Development and virtual validation of a novel digital workflow to rehabilitate palatal defects by using smartphone-integrated stereophotogrammetry (SPINS)

Abstract

Palatal defects are rehabilitated by fabricating maxillofacial prostheses called obturators. The treatment incorporates taking deviously unpredictable impressions to facsimile the palatal defects into plaster casts for obturator fabrication in the dental laboratory. The casts are then digitally stored using expensive hardware to prevent physical damage or data loss and, when required, future obturators are digitally designed, and 3D printed. Our objective was to construct and validate an economic in-house smartphone-integrated stereophotogrammetry (SPINS) 3D scanner and to evaluate its accuracy in designing prosthetics using open source/free (OS/F) digital pipeline. Palatal defect models were scanned using SPINS and its accuracy was compared against the standard laser scanner for virtual area and volumetric parameters. SPINS derived 3D models were then used to design obturators by using (OS/F) software. The resultant obturators were virtually compared against standard medical software designs. There were no significant differences in any of the virtual parameters when evaluating the accuracy of both SPINS, as well as OS/F derived obturators. However, limitations in the design process resulted in minimal dissimilarities. With further improvements, SPINS based prosthetic rehabilitation could create a viable, low cost method for rural and developing health services to embrace maxillofacial record keeping and digitised prosthetic rehabilitation.

Figure 1

A graphical flowchart summary of the workflow followed in the study. The phases (A–D) and their respective descriptions are colour coded. SPINS smartphone-integrated stereophotogrammetry, MSA mesh surface area, VV virtual volume, HD Hausdorff’s distance, DSC dice similarity coefficient.

Figure 2

Design of bulbs using 3-matics (a) import STL, (b) make hollow, (c) design curve around defect, (d) reconstruct surface, (e) trim the reconstruction zone, (f) remove any excess mesh, (g) create chamfered margins, (h) wrap, smooth and export prosthesis.

Figure 3

Design of bulbs using OS/F (a) import STL, (b) select the defect, (c) flip normal and select horizontal peripheral vertices, (d) fill outer surface, (e) analyse and auto repair to make watertight, (f) sculpt and export prosthesis.

Figure 4

Area discordance reports for Phase C. The amount of HD variation per model comparison is shown in the bar chart and is colour coded. The exact location of the discrepancy is shown on the model above with the respective colours.

Figure 5

Visual comparison of proprietary and OS/F workflows on Set A (left) and Set B (right). (a) Right lateral surface, (b) left lateral surface, (c) inner surface, (d) outer surface.