Mechanism-Based Classification and Quantitative Assessment of Panoramic Radiographic Artifacts

Background and Aim: Accurate identification of panoramicradiographic artifacts is essential for improving diagnosticreliability and reducing unnecessary repeat imaging. This studyaimed to classify panoramic radiographic artifacts by theirformation mechanisms and evaluate image quality using thecumulative artifact burden based on total artifact count.Materials and Methods: This retrospective study included 500panoramic radiographs. Images were classified into eight artifactcategories, and the cumulative artifact burden was calculated fromthe total artifact count. Inter-observer agreement was assessedusing Cohen’s kappa(κ), and reliability of the total artifact countusing the intraclass correlation coefficient (ICC).Results: A total of 500 panoramic radiographs were evaluated. Atleast one artifact was identified in 92.0% of radiographs, whereasonly 8.0% were artifact-free. According to the predefined imagequality classification, 8.0% of radiographs were classified asexcellent, 62.6% as acceptable, and 29.4% as unacceptable.Air space–related soft tissue artifacts were the most frequentfindings, with improper tongue positioning observed in 43.6% ofimages. Transverse and vertical positioning artifacts were alsocommon, whereas motion artifacts were relatively infrequent(3.0%). Inter-observer agreement demonstrated substantial toalmost perfect reliability, with Cohen’s kappa values ranging from0.80 to 0.92 and excellent agreement for total artifact countassessment (ICC = 0.958).Conclusion: A mechanism-based classification combinedwith an artifact count–based burden assessment may providea structured approach for evaluating panoramic imagequality, although further validation is needed to determine itsrelationship with diagnostic acceptability.