Medical Image Analysis
Volume 16, Issue 2 , Pages 427-450, February 2012

Temporal diffeomorphic free-form deformation: Application to motion and strain estimation from 3D echocardiography

  • Mathieu De Craene

      Affiliations

    • Center for Computational Imaging & Simulation Technologies in Biomedicine, Information and Communication Technologies Department, Universitat Pompeu Fabra, c/Roc Boronat 138, E08018 Barcelona, Spain
    • Centro de Investigación Biomédica en Red en Bioingeniería, Biomateriales y Nanomedicina (CIBER-BBN), Spain
    • Corresponding Author InformationCorresponding author at: Center for Computational Imaging and Simulation Technologies in Biomedicine, Information and Communication Technologies Department, Universitat Pompeu Fabra, c/Roc Boronat 138, E08018 Barcelona, Spain. Tel.: +34 93 542 1348; fax: +34 93 542 1445.
  • ,
  • Gemma Piella

      Affiliations

    • Center for Computational Imaging & Simulation Technologies in Biomedicine, Information and Communication Technologies Department, Universitat Pompeu Fabra, c/Roc Boronat 138, E08018 Barcelona, Spain
    • Centro de Investigación Biomédica en Red en Bioingeniería, Biomateriales y Nanomedicina (CIBER-BBN), Spain
  • ,
  • Oscar Camara

      Affiliations

    • Center for Computational Imaging & Simulation Technologies in Biomedicine, Information and Communication Technologies Department, Universitat Pompeu Fabra, c/Roc Boronat 138, E08018 Barcelona, Spain
    • Centro de Investigación Biomédica en Red en Bioingeniería, Biomateriales y Nanomedicina (CIBER-BBN), Spain
  • ,
  • Nicolas Duchateau

      Affiliations

    • Center for Computational Imaging & Simulation Technologies in Biomedicine, Information and Communication Technologies Department, Universitat Pompeu Fabra, c/Roc Boronat 138, E08018 Barcelona, Spain
    • Centro de Investigación Biomédica en Red en Bioingeniería, Biomateriales y Nanomedicina (CIBER-BBN), Spain
  • ,
  • Etelvino Silva

      Affiliations

    • Hospital Clínic i Provincial de Barcelona, IDIBAPS, Universitat de Barcelona, Spain
  • ,
  • Adelina Doltra

      Affiliations

    • Hospital Clínic i Provincial de Barcelona, IDIBAPS, Universitat de Barcelona, Spain
  • ,
  • Jan D’hooge

      Affiliations

    • Department of Cardiovascular Diseases, Cardiovascular Imaging and Dynamics, Katholieke Universiteit Leuven, Belgium
  • ,
  • Josep Brugada

      Affiliations

    • Hospital Clínic i Provincial de Barcelona, IDIBAPS, Universitat de Barcelona, Spain
  • ,
  • Marta Sitges

      Affiliations

    • Hospital Clínic i Provincial de Barcelona, IDIBAPS, Universitat de Barcelona, Spain
  • ,
  • Alejandro F. Frangi

      Affiliations

    • Center for Computational Imaging & Simulation Technologies in Biomedicine, Information and Communication Technologies Department, Universitat Pompeu Fabra, c/Roc Boronat 138, E08018 Barcelona, Spain
    • Centro de Investigación Biomédica en Red en Bioingeniería, Biomateriales y Nanomedicina (CIBER-BBN), Spain
    • Department of Mechanical Engineering, The University of Sheffield, Sheffield, UK

Received 16 February 2011; received in revised form 25 October 2011; accepted 25 October 2011. published online 16 November 2011.

Graphical abstract

Quantification of 3D Myocardial strain in one patient undergoing CRT before therapy and at follow-up.

Highlights

► We propose a new diffeomorphic temporal registration algorithm. ► It recovers strain and motion from an input 3D ultrasound image sequence. ► Longitudinal strain was quantified on 9 healthy volunteers and 13 CRT patients. ► On volunteers, results are in agreement with clinical literature. ► On patients, results match CRT outcome as quantified by reverse remodeling.

Abstract 

This paper presents a new registration algorithm, called Temporal Diffeomorphic Free Form Deformation (TDFFD), and its application to motion and strain quantification from a sequence of 3D ultrasound (US) images. The originality of our approach resides in enforcing time consistency by representing the 4D velocity field as the sum of continuous spatiotemporal B-Spline kernels. The spatiotemporal displacement field is then recovered through forward Eulerian integration of the non-stationary velocity field. The strain tensor is computed locally using the spatial derivatives of the reconstructed displacement field. The energy functional considered in this paper weighs two terms: the image similarity and a regularization term. The image similarity metric is the sum of squared differences between the intensities of each frame and a reference one. Any frame in the sequence can be chosen as reference. The regularization term is based on the incompressibility of myocardial tissue. TDFFD was compared to pairwise 3D FFD and 3D+t FFD, both on displacement and velocity fields, on a set of synthetic 3D US images with different noise levels. TDFFD showed increased robustness to noise compared to these two state-of-the-art algorithms. TDFFD also proved to be more resistant to a reduced temporal resolution when decimating this synthetic sequence. Finally, this synthetic dataset was used to determine optimal settings of the TDFFD algorithm. Subsequently, TDFFD was applied to a database of cardiac 3D US images of the left ventricle acquired from 9 healthy volunteers and 13 patients treated by Cardiac Resynchronization Therapy (CRT). On healthy cases, uniform strain patterns were observed over all myocardial segments, as physiologically expected. On all CRT patients, the improvement in synchrony of regional longitudinal strain correlated with CRT clinical outcome as quantified by the reduction of end-systolic left ventricular volume at follow-up (6 and 12months), showing the potential of the proposed algorithm for the assessment of CRT.

Keywords: Spatiotemporal registration, Diffeomorphism, FFD, Strain, 3D ultrasound

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PII: S1361-8415(11)00160-5

doi:10.1016/j.media.2011.10.006

Medical Image Analysis
Volume 16, Issue 2 , Pages 427-450, February 2012