Functional MRI in major depressive disorder: A review of findings, limitations, and future prospects

Jesper Pilmeyer*, Willem Huijbers, Rolf Lamerichs, Jacobus F A Jansen, Marcel Breeuwer, Svitlana Zinger

*Corresponding author for this work

Research output: Contribution to journal(Systematic) Review article peer-review

Abstract

Objective diagnosis and prognosis in major depressive disorder (MDD) remains a challenge due to the absence of biomarkers based on physiological parameters or medical tests. Numerous studies have been conducted to identify functional magnetic resonance imaging-based biomarkers of depression that either objectively differentiate patients with depression from healthy subjects, predict personalized treatment outcome, or characterize biological subtypes of depression. While there are some findings of consistent functional biomarkers, there is still lack of robust data acquisition and analysis methodology. According to current findings, primarily, the anterior cingulate cortex, prefrontal cortex, and default mode network play a crucial role in MDD. Yet, there are also less consistent results and the involvement of other regions or networks remains ambiguous. We further discuss image acquisition, processing, and analysis limitations that might underlie these inconsistencies. Finally, the current review aims to address and discuss possible remedies and future opportunities that could improve the search for consistent functional imaging biomarkers of depression. Novel acquisition techniques, such as multiband and multiecho imaging, and neural network-based cleaning approaches can enhance the signal quality in limbic and frontal regions. More comprehensive analyses, such as directed or dynamic functional features or the identification of biological depression subtypes, can improve objective diagnosis or treatment outcome prediction and mitigate the heterogeneity of MDD. Overall, these improvements in functional MRI imaging techniques, processing, and analysis could advance the search for biomarkers and ultimately aid patients with MDD and their treatment course.

Original languageEnglish
Pages (from-to)582-595
Number of pages14
JournalJournal of Neuroimaging
Volume32
Issue number4
Early online date21 May 2022
DOIs
Publication statusPublished - Jul 2022

Keywords

  • AMYGDALA REACTIVITY
  • ANTIDEPRESSANT TREATMENT
  • COMPONENT ANALYSIS
  • EFFECTIVE CONNECTIVITY
  • IMAGING BIOMARKERS
  • MOTION ARTIFACTS
  • MRI
  • NETWORK DYSFUNCTION
  • PHYSIOLOGICAL NOISE
  • REGIONAL HOMOGENEITY
  • UNIPOLAR DEPRESSION
  • biomarkers
  • major depressive disorder
  • review

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