Pull out strength calculator for pedicle screws using a surrogate ensemble approach. (December 2016)

• Record Type: Journal Article
• Authors: Varghese, Vicky; Ramu, Palaniappan; Krishnan, Venkatesh; Saravana Kumar, Gurunathan
• Is Part Of: Computer methods and programs in biomedicine. Volume 137(2016)
• Page Start: 11
• Page End: 22
• Publication Date: 2016-12
• Subjects: Pedicle screw -- Pull out -- Surrogate -- Surgical planning; Medicine -- Computer programs -- Periodicals; Biology -- Computer programs -- Periodicals; Computers -- Periodicals; Medicine -- Periodicals; Médecine -- Logiciels -- Périodiques; Biologie -- Logiciels -- Périodiques; Biology -- Computer programs; Medicine -- Computer programs; Periodicals; Electronic journals; 610.28
• DOI: 10.1016/j.cmpb.2016.08.023
• Languages: English
• ISSNs: 0169-2607

Abstract

Highlights: Density, insertion depth, insertion angle and reinsertion significantly affect ( p < 0.05) holding power of pedicle screw. A surrogate model was developed for predicting pull out strength of pedicle screw. Weighted average surrogate performs the best in predicting the holding power of pedicle screw. Pull out calculator can be used as a decision support for surgeons performing pedicle screw instrumentation. Abstract: Background and objective: Pedicle screw instrumentation is widely used in the treatment of spinal disorders and deformities. Currently, the surgeon decides the holding power of instrumentation based on the perioperative feeling which is subjective in nature. The objective of the paper is to develop a surrogate model which will predict the pullout strength of pedicle screw based on density, insertion angle, insertion depth and reinsertion. Methods: A Taguchi's orthogonal array was used to design an experiment to find the factors effecting pullout strength of pedicle screw. The pullout studies were carried using polyaxial pedicle screw on rigid polyurethane foam block according to American society for testing of materials (ASTM F543 ). Analysis of variance (ANOVA) and Tukey's honestly significant difference multiple comparison tests were done to find factor effect. Based on the experimental results, surrogate models based on Krigging, polynomial response surface and radial basis function were developed for predicting the pullout strength for different combination of factors. An ensemble of these surrogates based on weighted average surrogate model was also evaluated for prediction. Results: Density, insertion depth, insertion angle and reinsertion have a significant effect ( p < 0.05) on pullout strength of pedicle screw. Weighted average surrogate performed the best in predicting the pull out strength amongst the surrogate models considered in this study and acted as insurance against bad prediction. Conclusions: A predictive model for pullout strength of pedicle screw was developed using experimental values and surrogate models. This can be used in pre-surgical planning and decision support system for spine surgeon.