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 ArabEmail author
  • Aymeric Rauch
  • Mohammad B. Chawki
  • Francois Dap
  • Gilles Dautel
  • Alain Blum
  • Pedro Augusto Gondim Teixeira
Computed Tomography



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.


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.


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).


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.


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



Clenched fist


Coefficient of variation


Computerized tomography


CT dose index


Dose–length product


Intraclass correlation coefficient






Magnetic resonance imaging






Radial ulnar deviation


Scapholunate diastasis


Scapholunate ligament







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

Compliance with ethical standards


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.


• prospective

• diagnostic or prognostic study

• performed at one institution


  1. 1.
    Kitay A, Wolfe SW (2012) Scapholunate instability: current concepts in diagnosis and management. J Hand Surg Am 37:2175–2196CrossRefGoogle Scholar
  2. 2.
    Lee DH, Dickson KF, Bradley EL (2004) The incidence of wrist interosseous ligament and triangular fibrocartilage articular disc disruptions: a cadaveric study. J Hand Surg Am 29:676–684CrossRefGoogle Scholar
  3. 3.
    Kuo CE, Wolfe SW (2008) Scapholunate instability: current concepts in diagnosis and management. J Hand Surg Am 33:998–1013CrossRefGoogle Scholar
  4. 4.
    Schimmerl-Metz SM, Metz VM, Totterman SM et al (1999) Radiologic measurement of the scapholunate joint: implications of biologic variation in scapholunate joint morphology. J Hand Surg Am 24:1237–1244CrossRefGoogle Scholar
  5. 5.
    Cautilli GP, Wehbé MA (1991) Scapho-lunate distance and cortical ring sign. J Hand Surg Am 16:501–503CrossRefGoogle Scholar
  6. 6.
    Pliefke J, Stengel D, Rademacher G et al (2008) Diagnostic accuracy of plain radiographs and cineradiography in diagnosing traumatic scapholunate dissociation. Skeletal Radiol 37:139–145CrossRefGoogle Scholar
  7. 7.
    Kwon BC, Baek GH (2008) Fluoroscopic diagnosis of scapholunate interosseous ligament injuries in distal radius fractures. Clin Orthop Relat Res 466:969–976CrossRefGoogle Scholar
  8. 8.
    Lee YH, Choi YR, Kim S et al (2013) Intrinsic ligament and triangular fibrocartilage complex (TFCC) tears of the wrist: comparison of isovolumetric 3D-THRIVE sequence MR arthrography and conventional MR image at 3 T. Magn Reson Imaging 31:221–226CrossRefGoogle Scholar
  9. 9.
    Gondim Teixeira PA, Formery A-S, Jacquot A et al (2017) Quantitative analysis of subtalar joint motion with 4D CT: proof of concept with cadaveric and healthy subject evaluation. AJR Am J Roentgenol 208:150–158CrossRefGoogle Scholar
  10. 10.
    Demehri S, Hafezi-Nejad N, Morelli JN et al (2016) Scapholunate kinematics of asymptomatic wrists in comparison with symptomatic contralateral wrists using four-dimensional CT examinations: initial clinical experience. Skeletal Radiol 45:437–446CrossRefGoogle Scholar
  11. 11.
    Mat Jais IS, Tay SC (2017) Kinematic analysis of the scaphoid using gated four-dimensional CT. Clin Radiol 72:794.e1–794.e9CrossRefGoogle Scholar
  12. 12.
    Shores JT, Demehri S, Chhabra A (2013) Kinematic “4 dimensional” CT imaging in the assessment of wrist biomechanics before and after surgical repair. Eplasty 13:e9PubMedPubMedCentralGoogle Scholar
  13. 13.
    Leng S, Zhao K, Qu M et al (2011) Dynamic CT technique for assessment of wrist joint instabilities. Med Phys 38:S50CrossRefGoogle Scholar
  14. 14.
    Kakar S, Breighner RE, Leng S et al (2016) The role of dynamic (4D) CT in the detection of scapholunate ligament injury. J Wrist Surg 5:306–310CrossRefGoogle Scholar
  15. 15.
    Gervaise A, Osemont B, Lecocq S et al (2012) CT image quality improvement using Adaptive Iterative Dose Reduction with wide-volume acquisition on 320-detector CT. Eur Radiol 22:295–301CrossRefGoogle Scholar
  16. 16.
    Garcia-Elias M, Alomar Serrallach X, Monill Serra J (2014) Dart-throwing motion in patients with scapholunate instability: a dynamic four-dimensional computed tomography study. J Hand Surg Am Eur Vol 39:346–352CrossRefGoogle Scholar
  17. 17.
    Gondim Teixeira PA, Formery A-S, Hossu G et al (2017) Evidence-based recommendations for musculoskeletal kinematic 4D-CT studies using wide area-detector scanners: a phantom study with cadaveric correlation. Eur Radiol 27:437–446CrossRefGoogle Scholar
  18. 18.
    Peymani A, Foumani M, Dobbe JGG et al (2017) Four-dimensional rotational radiographic scanning of the wrist in patients after proximal row carpectomy. J Hand Surg Am Eur 42:846–851CrossRefGoogle Scholar
  19. 19.
    Foumani M, Strackee SD, Stekelenburg CM et al (2015) Dynamic in vivo evaluation of radiocarpal contact after a 4-corner arthrodesis. J Hand Surg Am 40:759–766CrossRefGoogle Scholar
  20. 20.
    Foumani M, Strackee SD, van de Giessen M et al (2013) In-vivo dynamic and static three-dimensional joint space distance maps for assessment of cartilage thickness in the radiocarpal joint. Clin Biomech (Bristol, Avon) 28:151–156CrossRefGoogle Scholar
  21. 21.
    Halpenny D, Courtney K, Torreggiani WC (2012) Dynamic four-dimensional 320 section CT and carpal bone injury—a description of a novel technique to diagnose scapholunate instability. Clin Radiol 67:185–187CrossRefGoogle Scholar
  22. 22.
    Lombard C, Gervaise A, Villani N et al (2018) The impact of dose reduction in quantitative kinematic CT of ankle joints using a full model based iterative reconstruction algorithm: a cadaveric study. AJR Am J Roentgenol 210:396–403CrossRefGoogle Scholar
  23. 23.
    Bille B, Harley B, Cohen H (2007) A comparison of CT arthrography of the wrist to findings during wrist arthroscopy. J Hand Surg Am 32:834–841CrossRefGoogle Scholar
  24. 24.
    Forsberg D, Lindblom M, Quick P, Gauffin H (2016) Quantitative analysis of the patellofemoral motion pattern using semi-automatic processing of 4D CT data. Int J Comput Assist Radiol Surg 11:1731–1741CrossRefGoogle Scholar
  25. 25.
    Gondim Teixeira PA, Badr S, Hossu G et al (2017) Quantitative analysis of scapholunate diastasis using stress speckle-tracking sonography: a proof-of-concept and feasibility study. Eur Radiol 27:5344–5351CrossRefGoogle Scholar

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

Personalised recommendations