Dr. Osamu Sakai, Dr. Carlota Andreu-Arasa, Dr. Baojun Li and Resident Dr. Pedro Staziaki Published in the European Journal of Radiology

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Using CT texture analysis to differentiate cystic and cystic-appearing odontogenic lesions

Masafumi Oda 1, Pedro V Staziaki 2, Muhammad M Qureshi 3, V Carlota Andreu-Arasa 2, Baojun Li 2, Koji Takumi 4, Margaret N Chapman 2, Albert Wang 2, Andrew R Salama 5, Osamu Sakai 6

Abstract

Purpose: Cystic and cystic-appearing odontogenic lesions of the jaw may appear similar on CT imaging. Accurate diagnosis is of

ten difficult although the relationship of the lesion to the tooth root or crown may offer a clue to the etiology. The purpose of this study was to evaluate CT texture analysis as an aid in differentiating cystic and cystic-appearing odontogenic lesions of the jaw.

Methods: This was an IRB-approved retrospective study including 42 pathology-proven dentigerous cysts, 37 odontogenic keratocysts, and 19 ameloblastomas. Each lesion was manually segmented on axial CT images, and textural features were analyzed using an in-house-developed Matlab-based texture analysis program that extracted 47 texture features from each segmented volume. Statistical analysis was performed comparing all pairs of the three types of lesions.

Results: Pairwise analysis revealed that nine histogram features, one GLCM feature, three GLRL features, two Laws features, four GLGM features and two Chi-square features showed significant differences between dentigerous cysts and odontogenic keratocysts. Four histogram features and one Chi-square feature showed significant differences between odontogenic keratocysts and ameloblastomas. Two histogram features showed significant differences between dentigerous cysts and ameloblastomas.

Conclusions: CT texture analysis may be useful as a noninvasive method to obtain additional quantitative information to differentiate cystic and cystic-appearing odontogenic lesions of the jaw.

Keywords
Ameloblastomas; CT; Dentigerous cysts; Jaw lesions; Odontogenic keratocysts; Texture analysis.

PMID: 31539792

DOI: 10.1016/j.ejrad.2019.108654
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