Quantitative measurements of the volume and surface area of the radial head.
OBJECTIVE
We investigated the hypothesis that a quantitative 3-dimensional computed tomography (Q3DCT) modeling technique based on anatomical and demographic data that can measure size, shape, and proximal articular surface area can be used to develop formulas that could predict the volume and proximal surface area of the intact radial head in patients with fractures of the radial head.


METHODS
We used a consecutive series of 50 computed tomography scans with a slice thickness of 1.25 mm or less obtained in patients with fracture of the distal humerus, but no injury to the radial head, to create 3-dimensional models. The volume and proximal articular surface area of the radial head were measured, and predictive formulas based on anatomical measurements and gender were calculated using multiple linear regression.


RESULTS
There were significant correlations between total radial head volume and proximal radial head articular surface area for height, weight, radial head diameter, radial neck diameter, coronoid diameter, and gender. Multiple linear regression modeling resulted in formulas that could account for 89% of the variation in radial head volume and 75% of the variation in proximal articular surface area.


CONCLUSIONS
The volume and proximal articular surface area of the radial head can be estimated based on anatomical measurements and gender. This may lead to better estimates of lost fragments when it is not possible to directly model the fractured radial head and computed tomography scan of the opposite limb is not available.
Guitton
Thierry G
TG
Orthopaedic Hand and Upper Extremity Service, Harvard Medical School, Massachusetts General Hospital, Boston, MA 02114, USA.
van der Werf
Huub J
HJ
Ring
David
D
D000328:Adult; D000368:Aged; D000369:Aged, 80 and over; D000704:Analysis of Variance; D002648:Child; D006801:Humans; D006810:Humeral Fractures / Q000000981:diagnostic imaging*; D021621:Imaging, Three-Dimensional; D007223:Infant; D016014:Linear Models; D008875:Middle Aged; D011857:Radiographic Image Interpretation, Computer-Assisted; D011884:Radius / Q000000981:diagnostic imaging*; D012737:Sex Factors; D018709:Statistics, Nonparametric; D014057:Tomography, X-Ray Computed