International Clinical Neuroscience Journal

Vol. 7 No. 4 (2020)

Comparison of the Effectiveness of Two Types of Single Port Minimal Invasive Neurosurgical Robots to Ablation and Resection of Brain Tumor

International Clinical Neuroscience Journal, Vol. 7 No. 4 (2020), 28 September 2020 , Page 201-207

Abstract

Background: Using minimally invasive neurosurgical robots is one of the most desirable ablation methods and resection of brain tumors. In this study, forward kinematics and Jacobian matrix calculated for two single-port robots for comparing the effectiveness of two types of single port minimal invasive surgical robots to ablation and resection of brain tumor
Methods: The motion analysis of robots type 1 and 2 has compared to each other. Ablation manipulator in robot type 1 has five degrees of freedom, but in robot type 2, three revolute degrees of freedom of this manipulator has replaced with a revolute joint perpendicular to the previous three revolute joints.
Results: Results showed that for resection surgery, in the same conditions, robot type 2 damaged 58.9 mm3 more of cerebral cortex tissue than robot type 1 to resect the brain tumors. To establish a static balance, robot type 2 needs to tolerate at least 41% more internal loading than robot type 1. The maximum velocity for robot type 1 in the contact location between the end-effector and the tumor is 1.7 times more than robot type 2. The maximum end-effector force of robot type 1 to apply the tumor for ablation surgery is more than 1.8 times in robot type 2, but the maximum moment and power for ablation surgery and resection of these two robots were the same less than 1% difference.
Conclusion: Despite the more straightforward mechanism, a minimum number of joints, and better kinematics range of robot type 2, robot types 1 has the possibility for transformation, establishes the static balancing, and does a better ablation surgery with less damage to the brain.

Keywords:
  • Surgical robot
  • Ablation of the tumor
  • Force
  • resection of tumor
  • Brain tumor

How to Cite

1.
Delasaei Marvi S, Sherafati A, Mohammad Tahery M, Zein S. Comparison of the Effectiveness of Two Types of Single Port Minimal Invasive Neurosurgical Robots to Ablation and Resection of Brain Tumor. Int Clin Neurosci J [Internet]. 2020 Sep. 28 [cited 2025 Jan. 17];7(4):201-7. Available from: https://journals.sbmu.ac.ir/neuroscience/article/view/31420

References

Beasley RA. Medical robots: current systems and research directions. Journal of Robotics J Robot. 2012;2012:401613. doi: 10.1155/2012/401613.

Gholampour S, Bahmani M, Shariati A. Comparing the efficiency of two treatment methods of hydrocephalus: shunt implantation and endoscopic third ventriculostomy. Basic Clin Neurosci. 2019;10(3):185-98. doi: 10.32598/bcn.9.10.285.

Liounakos JI, Wang MY. Lumbar 3-Lumbar 5 Robotic- Assisted Endoscopic Transforaminal Lumbar Interbody Fusion: 2-Dimensional Operative Video. Oper Neurosurg (Hagerstown). 2020;19(1):E73-E4. doi: 10.1093/ons/opz385.

Taher M, Gholampour S. Effect of ambient temperature changes on blood flow in anterior cerebral artery of patients with skull prosthesis. World Neurosurg. 2020;135:e358-e65. doi: 10.1016/j.wneu.2019.11.171.

Guo Z, Dong Z, Lee KH, Cheung CL, Fu HC, Ho JD, et al. Compact design of a hydraulic driving robot for intraoperative MRI-guided bilateral stereotactic neurosurgery. IEEE Robot Autom Lett. 2018;3(3):2515-22. doi: 10.1109/ lra.2018.2814637.

Gholampour S. FSI simulation of CSF hydrodynamic changes in a large population of non-communicating hydrocephalus patients during treatment process with regard to their clinical symptoms. PLoS One. 2018;13(4):e0196216. doi: 10.1371/ journal.pone.0196216.

Gholampour S, Soleimani N, Zalii AR, Zare Karizi F, Seddighi A. Numerical simulation of the cervical spine in a normal subject and a patient with intervertebral cage under various loadings and in various positions. Int Clin Neurosci J. 2016;3(2):92-8. doi: 10.22037/icnj.v3i2.13170.

Trybula SJ, Oyon DE, Wolinsky JP. Robotic tissue manipulation and resection in spine surgery. Neurosurg Clin N Am. 2020;31(1):121-9. doi: 10.1016/j.nec.2019.08.014.

Gholampour S, Fatouraee N, Seddighi AS, Seddighi A. Evaluating the effect of hydrocephalus cause on the manner of changes in the effective parameters and clinical symptoms of the disease. J Clin Neurosci. 2017;35:50-5. doi: 10.1016/j. jocn.2016.09.012.

Naghibzadeh M, Gholampour S, Naghibzadeh M, Sadeghian- Nodoushan F, Nikukar H. The effect of electromagnetic field on decreasing and increasing of the growth and proliferation rate of dermal fibroblast cell. Dermatol Ther. 2020:e13803. doi: 10.1111/dth.13803.

Sedaghat Y, Gholampour S, Tabatabai Ghomshe F. Comparison of the effectiveness of manual cleaning, hydrogen peroxide vapour and ultraviolet-c in disinfection of hospital equipment. Infektološki Glasnik. 2019;39(3):66-84. doi: 10.37797/ ig.39.3.2.

Aprile I, Germanotta M, Cruciani A, Loreti S, Pecchioli C, Cecchi F, et al. Upper limb robotic rehabilitation after stroke: a multicenter, randomized clinical trial. J Neurol Phys Ther. 2020;44(1):3-14. doi: 10.1097/npt.0000000000000295.

Le XF, Shi Z, Wang QL, Xu YF, Zhao JW, Tian W. Rate and risk factors of superior facet joint violation during cortical bone trajectory screw placement: a comparison of robot-assisted approach with a conventional technique. Orthop Surg. 2020;12(1):133-40. doi: 10.1111/os.12598.

Gholampour S, Haghighi Hassanali Deh H. The effect of spatial distances between holes and time delays between bone drillings based on examination of heat accumulation and risk of bone thermal necrosis. Biomed Eng Online. 2019;18(1):65. doi: 10.1186/s12938-019-0686-6.

Haber GP, White MA, Autorino R, Escobar PF, Kroh MD, Chalikonda S, et al. Novel robotic da Vinci instruments for laparoendoscopic single-site surgery. Urology. 2010;76(6):1279-82. doi: 10.1016/j.urology.2010.06.070.

Hajirayat K, Gholampour S, Sharifi I, Bizari D. Biomechanical simulation to compare the blood hemodynamics and cerebral aneurysm rupture risk in patients with different aneurysm necks. J Appl Mech Tech Phys. 2017;58(6):968-74. doi: 10.1134/s0021894417060025.

Prideaux N, van den Berg M, Drummond C, Barr C. Augmented performance feedback during robotic gait therapy results in moderate intensity cardiovascular exercise in subacute stroke. J Stroke Cerebrovasc Dis. 2020;29(6):104758. doi: 10.1016/j. jstrokecerebrovasdis.2020.104758.

Gholampour S, Hajirayat K. Minimizing thermal damage to vascular nerves while drilling of calcified plaque. BMC Res Notes. 2019;12(1):338. doi: 10.1186/s13104-019-4381-2.

Sergeeva A, Huysman M, Faraj S. Transforming Work Practices of Operating Room Teams: The Case of the Da Vinci robot. ICIS; 2015.

Seung S, Liu P, Park S, Park J-O, Ko SY. Single-port robotic manipulator system for brain tumor removal surgery: SiromanS. Mechatronics. 2015;26:16-28. doi: 10.1016/j. mechatronics.2014.12.002.

Hu D, Jiang Y, Belykh E, Gong Y, Preul MC, Hannaford B, et al. Toward real-time tumor margin identification in image-guided robotic brain tumor resection. In: Webster Iii RJ, Fei B, eds. Medical Imaging 2017: Image-Guided Procedures, Robotic Interventions, and Modeling. International Society for Optics and Photonics; 2017. doi: 10.1117/12.2255417.

Heredia S, Marinho MM, Ikemoto T, Harada K, Mitsuishi M, Padilla M, et al. Development of a virtual reality simulator for robotic brain tumor resection. 2016 International Symposium on Micro-NanoMechatronics and Human Science (MHS). Nagoya, Japan: IEEE; 2016. doi: 10.1109/mhs.2016.7824185.

Hu D, Gong Y, Hannaford B, Seibel EJ. Semi-autonomous simulated brain tumor ablation with ravenii surgical robot using behavior tree. IEEE Int Conf Robot Autom. 2015;2015:3868-75. doi: 10.1109/icra.2015.7139738.

Chinbe H, Yoneyama T, Watanabe T, Miyashita K, Nakada M. Finger-attachment device for the feedback of gripping and pulling force in a manipulating system for brain tumor resection. Int J Comput Assist Radiol Surg. 2018;13(1):3-12. doi: 10.1007/s11548-017-1640-3.

Azarnoush H, Siar S, Sawaya R, Zhrani GA, Winkler- Schwartz A, Alotaibi FE, et al. The force pyramid: a spatial analysis of force application during virtual reality brain tumor resection. J Neurosurg. 2017;127(1):171-81. doi: 10.3171/2016.7.jns16322.

Niccolini M, Castelli V, Diversi C, Kang B, Mussa F, Sinibaldi E. Development and preliminary assessment of a robotic platform for neuroendoscopy based on a lightweight robot. The International Journal of Medical Robotics and Computer Assisted Surgery Int J Med Robot. 2016;12(1):4-17. doi: 10.1002/rcs.1638.

Lefranc M, Capel C, Pruvot-Occean AS, Fichten A, Desenclos C, Toussaint P, et al. Frameless robotic stereotactic biopsies: a consecutive series of 100 cases. J Neurosurg. 2015;122(2):342- 52. doi: 10.3171/2014.9.jns14107.

Maddahi Y, Gan LS, Zareinia K, Lama S, Sepehri N, Sutherland GR. Quantifying workspace and forces of surgical dissection during robot-assisted neurosurgery. Int J Med Robot. 2016;12(3):528-37. doi: 10.1002/rcs.1679.

Ross WA, Hill WM, Hoang KB, Laarakker AS, Mann BP, Codd PJ. Automating neurosurgical tumor resection surgery: Volumetric laser ablation of cadaveric porcine brain with integrated surface mapping. Lasers Surg Med. 2018;50(10):1017-24. doi: 10.1002/lsm.23000.

Gholampour S, Gholampour H, Khanmohammadi H. Finite element analysis of occlusal splint therapy in patients with bruxism. BMC Oral Health. 2019;19(1):205. doi: 10.1186/ s12903-019-0897-z.

Gholampour S, Jalali A. Thermal analysis of the dentine tubule under hot and cold stimuli using fluid-structure interaction simulation. Biomech Model Mechanobiol. 2018;17(6):1599- 610. doi: 10.1007/s10237-018-1046-3.

Gholampour s GH. Correlation of a new hydrodynamic index with other effective indexes in Chiari I malformation patients with different associations. Scientific Reports. 2020.

Gholampour S, Mehrjoo S. Effect of bifurcation in the hemodynamic changes and rupture risk of small intracranial aneurysm. Neurosurg Rev. 2020. doi: 10.1007/s10143-020- 01367-3.

Haberland M, Kim S. On extracting design principles from biology: II. Case study-the effect of knee direction on bipedal robot running efficiency. Bioinspir Biomim. 2015;10(1):016011. doi: 10.1088/1748-3190/10/1/016011.

Hinkel G, Groenda H, Krach S, Vannucci L, Denninger O, Cauli N, et al. A framework for coupled simulations of robots and spiking neuronal networks. J Intell Robot Syst. 2017;85(1):71-91. doi: 10.1007/s10846-016-0412-6.

Kelty CM. Robot life: simulation and participation in the study of evolution and social behavior. Hist Philos Life Sci. 2018;40(1):16. doi: 10.1007/s40656-017-0181-y.

Liu Y, Sun S, Wu X, Mei T. A wheeled wall-climbing robot with bio-inspired spine mechanisms. J Bionic Eng. 2015;12(1):17- 28. doi: 10.1016/S1672-6529(14)60096-2.

Porez M, Boyer F, Ijspeert AJ. Improved Lighthill fish swimming model for bio-inspired robots: modeling, computational aspects and experimental comparisons. Int J Rob Res. 2014;33(10):1322-41. doi: 10.1177/0278364914525811.

Zhang J, Wang T, Wang J, Li B, Hong J, Zhang JXJ, et al. Dynamic modeling and simulation of inchworm movement towards bio-inspired soft robot design. Bioinspir Biomim. 2019;14(6):066012. doi: 10.1088/1748-3190/ab3e1f.

  • Abstract Viewed: 266 times
  • PDF Downloaded: 269 times

Download Statastics