TY - JOUR
T1 - Quantitative assessment of the maxillary sinusitis using computed tomography texture analysis
T2 - odontogenic vs non-odontogenic etiology
AU - Ito, Kotaro
AU - Kondo, Takumi
AU - Andreu-Arasa, V. Carlota
AU - Li, Baojun
AU - Hirahara, Naohisa
AU - Muraoka, Hirotaka
AU - Sakai, Osamu
AU - Kaneda, Takashi
N1 - Publisher Copyright:
© 2021, The Author(s), under exclusive licence to Japanese Society for Oral and Maxillofacial Radiology and Springer Nature Singapore Pte Ltd.
PY - 2022/7
Y1 - 2022/7
N2 - Objectives: The purpose of this study was to investigate computed tomography (CT) texture features of mucosal thickening of maxillary sinus mucosa to differentiate odontogenic maxillary sinusitis (OMS) from non-odontogenic maxillary sinusitis (NOMS). Methods: Eighteen OMS patients and age- and gender-matched 18 NOMS patients who underwent sinus CT were retrospectively reviewed. OMS patients were identified by histopathological examination of tissues excised at surgery combined with CT imaging findings. Patients with mucosal thickening in the maxillary sinus without apical periodontitis or advanced periodontal bone loss near the maxillary sinus on CT were defined as NOMS. Patients with thin mucosal thickening (< 10 mm), cyst, tumor, post-operative deformity, severe metal artifact precluding visualization of the maxillary sinus, and age younger than 20 years were excluded. CT texture features of the mucosal thickening were analyzed using an in-house developed Matlab-based texture analysis program. Forty-five texture features were extracted from each segmented volume. The results were tested with the Mann–Whitney U test. Results: Six histogram features (mean, median, standard deviation, entropy, geometric mean, harmonic mean) and two gray-level co-occurrence matrix features (entropy, correlation) showed significant differences between OMS and NOMS patients. Conclusions: CT texture analysis revealed the quantitative differences between OMS and NOMS. The texture features can serve as a quantitative indicator of maxillary sinusitis to differentiate between OMS and NOMS and help prevent incorrect treatment choices.
AB - Objectives: The purpose of this study was to investigate computed tomography (CT) texture features of mucosal thickening of maxillary sinus mucosa to differentiate odontogenic maxillary sinusitis (OMS) from non-odontogenic maxillary sinusitis (NOMS). Methods: Eighteen OMS patients and age- and gender-matched 18 NOMS patients who underwent sinus CT were retrospectively reviewed. OMS patients were identified by histopathological examination of tissues excised at surgery combined with CT imaging findings. Patients with mucosal thickening in the maxillary sinus without apical periodontitis or advanced periodontal bone loss near the maxillary sinus on CT were defined as NOMS. Patients with thin mucosal thickening (< 10 mm), cyst, tumor, post-operative deformity, severe metal artifact precluding visualization of the maxillary sinus, and age younger than 20 years were excluded. CT texture features of the mucosal thickening were analyzed using an in-house developed Matlab-based texture analysis program. Forty-five texture features were extracted from each segmented volume. The results were tested with the Mann–Whitney U test. Results: Six histogram features (mean, median, standard deviation, entropy, geometric mean, harmonic mean) and two gray-level co-occurrence matrix features (entropy, correlation) showed significant differences between OMS and NOMS patients. Conclusions: CT texture analysis revealed the quantitative differences between OMS and NOMS. The texture features can serve as a quantitative indicator of maxillary sinusitis to differentiate between OMS and NOMS and help prevent incorrect treatment choices.
KW - Computed tomography
KW - Maxillary sinus
KW - Maxillary sinusitis
KW - Odontogenic maxillary sinusitis
UR - http://www.scopus.com/inward/record.url?scp=85111520773&partnerID=8YFLogxK
U2 - 10.1007/s11282-021-00558-y
DO - 10.1007/s11282-021-00558-y
M3 - Article
C2 - 34327595
AN - SCOPUS:85111520773
SN - 0911-6028
VL - 38
SP - 315
EP - 324
JO - Oral Radiology
JF - Oral Radiology
IS - 3
ER -