Restoring the pre-morbid anatomy of the proximal humerus is a
goal of anatomical shoulder arthroplasty, but reliance is placed
on the surgeon’s experience and on anatomical estimations. The purpose
of this study was to present a novel method, ‘Statistical Shape
Modelling’, which accurately predicts the pre-morbid proximal humeral anatomy
and calculates the 3D geometric parameters needed to restore normal
anatomy in patients with severe degenerative osteoarthritis or a
fracture of the proximal humerus. From a database of 57 humeral CT scans 3D humeral reconstructions
were manually created. The reconstructions were used to construct
a statistical shape model (SSM), which was then tested on a second
set of 52 scans. For each humerus in the second set, 3D reconstructions
of four diaphyseal segments of varying lengths were created. These
reconstructions were chosen to mimic severe osteoarthritis, a fracture
of the surgical neck of the humerus and a proximal humeral fracture
with diaphyseal extension. The SSM was then applied to the diaphyseal
segments to see how well it predicted proximal morphology, using
the actual proximal humeral morphology for comparison.Aims
Materials and Methods
