Abstract
With ever-growing aging population and demand for denture treatments, pressure-induced mucosa lesion and residual ridge resorption remain main sources of clinical complications. Conventional denture design and fabrication are challenged for its labor and experience intensity, urgently necessitating an automatic procedure. This study aims to develop a fully automatic procedure enabling shape optimization and additive manufacturing of removable partial dentures (RPD), to maximize the uniformity of contact pressure distribution on the mucosa, thereby reducing associated clinical complications. A 3D heterogeneous finite element (FE) model was constructed from CT scan, and the critical tissue of mucosa was modeled as a hyperelastic material from in vivo clinical data. A contact shape optimization algorithm was developed based on the bi-directional evolutionary structural optimization (BESO) technique. Both initial and optimized dentures were prototyped by 3D printing technology and evaluated with in vitro tests. Through the optimization, the peak contact pressure was reduced by 70%, and the uniformity was improved by 63%. In vitro tests verified the effectiveness of this procedure, and the hydrostatic pressure induced in the mucosa is well below clinical pressure-pain thresholds (PPT), potentially lessening risk of residual ridge resorption. This proposed computational optimization and additive fabrication procedure provides a novel method for fast denture design and adjustment at low cost, with quantitative guidelines and computer aided design and manufacturing (CAD/CAM) for a specific patient. The integration of digitalized modeling, computational optimization, and free-form fabrication enables more efficient clinical adaptation. The customized optimal denture design is expected to minimize pain/discomfort and potentially reduce long-term residual ridge resorption.
Highlights
Denture treatments have been widely applied in dental practice to restore oral function of the edentulous group [1]
The first was to apply white silicone (Fit Checker II; GC Corporation, New South Wales, Australia) for checking the fit, and the second was using a pressure sensitive film to examining the pressure distribution. Both the maximum contact pressure (MAX) and standard deviation (SD) are plotted in Fig 3a against the iteration number of the bi-directional evolutionary structural optimization (BESO) computational design (Details are included in the S1 Table)
Previous research has revealed that high contact pressure can trigger pain in the oral mucosa, and a short term concern lies in discomfort and painful sensation for denture users, which is associated with denture-related stomatitis [52,53,54]
Summary
Denture treatments have been widely applied in dental practice to restore oral function of the edentulous group [1]. Conventional denture fabrication using final cast models [16,17,18,19] is unable to take into account either the nonlinear soft tissue responses or the heterogeneous jaw bone with local variations, and the fabricated denture base reflects only surface morphology of residual ridge. This labor-intensive process may result in variable adaptive accuracies with different fabrication techniques and experience levels [16]
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