Open-source surface mesh-based ultrasound-guided spinal intervention simulator.

Int J Comput Assist Radiol Surg

Laboratory for Percutaneous Surgery, School of Computing, Queen's University, Kingston, ON, Canada,

Published: November 2013

Purpose:    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.

Methods:    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.

Results:    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.

Conclusions:    The ultrasound simulator was implemented and integrated into the open-source Public Library for Ultrasound (PLUS) toolkit.

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Source
http://dx.doi.org/10.1007/s11548-013-0901-zDOI Listing

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