Acceleration of conventional data acquisition in dynamic contrast enhancement: Comparing keyhole approaches with compressive sensing

Sairam Geethanath, Praveen K. Gulaka, Vikram Kodibagkar

Research output: Contribution to journalArticle

2 Citations (Scopus)

Abstract

Dynamic contrast-enhanced (DCE) magnetic resonance imaging (MRI) has become a valuable clinical tool for cancer diagnosis and prognosis. DCE MRI provides pharmacokinetic parameters dependent on the extravasation of small molecular contrast agents, and thus high temporal resolution and/or spatial resolution is required for accurate estimation of parameters. In this article we investigate the efficacy of 2 under sampling approaches to speed up DCE MRI: a conventional keyhole approach and compressed sensing–based imaging. Data reconstructed from variants of these methods has been compared with the full k-space reconstruction with respect to data quality and pharmacokinetic parameters K<sup>trans</sup> and v<inf>e</inf>. Overall, compressive sensing provides better data quality and reproducible parametric maps than key-hole methods with higher acceleration factors. In particular, an under sampling mask based on a priori precontrast data showed high fidelity of reconstructed data and parametric maps up to 5× acceleration.

Original languageEnglish (US)
Pages (from-to)437-450
Number of pages14
JournalCritical Reviews in Biomedical Engineering
Volume42
Issue number6
DOIs
StatePublished - Jun 26 2015

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Data acquisition
Magnetic resonance
Imaging techniques
Pharmacokinetics
Sampling
Masks

Keywords

  • Compressed sensing
  • Dynamic contrast-enhanced MRI
  • Keyhole
  • Parametric mapping

ASJC Scopus subject areas

  • Biomedical Engineering

Cite this

Acceleration of conventional data acquisition in dynamic contrast enhancement : Comparing keyhole approaches with compressive sensing. / Geethanath, Sairam; Gulaka, Praveen K.; Kodibagkar, Vikram.

In: Critical Reviews in Biomedical Engineering, Vol. 42, No. 6, 26.06.2015, p. 437-450.

Research output: Contribution to journalArticle

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