Ebru Baykara1, Benno Gesierich1, Ruth Adam1, Anil Man Tuladhar2, J Matthijs Biesbroek3, Huiberdina L Koek4, Stefan Ropele5, Eric Jouvent6,7,8, Hugues Chabriat6,7,8, Birgit Ertl-Wagner9, Michael Ewers1, Reinhold Schmidt5, Frank-Erik de Leeuw2, Geert Jan Biessels3, Martin Dichgans1,10,11, Marco Duering12. 1. Institute for Stroke and Dementia Research, Klinikum der Universität München, Ludwig-Maximilians-University LMU, Munich, Germany. 2. Radboud University Medical Center, Donders Institute for Brain, Cognition, and Behavior, Department of Neurology, Nijmegen, the Netherlands. 3. Department of Neurology, Brain Center Rudolf Magnus, University Medical Center Utrecht, Utrecht, the Netherlands. 4. Department of Geriatrics, University Medical Center Utrecht, Utrecht, the Netherlands. 5. Department of Neurology, Medical University of Graz, Graz, Austria. 6. Université Paris Diderot, Sorbonne Paris Cité, UMR-S 1161 National Institute for Health and Medical Research (INSERM), Paris, France. 7. Departement Hospitalo-Universitaire NeuroVasc Sorbonne Paris Cité, Paris, France. 8. Department of Neurology, Lariboisière Hospital, Assistance Publique - Hôpitaux de Paris, Paris, France. 9. Institute of Clinical Radiology, Klinikum der Universität München, Ludwig-Maximilians-University LMU, Munich, Germany. 10. Munich Cluster for Systems Neurology (SyNergy), Munich, Germany. 11. German Center for Neurodegenerative Diseases (DZNE), Munich, Germany. 12. Institute for Stroke and Dementia Research, Klinikum der Universität München, Ludwig-Maximilians-University LMU, Munich, Germany. marco.duering@med.uni-muenchen.de.
Abstract
OBJECTIVE: To establish a fully automated, robust imaging marker for cerebral small vessel disease (SVD) and related cognitive impairment that is easy to implement, reflects disease burden, and is strongly associated with processing speed, the predominantly affected cognitive domain in SVD. METHODS: We developed a novel magnetic resonance imaging marker based on diffusion tensor imaging, skeletonization of white matter tracts, and histogram analysis. The marker (peak width of skeletonized mean diffusivity [PSMD]) was assessed along with conventional SVD imaging markers. We first evaluated associations with processing speed in patients with genetically defined SVD (n = 113). Next, we validated our findings in independent samples of inherited SVD (n = 57), sporadic SVD (n = 444), and memory clinic patients with SVD (n = 105). The new marker was further applied to healthy controls (n = 241) and to patients with Alzheimer's disease (n = 153). We further conducted a longitudinal analysis and interscanner reproducibility study. RESULTS: PSMD was associated with processing speed in all study samples with SVD (p-values between 2.8 × 10(-3) and 1.8 × 10(-10) ). PSMD explained most of the variance in processing speed (R(2) ranging from 8.8% to 46%) and consistently outperformed conventional imaging markers (white matter hyperintensity volume, lacune volume, and brain volume) in multiple regression analyses. Increases in PSMD were linked to vascular but not to neurodegenerative disease. In longitudinal analysis, PSMD captured SVD progression better than other imaging markers. INTERPRETATION: PSMD is a new, fully automated, and robust imaging marker for SVD. PSMD can easily be applied to large samples and may be of great utility for both research studies and clinical use. Ann Neurol 2016;80:581-592.
OBJECTIVE: To establish a fully automated, robust imaging marker for cerebral small vessel disease (SVD) and related cognitive impairment that is easy to implement, reflects disease burden, and is strongly associated with processing speed, the predominantly affected cognitive domain in SVD. METHODS: We developed a novel magnetic resonance imaging marker based on diffusion tensor imaging, skeletonization of white matter tracts, and histogram analysis. The marker (peak width of skeletonized mean diffusivity [PSMD]) was assessed along with conventional SVD imaging markers. We first evaluated associations with processing speed in patients with genetically defined SVD (n = 113). Next, we validated our findings in independent samples of inherited SVD (n = 57), sporadic SVD (n = 444), and memory clinic patients with SVD (n = 105). The new marker was further applied to healthy controls (n = 241) and to patients with Alzheimer's disease (n = 153). We further conducted a longitudinal analysis and interscanner reproducibility study. RESULTS: PSMD was associated with processing speed in all study samples with SVD (p-values between 2.8 × 10(-3) and 1.8 × 10(-10) ). PSMD explained most of the variance in processing speed (R(2) ranging from 8.8% to 46%) and consistently outperformed conventional imaging markers (white matter hyperintensity volume, lacune volume, and brain volume) in multiple regression analyses. Increases in PSMD were linked to vascular but not to neurodegenerative disease. In longitudinal analysis, PSMD captured SVD progression better than other imaging markers. INTERPRETATION: PSMD is a new, fully automated, and robust imaging marker for SVD. PSMD can easily be applied to large samples and may be of great utility for both research studies and clinical use. Ann Neurol 2016;80:581-592.
Authors: Adam M Staffaroni; Fanny M Elahi; Dana McDermott; Kacey Marton; Elissaios Karageorgiou; Simone Sacco; Matteo Paoletti; Eduardo Caverzasi; Christopher P Hess; Howard J Rosen; Michael D Geschwind Journal: Semin Neurol Date: 2017-12-05 Impact factor: 3.420
Authors: François De Guio; Marco Duering; Franz Fazekas; Frank-Erik De Leeuw; Steven M Greenberg; Leonardo Pantoni; Agnès Aghetti; Eric E Smith; Joanna Wardlaw; Eric Jouvent Journal: J Cereb Blood Flow Metab Date: 2019-11-20 Impact factor: 6.200
Authors: Marco Duering; Ruth Adam; Frank A Wollenweber; Anna Bayer-Karpinska; Ebru Baykara; Leidy Y Cubillos-Pinilla; Benno Gesierich; Miguel Á Araque Caballero; Sophia Stoecklein; Michael Ewers; Ofer Pasternak; Martin Dichgans Journal: J Cereb Blood Flow Metab Date: 2019-07-25 Impact factor: 6.200
Authors: J Matthijs Biesbroek; Alexander Leemans; Hanna den Bakker; Marco Duering; Benno Gesierich; Huiberdina L Koek; Esther van den Berg; Albert Postma; Geert Jan Biessels Journal: Dement Geriatr Cogn Disord Date: 2018-01-19 Impact factor: 2.959
Authors: Costantino Iadecola; Marco Duering; Vladimir Hachinski; Anne Joutel; Sarah T Pendlebury; Julie A Schneider; Martin Dichgans Journal: J Am Coll Cardiol Date: 2019-07-02 Impact factor: 24.094