Computer-aided design and fabrication of statistically shaped nasal prostheses: A feasibility study.

Abstract

Statement of problem: A nasal prosthesis may compensate for a partial or complete defect of the nose associated with trauma or amputation. However, the design and production is time-consuming, expensive, and expertize-dependent. Computer-generated prosthesis models and 3D printing can optimize the process.

Purpose: The purpose of this pilot study was to evaluate a novel method for nasal prosthesis design utilizing statistical shape modeling (SSM) on a cohort of participants.

Material and methods: The prosthesis shapes were generated by a design algorithm and fabricated through a 3-dimensionally (3D) printed mold. Combining a semi-automated algorithm with 3D printing reduced the dependence on expertize. A proof-of-concept assessment was conducted by enrolling 20 participants with total nose amputation with a conventionally created prosthesis (Cp). The faces of the participants were scanned with an optical scanner to acquire 3D surface scans that were loaded into the algorithm to create the statistically shape modeled prosthesis (SSMp). Participants were asked to digitally modify the SSMp by changing 9 parameters using the Scalismo Lab software program, allowing them to shape their preferred nose model, the patient-preferred prosthesis (PPp). The SSMps were fabricated using 3D printed molds and mailed to the participants for testing. They were asked to complete questionnaires comprising three FACE-Q modules: satisfaction with the nose and psychological and social function. In addition, the SSMp and Cp were compared with the PPp using anthropometric measurements.

Results: Fifteen participants were able to fit the SSMp and complete the questionnaire. The median satisfaction, psychological, and social function scores were 56, 67, and 62, respectively. All 20 participants filled out the questionnaires on their Cp, with scores of 71, 67, and 62, respectively. Anthropometric measurements comparing the SSMp with the PPp showed that the algorithm generates noses with a wider nasal root, a larger nostril floor width to nasal width ratio, a smaller columella length to nasal width as well as nostril floor width ratio than the patients prefer according to their set PPp. Comparing the Cp with the PPp showed a larger nasal width to nasal height ratio and nasal root width to intercanthal distance ratio.

Conclusions: SSM can facilitate the design and fabrication of nasal prostheses. Using the current models, however, patients were less satisfied than with prostheses made by the anaplastologist in consultation with the patient. Improving the SSM algorithm and incorporating patient manipulations into the resulting model should increase patient satisfaction and enable the production of nasal prostheses with minimal expert dependence.