Evolution of white matter hyperintensity segmentation methods and implementation over the past two decades; an incomplete shift towards deep learning.

Journal: Brain imaging and behavior
PMID: 39083144

Abstract

This systematic review examines the prevalence, underlying mechanisms, cohort characteristics, evaluation criteria, and cohort types in white matter hyperintensity (WMH) pipeline and implementation literature spanning the last two decades. Following Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) guidelines, we categorized WMH segmentation tools based on their methodologies from January 1, 2000, to November 18, 2022. Inclusion criteria involved articles using openly available techniques with detailed descriptions, focusing on WMH as a primary outcome. Our analysis identified 1007 visual rating scales, 118 pipeline development articles, and 509 implementation articles. These studies predominantly explored aging, dementia, psychiatric disorders, and small vessel disease, with aging and dementia being the most prevalent cohorts. Deep learning emerged as the most frequently developed segmentation technique, indicative of a heightened scrutiny in new technique development over the past two decades. We illustrate observed patterns and discrepancies between published and implemented WMH techniques. Despite increasingly sophisticated quantitative segmentation options, visual rating scales persist, with the SPM technique being the most utilized among quantitative methods and potentially serving as a reference standard for newer techniques. Our findings highlight the need for future standards in WMH segmentation, and we provide recommendations based on these observations.

Authors

  • Maryam Rahmani
    Advanced Diagnostic and Interventional Radiology Research Center (ADIR), Radiology Department, Imam Khomeini Hospital Complex (IKHC), Tehran University of Medical Sciences (TUMS), Tehran, No. 1419733141, Iran.
  • Donna Dierker
    Mallinckrodt Institute of Radiology, Washington University School of Medicine, St. Louis, MO, USA.
  • Lauren Yaeger
  • Andrew Saykin
    Department School of Medicine, Indiana University, Bloomington, IN, USA.
  • Patrick H Luckett
    Washington University in St. Louis, St. Louis, Missouri, USA.
  • Andrei G Vlassenko
    Mallinckrodt Institute of Radiology, Washington University School of Medicine, St. Louis, MO, USA.
  • Christopher Owens
    Mallinckrodt Institute of Radiology, Washington University School of Medicine, St. Louis, MO, USA.
  • Hussain Jafri
    Mallinckrodt Institute of Radiology, Washington University School of Medicine, St. Louis, MO, USA.
  • Kyle Womack
    Department of Neurology, Washington University School of Medicine, St. Louis, MO, USA.
  • Jurgen Fripp
    CSIRO Health and Biosecurity, Australian e-Health Research Centre CSIRO, Brisbane, Queensland, Australia.
  • Ying Xia
    Australian e-Health Research Centre, CSIRO, Brisbane, QLD, 4029, Australia.
  • Duygu Tosun
    Department of Radiology and Biomedical Imaging, University of California, San Francisco, San Francisco, CA, USA.
  • Tammie L S Benzinger
    Mallinckrodt Institute of Radiology, Washington University School of Medicine, St. Louis, MO, USA.
  • Colin L Masters
    Florey Institute, The University of Melbourne, Parkville, VIC, 3052, Australia.
  • Jin-Moo Lee
    Department of Neurology, Washington University School of Medicine, Saint Louis, Missouri; Department of Radiology, Washington University School of Medicine, Saint Louis, Missouri. Electronic address: leejm@wustl.edu.
  • John C Morris
    Knight Alzheimer Disease Research Center, Washington University in St. Louis, St. Louis, MO, USA.
  • Manu S Goyal
    Mallinckrodt Institute of Radiology, Washington University School of Medicine, St. Louis, MO, USA.
  • Jeremy F Strain
    Department of Neurology, Washington University School of Medicine, Saint Louis, MO; and.
  • Walter Kukull
  • Michael Weiner
    Department of Psychiatry, University of California, San Francisco and San Francisco VA Medical Center, San Francisco, CA, USA.
  • Samantha Burnham
  • Tim James CoxDoecke
  • Victor Fedyashov
  • Rosita Shishegar
  • Chengjie Xiong
    Washington University in St. Louis, St. Louis, Missouri, USA.
  • Daniel Marcus
  • Parnesh Raniga
    Australian e-Health Research Centre, CSIRO, Brisbane, QLD, 4029, Australia.
  • Shenpeng Li
    Monash Biomedical Imaging, Monash University, Building 220, Clayton Campus, 770 Blackburn Rd, Clayton, Victoria, 3168, Australia.
  • Andrew Aschenbrenner
  • Jason Hassenstab
    Department of Neurology, Washington University in St. Louis, MO, USA; Psychological & Brain Sciences, Washington University in St. Louis, MO, USA.
  • Yen Ying Lim
    The Florey Institute, The University of Melbourne, Parkville, Victoria, Australia.
  • Paul Maruff
    Florey Institute, The University of Melbourne, Parkville, VIC, 3052, Australia.
  • Hamid Sohrabi
  • Jo Robertson
  • Shaun Markovic
  • Pierrick Bourgeat
    CSIRO Health and Biosecurity, The Australian e-Health & Research Centre, Herston, QLD, Australia. Electronic address: pierrick.bourgeat@csiro.au.
  • Vincent DorĂ©
  • Clifford Jack Mayo
  • Parinaz Mussoumzadeh
  • Chris Rowe
  • Victor Villemagne
  • Randy Bateman
  • Chris Fowler
  • Qiao-Xin Li
    State Key Laboratory of Pathogenesis, Prevention, Treatment of Central Asian High Incidence Diseases, First Affiliated Hospital of Xinjiang Medical University, Urumqi, China.
  • Ralph Martins
  • Suzanne Schindler
    Department of Neurology, Washington University in St. Louis, St. Louis, Missouri, USA.
  • Les Shaw
  • Carlos Cruchaga
    Washington University in St. Louis, St. Louis, Missouri, USA.
  • Oscar Harari
  • Simon Laws
  • Tenielle Porter
  • Eleanor O'Brien
  • Richard Perrin
  • Eric McDade
    Knight Alzheimer's Disease Research Center, Washington University in St. Louis, St. Louis, Missouri, USA.
  • Clifford Jack
  • John Morris
    Virginia C. Crawford Research Institute, Shepherd Center, Atlanta, GA 30309, USA.
  • Nawaf Yassi
  • Blaine Roberts
  • Benjamin Goudey
    Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, The University of Melbourne, Parkville, Victoria, Australia.

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