Tool Sequence Trends in Minimally Invasive Surgery: Statistical Analysis and Implications for Predictive Control of Multifunction Instruments. Issue 2 (5th June 2012)

• Record Type: Journal Article
• Authors: Nelson, Carl A.; Luxon, Evan; Oleynikov, Dmitry
• Is Part Of: Journal of healthcare engineering. Volume 3:Issue 2(2012)
• Page Start: 261
• Page End: 278
• Publication Date: 2012-06-05
• Subjects: minimally invasive surgery (MIS) -- computer-assisted surgery -- surgical planning -- surgical tool use -- statistical analysis -- signal to noise ratio -- multifunction surgical instruments; Hospital buildings -- Environmental engineering -- Periodicals; Medical technology -- Periodicals; Medical informatics -- Periodicals; 610.28
• DOI: 10.1260/2040-2295.3.2.261
• Languages: English
• ISSNs: 2040-2295

Abstract

Abstract : This paper presents an analysis of 67 minimally invasive surgical procedures covering 11 different procedure types to determine patterns of tool use. A new graph-theoretic approach was taken to organize and analyze the data. Through grouping surgeries by type, trends of common tool changes were identified. Using the concept of signal/noise ratio, these trends were found to be statistically strong. The tool-use trends were used to generate tool placement patterns for modular (multi-tool, cartridge-type) surgical tool systems, and the same 67 surgeries were numerically simulated to determine the optimality of these tool arrangements. The results indicate that aggregated tool-use data (by procedure type) can be employed to predict tool-use sequences with good accuracy, and also indicate the potential for artificial intelligence as a means of preoperative and/or intraoperative planning. Furthermore, this suggests that the use of multifunction surgical tools can be optimized to streamline surgical workflow.