Panoramic Dental Reconstruction for Faster Detection of Dental Pathology on Medical Non-dental CT Scans: a Proof of Concept from CT Neck Soft Tissue

Even though teeth are often included in the field of view for a variety of medical CT studies, dental pathology is often missed by radiologists. Given the myriad morbidity and occasional mortality associated with sequelae of dental pathology, an important goal is to decrease these false negatives. However, given the ever-increasing volume of cases studies that radiologists have to read and the number of structures and diseases they have to evaluate, it is important not to place undue time restraints on the radiologist to this end. We hypothesized that generating panoramic dental radiographs from non-dental CT scans can permit identification of key diseases, while not adding much time to interpretation. The key advantage of panoramic dental radiographs is that they display the plane of the teeth in two dimensions, thereby facilitating fast and accurate assessment. We found that interpreting panoramic radiographic reconstructions compared to the full CT volumes reduced time-to-diagnosis of key dental pathology on average by roughly a factor of four. This expedition was statistically significant, and the average time-to-diagnosis for panoramic reconstructions was on the order of seconds, without a loss in accuracy compared to full CT. As such, we posit that panoramic reconstruction can serve as a one-slice additional series in any CT image stack that includes the teeth in its field of view.

[1]  I. Leichter,et al.  An artificial intelligence system using machine-learning for automatic detection and classification of dental restorations in panoramic radiography. , 2020, Oral surgery, oral medicine, oral pathology and oral radiology.

[2]  D. Fine,et al.  Classification and diagnosis of aggressive periodontitis , 2018, Journal of periodontology.

[3]  Joseph M Pappachan,et al.  Diabetes mellitus and oral health , 2015, Endocrine.

[4]  R. Flores-Ramírez,et al.  Periodontal Disease, Systemic Inflammation and the Risk of Cardiovascular Disease. , 2018, Heart, lung & circulation.

[5]  A. Katsumata,et al.  Evaluation of an artificial intelligence system for detecting vertical root fracture on panoramic radiography , 2019, Oral Radiology.

[6]  D. Michaud,et al.  Periodontal Disease, Tooth Loss, and Cancer Risk , 2017, Epidemiologic reviews.

[7]  A. Katsumata,et al.  A deep-learning artificial intelligence system for assessment of root morphology of the mandibular first molar on panoramic radiography. , 2019, Dento maxillo facial radiology.

[8]  A. Santarelli,et al.  Beyond Head and Neck Cancer: The Relationship Between Oral Microbiota and Tumour Development in Distant Organs , 2019, Front. Cell. Infect. Microbiol..

[9]  B. Mealey,et al.  Dental plaque–induced gingival conditions , 2018, Journal of periodontology.

[10]  P. Stanko,et al.  Bidirectional association between diabetes mellitus and inflammatory periodontal disease. A review. , 2014, Biomedical papers of the Medical Faculty of the University Palacky, Olomouc, Czechoslovakia.

[11]  T. Kaneda,et al.  Periapical lucency around the tooth: radiologic evaluation and differential diagnosis. , 2013, Radiographics : a review publication of the Radiological Society of North America, Inc.

[12]  S. Virani,et al.  Evaluating Periodontal Treatment to Prevent Cardiovascular Disease: Challenges and Possible Solutions , 2017, Current Atherosclerosis Reports.

[13]  I. Lamster,et al.  Periodontal disease and the metabolic syndrome. , 2017, International dental journal.

[14]  B. Griffith,et al.  Radiology Education in the 21st Century: Threats and Opportunities. , 2019, Journal of the American College of Radiology : JACR.

[15]  R. Jacobs,et al.  Artificial Intelligence (AI)-Driven Molar Angulation Measurements to Predict Third Molar Eruption on Panoramic Radiographs , 2020, International journal of environmental research and public health.

[16]  W. Mehan,et al.  Prevalence and Reporting Rates of Incidental Dental Disease on Head CT Examinations. , 2018, Academic radiology.

[17]  P. Ridker,et al.  Cardiovascular risks associated with incident and prevalent periodontal disease. , 2015, Journal of clinical periodontology.

[18]  B. Ferguson,et al.  Clinical aspects of odontogenic maxillary sinusitis: a case series , 2011, International forum of allergy & rhinology.

[19]  Tarek N. Hanna,et al.  After-Hours Radiology: Challenges and Strategies for the Radiologist. , 2015, AJR. American journal of roentgenology.

[20]  Reinhilde Jacobs,et al.  Artificial intelligence-driven novel tool for tooth detection and segmentation on panoramic radiographs , 2020, Clinical Oral Investigations.

[21]  C Matthew Hawkins,et al.  Diagnostic Radiology Resident and Fellow Workloads: A 12-Year Longitudinal Trend Analysis Using National Medicare Aggregate Claims Data. , 2015, Journal of the American College of Radiology : JACR.

[22]  J. Plemons,et al.  Non-plaque-induced gingival diseases. , 2018, Journal of periodontology.

[23]  A. Orekhov,et al.  Links between atherosclerotic and periodontal disease. , 2016, Experimental and molecular pathology.

[24]  B. Mealey,et al.  Dental plaque–induced gingival conditions , 2018, Journal of clinical periodontology.