Abstract
BACKGROUND: Accurate classification of acetabular fractures remains difficult. To aid in the classification of acetabular fractures and to aid in teaching, our department developed a diagnostic algorithm that involves the use of 1 standardized 3-dimensional reconstruction of a computed tomography (CT) scan (an exopelvic view without the femoral head) with 8 anatomical landmarks. The algorithm was integrated into a smartphone application (app). The main objective of this study was to test the efficacy of this algorithm and smartphone app. METHODS: Fourteen reviewers (3 experts, 3 fellows, 3 residents, and 5 novice reviewers) evaluated a set of 35 CT scans of acetabular fractures in 2 phases. During the first phase, the scans (including axial 2-dimensional views and 3-dimensional (3D) multiplanar reconstruction views) were assessed by each reviewer twice, with an interval of 4 weeks between the readings to decrease recall bias. During that phase, the reviewers were provided with a diagram of the Letournel classification system with no guidelines for interpretation. During the second phase, performed 4 weeks after the first phase, 1 standardized 3D reconstruction (an exopelvic view without the femoral head) was reviewed twice, with an interval of 4 weeks between the readings. During that phase, the reviewers used the smartphone app. The primary outcome was the accuracy of classification. Interobserver reliability, reading time, and time needed for accurate classification were noted. RESULTS: The accuracy of fracture classification was 64.5% when the standard method of analysis was used and 83.4% when the app was used (p < 0.001). Improvement was noted in all groups, with the expert group showing the least improvement (88.6% to 97.2%, p = 0.04) and the novice group showing the most improvement (42.0% to 75.5%, p < 0.001). Furthermore, use of the app greatly increased the accuracy of classification of complex fractures. The average reading time was 71.8 minutes when the standard method was used and 37.4 minutes when the app was used. The interobserver reliability improved in all groups to an excellent reliability (interclass correlation coefficient [ICC] > 0.79). CONCLUSIONS: The Letournel classification system is difficult to understand and to learn but remains the only system guiding the surgical strategy for acetabular fractures. The impact of diagnostic algorithms is debatable. The most important finding of the present study is the high accuracy for inexperienced groups when the app was used. Another important finding is the high reliability of this method for the diagnosis of complex acetabular fractures.