BACKGROUND: Accurate needle placement is the first concern in percutaneous MRI-guided prostate interventions. In this phantom study, different sources contributing to the overall needle placement error of a MRI-guided robot for prostate biopsy have been identified, quantified and minimized to the possible extent. METHODS: The overall needle placement error of the system was evaluated in a prostate phantom. This error was broken into two parts: the error associated with the robotic system (called 'before-insertion error') and the error associated with needle-tissue interaction (called 'due-to-insertion error'). Before-insertion error was measured directly in a soft phantom and different sources contributing into this part were identified and quantified. A calibration methodology was developed to minimize the 4-DOF manipulator's error. The due-to-insertion error was indirectly approximated by comparing the overall error and the before-insertion error. The effect of sterilization on the manipulator's accuracy and repeatability was also studied. RESULTS: The average overall system error in the phantom study was 2.5 mm (STD = 1.1 mm). The average robotic system error in the Super Soft plastic phantom was 1.3 mm (STD = 0.7 mm). Assuming orthogonal error components, the needle-tissue interaction error was found to be approximately 2.13 mm, thus making a larger contribution to the overall error. The average susceptibility artifact shift was 0.2 mm. The manipulator's targeting accuracy was 0.71 mm (STD = 0.21 mm) after robot calibration. The robot's repeatability was 0.13 mm. Sterilization had no noticeable influence on the robot's accuracy and repeatability. CONCLUSIONS: The experimental methodology presented in this paper may help researchers to identify, quantify and minimize different sources contributing into the overall needle placement error of an MRI-guided robotic system for prostate needle placement. In the robotic system analysed here, the overall error of the studied system remained within the acceptable range.
BACKGROUND: Accurate needle placement is the first concern in percutaneous MRI-guided prostate interventions. In this phantom study, different sources contributing to the overall needle placement error of a MRI-guided robot for prostate biopsy have been identified, quantified and minimized to the possible extent. METHODS: The overall needle placement error of the system was evaluated in a prostate phantom. This error was broken into two parts: the error associated with the robotic system (called 'before-insertion error') and the error associated with needle-tissue interaction (called 'due-to-insertion error'). Before-insertion error was measured directly in a soft phantom and different sources contributing into this part were identified and quantified. A calibration methodology was developed to minimize the 4-DOF manipulator's error. The due-to-insertion error was indirectly approximated by comparing the overall error and the before-insertion error. The effect of sterilization on the manipulator's accuracy and repeatability was also studied. RESULTS: The average overall system error in the phantom study was 2.5 mm (STD = 1.1 mm). The average robotic system error in the Super Soft plastic phantom was 1.3 mm (STD = 0.7 mm). Assuming orthogonal error components, the needle-tissue interaction error was found to be approximately 2.13 mm, thus making a larger contribution to the overall error. The average susceptibility artifact shift was 0.2 mm. The manipulator's targeting accuracy was 0.71 mm (STD = 0.21 mm) after robot calibration. The robot's repeatability was 0.13 mm. Sterilization had no noticeable influence on the robot's accuracy and repeatability. CONCLUSIONS: The experimental methodology presented in this paper may help researchers to identify, quantify and minimize different sources contributing into the overall needle placement error of an MRI-guided robotic system for prostate needle placement. In the robotic system analysed here, the overall error of the studied system remained within the acceptable range.
Authors: K Masamune; G Fichtinger; A Patriciu; R C Susil; R H Taylor; L R Kavoussi; J H Anderson; I Sakuma; T Dohi; D Stoianovici Journal: Comput Aided Surg Date: 2001
Authors: Philip Blumenfeld; Nobuhiko Hata; Simon DiMaio; Kelly Zou; Steven Haker; Gabor Fichtinger; Clare M C Tempany Journal: J Magn Reson Imaging Date: 2007-09 Impact factor: 4.813
Authors: Michiel R van den Bosch; Maaike R Moman; Marco van Vulpen; Jan J Battermann; Ed Duiveman; Leonard J van Schelven; Hendrik de Leeuw; Jan J W Lagendijk; Marinus A Moerland Journal: Phys Med Biol Date: 2010-02-10 Impact factor: 3.609
Authors: Dan Stoianovici; Danny Song; Doru Petrisor; Daniel Ursu; Dumitru Mazilu; Michael Muntener; Michael Mutener; Michael Schar; Alexandru Patriciu Journal: Minim Invasive Ther Allied Technol Date: 2007 Impact factor: 2.442
Authors: Ashwin N Sridhar; Archie Hughes-Hallett; Erik K Mayer; Philip J Pratt; Philip J Edwards; Guang-Zhong Yang; Ara W Darzi; Justin A Vale Journal: Nat Rev Urol Date: 2013-06-18 Impact factor: 14.432
Authors: Kareem K Elfatairy; Christopher P Filson; Martin G Sanda; Adeboye O Osunkoya; Rachel L Geller; Sherif G Nour Journal: Br J Radiol Date: 2018-02-13 Impact factor: 3.039
Authors: Yue Chen; Sheng Xu; Alexander Squires; Reza Seifabadi; Ismail Baris Turkbey; Peter A Pinto; Peter Choyke; Bradford Wood; Zion Tsz Ho Tse Journal: IEEE Trans Biomed Eng Date: 2017-09-26 Impact factor: 4.538