Shape Optimization for Additive Manufacturing of Removable Partial Dentures--A New Paradigm for Prosthetic CAD/CAM

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.

Fig 1

The model was created based on patient-specific clinical data, a) two sets of CBCT data were reconstructed to form masks (Set 1: white—teeth, orange—bone, transparent pink—mucosa, grey—teeth; Set 2: grey—artificial teeth, transparent cyan—denture base, blue—denture frame); b) both models are solidified by using NURBS and assembled; c) assignment of heterogeneous material property of the bone based on HU value; d) the nodes highlighted in red on the denture base are allowed to be modified during bi-directional evolutionary shape optimization (BESO), and the orange ones are fixed to maintain the denture functionality.

Fig 2. The flow chart illustrates the contact-based BESO procedure for optimization of denture contact surface.

Fig 3

Convergence history, a) the maximum contact pressure and the deviation of contact pressure (i.e. the objective function Eq (5)); b) the contact area and the load transferred from denture base during the optimization.

Fig 4

Optimization outcomes, a) the modification made to the denture base through the BESO shape optimization with an adaptive modification rate; the maximum material deposition and removal are 382 and 224 um; b) the contact pressure contours on the initial denture base (left) and the optimized denture base (right).

Fig 5

Prototypes and in vitro test, a) the subject jaw model (upper) and the optimized denture (lower); b) in vitro loading test performed under Instron, with a pressure sensitive firm between the denture and the jaw; c) the fitting white silicone test; d) the pressure sensitive film test.

Fig 6

Clinical implications, a) the maximum contact pressures induced by both initial and optimized dentures are compared with the clinical pressure-pain thresholds (PPTs) over the distal region of the mandible. The maximum contact pressure (*) under the optimized denture is significantly lower than the PPTs available from literature (p < 0.01). b) Hydrostatic pressure induced by the denture insertion through the optimization procedure, indicating the reduction of disturbance severity to the blood circulation.