Literature DB >> 28390188

Prediction of normal bone anatomy for the planning of corrective osteotomies of malunited forearm bones using a three-dimensional statistical shape model.

Flavien Mauler1, Christoph Langguth2, Andreas Schweizer1, Lazaros Vlachopoulos3, Tobias Gass4, Marcel Lüthi2, Philipp Fürnstahl3.   

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. © 2017 Orthopaedic Research Society. Published by Wiley Periodicals, Inc.

Keywords:  forearm; osteotomy; statistical shape model; template; three-dimensional

Mesh:

Year:  2017        PMID: 28390188     DOI: 10.1002/jor.23576

Source DB:  PubMed          Journal:  J Orthop Res        ISSN: 0736-0266            Impact factor:   3.494


  3 in total

1.  Predicting Knee Joint Instability Using a Tibio-Femoral Statistical Shape Model.

Authors:  Pietro Cerveri; Antonella Belfatto; Alfonso Manzotti
Journal:  Front Bioeng Biotechnol       Date:  2020-04-17

2.  The 3D skull 0-4 years: A validated, generative, statistical shape model.

Authors:  Eimear O' Sullivan; Lara S van de Lande; Anne-Jet C Oosting; Athanasios Papaioannou; N Owase Jeelani; Maarten J Koudstaal; Roman H Khonsari; David J Dunaway; Stefanos Zafeiriou; Silvia Schievano
Journal:  Bone Rep       Date:  2021-11-29

3.  Evaluation of Statistical Shape Modeling in Quantifying Femoral Morphologic Differences Between Symptomatic and Nonsymptomatic Hips in Patients with Unilateral Femoroacetabular Impingement Syndrome.

Authors:  Timothy C Keating; Natalie Leong; Edward C Beck; Benedict U Nwachukwu; Alejandro A Espinoza Orías; Xioaping Qian; Kang Li; Shane J Nho
Journal:  Arthrosc Sports Med Rehabil       Date:  2020-02-05
  3 in total

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