Preoperative planning and intraoperative guidance for accurate computer-assisted minimally invasive hip resurfacing surgery

Barrett, A.R.W.; Davies, Brian; Gomes, M.P.S.F.; Harris, Simon; Henckel, Johann; Jakopec, M.; Baena, Ferdinando Rodriguez y; Cobb, Justin P.

doi:10.1243/09544119jeim104

Cited by 16 publications

(10 citation statements)

References 18 publications

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“…18 Methods such as computer navigation have the potential to improve the accuracy of placement of the implant. [19][20][21][22][23][24][25][26][27][28] We describe the methods and results of intra-operative imageless computer navigation for placement of the femoral component in the first 100 such procedures performed at our institution (St. Michael's Hospital, Toronto, Canada).…”

mentioning

confidence: 99%

Imageless computer navigation for placement of the femoral component in resurfacing arthroplasty of the hip

Olsen

Davis

Waddell

et al. 2009

The Journal of Bone and Joint Surgery. British volume

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We have investigated the accuracy of placement of the femoral component using imageless navigation in 100 consecutive Birmingham Hip Resurfacings. Pre-operative templating determined the native neck-shaft angle and planned stem-shaft angle of the implant. The latter were verified post-operatively using digital anteroposterior unilateral radiographs of the hip. The mean neck-shaft angle determined before operation was 132.7 degrees (118 degrees to 160 degrees ). The mean planned stem-shaft angle was a relative valgus alignment of 9.7 degrees (SD 2.6). The stem-shaft angle after operation differed from that planned by a mean of 2.8 degrees (SD 2.0) and in 86% of cases the final angle measured within +/- 5 degrees of that planned. We had no instances of notching of the neck or varus alignment of the implant in our series. A learning curve was observed in the time taken for navigation, but not for accurate placement of the implant. Navigation in hip resurfacing may afford the surgeon a reliable and accurate method of placement of the femoral component.

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mentioning

confidence: 99%

Imageless computer navigation for placement of the femoral component in resurfacing arthroplasty of the hip

Olsen

Davis

Waddell

et al. 2009

The Journal of Bone and Joint Surgery. British volume

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“…2 In, Smit, 24 the author showed a significant reduction of the incidence of hip dislocation in 235 patients who received anatomically sized femoral head (analysis of 1-year follow-up results of total HA). Equivalently, proper morphologic and functional bone parameters identification proved essential for personalized prosthesis design.…”

Section: Discussionmentioning

confidence: 99%

“…In particular, (1) it does not require any initialization; (2) it can be automatically applied to the left and right femur; (3) it is independent of the coordinate system of the original CT dataset; (4) it is independent of the scale of the femur surface; and (5) the algorithms show high stability and reduced computational load. Future work focuses on developing an accurate and robust method for extracting a large number of anatomical and clinical parameters from the entire femur and automatically identifying the clinical condition of the bone.…”

Section: Discussionmentioning

confidence: 99%

Automated Method for Computing the Morphological and Clinical Parameters of the Proximal Femur Using Heuristic Modeling Techniques

et al. 2010

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Bone morphology and morphometric measurements of the lower limb provide significant and useful information for computer-assisted orthopedic surgery planning and intervention, surgical follow-up evaluation, and personalized prosthesis design. Femoral head radius and center, neck axis and size, femoral offset and shaft axis are morphological and functional parameters of the proximal femur utilized both in diagnosis and therapy. Obtaining this information from image data without any operator supervision or manual editing remains a practical objective to avoid variability intrinsic in the manual analysis. In this article, we propose a heuristic method that automatically computes the proximal femur morphological parameters by processing the mesh surface of the femur. The surface data are sequentially processed using geometrical properties such as symmetries, asymmetries, and principal elongation directions. Numerical methods identify the axis of the shaft of femur (least squares cylinder fitting), the head surface and center (least squares sphere fitting), and the femur neck axis and radius (minimal area of the cross section by evolutionary optimization). The repeatability of the method was tested upon 20 femur (10 left + 10 right) surfaces reconstructed from CT scans taken on cadavers. The repeatability error of the automated computation of anatomical landmarks, angles, sizes, and axes was less than 1.5 mm, 2.5 degrees, 1.0 mm, and 3.5 mm, respectively. The computed parameters were in good agreement (landmark difference: <2.0 mm; angle difference: <2.0 degrees; axes difference: <2.5 degrees; size difference: <1.5 mm) with the corresponding reference parameters manually identified in the original CT images by medical experts. In conclusion, the proposed method can improve the degree of automation of model-based hip replacement surgical systems.

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“…Such systems give greater accuracy than conventional surgery. A variation on this approach is that of the Acrobot Company, UK, that utilises a pair of tracked arms to locate the position of tools relative to the patient, 13,14 (Fig. 5).…”

Section: Cas Navigation Systemsmentioning

confidence: 99%

Robotic surgery: from autonomous systems to intelligent tools

Baena

Davies

2009

Robotica

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A brief history of robotic surgery is provided, which describes the transition from autonomous robots to hands-on systems that are under the direct control of the surgeon. An example of the latter is the Acrobot (for active-constraint robot) system used in orthopaedics, whilst soft-tissue surgery is illustrated by the daVinci telemanipulator system. Non-technological aspects of robotic surgery have often been a major impediment to their widespread clinical use. These are discussed in detail, together with the role of navigation systems, which are considered a major competitor to surgical robots. A detailed description is then given of a registration method for robots to achieve improved accuracy. Registration is a major source of error in robotic surgery, particularly in orthopaedics. The paper describes the design and clinical implementation of a novel method, coined the bounded registration method, applied to minimally invasive registration of the femur. Results of simulations which compare the performance of bounded registration with a standard implementation of the iterative closest point algorithm are also presented, alongside a description of their application in the Acrobot hands-on robot, used clinically for uni-condylar knee arthroplasty.

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Preoperative planning and intraoperative guidance for accurate computer-assisted minimally invasive hip resurfacing surgery

Cited by 16 publications

References 18 publications

Imageless computer navigation for placement of the femoral component in resurfacing arthroplasty of the hip

Imageless computer navigation for placement of the femoral component in resurfacing arthroplasty of the hip

Automated Method for Computing the Morphological and Clinical Parameters of the Proximal Femur Using Heuristic Modeling Techniques

Robotic surgery: from autonomous systems to intelligent tools

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