Epi-RP-skin

Systematic Quantification of the skin texture reproduction level in digital workflow

01.01.2018 bis 31.12.2018

Scholar: Dr. Alexey Unkovskiy

Patients suffering from the partial or total loss of their facial anatomy are commonly treated
by a team of maxillofacial surgeons and prosthetists. After the surgical stage is accomplished,
a prosthetic appliance in form of a removable facial prosthesis is usually made manually
based on the hand-crafted skills. The conventional process of facial prostheses manufacturing
is considered to be a time-consuming and complex process. Nowadays facial prostheses can
be produced digitally with the use of various computer-driven technologies, such as surface
scanning and additive manufacturing (AM). This digital approach was reported to be
beneficial to a conventional one, however, the topical literature provides little evidence-based
studies to the topic.
The herein applied project shall initiate a series of research activities coping with the general
attempt to implement the digital workflow into the daily practice of facial prostheses
manufacturing. As being a part of a general project, the applied study touches primarily upon
the clinical outcome of the patient’ rehabilitation by means of digitally-derived facial
prostheses. Besides the geometrical trueness and the marginal fit of prosthesis, the overall
prosthesis esthetics is dependent upon the level of skin surface reproduction. A good-looking
prosthesis must provide a well described skin details of an afflicted facial area such as pores
and wrinkles to aid is better camouflaging and making it inconspicuous. Conventionally, the
surface structure was sculpted manually onto prosthesis pattern. The aspect of skin surface
reproduction by means of digital approach remains almost untouched in the topical
literature. Thus, the applied study aims to quantify, which amount of skin details can be
transferred from the stage of prosthesis designing onto the definitive silicone prosthesis using
various AM approaches in context of a digital workflow.