Resumo A microtomografia computadorizada (microTC) é uma modalidade de imagem não destrutiva utilizada para avaliar a morfometria óssea. Para análise acurada, faz-se necessário segmentar o tecido ósseo do fundo (background) da imagem, evitando assim, sub ou sobre estimação do volume ósseo real. Desta forma, fica evidente que os métodos de segmentação em análise de microTC podem influenciar a precisão dos cálculos da morfometria óssea. A realização do presente estudo teve como objetivo comparar o desempenho de dois diferentes métodos de segmentação de imagem de microTC, subjetivo e objetivo, através da avaliação dos resultados das análises morfométricas obtidas de ossos humanos. Dezesseis amostras contendo parafusos de fixação cobertos por 0,5- 1 mm de osso humano foram escaneados usando o microtomógrafo SkyScan1173. Três examinadores realizaram a segmentação das imagens de forma subjetiva (visualmente) obtendo seus respectivos valores de threshold. Em seguida, a segmentação objetiva (automática) foi realizada. As análises tridimensionais foram obtidas utilizando os valores determinados por ambos os métodos no software CTAn. Cinco parâmetros morfométricos do osso foram calculados (BV / TV, Tb.Th, Tb.N, Tb.Sp, Conn.Den) e usados como variáveis dependentes. O teste ANOVA não mostrou diferenças estatisticamente significantes entre os métodos comparados: BV / TV (p=0,424), Tb.N (p=0,672), Tb.Th (p=0,183), Tb.Sp (p=0 973) e Conn.den (p=0,204). A concordância intra e interobservardores variou entre satisfatória e excelente (0,55-1 e 0,546-0,991, respectivamente). Portanto, os resultados obtidos com a segmentação subjetiva foram semelhantes aos obtidos com a automática. Entretanto, a segmentação automática dispensa intervenção humana, sendo um método verdadeiramente objetivo e deve ser a primeira escolha em estudos microTC que objetivam avaliar a morfometria óssea humana.

Abstract X-ray microtomography (microCT) is a nondestructive technique used to assess bone morphometry. For an accurate analysis, it is necessary to segment the bone tissue from the background images, avoiding under- or overestimation of the real bone volume. Thus, segmentation methods for microCT can influence the accuracy of bone morphometry analysis. The purpose of this study was to compare two different image segmentation methods available on microCT software (subjective and objective) regarding to the human bone morphometric analysis. Sixteen samples containing a fixation screws covered by 0.5-1mm of bone were scanned using the SkyScan 1173 scanner. Three examiners segmented the microCT images subjectively and recorded the threshold values. Subsequently, an objective segmentation was also done. The 3D analysis was performed for both images using the values previously determined in CTAn software. Five bone morphometric parameters were calculated (BV/TV, Tb.Th, Tb.N, Tb.Sp, Conn.Den) and used as dependent variables. ANOVA showed no significant differences between the methods concerning BV/TV (p=0.424), Tb.N (p=0.672), Tb.Th (p=0.183), Tb.Sp (p=0.973) and Conn.Den (p=0.204). Intra- and interobserver agreement ranged from satisfactory to excellent (0.55-1 and 0.546-0.991, respectively). Therefore, results obtained with subjective threshorlding were similar to those obtained with objective segmentation. Since objective segmentation does not have human input and it is a truly objective method, it should be the first choice in microCT studies that concern homogeneity and high resolution human bone sample.

Abstract To calculate root canal volume and surface area in microCT images, an image segmentation by selecting threshold values is required, which can be determined by visual or automatic methods. Visual determination is influenced by the operator's visual acuity, while the automatic method is done entirely by computer algorithms. Objective: To compare between visual and automatic segmentation, and to determine the influence of the operator's visual acuity on the reproducibility of root canal volume and area measurements. Material and methods: Images from 31 extracted human anterior teeth were scanned with a μCT scanner. Three experienced examiners performed visual image segmentation, and threshold values were recorded. Automatic segmentation was done using the “Automatic Threshold Tool” available in the dedicated software provided by the scanner's manufacturer. Volume and area measurements were performed using the threshold values determined both visually and automatically. Results: The paired Student's t-test showed no significant difference between visual and automatic segmentation methods regarding root canal volume measurements (p=0.93) and root canal surface (p=0.79). Conclusion: Although visual and automatic segmentation methods can be used to determine the threshold and calculate root canal volume and surface, the automatic method may be the most suitable for ensuring the reproducibility of threshold determination.