An understanding of anatomic variability can help guide the surgeon on intervention strategies. Well-functioning thumb metacarpophalangeal joints (MCPJ) are essential for carrying out typical daily activities. However, current options for arthroplasty are limited. This is further hindered by the lack of a precise understanding of the geometric variation present in the population. In this paper, we offer new insight into the major modes of geometric variation in the thumb MCP using Statistical Shape Modelling. Ten participants free from hand or wrist disease or injury were recruited for CT imaging (Ethics Ref:14/LO/1059)1. Participants were sex matched with mean age 31yrs (range 27–37yrs). Metacarpal (MC1) and proximal phalanx (PP1) bone surfaces were identified in the CT volumes using a greyscale threshold, and meshed. The ten MC1 and ten PP1 segmented bones were aligned by estimating their principal axes using Principal Component Analysis (PCA), and registration was performed to enable statistical comparison of the position of each mesh vertex. PCA was then used again, to reduce the dimensionality of the data by identifying the main ‘modes’ of independent size and shape variation (principal components, PCs) present in the population. Once the PCs were identified, the variation described by each PC was explored by inspecting the shape change at two standard deviations either side of the mean bone shape.Introduction
Methods
