Frontiers in Psychiatry (Jan 2023)

Performance evaluation of automated white matter hyperintensity segmentation algorithms in a multicenter cohort on cognitive impairment and dementia

  • Malo Gaubert,
  • Malo Gaubert,
  • Andrea Dell’Orco,
  • Andrea Dell’Orco,
  • Catharina Lange,
  • Catharina Lange,
  • Antoine Garnier-Crussard,
  • Antoine Garnier-Crussard,
  • Antoine Garnier-Crussard,
  • Isabella Zimmermann,
  • Martin Dyrba,
  • Marco Duering,
  • Gabriel Ziegler,
  • Oliver Peters,
  • Oliver Peters,
  • Lukas Preis,
  • Josef Priller,
  • Josef Priller,
  • Josef Priller,
  • Josef Priller,
  • Eike Jakob Spruth,
  • Eike Jakob Spruth,
  • Anja Schneider,
  • Anja Schneider,
  • Klaus Fliessbach,
  • Klaus Fliessbach,
  • Jens Wiltfang,
  • Jens Wiltfang,
  • Jens Wiltfang,
  • Björn H. Schott,
  • Björn H. Schott,
  • Björn H. Schott,
  • Franziska Maier,
  • Wenzel Glanz,
  • Katharina Buerger,
  • Katharina Buerger,
  • Daniel Janowitz,
  • Robert Perneczky,
  • Robert Perneczky,
  • Robert Perneczky,
  • Robert Perneczky,
  • Robert Perneczky,
  • Boris-Stephan Rauchmann,
  • Stefan Teipel,
  • Stefan Teipel,
  • Ingo Kilimann,
  • Ingo Kilimann,
  • Christoph Laske,
  • Christoph Laske,
  • Matthias H. Munk,
  • Matthias H. Munk,
  • Annika Spottke,
  • Annika Spottke,
  • Nina Roy,
  • Laura Dobisch,
  • Michael Ewers,
  • Peter Dechent,
  • John Dylan Haynes,
  • Klaus Scheffler,
  • Emrah Düzel,
  • Emrah Düzel,
  • Frank Jessen,
  • Frank Jessen,
  • Frank Jessen,
  • Miranka Wirth,
  • for the DELCODE study group,
  • Amthauer Holger,
  • Cetindag Arda Can,
  • Cosma Nicoleta Carmen,
  • Diesing Dominik,
  • Ehrlich Marie,
  • Fenski Frederike,
  • Freiesleben Silka Dawn,
  • Fuentes Manuel,
  • Hauser Dietmar,
  • Hujer Nicole,
  • Incesoy Enise Irem,
  • Kainz Christian,
  • Lange Catharina,
  • Lindner Katja,
  • Megges Herlind,
  • Peters Oliver,
  • Preis Lukas,
  • Altenstein Slawek,
  • Lohse Andrea,
  • Franke Christiana,
  • Priller Josef,
  • Spruth Eike,
  • Villar Munoz Irene,
  • Barkhoff Miriam,
  • Boecker Henning,
  • Brosseron Frederic,
  • Daamen Marcel,
  • Engels Tanja,
  • Faber Jennifer,
  • Fließbach Klaus,
  • Frommann Ingo,
  • Grobe-Einsler Marcus,
  • Hennes Guido,
  • Herrmann Gabi,
  • Jost Lorraine,
  • Kalbhen Pascal,
  • Kimmich Okka,
  • Kobeleva Xenia,
  • Kofler Barbara,
  • McCormick Cornelia,
  • Miebach Lisa,
  • Miklitz Carolin,
  • Müller Anna,
  • Oender Demet,
  • Polcher Alexandra,
  • Purrer Veronika,
  • Röske Sandra,
  • Schneider Christine,
  • Schneider Anja,
  • Spottke Annika,
  • Vogt Ina,
  • Wagner Michael,
  • wolfsgruber Steffen,
  • Yilmaz Sagik,
  • Bartels Claudia,
  • Dechent Peter,
  • Hansen Niels,
  • Hassoun Lina,
  • Hirschel Sina,
  • Nuhn Sabine,
  • Pfahlert Ilona,
  • Rausch Lena,
  • Schott Björn,
  • Timäus Charles,
  • Werner Christine,
  • Wiltfang Jens,
  • Zabel Lioba,
  • Zech Heike,
  • Bader Abdelmajid,
  • Baldermann Juan Carlos,
  • Dölle Britta,
  • Drzezga Alexander,
  • Escher Claus,
  • Ghiasi Nasim Roshan,
  • Hardenacke Katja,
  • Jessen Frank,
  • Lützerath Hannah,
  • Maier Franziska,
  • Marquardt Benjamin,
  • Martikke Anja,
  • Meiberth Dix,
  • Petzler Snjezana,
  • Rostamzadeh Ayda,
  • Sannemann Lena,
  • Schild Ann-Katrin,
  • Sorgalla Susanne,
  • Stockter Simone,
  • Thelen Manuela,
  • Tscheuschler Maike,
  • Uhle Franziska,
  • Zeyen Philip,
  • Bittner Daniel,
  • Cardenas-Blanco Arturo,
  • Dobisch Laura,
  • Düzel Emrah,
  • Grieger-Klose Doreen,
  • Hartmann Deike,
  • Metzger Coraline,
  • Nestor Peter,
  • Ruß Christin,
  • Schulze Franziska,
  • Speck Oliver,
  • Wenzel Glanz,
  • Yakupov Renat,
  • Ziegler Gabriel,
  • Brauneis Christine,
  • Bürger Katharina,
  • Catak Cihan,
  • Coloma Andrews Lisa,
  • Dichgans Martin,
  • Dörr Angelika,
  • Ertl-Wagner Birgit,
  • Frimmer Daniela,
  • Huber Brigitte,
  • Janowitz Daniel,
  • Kreuzer Max,
  • Markov Eva,
  • Müller Claudia,
  • Rominger Axel,
  • Schmid (ehemals Spreider) Jennifer,
  • Seegerer Anna,
  • Stephan Julia,
  • Zollver Adelgunde,
  • Burow Lena,
  • de Jonge Sylvia,
  • Falkai Peter,
  • Garcia Angarita Natalie,
  • Görlitz Thomas,
  • Gürsel Selim Üstün,
  • Horvath Ildiko,
  • Kurz Carolin,
  • Meisenzahl-Lechner Eva,
  • Perneczky Robert,
  • Utecht Julia,
  • Dyrba Martin,
  • Janecek-Meyer Heike,
  • Kilimann Ingo,
  • Lappe Chris,
  • Lau Esther,
  • Pfaff Henrike,
  • Raum Heike,
  • Sabik Petr,
  • Schmidt Monika,
  • Schulz Heike,
  • Schwarzenboeck Sarah,
  • Teipel Stefan,
  • Weber Marc-Andre,
  • Buchmann Martina,
  • Heger Tanja,
  • Hinderer Petra,
  • Kuder-Buletta Elke,
  • Laske Christoph,
  • Munk Matthias,
  • Mychajliw Christian,
  • Soekadar Surjo,
  • sulzer Patricia,
  • Trunk Theresia

DOI
https://doi.org/10.3389/fpsyt.2022.1010273
Journal volume & issue
Vol. 13

Abstract

Read online

BackgroundWhite matter hyperintensities (WMH), a biomarker of small vessel disease, are often found in Alzheimer’s disease (AD) and their advanced detection and quantification can be beneficial for research and clinical applications. To investigate WMH in large-scale multicenter studies on cognitive impairment and AD, appropriate automated WMH segmentation algorithms are required. This study aimed to compare the performance of segmentation tools and provide information on their application in multicenter research.MethodsWe used a pseudo-randomly selected dataset (n = 50) from the DZNE-multicenter observational Longitudinal Cognitive Impairment and Dementia Study (DELCODE) that included 3D fluid-attenuated inversion recovery (FLAIR) images from participants across the cognitive continuum. Performances of top-rated algorithms for automated WMH segmentation [Brain Intensity Abnormality Classification Algorithm (BIANCA), lesion segmentation toolbox (LST), lesion growth algorithm (LGA), LST lesion prediction algorithm (LPA), pgs, and sysu_media] were compared to manual reference segmentation (RS).ResultsAcross tools, segmentation performance was moderate for global WMH volume and number of detected lesions. After retraining on a DELCODE subset, the deep learning algorithm sysu_media showed the highest performances with an average Dice’s coefficient of 0.702 (±0.109 SD) for volume and a mean F1-score of 0.642 (±0.109 SD) for the number of lesions. The intra-class correlation was excellent for all algorithms (>0.9) but BIANCA (0.835). Performance improved with high WMH burden and varied across brain regions.ConclusionTo conclude, the deep learning algorithm, when retrained, performed well in the multicenter context. Nevertheless, the performance was close to traditional methods. We provide methodological recommendations for future studies using automated WMH segmentation to quantify and assess WMH along the continuum of cognitive impairment and AD dementia.

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