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Device to accurately place Epidural Tuohy needle for Anesthesia AdministrationVaughan, Neil; Dubey, Venketesh N.; Wee, Michael Y. K.; Isaacs, Richard; Bournemouth University; Poole Hospital NHS Foundation Trust (Copernicus Publications, 2014-01-02)The aim of this project is to design two sterile devices for epidural needle insertion which can measure in real time (i) the depth of needle tip during insertion and (ii) interspinous pressure changes through a pressure measurement device as the epidural needle is advanced through the tissue layers. The length measurement device uses a small wireless camera with video processing computer algorithms which can detect and measure the moving needle. The pressure measurement device uses entirely sterile componenets including a pressure transducer to accurately measure syringe saline in mm Hg. The data from these two devices accurately describe a needle insertion allowing comparison or review of insertions. The data was then cross-referenced to pre-measured data from MRI or ultrasound scan to identify how ligemant thickness correlates to our measured depth and pressure data. The developed devices have been tested on a porcine specimen during insertions performed by experienced anaesthetists. We have obtained epidural pressures for each ligament and demonstrated functionality of our devices to measure pressure and depth of epidural needle during insertion. This has not previously been possible to monitor in real-time. The benefits of these devices are (i) to provide an alternative method to identify correct needle placement during the procedure on real patients. (ii) The data describing the speed, depth and pressure during insertion can be used to configure an epidural simulator, simulating the needle insertion procedure. (iii) Our pressure and depth data can be compared to pre-measured MRI and ultrasound to identify previously unknown links between epidural pressure and depth with BMI, obesity and body shapes.
Haptic feedback from human tissues of various stiffness and homogeneity.Vaughan, Neil; Dubey, Venketesh N.; Wee, Michael Y. K.; Isaacs, Richard; Bournemouth University; Poole Hospital NHS Foundation Trust (Techno-Press, 2014-07-01)This work presents methods for haptic modelling of soft and hard tissue with varying stiffness. The model provides visualization of deformation and calculates force feedback during simulated epidural needle insertion. A spring-mass-damper (SMD) network is configured from magnetic resonance image (MRI) slices of patient’s lumbar region to represent varying stiffness throughout tissue structure. Reaction force is calculated from the SMD network and a haptic device is configured to produce a needle insertion simulation. The user can feel the changing forces as the needle is inserted through tissue layers and ligaments. Methods for calculating the force feedback at various depths of needle insertion are presented. Voxelization is used to fill ligament surface meshes with spring mass damper assemblies for simulated needle insertion into soft and hard tissues. Modelled vertebrae cannot be pierced by the needle. Graphs were produced during simulated needle insertions to compare the applied force to haptic reaction force. Preliminary saline pressure measurements during Tuohy epidural needle insertion are also used as a basis for forces generated in the simulation.
Parametric model of human body shape and ligaments for patient-specific epidural simulationVaughan, Neil; Dubey, Venketesh N.; Wee, Michael Y. K.; Isaacs, Richard; Bournemouth University; Poole Hospital NHS Foundation Trust (Elsevier, 2014-09-04)Objective: This work builds upon the concept of matching a person’s weight, height and age to their overall body shape to create an adjustable three-dimensional model. A versatile and accurate predictor of body size and shape and ligament thickness is required to improve simulation for medical procedures. A model which is adjustable for any size, shape, body mass, age or height would provide ability to simulate procedures on patients of various body compositions. Methods: Three methods are provided for estimating body circumferences and ligament thicknesses for each patient. The first method is using empirical relations from body shape and size. The second method is to load a dataset from a magnetic resonance imaging scan (MRI) or ultrasound scan containing accurate ligament measurements. The third method is a developed artificial neural network (ANN) which uses MRI dataset as a training set and improves accuracy using error back-propagation, which learns to increase accuracy as more patient data is added. The ANN is trained and tested with clinical data from 23088 patients. Results: The ANN can predict subscapular skinfold thickness within 3.54mm, waist circumference 3.92cm, thigh circumference 2.00cm, arm circumference 1.21cm, calf circumference 1.40cm, triceps skinfold thickness 3.43mm. Alternative regression analysis method gave overall slightly less accurate predictions for subscapular skinfold thickness within 3.75mm, waist circumference 3.84cm, thigh circumference 2.16cm, arm circumference 1.34cm, calf circumference 1.46cm, triceps skinfold thickness 3.89mm. These calculations are used to display a 3D graphics model of the patient’s body shape using OpenGL and adjusted by 3D mesh deformations. Conclusions: A patient-specific epidural simulator is presented using the developed body shape model, able to simulate needle insertion procedures on a 3D model of any patient size and shape. The developed ANN gave the most accurate results for body shape, size and ligament thickness. The resulting simulator offers the experience of simulating needle insertions accurately whilst allowing for variation in patient body mass, height or age.