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Brain Struct Funct. 2019 Nov;224(8):2823-2838. doi: 10.1007/s00429-019-01936-3. Epub 2019 Aug 21.

Improving sensitivity, specificity, and reproducibility of individual brainstem activation.

Author information

1
Department of Neurology, Medical University of Vienna, Spitalgasse 23, 1090, Vienna, Austria.
2
High Field Magnetic Resonance Centre, Medical University of Vienna, Spitalgasse 23, 1090, Vienna, Austria.
3
Institute of Psychology, University of Graz, Universitätsplatz 3, 8010, Graz, Austria.
4
Department of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna, Spitalgasse 23, 1090, Vienna, Austria.
5
Department of Neuroradiology, Medical University of Innsbruck, Anichstraße 35, 6020, Innsbruck, Austria.
6
Department of Neurology, Medical University of Vienna, Spitalgasse 23, 1090, Vienna, Austria. roland.beisteiner@meduniwien.ac.at.
7
High Field Magnetic Resonance Centre, Medical University of Vienna, Spitalgasse 23, 1090, Vienna, Austria. roland.beisteiner@meduniwien.ac.at.

Abstract

Functional imaging of the brainstem may open new avenues for clinical diagnostics. However, for reliable assessments of brainstem activation, further efforts improving signal quality are needed. Six healthy subjects performed four repeated functional magnetic resonance imaging (fMRI) sessions on different days with jaw clenching as a motor task to elicit activation in the trigeminal motor nucleus. Functional images were acquired with a 7 T MR scanner using an optimized multiband EPI sequence. Activation measures in the trigeminal nucleus and a control region were assessed using different physiological noise correction methods (aCompCor and RETROICOR-based approaches with variable numbers of regressors) combined with cerebrospinal fluid or brainstem masking. Receiver-operating characteristic analyses accounting for sensitivity and specificity, activation overlap analyses to estimate the reproducibility between sessions, and intraclass correlation analyses (ICC) for testing reliability between subjects and sessions were used to systematically compare the physiological noise correction approaches. Masking the brainstem led to increased activation in the target ROI and resulted in higher values for the area under the curve (AUC) as a combined measure for sensitivity and specificity. With the highest values for AUC, activation overlap, and ICC, the most favorable physiological noise correction method was to control for the cerebrospinal fluid time series (aCompCor with one regressor). Brainstem motor nuclei activation can be reliably identified using high-field fMRI with optimized acquisition and processing strategies-even on single-subject level. Applying specific physiological noise correction methods improves reproducibility and reliability of brainstem activation encouraging future clinical applications.

KEYWORDS:

Brainstem; Functional magnetic resonance imaging; Physiological noise; Reliability; Reproducibility; Trigeminal motor nucleus

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