Prediction of surface area size in orbital floor and medial orbital wall fractures based on topographical subregions.

OBJECTIVE

This retrospective study evaluates the occurrence and frequency of different fracture patterns in a series of computed tomography (CT) scans in terms of the AOCMF Trauma Classification (TC) orbit module and correlates the assigned defects with measurements of the fracture area in order to get an approximate guideline for fracture size predictions on the basis of the classification.

MATERIAL AND

METHODS

CT scans of patients with orbital floor fractures were evaluated using the AOCMFTC to determine the topographical subregions. The coding consisted of: W = orbital wall, 1 = anterior orbit, 2 = midorbit, i = inferior, m = medial. The 3-dimensional surface area size of the fractures was quantified by the "defect body" method (Brainlab, Munich, Germany). The fracture area size and its confidence and prediction interval within each topographical subregion was estimated by regression analysis.

RESULTS

A total of 137 CT scans exhibited 145 orbital floor fractures, which were combined with 34 medial orbital wall fractures in 31 patients. The floor fractures - W1(i)2(i) (n = 86) and W1(i) (n = 19) were the most frequent patterns. Combined floor and medial wall fractures most frequently corresponded to the pattern W1 (im)2 (im) (n = 15) ahead of W1 (im) 2(i) (n = 10). The surface area size ranged from 0.11 cm2 to 6.09 cm2 for orbital floor and from 0.29 cm2 to 5.43 cm2 for medial wall fractures. The prediction values of the mean fracture area size within the subregions were computed as follows: W1(i) = 2.25 cm2, W2(i) = 1.64 cm2, W1(i)2(i) = 3.10 cm2, W1(m) = 1.36 cm2, W2(m) = 1.65 cm2, W1(m)2(m) = 2.98 cm2, W1 (im) = 3.35 cm2, W1 (im) 2(i) = 4.63 cm2, W1 (im)2(m) = 4.06 cm2 and W1 (im)2 (im) = 7.16 cm2.

CONCLUSION

The AOCMFTC orbital module offers a suitable framework for topographical allocation of fracture patterns inside the infero-medial orbital cavity. The involvement of the subregions is of predictive value providing estimations of the mean 3-D fracture area size.