Sex estimation using paranasal sinus discriminant analysis: a new approach via cone beam computerized tomography volume analysis

Wanzeler, Ana Márcia Viana; Alves-Júnior, Sérgio Melo; Ayres, Lucas de Brito; Prestes, Maria Carolina da Costa; Gomes, Jessica Teixeira; Tuji, Fabrício Mesquita

doi:10.1007/s00414-019-02100-6

Cited by 32 publications

(24 citation statements)

References 23 publications

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“…It provides important information for the analysis of pathologies, planning of treatment strategies [ 19 ], monitoring of disease progression, and even for individual identification purposes [ 20 ]. For example, Wanzeler et al determined the sex of subjects by analyzing their paranasal sinus volumes, achieving a high accuracy of 100% for 200 CT scans [ 21 ]. Significant differences in the frontal and maxillary sinus volumes according to gender were also reported [ 22 ].…”

Section: Discussionmentioning

confidence: 99%

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Semi-Supervised Deep Learning Semantic Segmentation for 3D Volumetric Computed Tomographic Scoring of Chronic Rhinosinusitis: Clinical Correlations and Comparison with Lund-Mackay Scoring

et al. 2022

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Background: The traditional Lund-Mackay score (TLMs) is unable to subgrade the volume of inflammatory disease. We aimed to propose an effective modification and calculated the volume-based modified LM score (VMLMs), which should correlate more strongly with clinical symptoms than the TLMs. Methods: Semi-supervised learning with pseudo-labels used for self-training was adopted to train our convolutional neural networks, with the algorithm including a combination of MobileNet, SENet, and ResNet. A total of 175 CT sets, with 50 participants that would undergo sinus surgery, were recruited. The Sinonasal Outcomes Test-22 (SNOT-22) was used to assess disease-specific symptoms before and after surgery. A 3D-projected view was created and VMLMs were calculated for further comparison. Results: Our methods showed a significant improvement both in sinus classification and segmentation as compared to state-of-the-art networks, with an average Dice coefficient of 91.57%, an MioU of 89.43%, and a pixel accuracy of 99.75%. The sinus volume exhibited sex dimorphism. There was a significant positive correlation between volume and height, but a trend toward a negative correlation between maxillary sinus and age. Subjects who underwent surgery had significantly greater TLMs (14.9 vs. 7.38) and VMLMs (11.65 vs. 4.34) than those who did not. ROC-AUC analyses showed that the VMLMs had excellent discrimination at classifying a high probability of postoperative improvement with SNOT-22 reduction. Conclusions: Our method is suitable for obtaining detailed information, excellent sinus boundary prediction, and differentiating the target from its surrounding structure. These findings demonstrate the promise of CT-based volumetric analysis of sinus mucosal inflammation.

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Section: Discussionmentioning

confidence: 99%

“…Sizes, shapes, and pneumatization types vary from one person to another, even between twins, which could contribute to radiologic identification. This is extremely valuable for forensic identification purposes [ 21 ].…”

Section: Discussionmentioning

confidence: 99%

Semi-Supervised Deep Learning Semantic Segmentation for 3D Volumetric Computed Tomographic Scoring of Chronic Rhinosinusitis: Clinical Correlations and Comparison with Lund-Mackay Scoring

et al. 2022

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“…Several studies have attempted to predict age and gender using MS and SS volumes of patients of various populations. [1][2][3][4][5][6]9 Previous studies have utilized two-dimensional imaging techniques to determine the applicability of paranasal sinuses to determine gender and age. Luo et al 11 explored gender determination by estimating the area of the frontal sinus on lateral cephalograms of 475 patients and found that, when combined, the parameters of the frontal sinus index and area predicted gender in 76.6% of the cases.…”

Section: Discussionmentioning

confidence: 99%

“…Several studies have reported the usefulness of the paranasal sinuses in gender determination, particularly in postmortem examinations. 3,5,6 Other studies, however, have argued that the paranasal sinuses do not possess a dimorphic character. [7][8][9] Thus, no clear consensus exists in this regard.…”

Section: Introductionmentioning

confidence: 99%

Are Maxillary and Sphenoid Sinus Volumes Predictors of Gender and Age? A Cone Beam Computed Tomography Study

Koç

2020

Cumhuriyet Dental Journal

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This study aimed to analyze the applicability of maxillary sinus (MS) and sphenoid sinus (SS) volumes in determining gender and age. Materials and Methods:This retrospective study included cone beam computed tomography images of 164 MSs and 164 SSs of 82 patients (40 females and 42 males). Right, left, and total MS and SS volumes were estimated. The independent samples t-test, logistic regression, and Pearson correlation coefficient were used to explore their accuracy in determining age and gender.Results: Males had greater right SS, average, and total SS volumes than females (p=0.007, p=0.013, and p=0.013, respectively). The right SS volume had the best predictive power (65.9%) for gender. A regression formula using this parameter alone showed satisfactory accuracy. No significant correlations were found between age and MS or SS volumes (p>0.05). Conclusions:The SS volume is a valuable tool in determining gender, whereas neither MS nor SS are reliable predictors of age. A simple gender determination is possible with our regression formula using the right SS volume. Further studies are needed to investigate the role of paranasal sinus volumes with a view to develop formulations in determining age and gender in different populations.

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“…The use of CT with linear and volumetric measurements of the frontal sinus in the three anatomical planes led to an accuracy of 66.5% in estimating sex in the Brazilian population [ 68 ]. Cone-beam computed tomography (CBCT) resulted in 80% accuracy in sexual diagnosis using the frontal sinus [ 69 ] and 92%–96% when the frontal sinuses were evaluated together with the maxillary and sphenoid sinuses [ 70 ]. The simultaneous use of the external frontal bone surface coupled with the frontal sinus surface and volume in virtual 3 D models from CT images resulted in 98.05% accuracy in estimating sex in the population of the Czech Republic, reaching 84.46% accuracy after cross-validation [ 13 ].…”

Section: Sex Estimationmentioning

confidence: 99%

Contributions of anatomy to forensic sex estimation: focus on head and neck bones

Mello-Gentil

Souza-Mello

2021

Forensic Sciences Research

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This study sought to provide an up-to-date review of the importance of anatomy to human identification, focusing on the usefulness of anatomical knowledge about the head and neck bones and teeth to sex estimation in routine forensic anthropology methods. A detailed search of osteology applications in forensic sex estimation was conducted through the electronic databases for the 10 years prior to July 2020. Relevant articles and classic literature on the subject were gathered and are outlined in this review. Among the available literature, several metric analyses showed accuracy superior to 80% in sexual diagnosis. Angles measured from the inclination of glabellae and analysis of the external frontal bone surface through three-dimensional computer-aided design emerge as reliable cranial indexes for sex estimation. in the mandible, the condylar and coronoid height, bigonial width, and coronion-gonion distance express significant sexual dimorphism. Measurements of the canine are the best option for sex estimation using teeth, as well as the thickness of the dentine or enamel of incisors. The axis vertebra surpasses other neck bones for sex estimation due to its atypical shape and the presence of the odontoid process. Metric analyses based on anatomy can provide reliable accuracy in sexual diagnosis. Adequate training and anatomical knowledge can reduce bias and interobserver differences, and the use of three-dimensional models and computed tomography images can enhance the accuracy of these methods for sex estimation. However, every method should be validated before being applied to a different population. KEY POINTS• Anatomy-based metric analyses can provide reliable accuracy in forensic sex estimation. • Glabellae inclination, external frontal bone surface, mandible, and canine teeth measurements can reach accuracies superior to 80% in sexual diagnosis.• The use of three-dimensional models and computed tomography images can enhance accuracy in sex estimation.• every method should be validated before being applied to a different population.

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Sex estimation using paranasal sinus discriminant analysis: a new approach via cone beam computerized tomography volume analysis

Cited by 32 publications

References 23 publications

Semi-Supervised Deep Learning Semantic Segmentation for 3D Volumetric Computed Tomographic Scoring of Chronic Rhinosinusitis: Clinical Correlations and Comparison with Lund-Mackay Scoring

Semi-Supervised Deep Learning Semantic Segmentation for 3D Volumetric Computed Tomographic Scoring of Chronic Rhinosinusitis: Clinical Correlations and Comparison with Lund-Mackay Scoring

Are Maxillary and Sphenoid Sinus Volumes Predictors of Gender and Age? A Cone Beam Computed Tomography Study

Contributions of anatomy to forensic sex estimation: focus on head and neck bones

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