Deep Neural Networks for Chronological Age Estimation From OPG Images

Chronological age estimation is crucial labour in many clinical procedures, where the teeth have proven to be one of the best estimators. Although some methods to estimate the age from tooth measurements in orthopantomogram (OPG) images have been developed, they rely on time-consuming manual processes whose results are affected by the observer subjectivity. Furthermore, all those approaches have been tested only on OPG image sets of good radiological quality without any conditioning dental characteristic. In this work, two fully automatic methods to estimate the chronological age of a subject from the OPG image are proposed. The first (DANet) consists of a sequential Convolutional Neural Network (CNN) path to predict the age, while the second (DASNet) adds a second CNN path to predict the sex and uses sex-specific features with the aim of improving the age prediction performance. Both methods were tested on a set of 2289 OPG images of subjects from 4.5 to 89.2 years old, where both bad radiological quality images and images showing conditioning dental characteristics were not discarded. The results showed that the DASNet outperforms the DANet in every aspect, reducing the median Error (E) and the median Absolute Error (AE) by about 4 months in the entire database. When evaluating the DASNet in the reduced datasets, the AE values decrease as the real age of the subjects decreases, until reaching a median of about 8 months in the subjects younger than 15. The DASNet method was also compared to the state-of-the-art manual age estimation methods, showing significantly less over- or under-estimation problems. Consequently, we conclude that the DASNet can be used to automatically predict the chronological age of a subject accurately, especially in young subjects with developing dentitionsThis work was supported in part by the Consellería de Cultura, Educación e Ordenación Universitaria under Grant ED431G/08, in part by the Potential Growth Group ED431B 2017/029, in part by the Competitive Reference Group ED431C 2017/69, in part by the N Vila-Blanco Support ED481A-2017, and in part by the European Regional Development Fund (ERDF)S

Parâmetros ósseos para avaliação de baixa densidade mineral óssea e risco de fratura por osteoporose em TCFC de mulheres na pós-menopausa

Tese (doutorado) — Universidade de Brasília, Faculdade de Ciências da Saúde, Departamento de Odontologia, Programa de Pós-Graduação em em Odontologia, 2022.O presente trabalho teve como objetivo principal analisar parâmetros ósseos mandibulares para avaliação de osteoporose e do risco de fratura em mulheres na pós-menopausa, por meio de tomografia computadorizada de feixe cônico (TCFC). A amostra final foi composta por 103 pacientes, sendo 52 com densidade mineral óssea (DMO) normal e 51 com diagnóstico densitométrico de osteoporose. A mensuração dos índices radiomorfométricos e da dimensão fractal foi realizada no programa ImageJ. O primeiro artigo avaliou qualitativamente e quantitativamente a cortical mandibular, com o estabelecimento de um novo índice denominado índice mandibular tridimensional para osteoporose (3D MOI). Este índice foi significativamente diferente entre mulheres na pós-menopausa com osteoporose e com DMO normal. Mulheres idosas, com a cortical inferior da mandíbula com espessura inferior a 2,75mm na TCFC e classificadas como C3 devem ser investigadas para osteoporose. O segundo artigo avaliou o parâmetro trabecular dimensão fractal em dois sítios distintos (mandíbula e segunda vértebra cervical). Apesar dos valores de dimensão fractal na mandíbula terem sido menores nos pacientes com osteoporose quando comparados aos das mulheres com DMO normal, a análise não apresentou boa reprodutibilidade e acurácia para predizer o diagnóstico densitométrico. Por fim, o terceiro artigo analisou a relação entre a densidade mineral óssea (DXA), o risco de fratura calculado pela ferramenta FRAX e dados de microarquitetura óssea. Neste último estudo, dados de microarquitetura óssea (MAO) foram analisadas pelo programa CT Analyzer, com a seleção de um volume de interesse nas regiões de segunda vértebra cervical e anteriormente ao forame mentual. As análises foram realizadas em TCFCs de 100 mulheres na pós-menopausa e, destas, 46 também responderam à ferramenta FRAX. O parâmetro número de trabéculas correlacionou-se com os dados densitométricos e com o FRAX em ambos os sítios de interesse. A área abaixo da curva foi de 0.732 para predizer o alto risco de fratura no quadril considerando o ponto de corte do FRAX brasileiro de 3%. Na coluna vertebral, o parâmetro espessura das trabéculas e a anisotropia também se correlacionaram com a DMO e com o FRAX. Como conclusão final destes estudos, a TCFC demonstrou acurácia para predizer o diagnóstico densitométrico de osteoporose, com base em um novo índice tridimensional baseado na análise da cortical mandibular, conforme descrito no primeiro artigo. Por outro lado, a análise da dimensão fractal não demonstrou boa acurácia e reprodutibilidade para a mesma finalidade, conforme evidenciado no artigo 2. Já os parâmetros trabeculares, avaliados de forma tridimensional, como o número e a espessura das trabéculas e anisotropia apresentaram correlação com os resultados do DXA e com o FRAX. O parâmetro número de trabéculas apresentou potencial para predizer o risco de fratura baseado nos pontos de corte do FRAX.The present work aimed to analyze mandibular bone parameters for evaluating osteoporosis and fracture risk in postmenopausal women, by means of Cone-Beam Computed Tomography (CBCT). The final sample consisted of 103 patients, 52 with normal BMD and 51 with osteoporosis. The measurement of radiomorphometric indices and fractal dimension was performed using ImageJ software. The first article qualitatively and quantitatively evaluated the mandibular cortical bone. A composite CBCT-driven index (3D MOI) was established and demonstrated to be significantly different between postmenopausal women with normal BMD and those with osteoporosis. Elderly women with inferior mandibular cortical thickness lower than 2.75 mm on CBCT and classified as C3 should be investigated for osteoporosis. The second article calculated fractal dimension in two different sites (mandible and second cervical vertebra). Although the fractal dimension values in the mandible were lower in patients with osteoporosis when compared to those of women with normal BMD, the analysis did not present good reproducibility and accuracy to predict the densitometric diagnosis. Finally, the last article aimed to analyze the relationship between bone mineral density (DXA results), fracture risk calculated by FRAX tool and bone microarchitecture data. In the third study, bone microarchitecture data were analyzed by the CT Analyzer program, with the selection of two volume of interests in the regions of the second cervical vertebra and anterior to the mental foramen. The analyses were performed on CBCT scans of 100 postmenopausal women and, from these, 46 also responded to the FRAX tool. The bone parameter number of trabeculae correlated with densitometric data and with FRAX at both sites of interest. The trabecular number assessed in the mandible showed the most promising results in comparison to the other variables, since it presented a strong inverse correlation both for hip fractures and major osteoporotic fractures. The area under the curve value was 0.732 for predicting high hip fracture risk by using the Brazilian FRAX cut-off. In the spine, bone parameter trabecular thickness and anisotropy also correlated with BMD and FRAX. As a final conclusion of the three studies, CBCT showed accuracy to predict the densitometric diagnosis of osteoporosis, based on a new cortical index (3D MOI), as described in the first article. On the other hand, the analysis of fractal dimension did not demonstrate good accuracy and reproducibility for the same purpose, as shown in article 2. Some 3D trabecular parameters, such as the number and thickness of trabeculae and anisotropy were correlated with DXA and FRAX results, and the trabecular number at the mandibular site may be further investigated as potential tool to predict fracture risk, as shown in article 3