Using CT texture analysis to differentiate cystic and cystic-appearing odontogenic lesions. Issue 120 (November 2019)

• Record Type: Journal Article
• Authors: Oda, Masafumi; Staziaki, Pedro V.; Qureshi, Muhammad M.; Andreu-Arasa, V. Carlota; Li, Baojun; Takumi, Koji; Chapman, Margaret N.; Wang, Albert; Salama, Andrew R.; Sakai, Osamu
• Is Part Of: European journal of radiology. Issue 120(2019)
• Publication Date: 2019-11
• Subjects: AM ameloblastoma -- DC dentigerous cyst -- OKC odontogenic keratocyst -- GLCM gray-level co-occurrence matrix -- GLN gray-level nonuniformity -- GLRL gray-level run-length -- HR hazard ratio -- HU hounsfield units -- RLN run-length nonuniformity -- SRE short-run emphasis -- SRLGE short-run low gray-level emphasis; CT -- Texture analysis -- Jaw lesions -- Dentigerous cysts -- Odontogenic keratocysts -- Ameloblastomas; Medical radiology -- Periodicals; Radiology -- Periodicals; Radiologie médicale -- Périodiques; Medical radiology; Periodicals; 616.075705
• DOI: 10.1016/j.ejrad.2019.108654
• Languages: English
• ISSNs: 0720-048X

Abstract

Highlights: Several texture features demonstrated differences between dentigerous cysts and odontogenic keratocysts. Several texture features demonstrated differences between odontogenic keratocysts and ameloblastomas. Several texture features demonstrated differences between dentigerous cysts and ameloblastomas. Texture analysis provides quantitative information to differentiate cystic odontogenic lesions. Abstract: Purpose: Cystic and cystic-appearing odontogenic lesions of the jaw may appear similar on CT imaging. Accurate diagnosis is often 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.