RESUMEN
OBJECTIVE: Rapid maxillary expansion is a common orthodontic procedure to correct maxillary constriction. Assessing the midpalatal suture (MPS) expansion plays a crucial role in treatment planning to determine its effectiveness. The objectives of this preliminary investigation are to demonstrate a proof of concept that the palatal bone underlying the rugae can be clearly imaged by ultrasound (US) and the reconstructed axial view of the US image accurately maps the MPS patency. METHODS: An ex-vivo US scanning was conducted on the upper jawbones of two piglet's carcasses before and after the creation of bone defects, which simulated the suture opening. The planar images were processed to enhance bone intensity distribution before being orderly stacked to fuse into a volume. Graph-cut segmentation was applied to delineate the palatal bone to generate a bone volume. The accuracy of the reconstructed bone volume and the suture opening was validated by the micro-computed tomography (µCT) data used as the ground truth and compared with cone beam computed tomography (CBCT) data as the clinical standard. Also included in the comparison is the rugae thickness. Correlation and Bland-Altman plots were used to test the agreement between the two methods: US versus µCT/CBCT. RESULTS: The reconstruction of the US palatal bone volumes was accurate based on surface topography comparison with a mean error of 0.19 mm for pre-defect and 0.15 mm and 0.09 mm for post-defect models of the two samples, respectively when compared with µCT volumes. A strong correlation (R2 ≥ 0.99) in measuring MPS expansion was found between US and µCT/CBCT with MADs of less than 0.05 mm, 0.11 mm and 0.23 mm for US, µCT and CBCT, respectively. CONCLUSIONS: It was possible to axially image the MPS opening and rugae thickness accurately using high-frequency ultrasound. CLINICAL SIGNIFICANCE: This study introduces an ionizing radiation-free, low-cost, and portable technique to accurately image a difficult part of oral cavity anatomy. The advantages of conceivable visualization could promise a successful clinical examination of MPS to support the predictable treatment outcome of maxillary transverse deficiency.
Asunto(s)
Tomografía Computarizada de Haz Cónico , Técnica de Expansión Palatina , Ultrasonografía , Microtomografía por Rayos X , Animales , Porcinos , Microtomografía por Rayos X/métodos , Tomografía Computarizada de Haz Cónico/métodos , Técnica de Expansión Palatina/instrumentación , Ultrasonografía/métodos , Hueso Paladar/diagnóstico por imagen , Hueso Paladar/anatomía & histología , Suturas Craneales/diagnóstico por imagen , Suturas Craneales/anatomía & histología , Maxilar/diagnóstico por imagen , Paladar Duro/diagnóstico por imagen , Paladar Duro/anatomía & histología , Procesamiento de Imagen Asistido por Computador/métodos , Imagenología Tridimensional/métodosRESUMEN
Innovative intraoral ultrasound devices with smart artificial intelligence-based identification for dento-anatomy could provide crucial information for oral health diagnosis and treatment and shed light on real-time detection of developmental dentistry. However, the grand challenge is that the current ultrasound technologies are meant for external use due to their bulkiness and low frequency. We report a compact versatile ultrasound intraoral device that consists of a rotational probe head robustly pivoted around a hand-held and portable handle for real-time imaging of intraoral anatomy using high-frequency ultrasonography (up to 25 MHz). The intraoral ultrasound device that could be adjusted for various orientations of the imaging planes by rotating the head provides real-time, high-resolution ultrasonograms of intraoral structures, including dento-periodontium of most tooth types and maxillary palate. Machine learning-based algorithms are integrated to automate the identification of important structures, including alveolar bone and cementum-enamel junction. The intraoral ultrasound device smartened with artificial intelligence could innovate oral health diagnosis and treatment plans toward precision health and patient care.