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European Radiology

, Volume 28, Issue 10, pp 4397–4406 | Cite as

Scapholunate instability: improved detection with semi-automated kinematic CT analysis during stress maneuvers

  • Waled Abou Arab
  • Aymeric Rauch
  • Mohammad B. Chawki
  • Francois Dap
  • Gilles Dautel
  • Alain Blum
  • Pedro Augusto Gondim Teixeira
Computed Tomography
  • 207 Downloads

Abstract

Objectives

To evaluate the diagnostic performance of radioulnar deviation (RUD) and clenching fist (CF) maneuvers for the evaluation of scapholunate dissociation (SLD) using quantitative kinematic CT.

Methods

Thirty-seven patients with suspected scapholunate instability were prospectively evaluated with kinematic CT. Two radiologists independently evaluated the SLD during RUD and CF maneuvers. Various dynamic parameters describing SLD were compared (maximal value, variation coefficient and range) in patients with and without scapholunate ligament ruptures confirmed by CT arthrography.

Results

SLD in CF varied from 3.17 ± 0.38 to 3.24 ± 0.80 mm in controls and from 4.11 ± 0.77 and 4.01 ± 0.85 mm in patients with scapholunate ligament ruptures for reader 1 and 2 (p < 0.009). SLD in RUD varied from 3.35 ± 0.51 and 3.01 ± 0.78 mm in controls and from 4.51 ± 1.26 to 4.42 ± 1.75 mm in patients with scapholunate ligament ruptures for reader 1 and 2 (p varied from 0.001 to 0.002). The inter-observer variability was better for RUD (ICC = 0.85 versus 0.6 for RUD and CF respectively).

Conclusion

Analysis of SLD using kinematic CT has shown significant measurement differences between the groups with or without scapholunate instability with good diagnostic performance.

Key Points

• Kinematic CT can quantitatively assess scapholunate dissociation.

• SLD analysis on kinematic CT has excellent reproducibility with radioulnar deviation maneuver.

• Scapholunate dissociation was significantly different in patients with and without instability.

• Diagnostic performance for scapholunate instability identification was better with radioulnar deviation.

Keywords

Four-dimensional computed tomography Multidetector computed tomography Wrist injury Kinematics Joint instability 

Abbreviations

CF

Clenched fist

CV

Coefficient of variation

CT

Computerized tomography

CTDIvol

CT dose index

DLP

Dose–length product

ICC

Intraclass correlation coefficient

kV

Kilovolts

mGy

Milligray

MRI

Magnetic resonance imaging

mAs

Milliampere-second

Max

Maximum

RUD

Radial ulnar deviation

SLD

Scapholunate diastasis

SLL

Scapholunate ligament

Se

Sensitivity

Sp

Specificity

Notes

Funding

The authors state that this work has not received any funding.

Compliance with ethical standards

Guarantor

The scientific guarantor of this publication is Pedro Augusto Gondim Teixeira.

Conflict of interest

Two authors involved in this work (Pedro Augusto Gondim Teixeira and Alain Blum) participate on a non-remunerated research contract with TOSHIBA Medical Systems for the development and clinical testing of post-processing tools for musculoskeletal CT. The other authors have no potential conflicts of interest to disclose.

Statistics and biometry

No complex statistical methods were necessary for this paper.

Informed consent

Written informed consent was obtained from all subjects (patients) in this study.

Ethical approval

Institutional review board approval was obtained.

Methodology

• prospective

• diagnostic or prognostic study

• performed at one institution

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Copyright information

© European Society of Radiology 2018

Authors and Affiliations

  1. 1.Guilloz Imaging Department, Central HospitalUniversity Hospital Center of NancyNancy cedexFrance
  2. 2.Nuclear Medecine Department, Central HospitalUniversity Hospital Center of NancyNancy cedexFrance
  3. 3.Centre Chirurgical Emile GalléNancyFrance
  4. 4.Lorraine University, IADI laboratory, UMR S 947Vandoeuvre-lès-NancyFrance

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