Efficacy of 3D Printed Models on Resident Learning and Understanding of Common Acetabular Fracturers.

RATIONALE AND OBJECTIVES: The conceptualization of acetabular fractures can present a daunting challenge to radiology residents. 3D models have been shown to aid in the spatial perception of complicated anatomy and may help residents grasp the elaborate classification systems for these anatomically complex fractures. Prior studies have explored the utility of 3D printed models for surgical planning in various settings. To our knowledge, no study has evaluated their efficacy in radiology resident training. MATERIALS AND METHODS: Following IRB approval, 22 radiology residents were randomized and stratified by Post Graduate Year into two groups of 11 residents. Both groups received separate identical presentations on the 5 most common acetabular fractures given by a musculoskeletal trained radiologist. Residents in the experimental group received 3D printed models of the five most common fracture types with which to interact during the presentation, while the control group did not. Both groups received a pretest and a follow up posttest three weeks later. RESULTS: A Wilcoxon rank sum test was performed to determine if statistically significant differences between the pretest and posttest scores of the experimental and control groups existed. There was no statistically significant difference in scores on the pre-test, which confirmed successful randomization. There was a statistically significant difference (P = 0.02) on the posttest scores between the experimental and control groups. CONCLUSION: 3D printed models promise as an effective educational tool for resident learning with respect to acetabular fractures, improving short-term understanding of complex anatomy and classification systems.

Identifying risk factors in renal allografts before transplant: machine-measured renal resistance and posttransplant allograft survival.

Enhancement of renal allograft function and survival in an era where expanded criteria donors are increasingly used requires validated selection criteria. The goal of this retrospective study was to evaluate the significance of pretransplant donor and allograft parameters to identify risk factors that can be used in a model to predict 1-year allograft outcomes. Donor demographic factors, donor type, and allograft parameters such as biopsy results and machine-measured renal resistance were correlated with 1-year graft outcome. The Kaplan-Meier method was used to estimate graft survival using the categorical predictors of donor type, donor age, and machine measured renal resistance at 1.5, 3, and 5 hours. The log-rank test was used to test the difference in survival curves between cohorts. The Cox regression analysis was used to estimate hazard ratios for machine-measured renal resistance, donor age, donor terminal creatinine level, donor's estimated glomerular filtration rate, cold ischemia time, and percent glomerulosclerosis. The data show that machine-measured renal resistance at 3 and 5 hours has a statistically significant inverse relationship to 1-year graft survival. All other risk factors had no correlation with 1-year graft survival. The machine-measured renal resistance at 3 hours is the earliest significant predictor of 1-year allograft outcome.