Yang Minglei, Ding Hui, Kang Jingang, Zhu Lei, Wang Guangzhi
Department of Biomedical Engineering, School of Medicine, Tsinghua University, Room C249, Beijing, 100084, People's Republic of China,
Int J Comput Assist Radiol Surg. 2015 May;10(5):517-29. doi: 10.1007/s11548-014-1085-x. Epub 2014 Jun 14.
Ultrasound-MRI/CT fusion imaging is widely used in minimal invasive surgeries, such as liver biopsy and tumor ablation. However, respiration-induced quasi-periodic liver motion and deformation cause unacceptable misalignment of the fusion images (i.e., fusion error). A subject-specific liver motion model based on skin-mounted position sensor and corresponding ultrasound liver image sequence was developed to compensate for liver motion.
External surrogate respiratory motion signal is used to predict internal liver motion. An electromagnetic position sensor fixed on abdominal skin is introduced to track the respiratory motion, and 2D ultrasound images are used to track the liver motion synchronously. Based on these measurements, a subject-specific model describing the relationship of respiratory skin motion and internal liver motion is built and applied in real time (ultrasound-MRI/CT fusion imaging system) to predict and to compensate for the liver motion due to respiratory movement. Feasibility experiments and clinical trials were carried out on a phantom and eight volunteers.
Qualitative and quantitative analyses and visual inspections performed by experienced clinicians show that the proposed model could effectively compensate for the liver motion, and the ratio of motion-compensated fusion error to the original varied from 10 % (0.96/9.40 mm) to 28 % (2.90/10.22 mm).
An online liver motion modeling and compensation method was developed that provides surgeons with stable and accurate multimodality fusion images in real time.
超声 - MRI/CT融合成像广泛应用于肝脏活检和肿瘤消融等微创手术中。然而,呼吸引起的肝脏准周期性运动和变形会导致融合图像出现不可接受的错位(即融合误差)。基于皮肤安装的位置传感器和相应的肝脏超声图像序列,开发了一种针对个体的肝脏运动模型,以补偿肝脏运动。
利用外部替代呼吸运动信号来预测肝脏内部运动。引入一个固定在腹部皮肤上的电磁位置传感器来跟踪呼吸运动,并使用二维超声图像同步跟踪肝脏运动。基于这些测量结果,建立一个描述呼吸皮肤运动与肝脏内部运动关系的个体模型,并实时应用于(超声 - MRI/CT融合成像系统),以预测和补偿由于呼吸运动引起的肝脏运动。在体模和八名志愿者身上进行了可行性实验和临床试验。
由经验丰富的临床医生进行的定性和定量分析以及视觉检查表明,所提出的模型能够有效补偿肝脏运动,运动补偿后的融合误差与原始误差的比值在10%(0.96/9.40毫米)至28%(2.90/10.22毫米)之间。
开发了一种在线肝脏运动建模和补偿方法,可为外科医生实时提供稳定且准确的多模态融合图像。