Dataset Information

Evaluating Pedicle-Screw Instrumentation Using Decision-Tree Analysis Based on Pullout Strength.

ABSTRACT: A biomechanical study of pedicle-screw pullout strength.To develop a decision tree based on pullout strength for evaluating pedicle-screw instrumentation.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.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.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.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.

SUBMITTER: Varghese V

PROVIDER: S-EPMC6068417 | biostudies-other | 2018 Aug

REPOSITORIES: biostudies-other

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Evaluating Pedicle-Screw Instrumentation Using Decision-Tree Analysis Based on Pullout Strength.

Varghese Vicky V Krishnan Venkatesh V Kumar Gurunathan Saravana GS

Asian spine journal 20180727 4

<h4>Study design</h4>A biomechanical study of pedicle-screw pullout strength.<h4>Purpose</h4>To develop a decision tree based on pullout strength for evaluating pedicle-screw instrumentation.<h4>Overview of literature</h4>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 ...[more]

PMID: 30060368

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Project description:The expectations of both the patient and surgeon have been greatly revised in the last 10 years with the introduction of pedicle screws (PS) in spinal surgery. In this study, we have retrospectively evaluated and compared the results of PS instrumentation and the Hybrid System (HS), the latter consists of pedicle screws, sublaminar wire and hooks. The mean follow-up period was 60.1 months (range: 49-94 months) for the patients of the HS group and 29.3 months (range: 24-35 months) for those of the PS group. In the HS group, pedicle screws were used at the thoracolumbar junction and lumbar vertebra, the bilateral pediculotransverse claw hook configuration was used at the cranial end of the instrumentation, sublaminar wire was used on the concave side of the apical region and the compressive hook was used on the convex side. In the PS group, PS were used on the concave sides at all levels and on the convex side of the cranial and caudal end of instrumentation, in the transition zone and at the apex. The two groups were comparable for variables such as mean age, preoperative Cobb angle, thoracic kyphosis angle, lordosis angle, coronal balance, flexibility of the curve, apical vertebra rotation (AVR), apical vertebra rotation (AVT) and the number of vertebrae included in the fusion (p>0.05). The parameters of values of correction, ratio of correction loss, AV derotation, AVT correction ratio, amount of blood loss, operation time, postoperative global coronal and sagittal balance, thoracic kyphosis angle and lumbar lordosis angle were measured at the last follow-up and used for comparing the HS and PS groups. There was no statistically significant difference between the groups for correction ratio, postoperative coronal balance, postoperative thoracic kyphosis and lumbar lordosis angle, operation time, amount of blood loss and number of fixation points (p>0.05) The difference for the ratio of correction loss, AV derotation angle and the AVT correction ratio at the last follow-up visit and for the total follow-up period between the groups was found to be statistically significant (p<0.05). Although it is possible to obtain a similar amount of correction by either instrumentation system, the loss of correction seems to be lower with the more rigid PS construction. The PS system also has a stronger effect on vertebral bodies, thereby providing better AV de-rotation. There was no significant difference (p>0.05) between the groups in terms of correction rate, postoperative coronal and sagittal balance, operation time, blood loss and number of fixation points. This may indicate that anchor points are more important than the use--or not--of screws. Correction durability and AV de-rotation was better with PS instrumentation, while AVT was better corrected by HS instrumentation (p<0.05). We propose that the reason for the better correction of AVT with HS instrumentation is the forceful translation offered by the sublaminar wire at the apical region, while the reason for the better correction durability of the PS instrumentation may be due to the fact that multiple pedicle screws which afford three-column control are better at maintaining the correction and preventing late deterioration.

Dataset Information

Evaluating Pedicle-Screw Instrumentation Using Decision-Tree Analysis Based on Pullout Strength.

Publications

Evaluating Pedicle-Screw Instrumentation Using Decision-Tree Analysis Based on Pullout Strength.

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