, or contradictory and inconsistent measurements occur within and across studies. Here, we present a new method of measuring vessel tortuosity that ensures improved accuracy. Our method relies on numerical integration of the Frenet-Serret equations. By reconstructing the three-dimensional vessel coordinates from tortuosity measurements, we explain how to identify and use a minimally-sufficient sampling rate based on vessel radius while avoiding errors associated with oversampling and overfitting. Our work identifies a key failing in current practices of filtering asymptotic measurements and highlights inconsistencies and redundancies between existing tortuosity metrics. We demonstrate our method by applying it to manually constructed vessel phantoms with known measures of tortuousity, and 9,000 vessels from medical image data spanning human cerebral, coronary, and pulmonary vascular trees, and the carotid, abdominal, renal, and iliac arteries.
血管迂曲度的测量方法——即血管的弯曲和扭曲程度——与多种血管疾病有关。因此,非常需要能够在模态、分辨率和尺寸上准确且可比较的血管迂曲度测量方法。然而,在实际应用中,精确和一致的测量方法存在问题,例如在同一研究或不同研究中会出现测量误差、无法计算或测量结果相互矛盾和不一致等情况。在这里,我们提出了一种新的血管迂曲度测量方法,以确保提高准确性。我们的方法依赖于弗雷内特-塞雷特方程的数值积分。通过从迂曲度测量中重建三维血管坐标,我们解释了如何根据血管半径确定并使用最小充分采样率,同时避免与过采样和过拟合相关的误差。我们的工作还发现了当前过滤渐近测量方法中的一个关键缺陷,并强调了现有迂曲度指标之间的不一致性和冗余性。我们通过将其应用于具有已知迂曲度的手动构建的血管模型以及来自涵盖人类大脑、冠状动脉和肺血管树以及颈动脉、腹部、肾脏和髂动脉的 9000 条医学图像数据中的血管,来验证我们的方法。