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Modeling brain compartmental lactate response to metabolic challenge: a feasibility study

Magnetic resonance spectroscopy has been used to characterize abnormal brain lactate response in panic disorder (PD) subjects following lactate infusion. The present study integrated water quantification and tissue segmentation to evaluate compartmental lactate response within brain and cerebrospina...

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Bibliographic Details
Published in:Psychiatry research 2000-02, Vol.98 (1), p.55-66
Main Authors: Friedman, Seth D, Dager, Stephen R, Richards, Todd L, Petropoulos, Helen, Posse, Stefan
Format: Article
Language:English
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Summary:Magnetic resonance spectroscopy has been used to characterize abnormal brain lactate response in panic disorder (PD) subjects following lactate infusion. The present study integrated water quantification and tissue segmentation to evaluate compartmental lactate response within brain and cerebrospinal fluid (CSF). As there is evidence of brain parenchymal pH changes during lactate infusion, water scans were collected at baseline and post-infusion to address brain water stability. Water levels remained essentially stable across the protocol suggesting internal water provides an improved reference signal for measuring dynamic changes in response to metabolic challenge paradigms such as lactate infusion. To model brain lactate changes by compartments, we took the null hypothesis that lactate rises occur only in tissue. The approach referenced lactate amplitude (potentially from both compartments) to ‘voxel’ water (water scan corrected for differential T 2 between CSF brain at long-echo times — synonymous to a short-echo water scan). If the magnitude of lactate rise in CSF was equal to or greater than brain, voxels with substantial CSF fractions should demonstrate an equivalent or elevated response to voxels comprised only of tissue. The magnitude of lactate increases paralleled voxel tissue fraction suggesting the abnormal lactate rise observed in PD is tissue-based. The feasibility of lactate quantification and compartmental modeling are discussed.
ISSN:0925-4927
0165-1781
1872-7506
DOI:10.1016/S0925-4927(99)00053-0