A new classification of impacted proximal humerus fractures based on the morpho-volumetric evaluation of humeral head bone loss with a 3D model.


Journal

Journal of shoulder and elbow surgery
ISSN: 1532-6500
Titre abrégé: J Shoulder Elbow Surg
Pays: United States
ID NLM: 9206499

Informations de publication

Date de publication:
Oct 2020
Historique:
received: 30 10 2019
revised: 13 02 2020
accepted: 20 02 2020
pubmed: 24 6 2020
medline: 10 2 2021
entrez: 24 6 2020
Statut: ppublish

Résumé

This study aimed to classify the pathomorphology of impacted proximal humeral fractures according to the control volume theory, with the intention to introduce a severity index to support surgeons in decision making. In total, 50 proximal humeral fractures were randomly selected from 200 medical records of adult patients treated from 2009 to 2016. Four nonindependent observers used 2 different imaging modalities (computed tomography scans plus volume rendering; 3D model) to test the classification reliability. A fracture classification system was created according to the control volume theory to provide simple and understandable patterns that would help surgeons make quick assessments. The impacted fractures table was generated based on an evaluation of the calcar condition, determined by the impairment of a defined volumetric area under the cephalic cup and the humeral head malposition. In addition to the main fracture pattern, the comminution degree (low, medium, high), providing important information on fracture severity, could also be evaluated. From 3D imaging, the inter- and intraobserver reliability revealed a k value (95% confidence interval) of 0.55 (0.50-0.60) and 0.91 (0.79-1.00), respectively, for the pattern code, and 0.52 (0.43-0.76) and 0.91 (0.56-0.96), respectively, for the comminution degree. The new classification provides a useful synoptic framework for identifying complex fracture patterns. It can provide the surgeon with useful information for fracture analysis and may represent a good starting point for an automated system.

Sections du résumé

BACKGROUND BACKGROUND
This study aimed to classify the pathomorphology of impacted proximal humeral fractures according to the control volume theory, with the intention to introduce a severity index to support surgeons in decision making.
METHODS METHODS
In total, 50 proximal humeral fractures were randomly selected from 200 medical records of adult patients treated from 2009 to 2016. Four nonindependent observers used 2 different imaging modalities (computed tomography scans plus volume rendering; 3D model) to test the classification reliability. A fracture classification system was created according to the control volume theory to provide simple and understandable patterns that would help surgeons make quick assessments. The impacted fractures table was generated based on an evaluation of the calcar condition, determined by the impairment of a defined volumetric area under the cephalic cup and the humeral head malposition. In addition to the main fracture pattern, the comminution degree (low, medium, high), providing important information on fracture severity, could also be evaluated.
RESULTS RESULTS
From 3D imaging, the inter- and intraobserver reliability revealed a k value (95% confidence interval) of 0.55 (0.50-0.60) and 0.91 (0.79-1.00), respectively, for the pattern code, and 0.52 (0.43-0.76) and 0.91 (0.56-0.96), respectively, for the comminution degree.
CONCLUSIONS CONCLUSIONS
The new classification provides a useful synoptic framework for identifying complex fracture patterns. It can provide the surgeon with useful information for fracture analysis and may represent a good starting point for an automated system.

Identifiants

pubmed: 32573449
pii: S1058-2746(20)30233-0
doi: 10.1016/j.jse.2020.02.022
pii:
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

e374-e385

Informations de copyright

Copyright © 2020 Journal of Shoulder and Elbow Surgery Board of Trustees. Published by Elsevier Inc. All rights reserved.

Auteurs

Raffaele Russo (R)

Department of Orthopedic Surgery, Pineta Grande Hospital, Caserta, Italy. Electronic address: raff.russo55@gmail.com.

Antonio Guastafierro (A)

Department of Orthopedic Surgery, Pineta Grande Hospital, Caserta, Italy.

Giuseppe Della Rotonda (GD)

Department of Orthopedic Surgery, Pineta Grande Hospital, Caserta, Italy.

Stefano Viglione (S)

Department of Orthopedic Surgery, Pineta Grande Hospital, Caserta, Italy.

Michele Ciccarelli (M)

Department of Orthopedic Surgery, Pineta Grande Hospital, Caserta, Italy.

Marco Mortellaro (M)

E-lisa s.r.l., Naples, Italy.

Paolo Minopoli (P)

E-lisa s.r.l., Naples, Italy.

Fabrizio Fiorentino (F)

E-lisa s.r.l., Naples, Italy.

Livia Renata Pietroluongo (LR)

E-lisa s.r.l., Naples, Italy.

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Classifications MeSH