Literature DB >> 28663399

Prediction of the pre-morbid 3D anatomy of the proximal humerus based on statistical shape modelling.

S Poltaretskyi1, J Chaoui2, M Mayya2, C Hamitouche3, M J Bercik4, P Boileau5, G Walch6.   

Abstract

AIMS: Restoring the pre-morbid anatomy of the proximal humerus is a goal of anatomical shoulder arthroplasty, but reliance is placed on the surgeon's experience and on anatomical estimations. The purpose of this study was to present a novel method, 'Statistical Shape Modelling', which accurately predicts the pre-morbid proximal humeral anatomy and calculates the 3D geometric parameters needed to restore normal anatomy in patients with severe degenerative osteoarthritis or a fracture of the proximal humerus.
MATERIALS AND METHODS: From a database of 57 humeral CT scans 3D humeral reconstructions were manually created. The reconstructions were used to construct a statistical shape model (SSM), which was then tested on a second set of 52 scans. For each humerus in the second set, 3D reconstructions of four diaphyseal segments of varying lengths were created. These reconstructions were chosen to mimic severe osteoarthritis, a fracture of the surgical neck of the humerus and a proximal humeral fracture with diaphyseal extension. The SSM was then applied to the diaphyseal segments to see how well it predicted proximal morphology, using the actual proximal humeral morphology for comparison.
RESULTS: With the metaphysis included, mimicking osteoarthritis, the errors of prediction for retroversion, inclination, height, radius of curvature and posterior and medial offset of the head of the humerus were 2.9° (± 2.3°), 4.0° (± 3.3°), 1.0 mm (± 0.8 mm), 0.8 mm (± 0.6 mm), 0.7 mm (± 0.5 mm) and 1.0 mm (± 0.7 mm), respectively. With the metaphysis excluded, mimicking a fracture of the surgical neck, the errors of prediction for retroversion, inclination, height, radius of curvature and posterior and medial offset of the head of the humerus were 3.8° (± 2.9°), 3.9° (± 3.4°), 2.4 mm (± 1.9 mm), 1.3 mm (± 0.9 mm), 0.8 mm (± 0.5 mm) and 0.9 mm (± 0.6 mm), respectively.
CONCLUSION: This study reports a novel, computerised method that accurately predicts the pre-morbid proximal humeral anatomy even in challenging situations. This information can be used in the surgical planning and operative reconstruction of patients with severe degenerative osteoarthritis or with a fracture of the proximal humerus. Cite this article: Bone Joint J 2017;99-B:927-33. ©2017 The British Editorial Society of Bone & Joint Surgery.

Entities:  

Keywords:  3D pre-operative planning; Prediction; Proximal humerus geometry; Statistical shape modelling; Trauma

Mesh:

Year:  2017        PMID: 28663399     DOI: 10.1302/0301-620X.99B7.BJJ-2017-0014

Source DB:  PubMed          Journal:  Bone Joint J        ISSN: 2049-4394            Impact factor:   5.082


  6 in total

1.  Thinking outside the glenohumeral box: Hierarchical shape variation of the periarticular anatomy of the scapula using statistical shape modeling.

Authors:  Matthijs Jacxsens; Shireen Y Elhabian; Sarah E Brady; Peter N Chalmers; Andreas M Mueller; Robert Z Tashjian; Heath B Henninger
Journal:  J Orthop Res       Date:  2020-01-24       Impact factor: 3.494

2.  Anatomical Variation of the Tibia - a Principal Component Analysis.

Authors:  Liselore Quintens; Michiel Herteleer; Sanne Vancleef; Yannick Carette; Joost Duflou; Stefaan Nijs; Jos Vander Sloten; Harm Hoekstra
Journal:  Sci Rep       Date:  2019-05-21       Impact factor: 4.379

Review 3.  The evolution of virtual reality in shoulder and elbow surgery.

Authors:  Ryan Lohre; Jon J P Warner; George S Athwal; Danny P Goel
Journal:  JSES Int       Date:  2020-05-07

4.  Cranial reconstruction evaluation - comparison of European statistical shape model performance on Chinese dataset.

Authors:  Marc Anton Fuessinger; Marc Christian Metzger; Rene Rothweiler; Leonard Simon Brandenburg; Stefan Schlager
Journal:  Bone Rep       Date:  2022-08-13

5.  Distal Humerus Morphological Analysis of Chinese Individuals: A Statistical Shape Modeling Approach.

Authors:  Wei Zhao; Yao Guo; Chuangye Xu; Guoxian Pei; Shiva Basnet; Yanjun Pei; Xiuyun Su
Journal:  Orthop Surg       Date:  2022-09-14       Impact factor: 2.279

6.  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
  6 in total

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