Active Shape Models (ASM) have been widely used in the literature for the extraction of the tibial and the femoral bones from MRI. These methods use Statistical Shape Models (SSM) to drive the deformation and make the segmentation more robust. One crucial step for building such SSM is the shape correspondence (SC). Several methods have been described in the literature. The goal of this paper is to compare two SC methods, the Iterative Median Closest Point-Gaussian Mixture Model (IMCP-GMM) and the Minimum Description Length (MDL) approaches for the creation of a SSM, and to assess the impact on the accuracy of the femur segmentation in MRI.

28 MRI of the knee have been used. The validation has been performed by using the leave-one-out cross-validation technique. An ASMMDL and an ASMIMCP-GMMM has been built with the SSMs computed respectively with the MDL and IMCP-GMM methods. The computation time for building both SSMs has been also measured.

For 90% of data, the error is inferior to 1.78 mm and 1.85 mm for respectively the ASMIMCP-GMM and the ASMMDL methods. The computation time for building the SSMs is five hours and two days for respectively the IMCP-GMM and the MDL methods.

Both methods seem to give, at least, similar results for the femur segmentation in MRI. But (1) IMCP-GMM can be used for all types of shape, this is not the case for the MDL method which only works for closed shape, and (2) IMCP-GMM is much faster than MDL.

Introduction

Reverse Total Shoulder Arthroplasty (rTSA) is an efficient treatment, to relieve from pain and to increase function. However, scapular notching remains a serious issue and post-operative range of motion (ROM) presents many variations. No study compared implant positioning, different implant combinations, different implant sizes on different types of patient representative to undergo for rTSA, on glenohumeral ROM in every degree of freedom.

Functional approaches for the localisation of the hip centre (HC) are widely used in Computer Assisted Orthopedic Surgery (CAOS). These methods aim to compute the HC defined as the centre of rotation (CoR) of the femur with respect to the pelvis. The Least-Moving-Point (LMP) method is one approach which consists in detecting the point that moves the least during the circumduction motion. The goal of this paper is to highlight the limits of the native LMP (nLMP) and to propose a modified version (mLMP).

A software application has been developed allowing the simulation of a circumduction motion of a hip in order to generate the required data for the computation of the HC. Two tests have been defined in order to assess and compare both LMP methods with respect to (1) the camera noise (CN) and (2) the acetabular noise (AN).

The mLMP and nLMP error is respectively: (1) 0.5±0.2mm and 9.3±1.4mm for a low CN, 21.7±3.6mm and 184.7±13.1mm for a high CN, and (2) 2.2±1.2mm and 0.5±0.3mm for a low AN, 35.2±18.5mm and 13.0±8.2mm for a high AN.

In conclusion, mLMP is more robust and accurate than the nLMP algorithm.

The hip centre (HC) in Computer Assisted Orthopedic Surgery (CAOS) can be determined either with anatomical (AA) or functional approaches (FA). AA is considered as the reference while FA compute the hip centre of rotation (CoR). Four main FA can be used in CAOS: the Gammage, Halvorsen, pivot, and least-moving point (LMP) methods. The goal of this paper is to evaluate and compare with an in-vitro experiment (a) the four main FA for the HC determination, and (b) the impact on the HKA.

The experiment has been performed on six cadavers. A CAOS software application has been developed for the acquisitions of (a) the hip rotation motion, (b) the anatomical HC, and (c) the HKA angle. Two studies have been defined allowing (a) the evaluation of the precision and the accuracy of the four FA with respect to the AA, and (b) the impact on the HKA angle.

For the pivot, LMP, Gammage and Halvorsen methods respectively: (1) the maximum precision reach 14.2, 22.8, 111.4 and 132.5 mm; (2) the maximum accuracy reach 23.6, 40.7, 176.6 and 130.3 mm; (3) the maximum error of the frontal HKA is 2.5°, 3.7°, 12.7° and 13.3°; and (4) the maximum error of the sagittal HKA is 2.3°, 4.3°, 5.9°, 6.1°.

The pivot method is the most precise and accurate approach for the HC localisation and the HKA computation.

Tracking of the anterior pelvic plane is of interest for medical interventions such as total hip arthroplasty, for which it is used as a reference for the positioning of the acetabular cup.

We introduce and evaluate a new portable ultrasound device for the measure of the pelvic tilt in different positions of daily living. This device consists of two ultrasound probes articulated with respect to each other in order to visualise simultaneously the bony landmarks of interest that are one of the anterior superior iliac spine and the pubic symphysis. A series of sensors and the calibration of the ultrasound probes allow the measurement of the relative position of the landmarks with respect to a vertical line.

The accuracy of the device has been investigated through a simulation study and showed errors (mean ± standard deviation [minimum; maximum]) as 0.18° ± 0.96° [−3.85°; 4.33°], with 99% of measurements within a ± 2.5° with respect to the actual pelvic tilt.

This level of accuracy is similar to what can be found in the literature for the same purposes. Our device gathers advantages such as being portable and user friendly in order to be used during the pre-operative consultation. It is also non invasive and non irradiant. Further investigations will be run to assess this accuracy in vitro and in vivo.

Opening-wedge High Tibial Osteotomy (HTO) has been shown to be an effective procedure to treat mild to moderate osteoarthritis of the medial compartment of the knee in active individuals. It has also become a mandatory surgical adjunct to articular cartilage restoration when there is preoperative mal-alignment. However, its efficacy is directly correlated with the accuracy of the correction, which must be within 3° of the preoperative target. Achieving this goal is a significant challenge with conventional techniques. Therefore, computer-assisted navigation protocols have been developed; however, they do not adequately address the technical difficulties associated with this procedure. We present an integrated solution dedicated to the opening-wedge HTO. Advantages to the technique we propose include: 1) a minimum number of implanted bone trackers, 2) depth control of the saw, 3) improved 3-D accuracy in the location of the lateral tibial hinge, and 4) micrometric adjustment of the degree of correction. The proof of concept has been completed on all six specimens. The following key points have been validated: a) Compatibility with a minimally-invasive (5–6 cm) surgical incision b) The compact navigation station can be placed close to the operative field and manipulated through a sterile draping device c) Only two trackers are necessary to acquire the required landmarks and to provide 3-D control of the correction. These can be inserted within the surgical wound without any secondary incisions d) The optimised guide accurately controlled the external tibial hinge in all six cases e) The implant cavity could be milled effectively f) The distractor used to complete the desired realignment maintained stability of the distraction until final fixation with the PEEK implant g) The PEEK implant could be fixed to the tibia with excellent stability in a low-profile fashion. The solution presented here has the potential to help surgeons perform a medial opening-wedge HTO more safely and accurately. This will likely result in an increase in the number of HTOs performed for both isolated medial compartment osteoarthritis as well as for lower extremity realignment in association with cartilage restorative procedures.

INTRODUCTION

Over the last twenty years, image-guided interventions have been greatly expanded by the advances in medical imaging and computing power. A key step for any image-guided intervention is to find the image-to-patient transformation matrix, which is the transformation matrix between the preoperative 3D model of patient anatomy and the real position of the patient in the operating room. In this work, we propose a robust registration algorithm to match ultrasound (US) images with preoperative Magnetic Resonance (MR) images of the Humerus.

INTRODUCTION

In orthopedic surgery, the lower limb alignment defined by the HKA parameter i.e. the angle between the hip, knee and ankle centers, is a crucial clinical criterion used for the achievement of several surgeries. It can be intraoperatively determined with Computer Assisted Orthopedic Surgery (CAOS) systems by computing the 3D location of these joint centres. The hip centre used for the computation of the HKA is defined by the experts as the anatomical centre of the femoral head. However, except for Total Hip Replacement procedure, the hip joint is not accessible and the hip center is computed using functional methods. The two most common are the Least Moving Point (LMP) and the Pivoting (PIV).

For any image guided surgery, independently of the technique which is used (navigation, templates, robotics), it is necessary to get a 3D bone surface model from CT or MR images. Such model is used for planning, registration and visualization. We report that graphical representation of patient bony structure and the surgical tools, inter-connectively with the tracking device and patient-to-image registration, are crucial components in such system. For Total Shoulder Arthroplasty (TSA), there are many challenges. The most of cases that we are working with are pathological cases such as rheumatoid arthritis, osteoarthritis disease. The CT images of these cases often show a fusion area between the glenoid cavity and the humeral head. They also show severe deformations of the humeral head surface that result in a loss of contours. These fusion area and image quality problems are also amplified by well-known CT-scan artefacts like beam-hardening or partial volume effects. The state of the art shows that several segmentation techniques, applied to CT-Scans of the shoulder, have already been disclosed. Unfortunately, their performances, when used on pathological data, are quite poor.

In severe cases, bone-on-bone arthritis may lead to erosion-wearing away of the bone. Shoulder replacement surgery, also called shoulder arthroplasty, is a successful, pain-relieving option for many people. During the procedure, the humeral head and the glenoid bone are replaced with metal and plastic components to alleviate pain and improve function. This surgical procedure is very difficult and limited to expert centres. The two main problems are the minimal surgical incision and limited access to the operated structures. The success of such procedure is related to optimal prosthesis positioning. For TSA, separating the humeral head in the 3D scanner images would allow enhancing the vision field for the surgeon on the glenoid surface. So far, none of the existing systems or software packages makes it possible to obtain such 3D surface model automatically from CT images and this is probably one of the reasons for very limited success of Computer Assisted Orthopaedic Surgery (CAOS) applications for shoulder surgery. This kind of application often has been limited due to CT-image segmentation for severe pathologic cases and patient to image registration.

The aim of this paper is to present a new image guided planning software based on CT scan of the patient and using bony structure recognition, morphological and anatomical analysis for the operated region. Volumetric preoperative CT datasets have been used to derive a surface model shape of the shoulder. The proposed planning software could be used with a conventional localisation system, which locates in 3D and in real time position and orientation for surgical tools using passive markers associated to rigid bodies that will be fixed on the patient bone and on the surgical instruments.

20 series of patients aged from 42 years to 91 years (mean age of 71 years) were analysed. The first step of this planning software is fully automatic segmentation method based on 3D shape recognition algorithms applied to each object detected in the volume. The second step is a specific processing that only treats the region between the humerus and the glenoid surface in order to separate possible contact areas. The third step is a full morphological analysis of anatomical structure of the bone. The glenoid surface and the glenoid vault are detected and a 3D version and inclination angle of the glenoid surface are computed. These parameters are very important to define an optimal path for drilling and reaming glenoid surface. The surgeon can easily modify the position of the implant in 3D aided by 3D and 2D view of the patient anatomy. The glenoid version/inclination angle and the glenoid vault are computed for each postion in real time to help the surgeon to evaluate the implant position and orientation.

In summary, preoperative planning, 3D CT modelling and intraoperative tracking produced improved accuracy of glenoid implantation. The current paper has presented new planning software in the world of image guided surgery focused on shoulder arthroplasty. Within our approach, we propose, to use pattern recognition instead of manual picking of landmarks to avoid user intervention, in addition to potentially reducing the procedure time. A very important role is played by 3D data sets to visualise specific anatomical structures of the patient. The automatic segmentation of arthritic joints with bone recognition is intended to form a solid basis for the registration. The results of this methodology were tested on arthritic patients to prove that it is not just easy and fast to perform but also very accurate so it realises all conditions for the clinical use in OR.

Purpose of the study: The purpose of this retrospective work was to analyse a series of ten patients (11 osteotomies) who underwent closed rotation osteotomy of the femur performed with an endomedullary saw and stabilized with a centromedullar locked nail. We identified the proper indications, technical aspects, clinical and radiological outcome and describe the complications of this surgical technique.

Material and method: The 11 osteotomies were performed in ten patients from January 1999 to July 2007 for post-trauma rotation defects or congenital deformity. On average the rotation defect was 33.5 (range 24–52), mainly internal rotation (10 cases versus 1 with external rotation). One female patient required a bilateral procedure in a context of congenital bilateral trochlea dysplasia. For two other patients the corrective osteotomy was associated with a lengthening procedure performed during the same operative time (totally closed operation). Clinical and radiological follow-up was available to 4 years 9 months on average (range 26–104 months). The angle corrections were determined on bone tomographs.

Results: Ten of the 11 osteotomies yielded correction to ±4° physiological values (or controlateral values if the other side was healthy) for anteversion of the femoral neck. There were no infections (bone, joint, skin, soft tissue) and not late healing or non-union. There was one transient neurological complication involving the pudendal nerve during a rotation-lengthening procedure and one bilateral fracture of the femur during a bilateral osteotomy. All patients healed within 3 to 5 months. Subjective outcome was satisfactory very satisfactory for 8 of 9 patients (one lost to follow-up) in terms of functional recovery and aesthetic aspect of the scars.

Discussion: The closed procedure for rotation osteotomy of the adult femur is a reliable, effective, safe and reproducible technique for the correction of rotation defects of the femur resulting from trauma or congenital disorders. These results can be obtained only with rigorous technique requiring experience and skill with centromedullary nailing.

One of the advantages of Computer Assisted Orthopaedic Surgery is to obtain functional and morphological information in real time during the procedure. 3D models can be built, without preoperative images, based on elastic 3D to 3D registration methods. The bone morphing algorithm is one of them. It allows to specifically build the 3D shape of bones using a deformable model and a set of spare points obtained on the patient. These points are obtained with a pointer tracker visible by the station which digitises the surface of the bone. However, it’s not always possible to digitise directly the bone in the context of minimal invasive surgery. In this case, the lack of information leads to an inaccurate reconstruction of bone’s surfaces. To collect such missing information we propose to rely on ultrasound (US) images despite the fact that ultrasound is not the best modality to image bones.

To use this method, a segmentation step is first needed to detect automatically the bone in US images. Then, a calibration step of the US probe is carried out to obtain the 3D position of any point of the 2D ultrasonic images using 3D infra-red localizer. Several methods can be carried out to calibrate US probes, however to take into account surgical constraints such as accuracy, robustness, speed and ease of use, we decided to implement the single wall procedure.

The calibration step consists in the estimation of a transformation matrix which carries out the connection between the 2D reference system of the US image and a 3D reference system in the space. To estimate correctly this matrix, a wall is scanned with different motions of the US probe. The images are then processed to automatically detect the lines representing the wall in the US images. A preliminary step allows to clean the images using a threshold and a gradient operation. Then, a method based on the Hough transform detects the lines on the images. Once all the images are processed, the calibration parameters can be estimated by using a new method which minimises the distance between the real plane and the points obtained with the US images. This optimisation step is composed of the genetic algorithms and of the Levenberg-Marquardt (LM) method. The first algorithm allows to obtain a good initialisation in a defined space for the LM algorithm. This good initialisation found thanks to the stochastic behaviour of the genetic algorithms is very important otherwise the LM algorithm could detect local minimum and the calibration parameters could be wrong.

The accuracy of the calibration method is assessed by measuring the distance between the position of a known point in the space and the same point obtained with the US image and the calibration. 40 calibrations matrices are used to estimate correctly the accuracy. An average accuracy of 1.22 mm and a standard deviation (Std. Dev.) of 0.42 mm are measured. The accuracy of the system is quite high but the reproducibility is too low to use this approach in a clinical environment. The main reason of this lack of reproducibility is the thickness of the US beam.

A slight modification in the design of the calibration tool will allow to increase the reproducibility. We will then have an efficient and automatic calibration procedure with the required accuracy and robustness, usable for clinical purposes.