An investigation of Saudi Arabian MR radiographers' knowledge and confidence in relation to MR image-quality-related errors. Issue 2 (May 2017) - Alsharif, W.; Davis, M.; McGee, A.; Rainford, L.
Abstract: Objective: To investigate MR radiographers' current knowledge base and confidence level in relation to quality-related errors within MR images. Method: Thirty-five MR radiographers within 16 MRI departments in the Kingdom of Saudi Arabia (KSA) independently reviewed a prepared set of 25 MR images, naming the error, specifying the error-correction strategy, scoring how confident they were in recognising this error and suggesting a correction strategy by using a scale of 1–100. The datasets were obtained from MRI departments in the KSA to represent the range of images which depicted excellent, acceptable and poor image quality. Results: The findings demonstrated a low level of radiographer knowledge in identifying the type of quality errors and when suggesting an appropriate strategy to rectify those errors. The findings show that only (n = 7) 20% of the radiographers could correctly name what the quality errors were in 70% of the dataset, and none of the radiographers correctly specified the error-correction strategy in more than 68% of the MR datasets. The confidence level of radiography participants in their ability to state the type of image quality errors was significantly different (p < 0.001) for who work in different hospital types. Conclusion: The findings of this study suggest there is a need to establish a national association for MR radiographers to monitor training and the development of postgraduate MRI education in Saudi Arabia to improve the current status of the MR radiographers' knowledge and direct high quality service delivery. Highlights: MR radiographers recognised the existence of the image quality related errors. A few MR radiographers were able to correctly identify which image quality errors were being shown. None of MR radiographers were able to correctly specify error-correction strategy of the image quality errors. A low level of knowledge was demonstrated in identifying and rectify image quality errors.