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

ObjectiveThis 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 methodsCT 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.ResultsA 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.ConclusionThe 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.     

Using Reference Databases of Genetic Variation to Evaluate the Potential Pathogenicity of Candidate Disease Variants

The potential pathogenicity of genetic variants identified in disease‐based resequencing studies is often overlooked where variants have previously been reported in dbSNP, the 1000 genomes project, or the National Heart, Lung and Blood Institute Exome Sequencing Project (ESP). In this work, we estimate that collectively, these databases capture ～52% of mutations (dbSNP 50.4%; 1000 genomes 4.8%; and ESP 10.2%) reported as disease causing within phenotype‐based locus‐specific databases (LSDBs). To investigate whether these mutations may simply represent benign population variants, we evaluated whether the carrier frequencies associated with mutations implicated in amyotrophic lateral sclerosis were higher than what could be accounted for by high‐penetrance disease models. In doing so, we have questioned the veracity of 51 mutations, but also demonstrated that each of the three databases included credible disease variants. Our results demonstrate the benefits of using databases such as dbSNP, the 1000 genomes project, and the ESP to evaluate the pathogenicity of putative disease variants, and suggest that many disease mutations reported across LSDBs may not actually be pathogenic. However, they also demonstrate that even in the context of rare Mendelian disorders, the potential pathogenicity of variants reported by these databases should not be overlooked without proper evaluation.