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논문 기본 정보

자료유형
학술저널
저자정보
Vicky Varghese (Indian Institute of Technology Madras) Venkatesh Krishnan (Christian Medical College) Gurunathan Saravana Kumar (Indian Institute of Technology Madras)
저널정보
대한척추외과학회 Asian Spine Journal Asian Spine Journal Vol.12 No.4
발행연도
2018.1
수록면
611 - 621 (11page)

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Study Design: A biomechanical study of pedicle-screw pullout strength. Purpose: To develop a decision tree based on pullout strength for evaluating pedicle-screw instrumentation. Overview of Literature: Clinically, a surgeon’s understanding of the holding power of a pedicle screw is based on perioperative intuition (which is like insertion torque) while inserting the screw. This is a subjective feeling that depends on the skill and experience of the surgeon. With the advent of robotic surgery, there is an urgent need for the creation of a patient-specific surgical planning system. A learning-based predictive model is needed to understand the sensitivity of pedicle-screw holding power to various factors. Methods: Pullout studies were carried out on rigid polyurethane foam, representing extremely osteoporotic to normal bone for different insertion depths and angles of a pedicle screw. The results of these experimental studies were used to build a pullout-strength predictor and a decision tree using a machine-learning approach. Results: Based on analysis of variance, it was found that all the factors under study had a significant effect (p <0.05) on the holding power of a pedicle screw. Of the various machine-learning techniques, the random forest regression model performed well in predicting the pullout strength and in creating a decision tree. Performance was evaluated, and a correlation coefficient of 0.99 was obtained between the observed and predicted values. The mean and standard deviation of the normalized predicted pullout strength for the confirmation experiment using the current model was 1.01±0.04. Conclusions: The random forest regression model was used to build a pullout-strength predictor and decision tree. The model was able to predict the holding power of a pedicle screw for any combination of density, insertion depth, and insertion angle for the chosen range. The decision-tree model can be applied in patient-specific surgical planning and a decision-support system for spine-fusion surgery.

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참고문헌 (30)

참고문헌 신청
Hsu CC / 2003 / Pushout strength of tibial locking screws: development of finite element models / J Chin Inst Eng 26:817~823 Crossref Venkatesh Krishnan / 2016 / Comparative Analysis of Effect of Density, Insertion Angle and Reinsertion on Pull-Out Strength of Single and Two Pedicle Screw Constructs Using Synthetic Bone Model / Asian Spine Journal 10(3):414~421 dbpia Patel PS / 2010 / The effect of screw insertion angle and thread type on the pullout strength of bone screws in normal and osteoporotic cancellous bone models / Med Eng Phys 32:822~828 Crossref Varghese V / 2015 / Pull out strength of pedicle screw in normal and osteoporotic cancellous bone models / Proceedings of the 2014 IEEE Conference on Biomedical Engineering and Sciences (IECBES) Crossref Varghese V / 2017 / Effect of various factors on pull out strength of pedicle screw in normal and osteoporotic cancellous bone models / Med Eng Phys 40:28~38 Crossref

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