Dento maxillo facial radiology · 2011
Imaging features contributing to the diagnosis of ameloblastomas and keratocystic odontogenic tumours: logistic regression analysis.
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Ariji Y, Morita M, Katsumata A, Sugita Y, Naitoh M, Goto M, Izumi M, Kise Y, Shimozato K, Kurita K, Maeda H, Ariji E
Аннотация
OBJECTIVE: The aim of this study was to clarify the characteristic imaging features that can be used to differentiate ameloblastomas from keratocystic odontogenic tumours and to examine the significant imaging features contributing to a correct diagnosis.
METHODS: 60 observers (39 specialists in oral and maxillofacial radiology and 21 non-specialists) examined CT and/or panoramic images of 10 ameloblastomas and 10 keratocystic odontogenic tumours shown on a webpage and made diagnoses. Their correct answer ratios were then calculated. The imaging features of the tumours were evaluated and expressed as binary numbers or quantitative values. The imaging features that contributed to a correct diagnosis were elucidated using logistic regression analysis.
RESULTS: The mean correct answer ratio was 61.3% ± 17.2% for the diagnosis of ameloblastomas and keratocystic odontogenic tumours. CT images produced higher correct answer ratios for diagnosis of keratocystic odontogenic tumours by specialists. The significantly different imaging features between ameloblastomas and keratocystic odontogenic tumours were the degree of bone expansion and the presence of high-density areas. The significant imaging features contributing to a correct imaging diagnosis were the number of locules, the presence of high-density areas and the inclusion of impacted teeth.
CONCLUSION: The presence of high-density areas is the most useful feature in the differential diagnosis of ameloblastomas and keratocystic odontogenic tumours based on comparison of the imaging features of both tumours and examination of the diagnostic contributions of these features.
METHODS: 60 observers (39 specialists in oral and maxillofacial radiology and 21 non-specialists) examined CT and/or panoramic images of 10 ameloblastomas and 10 keratocystic odontogenic tumours shown on a webpage and made diagnoses. Their correct answer ratios were then calculated. The imaging features of the tumours were evaluated and expressed as binary numbers or quantitative values. The imaging features that contributed to a correct diagnosis were elucidated using logistic regression analysis.
RESULTS: The mean correct answer ratio was 61.3% ± 17.2% for the diagnosis of ameloblastomas and keratocystic odontogenic tumours. CT images produced higher correct answer ratios for diagnosis of keratocystic odontogenic tumours by specialists. The significantly different imaging features between ameloblastomas and keratocystic odontogenic tumours were the degree of bone expansion and the presence of high-density areas. The significant imaging features contributing to a correct imaging diagnosis were the number of locules, the presence of high-density areas and the inclusion of impacted teeth.
CONCLUSION: The presence of high-density areas is the most useful feature in the differential diagnosis of ameloblastomas and keratocystic odontogenic tumours based on comparison of the imaging features of both tumours and examination of the diagnostic contributions of these features.