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Clinical Trial
. 2011 Sep;38(9):1715-22.
doi: 10.1007/s00259-011-1850-9. Epub 2011 Jun 7.

Predictive value of brain perfusion SPECT for rTMS response in pharmacoresistant depression

Affiliations
Clinical Trial

Predictive value of brain perfusion SPECT for rTMS response in pharmacoresistant depression

Raphaelle Richieri et al. Eur J Nucl Med Mol Imaging. 2011 Sep.

Abstract

Purpose: The aim of this study was to determine the predictive value of whole-brain voxel-based regional cerebral blood flow (rCBF) for repetitive transcranial magnetic stimulation (rTMS) response in patients with pharmacoresistant depression.

Methods: Thirty-three right-handed patients who met DSM-IV criteria for major depressive disorder (unipolar or bipolar depression) were included before rTMS. rTMS response was defined as at least 50% reduction in the baseline Beck Depression Inventory scores. The predictive value of (99m)Tc-ethyl cysteinate dimer (ECD) single photon emission computed tomography (SPECT) for rTMS response was studied before treatment by comparing rTMS responders to non-responders at voxel level using Statistical Parametric Mapping (SPM) (p < 0.001, uncorrected).

Results: Of the patients, 18 (54.5%) were responders to rTMS and 15 were non-responders (45.5%). There were no statistically significant differences in demographic and clinical characteristics (p > 0.10). In comparison to responders, non-responders showed significant hypoperfusions (p < 0.001, uncorrected) in the left medial and bilateral superior frontal cortices (BA10), the left uncus/parahippocampal cortex (BA20/BA35) and the right thalamus. The area under the curve for the combination of SPECT clusters to predict rTMS response was 0.89 (p < 0.001). Sensitivity, specificity, positive predictive value and negative predictive value for the combination of clusters were: 94, 73, 81 and 92%, respectively.

Conclusion: This study shows that, in pharmacoresistant depression, pretreatment rCBF of specific brain regions is a strong predictor for response to rTMS in patients with homogeneous demographic/clinical features.

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