Abstract

Abstract

Aims

To devise a method to quantify and optimize tightness when inserting cortical screws, based on bone characterization and screw geometry.

Nearly a quarter of screws cause damage during insertion by stripping the bone, reducing pullout strength by over 80%. Studies assessing surgically achieved tightness have predominately shown that variations between individual surgeons can lead to underpowered investigations. Further to the variables that have been previously explored, several basic aspects related to tightening screws have not been evaluated with regards to how they affect screw insertion. This study aims to identify the achieved tightness for several variables, firstly to better understand factors related to achieving optimal intraoperative screw purchase and secondly to establish improved methodologies for future studies.

Two torque screwdrivers were used consecutively by two orthopaedic surgeons to insert 60 cortical, non-locking, stainless-steel screws of 3.5 mm diameter through a 3.5 mm plate, into custom-made 4 mm thick 20 PCF sheets of Sawbone, mounted on a custom-made jig. Screws were inserted to optimal tightness subjectively chosen by each surgeon. The jig was attached to a bench for vertical screw insertion, before a further 60 screws were inserted using the first torque screwdriver with the jig mounted vertically, enabling horizontal screw insertion. Following the decision to use the first screwdriver to insert the remaining screws in the vertical position for the other variables, the following test parameters were assessed with 60 screws inserted per surgeon: without gloves, double surgical gloves, single surgical gloves, non-sterile nitrile gloves and, with and then without augmented feedback (using digitally displayed real-time achieved torque). For all tests, except when augmented feedback was used, the surgeon was blinded to the insertion torque. Once the stopping torque was reached, screws were tightened until the stripping torque was found, this being used to calculate tightness (stopping/stripping torque ratio). Screws were recorded to have stripped the material if the stopping torque was greater than the stripping torque. Following tests of normality, Mann-Whitney-U comparisons were performed between and combining both surgeons for each variable, with Bonferroni corrections for multiple comparisons.

There was no significant (p=0.29) difference in the achieved tightness between different torque screw drivers nor different jig positions (p=0.53). The use of any gloves led to significant (p < 0 .001) increases in achieved tightness compared to not using gloves for one surgeon but made no difference for the other (p=0.38–0.74). Using augmented feedback was found to virtually eliminate stripping. For one surgeon average tightness increased significantly (p < 0 .001) when torque values were displayed from 55 to 75%, whilst for the other, this was associated with significantly decreases (p < 0 .001), 72 to 57%, both surgeons returned to their pre-augmentation tightness when it was removed.

Individual techniques make a considerable difference to the impact from some variables involved when inserting screws. However, the orientation of screws insertion and the type of screwdriver did not affect achieved screw tightness. Using visual feedback reduces rates of stripping and investigating ways to incorporate this into clinical use are recommended. Further work is underway into the effect of other variables such as bone density and cortical thickness.

Digital image correlation (DIC) is rapidly increasing in popularity in biomechanical studies of the musculoskeletal system. DIC allows the re-construction of full field displacement and/or strain maps of the surface of an object. DIC systems typically consist of two cameras focussing on the same region of interest. This constrains the angle between the cameras to be relatively narrow when studying specimens characterised by complex geometrical features, giving rise to concerns on the accuracy of the out of plane estimates of movement.

The aim of this research was to compare the movement profiles of bony segments measured by DIC and by an optoelectronic motion capture system.

Five porcine cervical spine segments (C2-C6) were obtained from the local butcher. These were stripped of all anterior soft tissues while the posterior structures were left intact. A speckle pattern was applied to the anterior aspect of the specimens, while custom made infrared clusters were rigidly attached to the 3 middle vertebral bodies (C3-C5). The specimens were mounted in a custom made impact rig which fully constrained C6 but allowed C2 to translate in the axial direction of the segment. Images were acquired at 4kHz, both for the DIC (Photron Europe Ltd, UK) and motion capture cameras (Qualisys Oqus 400, Sweden). The in-plane and out of plane displacements of each of the VBs were plotted as a function of time and the similarity between the curves thus obtained was analysed using the SPM1D technique which allowed a comparison to be made in terms of t-statistics. No statistical differences were found between the two techniques in all axis of movement, however the out of plane movements were characterised by higher variance which is attributed to the uncertainty arising from the near parallel positioning of the cameras in the experimental set-up.

Head collisions in sport can result in catastrophic cervical spine injuries. Musculo-skeletal (MSK) modelling can help analyse the relationship between players' motion, external loading and internal stresses that lead to injury. However, the literature lacks sport specific MSK models. In automotive research the intervertebral disc behaviour has been represented as viscoelastic elements (“bushing”), whose stiffness and damping parameters are often estimated under quasi-static conditions and may lack validity in dynamic impacts. The aim of this study was to develop a validated cervical spine model for axial impacts for future use in the analysis of head-first rugby collisions.

A drop test rig was used to replicate a sub-catastrophic axial head impact. A load of 80 N from 0.5 m was applied to the cranial aspect of a C2-C6 porcine spinal specimen mounted in the neutral position. The 3D motion of C3-C5 vertebras (4 kHz) and the cranial axial load (1 MHz) were measured via motion capture (Qualysis, Sweden) and a uniaxial load cell (RDP Electronics Ltd, UK). Specimen specific models were created in NMSBuilder and OpenSim after the vertebrae geometries were obtained from the segmentation of micro-CT images of the specimens. The compressive viscoelastic properties of four vertebral joints (C2-C3 through to C5-C6) were optimised via a Genetic Algorithm (MATLAB v2016b, The Mathworks Inc) to minimise tracking errors.

The optimisation converged to a solution of 140–49000 kN/m and 2000–8000 Ns/m for stiffness and damping respectively (RMSE=5.1 mm). Simulated joint displacements ranged between 0.09 – 1.75 mm compared to experimental 0.1 – 0.8 mm.

Optimal bushing parameters were higher than previously reported values measured through quasi-static testing. Higher stiffness and damping values could be explained by the higher-dynamics nature of the event analysed related to a different part of the non-linear intervertebral disc load-displacement curve.

The screw fastening torque applied during bone fracture fixation has a decisive influence on subsequent bone healing. Insufficient screw tightness can result in device/construct instability; conversely, excessive torques risk damaging the bone causing premature fixation failure. This effect is even more prominent in osteoporotic bone, a condition associated annually with almost 9 million fractures worldwide. During fracture fixation, screw tightening torque is applied using subjective feel. This approach may not be optimal for patient”s recovery, increasing risk of fixation failure, particularly in osteoporotic bone, and potentially require revision surgical interventions.

Besides bone density, various factors influence the performance of screw fixation. These factors include bone geometry, cortical thickness and time-dependant relaxation behaviour of the bone. If the influence of screw fastening torque on the bone and relationships between these factors was better understood, the surgical technique could be optimised to reduce the risk of complications.

Within this study, we developed an axisymmetric finite element (FE) model of bone screw tightening incorporating viscoelastic behaviour of the cortical bone such as creep and stress relaxation. The model anticipated time-dependent behaviour of the bone for different bone thickness and density after a typical bone fixation screw had been inserted. The idealised model has been developed based on CT scans of bones with varying densities and inserted screws. The model was validated through a series of experiments involving bovine tibiae (4–5 months) to evaluate the evolution of surface strains with time (Ncorr v1.2). Stress distribution was assessed in photoelastic experiments using acrylic analogues. Relaxation tests have been performed in aqueous environment for up to 48 hours to ensure the relaxation would be complete. The creep behaviour (maximum principal strain) was compared against computational predictions. Our early simulations predicted relaxation strains on the surface of the bone to be 1.1% within 24 hours comparing favourably to 1.3% measured experimentally. Stress distribution patterns were in agreement with photoelastic results.

Using experimentally derived viscoelastic properties, the model has the potential to predict creep and stress relaxation patterns after screw insertion with different fastening torques for bones with varying density and geometry. We aim to develop this into a planning tool providing guidance to surgeons for optimal tightening when using screw fixation, particularly in reduced quality bone.