Progressive multifocal leukoencephalopathy lesion and brain parenchymal segmentation from MRI using serial deep convolutional neural networks.

Journal: NeuroImage. Clinical
Published Date: Jan 1, 2020

Abstract

Progressive multifocal leukoencephalopathy (PML) is a rare opportunistic brain infection caused by the JC virus and associated with substantial morbidity and mortality. Accurate MRI assessment of PML lesion burden and brain parenchymal atrophy is of decisive value in monitoring the disease course and response to therapy. However, there are currently no validated automatic methods for quantification of PML lesion burden or associated parenchymal volume loss. Furthermore, manual brain or lesion delineations can be tedious, require the use of valuable time resources by radiologists or trained experts, and are often subjective. In this work, we introduce JCnet (named after the causative viral agent), an end-to-end, fully automated method for brain parenchymal and lesion segmentation in PML using consecutive 3D patch-based convolutional neural networks. The network architecture consists of multi-view feature pyramid networks with hierarchical residual learning blocks containing embedded batch normalization and nonlinear activation functions. The feature maps across the bottom-up and top-down pathways of the feature pyramids are merged, and an output probability membership generated through convolutional pathways, thus rendering the method fully convolutional. Our results show that this approach outperforms and improves longitudinal consistency compared to conventional, state-of-the-art methods of healthy brain and multiple sclerosis lesion segmentation, utilized here as comparators given the lack of available methods validated for use in PML. The ability to produce robust and accurate automated measures of brain atrophy and lesion segmentation in PML is not only valuable clinically but holds promise toward including standardized quantitative MRI measures in clinical trials of targeted therapies. Code is available at: https://github.com/omarallouz/JCnet.

Authors

  • Omar Al-Louzi
    Translational Neuroradiology Section, National Institute of Neurological Disorders and Stroke, Bethesda, MD, USA; Neuroimmunology Clinic, National Institute of Neurological Disorders and Stroke, Bethesda, MD, USA.
  • Snehashis Roy
    The Henry M. Jackson Foundation for the Advancement of Military Medicine, United States.
  • Ikesinachi Osuorah
    Neuroimmunology Clinic, National Institute of Neurological Disorders and Stroke, Bethesda, MD, USA.
  • Prasanna Parvathaneni
  • Bryan R Smith
    Section of Infections of the Nervous System, National Institute of Neurological Disorders and Stroke, Bethesda, MD, USA.
  • Joan Ohayon
    Neuroimmunology Clinic, National Institute of Neurological Disorders and Stroke, Bethesda, MD, USA.
  • Pascal Sati
    Translational Neuroradiology Section, National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD, USA.
  • Dzung L Pham
    Clinical Center, National Institutes of Health, Bethesda MD 20814, USA.
  • Steven Jacobson
    Viral Immunology Section, National Institute of Neurological Disorders and Stroke, Bethesda, MD, USA.
  • Avindra Nath
    Section of Infections of the Nervous System, National Institute of Neurological Disorders and Stroke, Bethesda, MD, USA.
  • Daniel S Reich
  • Irene Cortese
    Neuroimmunology Clinic, National Institute of Neurological Disorders and Stroke, Bethesda, MD, USA. Electronic address: corteseir@ninds.nih.gov.

Keywords

External Resources

Popular Topics
Recent Journals