Three-dimensional soft tissue prediction using finite elements. Part I: Implementation of a new procedure.
OBJECTIVE
The prediction of soft tissue esthetics is important for achieving an optimal esthetic outcome in orthodontic treatment planning. Applicable procedures have so far been restricted to two-dimensional profile predictions that have not proven to be very reliable. The goal of this investigation was therefore to develop a novel finite element-based procedure that allows a three-dimensional, easily visualized, quantitative analysis and prediction of soft tissue behavior for the clinician. The procedure to be developed should be easy to handle and not entail any additional radiation exposure for the patient.


METHODS
Using a three-dimensional scanner, the facial surfaces of 20 probands were digitalized and individual FEM models were generated.


RESULTS
After reduction of data redundancy via several conversion steps, a patient-specific simulation model was prepared consisting of 20,000 to 40,000 individual elements to which specific physical properties could be assigned. The average time required for generating a virtual model was 50 minutes. Problems occurring during model generation were rare (mainly shadowing phenomena and movement artifacts).


CONCLUSIONS
The procedure outlined herein makes the reliable generation of patient-specific simulation models possible for facial soft tissue prediction in orthodontics.
Holberg
Christof
C
Department of Orthodontics, University of Munich, Germany. christof.holberg@med.uni-muenchen.de
Schwenzer
Katja
K
Rudzki-Janson
Ingrid
I
D000328:Adult; D003198:Computer Simulation; D003238:Connective Tissue / Q000033:anatomy & histology* / Q000502:physiology*; D005145:Face / Q000033:anatomy & histology* / Q000502:physiology*; D005260:Female; D020342:Finite Element Analysis; D006801:Humans; D021621:Imaging, Three-Dimensional / Q000379:methods*; D053685:Laser Therapy; D007834:Lasers; D008297:Male; D008953:Models, Anatomic; D008954:Models, Biological; D009970:Orthodontics / Q000379:methods; D011379:Prognosis; D012815:Signal Processing, Computer-Assisted; D013813:Therapy, Computer-Assisted / Q000379:methods*