Computed tomography texture analysis of mandibular condylar bone marrow in diabetes mellitus patients

Objectives Diabetes mellitus (DM) is associated with a broad range of complications, such as retinopathy, nephropathy, neuropathy, and cardiovascular disease. Therefore, predicting DM from head and neck images is a challenge for clinicians. The purpose of this study was to assess the mandibular cond...

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Bibliographic Details
Published in:Oral radiology 2021-10, Vol.37 (4), p.693-699
Main Authors: Ito, Kotaro, Muraoka, Hirotaka, Hirahara, Naohisa, Sawada, Eri, Okada, Shunya, Kaneda, Takashi
Format: Article
Language:English
Subjects:
Bisphosphonates
Bone marrow
Cardiovascular diseases
Computed tomography
Dentistry
Diabetes
Diabetes mellitus
Diabetic neuropathy
Head and neck
Imaging
Mandible
Medicine
Nephropathy
Oral and Maxillofacial Surgery
Original Article
Osteoarthritis
Radiology
Retinopathy
Statistical analysis
Temporomandibular joint
Tomography
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Summary:Objectives Diabetes mellitus (DM) is associated with a broad range of complications, such as retinopathy, nephropathy, neuropathy, and cardiovascular disease. Therefore, predicting DM from head and neck images is a challenge for clinicians. The purpose of this study was to assess the mandibular condylar bone marrow in DM patients using computed tomography (CT) texture analysis. Methods This retrospective study included 16 DM and age and sex matched 16 control patients (11 men, 5 women; mean age, 56.8 ± 14.4 years; range 31–78 years). Patients with Type I DM, prior history of taking bisphosphonates, osteoarthritis of the temporomandibular joint, and CT images with metal artifacts were excluded from this study. Bilateral mandibular condylar bone marrow was manually contoured on axial CT images. The presence or absence of DM is the primary predictor variable. Texture features of the region of interest was the outcome variable, that were analyzed using an open-access software, MaZda Ver.3.3. For each group, 20 features out of 279 parameters were selected with Fisher, probability of error and average correlation coefficient methods in MaZda. Bivariate statistics were computed with the Mann–Whitney U test and the P value was set at .05. Results One histogram feature, 15 Gy level co-occurrence matrix features, and four gray level run length matrix features showed differences between the DM patients and non-DM patients ( P  
ISSN:0911-6028
1613-9674
DOI:10.1007/s11282-021-00517-7