{"title":"Body-mounted robotic instrument guide for image-guided cryotherapy of renal cancer.","authors":"Nobuhiko Hata, Sang-Eun Song, Olutayo Olubiyi, Yasumichi Arimitsu, Kosuke Fujimoto, Takahisa Kato, Kemal Tuncali, Soichiro Tani, Junichi Tokuda","doi":"10.1118/1.4939875","DOIUrl":null,"url":null,"abstract":"<p><strong>Purpose: </strong>Image-guided cryotherapy of renal cancer is an emerging alternative to surgical nephrectomy, particularly for those who cannot sustain the physical burden of surgery. It is well known that the outcome of this therapy depends on the accurate placement of the cryotherapy probe. Therefore, a robotic instrument guide may help physicians aim the cryotherapy probe precisely to maximize the efficacy of the treatment and avoid damage to critical surrounding structures. The objective of this paper was to propose a robotic instrument guide for orienting cryotherapy probes in image-guided cryotherapy of renal cancers. The authors propose a body-mounted robotic guide that is expected to be less susceptible to guidance errors caused by the patient's whole body motion.</p><p><strong>Methods: </strong>Keeping the device's minimal footprint in mind, the authors developed and validated a body-mounted, robotic instrument guide that can maintain the geometrical relationship between the device and the patient's body, even in the presence of the patient's frequent body motions. The guide can orient the cryotherapy probe with the skin incision point as the remote-center-of-motion. The authors' validation studies included an evaluation of the mechanical accuracy and position repeatability of the robotic instrument guide. The authors also performed a mock MRI-guided cryotherapy procedure with a phantom to compare the advantage of robotically assisted probe replacements over a free-hand approach, by introducing organ motions to investigate their effects on the accurate placement of the cryotherapy probe. Measurements collected for performance analysis included accuracy and time taken for probe placements. Multivariate analysis was performed to assess if either or both organ motion and the robotic guide impacted these measurements.</p><p><strong>Results: </strong>The mechanical accuracy and position repeatability of the probe placement using the robotic instrument guide were 0.3 and 0.1 mm, respectively, at a depth of 80 mm. The phantom test indicated that the accuracy of probe placement was significantly better with the robotic instrument guide (4.1 mm) than without the guide (6.3 mm, p<0.001), even in the presence of body motion. When independent organ motion was artificially added, in addition to body motion, the advantage of accurate probe placement using the robotic instrument guide disappeared statistically [i.e., 6.0 mm with the robotic guide and 5.9 mm without the robotic guide (p = 0.906)]. When the robotic instrument guide was used, the total time required to complete the procedure was reduced from 19.6 to 12.7 min (p<0.001). Multivariable analysis indicated that the robotic instrument guide, not the organ motion, was the cause of statistical significance. The statistical power the authors obtained was 88% in accuracy assessment and 99% higher in duration measurement.</p><p><strong>Conclusions: </strong>The body-mounted robotic instrument guide allows positioning of the probe during image-guided cryotherapy of renal cancer and was done in fewer attempts and in less time than the free-hand approach. The accuracy of the placement of the cryotherapy probe was better using the robotic instrument guide than without the guide when no organ motion was present. The accuracy between the robotic and free-hand approach becomes comparable when organ motion was present.</p>","PeriodicalId":51731,"journal":{"name":"Journal of Computational Finance","volume":"6 1","pages":"843-53"},"PeriodicalIF":0.8000,"publicationDate":"2016-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1118/1.4939875","citationCount":"22","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Computational Finance","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1118/1.4939875","RegionNum":4,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"BUSINESS, FINANCE","Score":null,"Total":0}
引用次数: 22
Abstract
Purpose: Image-guided cryotherapy of renal cancer is an emerging alternative to surgical nephrectomy, particularly for those who cannot sustain the physical burden of surgery. It is well known that the outcome of this therapy depends on the accurate placement of the cryotherapy probe. Therefore, a robotic instrument guide may help physicians aim the cryotherapy probe precisely to maximize the efficacy of the treatment and avoid damage to critical surrounding structures. The objective of this paper was to propose a robotic instrument guide for orienting cryotherapy probes in image-guided cryotherapy of renal cancers. The authors propose a body-mounted robotic guide that is expected to be less susceptible to guidance errors caused by the patient's whole body motion.
Methods: Keeping the device's minimal footprint in mind, the authors developed and validated a body-mounted, robotic instrument guide that can maintain the geometrical relationship between the device and the patient's body, even in the presence of the patient's frequent body motions. The guide can orient the cryotherapy probe with the skin incision point as the remote-center-of-motion. The authors' validation studies included an evaluation of the mechanical accuracy and position repeatability of the robotic instrument guide. The authors also performed a mock MRI-guided cryotherapy procedure with a phantom to compare the advantage of robotically assisted probe replacements over a free-hand approach, by introducing organ motions to investigate their effects on the accurate placement of the cryotherapy probe. Measurements collected for performance analysis included accuracy and time taken for probe placements. Multivariate analysis was performed to assess if either or both organ motion and the robotic guide impacted these measurements.
Results: The mechanical accuracy and position repeatability of the probe placement using the robotic instrument guide were 0.3 and 0.1 mm, respectively, at a depth of 80 mm. The phantom test indicated that the accuracy of probe placement was significantly better with the robotic instrument guide (4.1 mm) than without the guide (6.3 mm, p<0.001), even in the presence of body motion. When independent organ motion was artificially added, in addition to body motion, the advantage of accurate probe placement using the robotic instrument guide disappeared statistically [i.e., 6.0 mm with the robotic guide and 5.9 mm without the robotic guide (p = 0.906)]. When the robotic instrument guide was used, the total time required to complete the procedure was reduced from 19.6 to 12.7 min (p<0.001). Multivariable analysis indicated that the robotic instrument guide, not the organ motion, was the cause of statistical significance. The statistical power the authors obtained was 88% in accuracy assessment and 99% higher in duration measurement.
Conclusions: The body-mounted robotic instrument guide allows positioning of the probe during image-guided cryotherapy of renal cancer and was done in fewer attempts and in less time than the free-hand approach. The accuracy of the placement of the cryotherapy probe was better using the robotic instrument guide than without the guide when no organ motion was present. The accuracy between the robotic and free-hand approach becomes comparable when organ motion was present.
期刊介绍:
The Journal of Computational Finance is an international peer-reviewed journal dedicated to advancing knowledge in the area of financial mathematics. The journal is focused on the measurement, management and analysis of financial risk, and provides detailed insight into numerical and computational techniques in the pricing, hedging and risk management of financial instruments. The journal welcomes papers dealing with innovative computational techniques in the following areas: Numerical solutions of pricing equations: finite differences, finite elements, and spectral techniques in one and multiple dimensions. Simulation approaches in pricing and risk management: advances in Monte Carlo and quasi-Monte Carlo methodologies; new strategies for market factors simulation. Optimization techniques in hedging and risk management. Fundamental numerical analysis relevant to finance: effect of boundary treatments on accuracy; new discretization of time-series analysis. Developments in free-boundary problems in finance: alternative ways and numerical implications in American option pricing.