Advertisement for orthosearch.org.uk
Results 1 - 2 of 2
Results per page:
Bone & Joint Open
Vol. 2, Issue 10 | Pages 834 - 841
11 Oct 2021
O'Connor PB Thompson MT Esposito CI Poli N McGree J Donnelly T Donnelly W

Aims

Pelvic tilt (PT) can significantly change the functional orientation of the acetabular component and may differ markedly between patients undergoing total hip arthroplasty (THA). Patients with stiff spines who have little change in PT are considered at high risk for instability following THA. Femoral component position also contributes to the limits of impingement-free range of motion (ROM), but has been less studied. Little is known about the impact of combined anteversion on risk of impingement with changing pelvic position.

Methods

We used a virtual hip ROM (vROM) tool to investigate whether there is an ideal functional combined anteversion for reduced risk of hip impingement. We collected PT information from functional lateral radiographs (standing and sitting) and a supine CT scan, which was then input into the vROM tool. We developed a novel vROM scoring system, considering both seated flexion and standing extension manoeuvres, to quantify whether hips had limited ROM and then correlated the vROM score to component position.


Orthopaedic Proceedings
Vol. 92-B, Issue SUPP_I | Pages 202 - 202
1 Mar 2010
Noble PC Schroder SJ Ellis AR Usrey MM Thompson MT Kamaric E Sugano N Stocks GW
Full Access

Introduction: With the development of powerful computing tools, it is now possible to quantify variations in skeletal morphology using standardized analytical protocols. In this presentation, we describe the development of computer-based tools to analyze components of femoral deformity in developmental hip dysplasia (DDH) and femoro-acetabular impingement (FAI).

Methods: Typically, three dimensional surface-splined computer models of bones are generated by reconstructing CT scan data. The models generated are then segmented into discrete objects (e.g. the femoral head, neck, shaft, condyles, sulcus, and apophyses) and a coordinate system is attached to each anatomic object to define its relative position and orientation in space. The size of each object can be described by characteristic parameters (eg height, length, width), and its shape with dimensionless ratios (eg width/length). Other methods include principal component analysis which expresses te principal sources of statistical variation in object dimensions, and correspondence analysis, which describes the variation of each point on the surface of a bone compared to the average specimen in the observed population.

Illustrative Applications:

DDH

These methods have been applied to examine systematic variations in the shape and dimensions of the dysplastic femur through reference to data from 171 dysplastic and 84 skeletally normal patients. Of the 171 dysplastic femora, 74 (43%) were graded as Crowe I, 82 (48%) as Crowe stages II or III, and 15 (9%) as Crowe IV. The change in femoral morphology was quantified as a function of the grade of deformity in comparison with normal controls. The principal sources of deformity were also identified.

FAI

We examined the hypothesis that the femur of patients with femoro-acetbular impingement has multiple morphologic characteristics leading to reduced range of motion. Sixty-six cadaveric femora (30 male and 36 female, average age: 76 years) were selected from a large osteologic collection. Thirteen femora were morphologically normal and 53 were abnormal. Standard morphologic parameters were calculated and normalized with respect to the femoral head diameter. Additional parameters were determined to quantify the head/neck relationship. These included the I angle, the. angle, the anterior offset ratio (OSR), the anterior head-neck ratio, the posterior ‘slip’ of the femoral head, the neck shaft angle and the femoral neck anteversion.

Results: The results of these analyses will be presented during the lecture.

Conclusions: Mathematical analysis of the shape of bones allows us to describe the type and severity of skeletal deformities in precise quantitative terms. This leads to new, three-dimensional definitions of skeletal phenotypes, and allows automated screening and classification of imaging data sets for the detection of dysmorphic conditions. This approach also has the potential to provide new insights into the true nature of complex deformities presenting for orthopedic treatment.