Psychiatry Research: Neuroimaging
Volume 182, Issue 1 , Pages 40-47, 30 April 2010

Improving 1H MRSI measurement of cerebral lactate for clinical applications

  • Neva M. Corrigan

      Affiliations

    • Department of Radiology, University of Washington, Seattle, WA, USA
    • Corresponding Author InformationCorresponding author. Neuroimaging Research Group, Department of Radiology, University of Washington, 1100 NE 45th St. Suite 555, Seattle, WA, 98105, USA. Tel.: +1 206 685 8404; fax: +1 206 616 7791.
  • ,
  • Todd L. Richards

      Affiliations

    • Department of Radiology, University of Washington, Seattle, WA, USA
  • ,
  • Seth D. Friedman

      Affiliations

    • Seattle Children's Hospital, Seattle, WA, USA
  • ,
  • Helen Petropoulos

      Affiliations

    • Department of Radiology, University of Washington, Seattle, WA, USA
  • ,
  • Stephen R. Dager

      Affiliations

    • Department of Radiology, University of Washington, Seattle, WA, USA

Received 14 August 2009; received in revised form 10 November 2009; accepted 16 November 2009.

Abstract 

Accurate measurement of cerebral lactate is critical to the understanding of brain function for psychiatric disorders such as panic disorder and bipolar disorder as well as mitochondrial dysfunction. Proton magnetic spectroscopic imaging (MRSI) techniques can be used to study lactate in vivo; however, accurate measurement of cerebral lactate, which is normally at low basal abundance, can be challenging. In this study, regional lactate measurements obtained with two different MRSI analytic approaches were evaluated using proton echo-planar spectroscopic imaging (PEPSI) data from 18 healthy adults participating in an in vivo sodium lactate infusion study. The results demonstrate that averaging data within a region of interest (ROI) before spectral fitting with LCModel results in significantly improved lactate measurement as compared to averaging chemical concentrations derived from the fitting of individual voxels in the ROI. Simulation results that confirm this finding are also presented. This study additionally outlines an atlas-based approach for the systematic computation of regional distributions of chemical concentrations in large MRSI data sets.

Keywords: Magnetic resonance spectroscopy, Brain bioenergetics, Neuronal metabolism, Panic disorder

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PII: S0925-4927(09)00276-5

doi:10.1016/j.pscychresns.2009.11.007

Psychiatry Research: Neuroimaging
Volume 182, Issue 1 , Pages 40-47, 30 April 2010