Validation of the automated method VIENA: An accurate, precise, and robust measure of ventricular enlargement

Authors

  • Hugo Vrenken,

    Corresponding author
    1. Department of Radiology, Neuroscience Campus Amsterdam, VU University Medical Center, Amsterdam, The Netherlands
    2. Department of Physics and Medical Technology, Neuroscience Campus Amsterdam, VU University Medical Center, Amsterdam, The Netherlands
    • Departments of Radiology and Physics and Medical Technology, VU University Medical Center, De Boelelaan 1118, 1081 HZ Amsterdam, The Netherlands. E-mail: H.Vrenken@vumc.nl

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  • Eline K. Vos,

    1. Department of Radiology, Neuroscience Campus Amsterdam, VU University Medical Center, Amsterdam, The Netherlands
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  • W.M. van der Flier,

    1. Alzheimer Center, Neuroscience Campus Amsterdam, VU University Medical Center, Amsterdam, The Netherlands
    2. Department of Neurology, Neuroscience Campus Amsterdam, VU University Medical Center, Amsterdam, The Netherlands
    3. Department of Epidemiology and Biostatistics, Neuroscience Campus Amsterdam, VU University Medical Center, Amsterdam, The Netherlands
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  • Ingrid C. Sluimer,

    1. Department of Radiology, Neuroscience Campus Amsterdam, VU University Medical Center, Amsterdam, The Netherlands
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  • Keith S. Cover,

    1. Department of Physics and Medical Technology, Neuroscience Campus Amsterdam, VU University Medical Center, Amsterdam, The Netherlands
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  • Dirk L. Knol,

    1. Department of Epidemiology and Biostatistics, Neuroscience Campus Amsterdam, VU University Medical Center, Amsterdam, The Netherlands
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  • Frederik Barkhof

    1. Department of Radiology, Neuroscience Campus Amsterdam, VU University Medical Center, Amsterdam, The Netherlands
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Abstract

Background: In many retrospective studies and large clinical trials, high-resolution, good-contrast 3DT1 images are unavailable, hampering detailed analysis of brain atrophy. Ventricular enlargement then provides a sensitive indirect measure of ongoing central brain atrophy. Validated automated methods are required that can reliably measure ventricular enlargement and are robust across magnetic resonance (MR) image types. Aim: To validate the automated method VIENA for measuring the percentage ventricular volume change (PVVC) between two scans. Materials and Methods: Accuracy was assessed using four image types, acquired in 15 elderly patients (five with Alzheimer's disease, five with mild cognitive impairment, and five cognitively normal elderly) and 58 patients with multiple sclerosis (MS), by comparing PVVC values from VIENA to manual outlining. Precision was assessed from data with three imaging time points per MS patient, by measuring the difference between the direct (one-step) and indirect (two-step) measurement of ventricular volume change between the first and last time points. The stringent concordance correlation coefficient (CCC) was used to quantify absolute agreement. Results: CCC of VIENA with manual measurement was 0.84, indicating good absolute agreement. The median absolute difference between two-step and one-step measurement with VIENA was 1.01%, while CCC was 0.98. Neither initial ventricular volume nor ventricular volume change affected performance of the method. Discussion: VIENA has good accuracy and good precision across four image types. VIENA therefore provides a useful fully automated method for measuring ventricular volume change in large datasets. Conclusion: VIENA is a robust, accurate, and precise method for measuring ventricular volume change. Hum Brain Mapp 35:1101–1110, 2014. © 2013 Wiley Periodicals, Inc.

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