Reliability of EUCLIDIAN: An autonomous robotic system for image-guided prostate brachytherapy.

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Bibliographic Details
Title:	Reliability of EUCLIDIAN: An autonomous robotic system for image-guided prostate brachytherapy.
Authors:	Podder, Tarun K.¹, Buzurovic, Ivan¹, Huang, Ke¹, Showalter, Timothy¹, Dicker, Adam P.¹, Yu, Yan¹
Source:	Medical Physics. Jan2011, Vol. 38 Issue 1, p96-106. 11p.
Subjects:	Medical equipment reliability, Autonomous robots, Radioisotope brachytherapy, Medical equipment, Euclidean algorithm, Medical imaging systems, Characteristic functions, Parameter estimation
Abstract:	Purpose: Recently, several robotic systems have been developed to perform accurate and consistent image-guided brachytherapy. Before introducing a new device into clinical operations, it is important to assess the reliability and mean time before failure (MTBF) of the system. In this article, the authors present the preclinical evaluation and analysis of the reliability and MTBF of an autonomous robotic system, which is developed for prostate seed implantation. Methods: The authors have considered three steps that are important in reliability growth analysis. These steps are: Identification and isolation of failures, classification of failures, and trend analysis. For any one-of-a-kind product, the reliability enhancement is accomplished through test-fix-test. The authors have used failure mode and effect analysis for collection and analysis of reliability data by identifying and categorizing the failure modes. Failures were classified according to severity. Failures that occurred during the operation of this robotic system were considered as nonhomogenous Poisson process. The failure occurrence trend was analyzed using Laplace test. For analyzing and predicting reliability growth, commonly used and widely accepted models, Duane's model and the Army Material Systems Analysis Activity, i.e., Crow's model, were applied. The MTBF was used as an important measure for assessing the system's reliability. Results: During preclinical testing, 3196 seeds (in 53 test cases) were deposited autonomously by the robot and 14 critical failures were encountered. The majority of the failures occurred during the first few cases. The distribution of failures followed Duane's postulation as well as Crow's postulation of reliability growth. The Laplace test index was -3.82 (<0), indicating a significant trend in failure data, and the failure intervals lengthened gradually. The continuous increase in the failure occurrence interval suggested a trend toward improved reliability. The MTBF was 592 seeds, which implied that several prostate seed implantation cases would be possible without encountering any critical failure. The shape parameter for the MTBF was 0.3859 (<1), suggesting a positive reliability growth of this robotic system. At 95% confidence, the reliability for deposition of 65 seeds was more than 90%. Conclusions: Analyses of failure mode strongly indicated a gradual improvement of reliability of this autonomous robotic system. High MTBF implied that several prostate seed implant cases would be possible without encountering any critical failure. [ABSTRACT FROM AUTHOR]
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Database:	Engineering Source

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Abstract:	Purpose: Recently, several robotic systems have been developed to perform accurate and consistent image-guided brachytherapy. Before introducing a new device into clinical operations, it is important to assess the reliability and mean time before failure (MTBF) of the system. In this article, the authors present the preclinical evaluation and analysis of the reliability and MTBF of an autonomous robotic system, which is developed for prostate seed implantation. Methods: The authors have considered three steps that are important in reliability growth analysis. These steps are: Identification and isolation of failures, classification of failures, and trend analysis. For any one-of-a-kind product, the reliability enhancement is accomplished through test-fix-test. The authors have used failure mode and effect analysis for collection and analysis of reliability data by identifying and categorizing the failure modes. Failures were classified according to severity. Failures that occurred during the operation of this robotic system were considered as nonhomogenous Poisson process. The failure occurrence trend was analyzed using Laplace test. For analyzing and predicting reliability growth, commonly used and widely accepted models, Duane's model and the Army Material Systems Analysis Activity, i.e., Crow's model, were applied. The MTBF was used as an important measure for assessing the system's reliability. Results: During preclinical testing, 3196 seeds (in 53 test cases) were deposited autonomously by the robot and 14 critical failures were encountered. The majority of the failures occurred during the first few cases. The distribution of failures followed Duane's postulation as well as Crow's postulation of reliability growth. The Laplace test index was -3.82 (<0), indicating a significant trend in failure data, and the failure intervals lengthened gradually. The continuous increase in the failure occurrence interval suggested a trend toward improved reliability. The MTBF was 592 seeds, which implied that several prostate seed implantation cases would be possible without encountering any critical failure. The shape parameter for the MTBF was 0.3859 (<1), suggesting a positive reliability growth of this robotic system. At 95% confidence, the reliability for deposition of 65 seeds was more than 90%. Conclusions: Analyses of failure mode strongly indicated a gradual improvement of reliability of this autonomous robotic system. High MTBF implied that several prostate seed implant cases would be possible without encountering any critical failure. [ABSTRACT FROM AUTHOR]
ISSN:	00942405
DOI:	10.1118/1.3523097