title: Prediction of normal bone anatomy for the planning of corrective osteotomies of malunited forearm bones using a three-dimensional statistical shape model.
abstract: Corrective osteotomies of the forearm based on 3D computer simulation using contralateral anatomy as a reconstruction template is an approved method. Limitations are existing considerable differences between left and right forearms, and that a healthy contralateral anatomy is required. We evaluated if a computer model, not relying on the contralateral anatomy, may replace the current method by predicting the pre-traumatic healthy shape. A statistical shape model (SSM) was generated from a set of 59 CT scans of healthy forearms, encoding the normal anatomical variations. Three different configurations were simulated to predict the pre-traumatic shape with the SSM (cross-validation). In the first two, only the distal or proximal 50% of the radius were considered as pathological. In a third configuration, the entire radius was assumed to be pathological, only the ulna being intact. Corresponding experiments were performed with the ulna. Accuracy of the prediction was assessed by comparing the predicted bone with the healthy model. For the radius, mean rotation accuracy of the prediction between 2.9 ± 2.2° and 4.0 ± 3.1° in pronation/supination, 0.4 ± 0.3° and 0.6 ± 0.5° in flexion/extension, between 0.5 ± 0.3° and 0.5 ± 0.4° in radial-/ulnarduction. Mean translation accuracy along the same axes between 0.8 ± 0.7 and 1.0 ± 0.8 mm, 0.5 ± 0.4 and 0.6 ± 0.4 mm, 0.6 ± 0.4 and 0.6 ± 0.5 mm, respectively. For the ulna, mean rotation accuracy between 2.4 ± 1.9° and 4.7 ± 3.8° in pronation/supination, 0.3 ± 0.3° and 0.8 ± 0.6° in flexion/extension, 0.3 ± 0.2° and 0.7 ± 0.6° in radial-/ulnarduction. Mean translation accuracy between 0.6 ± 0.4 mm and 1.3 ± 0.9 mm, 0.4 ± 0.4 mm and 0.7 ± 0.5 mm, 0.5 ± 0.4 mm and 0.8 ± 0.6 mm, respectively. This technique provided high accuracy, and may replace the current method, if validated in clinical studies. © 2017 Orthopaedic Research Society. Published by Wiley Periodicals, Inc. J Orthop Res 35:2630-2636, 2017.
authors.affiliation: Department of Orthopaedics, Balgrist University Hospital, University of Zurich, Zurich, Switzerland.
authors.forename: Flavien
authors.initials: F
authors.lastname: Mauler
authors.affiliation: Department of Mathematics and Computer Science, University of Basel, Basel, Switzerland.
authors.forename: Christoph
authors.initials: C
authors.lastname: Langguth
authors.affiliation: Department of Orthopaedics, Balgrist University Hospital, University of Zurich, Zurich, Switzerland.
authors.forename: Andreas
authors.initials: A
authors.lastname: Schweizer
authors.affiliation: Computer Assisted Research and Development Group, Balgrist University Hospital, University of Zurich, Zurich, Switzerland.
authors.forename: Lazaros
authors.initials: L
authors.lastname: Vlachopoulos
authors.affiliation: Computer Vision Laboratory, ETH Zurich, Zurich, Switzerland.
authors.forename: Tobias
authors.initials: T
authors.lastname: Gass
authors.affiliation: Department of Mathematics and Computer Science, University of Basel, Basel, Switzerland.
authors.forename: Marcel
authors.initials: M
authors.lastname: Lüthi
authors.affiliation: Computer Assisted Research and Development Group, Balgrist University Hospital, University of Zurich, Zurich, Switzerland.
authors.forename: Philipp
authors.initials: P
authors.lastname: Fürnstahl
mesh_terms: D063405:Anatomic Variation; D017759:Fractures, Malunited / Q000601:surgery*; D006801:Humans; D021621:Imaging, Three-Dimensional; D015233:Models, Statistical; D011884:Radius / Q000033:anatomy & histology*; D011885:Radius Fractures / Q000601:surgery; D014457:Ulna / Q000033:anatomy & histology*; D014458:Ulna Fractures / Q000601:surgery
keywords: forearm; osteotomy; statistical shape model; template; three-dimensional