edoc

Prediction of Normal Bone Anatomy for the Planning of Corrective Osteotomies of Malunited Forearm Bones Using a Three-Dimensional Statistical Shape Model

Mauler, Flavien and Langguth, Christoph and Schweizer, Andreas and Vlachopoulos, Lazaros and Gass, Tobias and Lüthi, Marcel and Fürnstahl, Philipp. (2017) Prediction of Normal Bone Anatomy for the Planning of Corrective Osteotomies of Malunited Forearm Bones Using a Three-Dimensional Statistical Shape Model. Journal of Orthopaedic Research, 35 (12). pp. 2630-2636.

[img] PDF - Accepted Version
529Kb

Official URL: https://edoc.unibas.ch/59208/

Downloads: Statistics Overview

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.
Faculties and Departments:05 Faculty of Science > Departement Mathematik und Informatik > Informatik > Computergraphik Bilderkennung (Vetter)
UniBasel Contributors:Lüthi, Marcel
Item Type:Article, refereed
Article Subtype:Research Article
Publisher:Wiley
ISSN:0736-0266
e-ISSN:1554-527X
Note:Publication type according to Uni Basel Research Database: Journal article -- The final publication ist available at Wiley, see DOI link.
Language:English
Identification Number:
edoc DOI:
Last Modified:08 Feb 2020 14:49
Deposited On:09 Feb 2018 12:28

Repository Staff Only: item control page