RESUMEN
We present the proof of concept of a general model that uses the tissue sample transmittance as input to estimate the depth-resolved attenuation coefficient of tissue samples using optical coherence tomography (OCT). This method allows us to obtain an image of tissue optical properties instead of intensity contrast, guiding diagnosis and tissues differentiation, extending its application from thick to thin samples. The performance of our method was simulated and tested with the assistance of a home built single-layered and multilayered phantoms (~100 µm each layer) with known attenuation coefficient on the range of 0.9 to 2.32 mm-1 . It is shown that the estimated depth-resolved attenuation coefficient recovers the reference values, measured by using an integrating sphere followed by the inverse adding doubling processing technique. That was corroborated for all situations when the correct transmittance value is used with an average difference of 7%. Finally, we applied the proposed method to estimate the depth-resolved attenuation coefficient for a thin biological sample, demonstrating the ability of our method on real OCT images.
Asunto(s)
Modelos Teóricos , Fenómenos Ópticos , Tomografía de Coherencia Óptica , Fantasmas de ImagenRESUMEN
BACKGROUND AND OBJECTIVE: We aimed to evaluate in the same study two quantitative methods for quantification of incipient caries in human dental enamel by using optical coherence tomography (OCT): the optical attenuation coefficient and the area under the A-scan signal, and to compare their results with those obtained from microhardness analysis. STUDY DESIGN/MATERIALS AND METHODS: One hundred and sixty samples were obtained from 40 sound human third molars, which had their crowns sectioned. Simulated caries were created by a pH cycling method. OCT measurements were performed on the samples, before and after the induced demineralization. We determined the total optical attenuation coefficient from the OCT signal in each site and evaluated the sensitivity and specificity of this approach to the detection of the demineralization. Also, the areas under the OCT curves (AUC-OCT) and those from sectional microhardness tests (AUC-MH) were compared. RESULTS: Both the analysis of the optical attenuation coefficient and the AUC-OCT were adequate to efficiently distinguish sound and demineralized samples with sensitivity of 0.93 and specificity of 0.96. The AUC-MH and the AUC-OCT data presented linear relationship and correlation of 0.99. CONCLUSION: Both methods for signal analysis from OCT allowed detection of demineralization with good performance. The AUC-OCT approach enables obtaining a linear relation with the microhardness results, for a quantitative assessment of mineral loss in human teeth.