Objective: To determine the correlation between dentoskeletal parameters related to craniofacial morphology and the upper airway (UA) volume. Methods: Cone-beam computed tomography images of 106 randomly selected orthodontic patients were analyzed using NemoFab Ortho software. The dentoskeletal variables assessed were anterior facial height (AFH), posterior facial height (PFH), PFH/AFH ratio, hyoid position, maxillary width (MW), and palatal depth. The UA volume (evaluation in anatomical regions and as a whole) was also assessed using the same software. We also evaluated potential differences in UA variables between age and sex groups. The correlation between the dentoskeletal parameters and UA volume was calculated using the Pearson correlation coefficient (R). Analysis of variance and Student’s t test were performed to assess differences between age and sex for UA variables. Statistical analyses were performed using SPSS software (version 26 for Windows). Results: This study found that PFH, AFH, and MW were the dentoskeletal parameters most strongly correlated with UA volume. However, the ANB angle did not show any significant correlation with UA volume. Additionally, differences in UA volumes were observed between age groups. Sex differences were found in both the “8–12” and “≥ 16” age groups for oropharyngeal and pharyngeal volumes. Conclusions In conclusion, our findings indicate a significant correlation between UA volume and dentoskeletal parameters, particularly those related to facial height and MW.

Objective: To determine the correlation between dentoskeletal parameters related to craniofacial morphology and the upper airway (UA) volume. Methods: Cone-beam computed tomography images of 106 randomly selected orthodontic patients were analyzed using NemoFab Ortho software. The dentoskeletal variables assessed were anterior facial height (AFH), posterior facial height (PFH), PFH/AFH ratio, hyoid position, maxillary width (MW), and palatal depth. The UA volume (evaluation in anatomical regions and as a whole) was also assessed using the same software. We also evaluated potential differences in UA variables between age and sex groups. The correlation between the dentoskeletal parameters and UA volume was calculated using the Pearson correlation coefficient (R). Analysis of variance and Student’s t test were performed to assess differences between age and sex for UA variables. Statistical analyses were performed using SPSS software (version 26 for Windows). Results: This study found that PFH, AFH, and MW were the dentoskeletal parameters most strongly correlated with UA volume. However, the ANB angle did not show any significant correlation with UA volume. Additionally, differences in UA volumes were observed between age groups. Sex differences were found in both the “8–12” and “≥ 16” age groups for oropharyngeal and pharyngeal volumes. Conclusions In conclusion, our findings indicate a significant correlation between UA volume and dentoskeletal parameters, particularly those related to facial height and MW.

Objective: To determine the correlation between dentoskeletal parameters related to craniofacial morphology and the upper airway (UA) volume. Methods: Cone-beam computed tomography images of 106 randomly selected orthodontic patients were analyzed using NemoFab Ortho software. The dentoskeletal variables assessed were anterior facial height (AFH), posterior facial height (PFH), PFH/AFH ratio, hyoid position, maxillary width (MW), and palatal depth. The UA volume (evaluation in anatomical regions and as a whole) was also assessed using the same software. We also evaluated potential differences in UA variables between age and sex groups. The correlation between the dentoskeletal parameters and UA volume was calculated using the Pearson correlation coefficient (R). Analysis of variance and Student’s t test were performed to assess differences between age and sex for UA variables. Statistical analyses were performed using SPSS software (version 26 for Windows). Results: This study found that PFH, AFH, and MW were the dentoskeletal parameters most strongly correlated with UA volume. However, the ANB angle did not show any significant correlation with UA volume. Additionally, differences in UA volumes were observed between age groups. Sex differences were found in both the “8–12” and “≥ 16” age groups for oropharyngeal and pharyngeal volumes. Conclusions In conclusion, our findings indicate a significant correlation between UA volume and dentoskeletal parameters, particularly those related to facial height and MW.

Objective: To determine the correlation between dentoskeletal parameters related to craniofacial morphology and the upper airway (UA) volume. Methods: Cone-beam computed tomography images of 106 randomly selected orthodontic patients were analyzed using NemoFab Ortho software. The dentoskeletal variables assessed were anterior facial height (AFH), posterior facial height (PFH), PFH/AFH ratio, hyoid position, maxillary width (MW), and palatal depth. The UA volume (evaluation in anatomical regions and as a whole) was also assessed using the same software. We also evaluated potential differences in UA variables between age and sex groups. The correlation between the dentoskeletal parameters and UA volume was calculated using the Pearson correlation coefficient (R). Analysis of variance and Student’s t test were performed to assess differences between age and sex for UA variables. Statistical analyses were performed using SPSS software (version 26 for Windows). Results: This study found that PFH, AFH, and MW were the dentoskeletal parameters most strongly correlated with UA volume. However, the ANB angle did not show any significant correlation with UA volume. Additionally, differences in UA volumes were observed between age groups. Sex differences were found in both the “8–12” and “≥ 16” age groups for oropharyngeal and pharyngeal volumes. Conclusions In conclusion, our findings indicate a significant correlation between UA volume and dentoskeletal parameters, particularly those related to facial height and MW.

Objective: To determine the correlation between dentoskeletal parameters related to craniofacial morphology and the upper airway (UA) volume. Methods: Cone-beam computed tomography images of 106 randomly selected orthodontic patients were analyzed using NemoFab Ortho software. The dentoskeletal variables assessed were anterior facial height (AFH), posterior facial height (PFH), PFH/AFH ratio, hyoid position, maxillary width (MW), and palatal depth. The UA volume (evaluation in anatomical regions and as a whole) was also assessed using the same software. We also evaluated potential differences in UA variables between age and sex groups. The correlation between the dentoskeletal parameters and UA volume was calculated using the Pearson correlation coefficient (R). Analysis of variance and Student’s t test were performed to assess differences between age and sex for UA variables. Statistical analyses were performed using SPSS software (version 26 for Windows). Results: This study found that PFH, AFH, and MW were the dentoskeletal parameters most strongly correlated with UA volume. However, the ANB angle did not show any significant correlation with UA volume. Additionally, differences in UA volumes were observed between age groups. Sex differences were found in both the “8–12” and “≥ 16” age groups for oropharyngeal and pharyngeal volumes. Conclusions In conclusion, our findings indicate a significant correlation between UA volume and dentoskeletal parameters, particularly those related to facial height and MW.

Non-secretory multiple myeloma (NSMM) is a rare cancer of plasma cells characterized by the absence of detectable monoclonal M protein in the blood or urine. A 57-year-old woman presented with mandibular pain but without intraoral swelling. Imaging studies revealed multiple osteolytic lesions in her mandible and pronounced root resorption of the left mandibular second molar. Biopsy results showed atypical plasmacytoid cells positive for anti-kappa, CD138, MUM1, and CD79a antibodies, but negative for anti-lambda and CD20. These results were indicative of a malignant plasma cell neoplasm. No abnormalities were revealed by free light chain assay or by serum or urine protein electrophoresis, leading to a diagnosis of NSMM. The patient began chemotherapy in conjunction with bisphosphonate therapy and achieved remission following treatment. This case underscores the critical role of dentists in the early detection and prevention of NSMM complications, as the disease can initially present in the oral cavity.

Purpose: This study aimed to assess texture analysis (TA) of cone-beam computed tomography (CBCT) images as a quantitative tool for the differential diagnosis of odontogenic and non-odontogenic maxillary sinusitis (OS and NOS, respectively). Materials and Methods: CBCT images of 40 patients diagnosed with OS (N=20) and NOS (N=20) were evaluated. The gray level co-occurrence (GLCM) matrix parameters, and gray level run length matrix texture (GLRLM) parameters were extracted using manually placed regions of interest on lesion images. Seven texture parameters were calculated using GLCM and 4 parameters using GLRLM. The Mann-Whitney test was used for comparisons between the groups, and the Levene test was performed to confirm the homogeneity of variance (α=5%). Results: The results showed statistically significant differences (P<0.05) between the OS and NOS patients regarding 3 TA parameters. NOS patients presented higher values for contrast, while OS patients presented higher values for correlation and inverse difference moment. Greater textural homogeneity was observed in the OS patients than in the NOS patients, with statistically significant differences in standard deviations between the groups for correlation, sum of squares, sum of entropy, and entropy. Conclusion TA enabled quantitative differentiation between OS and NOS on CBCT images by using the parameters of contrast, correlation, and inverse difference moment.