Dual Energy X-ray Absorptiometry: Radiographer'S Role in Assessing Fracture Risk Assessment Tool (FRAX) Questionnaire Variables

Background: The FRAX (R) algorithm is a tool used to calculate the 10-year probability of fracture in patients with osteoporosis and is based the assessment of several risk factors. We assessed the performance and accuracy of the completion of the FRAX (R) anamnestic questionnaire by the radiographer without impact on the clinical workflow.Methodology: We evaluated the accuracy of fracture risk calculation by the radiographer using the FRAX (R) algorithm before and after specific training. A total of 100 women were enrolled in the study. The radiographer preliminarily administered the FRAX (R) questionnaire to all subjects before the execution of the DXA examination. After the end of the examination, a radiologist administered the questionnaire to the patient. Women were divided into two groups: group A (pre-training) and group B (post-training). The radiographer in group A completed the FRAX (R) questionnaire for the patients before training. For group B, the same radiographer completed the FRAX (R) questionnaire after training. The results of the FRAX (R) questionnaire completed by radiographer were compared with that completed by the referring physician.Results: Before training, radiographer's accuracy ranged from 92% (question 7, alcohol consumption) to 36% (question 6, secondary osteoporosis). After training, accuracy values improved substantially, ranging from 100% to 92%. Analysis of the absolute values of FRAX (R) showed that in the pre-training group data tended to be overestimated by the radiographer, with both major and fractures probabilities being significantly higher when assessed by the radiographer (12% and 5.8%, respectively). After the training, there was a marked decrease in the variation between the FRAX (R) data calculated by the radiographer and the radiologist.Conclusions: The accuracy of fracture risk calculation by the radiographer using the FRAX (R) algorithm is significantly improved after a specific training period. This study demonstrates the importance of dedicated training radiographers on the FRAX (R) algorithm.