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Visualizing the dynamics of tuberculosis pathology using molecular imaging

  • Alvaro A. Ordonez
  • , Elizabeth W. Tucker
  • , Carolyn J. Anderson
  • , Claire L. Carter
  • , Shashank Ganatra
  • , Deepak Kaushal
  • , Igor Kramnik
  • , Philana L. Lin
  • , Cressida A. Madigan
  • , Susana Mendez
  • , Jianghong Rao
  • , Rada M. Savic
  • , David M. Tobin
  • , Gerhard Walzl
  • , Robert J. Wilkinson
  • , Karen A. Lacourciere
  • , Laura E. Via
  • , Sanjay K. Jain
  • Johns Hopkins University
  • University of Missouri
  • Southwest Foundation for Biomedical Research
  • Boston University
  • University of Pittsburgh
  • University of California at San Diego
  • National Institutes of Health
  • Stanford University
  • University of California at San Francisco
  • Duke University
  • Stellenbosch University
  • Imperial College London
  • University of Cape Town
  • The Francis Crick Institute

Research output: Contribution to journal › Review article › peer-review

28 Scopus citations

Abstract

Nearly 140 years after Robert Koch discovered Mycobacterium tuberculosis, tuberculosis (TB) remains a global threat and a deadly human pathogen. M. tuberculosis is notable for complex host-pathogen interactions that lead to poorly understood disease states ranging from latent infection to active disease. Additionally, multiple pathologies with a distinct local milieu (bacterial burden, antibiotic exposure, and host response) can coexist simultaneously within the same subject and change independently over time. Current tools cannot optimally measure these distinct pathologies or the spatiotemporal changes. Next-generation molecular imaging affords unparalleled opportunities to visualize infection by providing holistic, 3D spatial characterization and noninvasive, temporal monitoring within the same subject. This rapidly evolving technology could powerfully augment TB research by advancing fundamental knowledge and accelerating the development of novel diagnostics, biomarkers, and therapeutics.

Original languageEnglish
Article numbere145107
JournalJournal of Clinical Investigation
Volume131
Issue number5
DOIs
StatePublished - 1 Mar 2021

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 3 - Good Health and Well-being
    SDG 3 Good Health and Well-being

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