Validation of a novel technique for creating simulated radiographs using computed tomography datasets

Understanding radiographic anatomy and the effects of varying patient and radiographic tube positioning on image quality can be a challenge for students. The purposes of this study were to develop and validate a novel technique for creating simulated radiographs using computed tomography (CT) datasets. A DICOM viewer (ORS Visual) plug-in was developed with the ability to move and deform cuboidal volumetric CT datasets, and to produce images simulating the effects of tube-patient-detector distance and angulation. Computed tomographic datasets were acquired from two dogs, one cat, and one horse. Simulated radiographs of different body parts (n = 9) were produced using different angles to mimic conventional projections, before actual digital radiographs were obtained using the same projections. These studies (n = 18) were then submitted to 10 board-certified radiologists who were asked to score visualization of anatomical landmarks, depiction of patient positioning, realism of distortion/magnification, and image quality. No significant differences between simulated and actual radiographs were found for anatomic structure visualization and patient positioning in the majority of body parts. For the assessment of radiographic realism, no significant differences were found between simulated and digital radiographs for canine pelvis, equine tarsus, and feline abdomen body parts. Overall, image quality and contrast resolution of simulated radiographs were considered satisfactory. Findings from the current study indicated that radiographs simulated using this new technique are comparable to actual digital radiographs. Further studies are needed to apply this technique in developing interactive tools for teaching radiographic anatomy and the effects of varying patient and tube positioning.