Bartha Laura, Lasso Andras, Pinter Csaba, Ungi Tamas, Keri Zsuzsanna, Fichtinger Gabor
Laboratory for Percutaneous Surgery, School of Computing, Queen's University, Kingston, ON, Canada,
Int J Comput Assist Radiol Surg. 2013 Nov;8(6):1043-51. doi: 10.1007/s11548-013-0901-z. Epub 2013 Jun 1.
Ultrasound is prevalent in image-guided therapy as a safe, inexpensive, and widely available imaging modality. However, extensive training in interpreting ultrasound images is essential for successful procedures. An open-source ultrasound image simulator was developed to facilitate the training of ultrasound-guided spinal intervention procedures, thereby eliminating the need for an ultrasound machine from the phantom-based training environment.
Anatomical structures and surgical tools are converted to surface meshes for data compression. Anatomical data are converted from segmented volumetric images, while the geometry of surgical tools is available as a surface mesh. The pose of the objects are either constants or coming from a pose-tracking device. Intersection points between the surface models and the ultrasound scan lines are determined with a binary space partitioning tree. The scan lines are divided into segments and filled with gray values determined by an intensity calculation accounting for material properties, reflection, and attenuation parameters defined in a configuration file. The scan lines are finally converted to a regular brightness-mode ultrasound image.
The simulator was tested in a tracked ultrasound imaging system, with a mock transducer tracked with an Ascension trakSTAR electromagnetic tracker, on a spine phantom. A mesh model of the spine was created from CT data. The simulated ultrasound images were generated at a speed of 50 frames per second, and a resolution of [Formula: see text] pixels, with 256 scan lines per frame, on a PC with a 3.4 GHz processor. A human subject trial was conducted to compare the learning performance of novice trainees, with real and simulated ultrasound, in the localization of facet joints of a spine phantom. With 22 participants split into two equal groups, and each participant localizing 6 facet joints, there was no statistical difference in the performance of the two groups, indicating that simulated ultrasound could indeed replace the real ultrasound in phantom-based ultrasonography training for spinal interventions.
The ultrasound simulator was implemented and integrated into the open-source Public Library for Ultrasound (PLUS) toolkit.
超声作为一种安全、廉价且广泛可用的成像方式，在图像引导治疗中很常见。然而，要成功进行手术，对超声图像解读进行广泛培训至关重要。开发了一种开源超声图像模拟器，以促进超声引导脊柱介入手术的培训，从而消除基于体模的培训环境中对超声机器的需求。
将解剖结构和手术工具转换为表面网格以进行数据压缩。解剖数据从分割的体积图像转换而来，而手术工具的几何形状以表面网格形式提供。物体的姿态要么是固定的，要么来自姿态跟踪设备。使用二叉空间划分树确定表面模型与超声扫描线之间的交点。扫描线被分成段，并填充由强度计算确定的灰度值，并考虑配置文件中定义的数据属性、反射和衰减参数。扫描线最终转换为常规亮度模式的超声图像。
该模拟器在一个跟踪超声成像系统中进行了测试，在一个脊柱体模上，使用Ascension trakSTAR电磁跟踪器跟踪一个模拟换能器。从CT数据创建了脊柱的网格模型。在一台具有3.4 GHz处理器的个人电脑上，模拟超声图像以每秒50帧的速度生成，分辨率为[公式：见原文]像素，每帧有256条扫描线。进行了一项人体试验，以比较新手学员在脊柱体模小关节定位中使用真实和模拟超声的学习表现。22名参与者分成两组，每组人数相等，每名参与者定位6个小关节，两组表现无统计学差异，表明在基于体模的脊柱介入超声检查培训中，模拟超声确实可以替代真实超声。
该超声模拟器已实现并集成到开源的超声公共库（PLUS）工具包中。
