Ever since the early 1980s, surgical robotics/robot assisted surgeries have gained more of a foothold in modern treatments. The extra guidance/precision that surgical robotics have provided in operations has been indispensable. The next step for surgical robotics is MRI compatibility to provide close to real time intraoperative imaging for space constrained operations. The robotic component artifact influence over the region of surgical interest (ROSI) is to be mitigated for complications in addition to providing accurate guidance for the surgeon. This study defines a large MRI phantom design for specimen submersion to verify/quantify artifact generation from robotic components as well as provide a better visualization platform for robotic performance during preliminary testing and evaluation. The main topics of focus for the phantom design are fluid selection, phantom shape, phantom containment material, and 3D printed artifact measurement evaluation grids. The MRI scans were conducted using a 3T Magnetom Prisma MRI. Three scan types were selected: T1 weighted, T2 weighted, and SGE (spoiled gradient echo). The investigated phantom fluids were a solution of nickel chloride and sodium chloride (the ACR phantom, 10mM NiCl2 75mM NaCl), two salt doped distilled water (13g, 26g), and food grade mineral oil. The oil and ACR phantom outperformed the doped water with similar SNR/CNR returns (SGE: SNR/CNR 250/240/57, PIU 83/60/85). The phantom containment material was inconclusive due to motion artifact production and will be rerun with alternative fluid. The 3D printed artifact measurement grid was printed in PETG as a cost-effective substitute as PLA started warping the grid after extended water exposure (0.2mm). After N4 implementation, the image uniformity was determined through the ACR method while the SNR/CNR values were calculated in Fiji. The results illustrated the preferred environmental constraints according to the main topics: food grade mineral oil, cylindrical, motion artifact interference, and PETG 3D printed grid.
Tracked intraoperative ultrasound (iUS) is growing in use. Accurate spatial calibration is essential to enable iUS navigation. Utilizing sterilizable probes introduces new challenges that can be solved by time-of-surgery calibration that is robust, efficient and user independent performed within the sterile field. This study demonstrates a smart line detection scheme to perform calibration based on video acquisition data and investigates the effect of pose variation on the accuracy of a plane-based calibration. A user-independent US video is collected of a calibration phantom and a smart line detection and tracking filter applied to the video-tracking data pairs to remove poor calibration candidates. A localized point target phantom is imaged to provide a TRE assessment of the calibration. The tracking data is decoupled into 6 degrees of freedom and these ranges iteratively reduced to study the effect on the spatial calibration accuracy in order to indicate the sufficient amount of pose variation required during video acquisition to maintain high TRE accuracy. This work facilitates a larger development toward user-independent, video based iUS calibration at the time of surgery.
Registration of preoperative or intraoperative imaging is necessary to facilitate surgical navigation in spine surgery. After image acquisition, intervertebral motion and spine pose changes can occur during surgery from instrumentation, decompression, physician manipulation or correction. This causes deviations from the reference imaging reducing the navigation accuracy. To evaluate the ability to use the registration between stereovision surfaces in order to account for this intraoperative spine motion through a simulation study. Co-registered CT and stereovision surface data were obtained of a swine cadaver’s exposed lumbar spine in the prone position. Data was segmented and labeled by vertebral level. A simulation of biomechanically bounded motion was applied to each vertebral level to move the prone spine to a new position. A reduced surface data set was then registered level-wise back to the prone spines original position. The average surface to surface distance was recorded between simulated and prone positions. Localized targets on these surfaces were used for a calculation of target registration error. Target registration error increases with distance between surfaces. Movement exceeding 2.43 cm between stereovision acquisitions exceeds registration accuracy of 2mm. Lateral bending of the spine contributes most to this effect compared to axial rotation and flexion-extension. In conclusion, the viability of using stereovision-to-stereovision registration to account for interoperative motion of the spine is shown through this simulation. It is suggested the distance of spine movement between corresponding points does not surpass 2.43 cm between stereovision acquisitions.
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