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Quantitative 18F-FDG PET-CT scan characteristics correlate with tuberculosis treatment response

Authors
  • Malherbe, Stephanus T.1, 2
  • Chen, Ray Y.3
  • Dupont, Patrick4, 2
  • Kant, Ilse2
  • Kriel, Magdalena1, 2
  • Loxton, André G.1, 2
  • Smith, Bronwyn1, 2
  • Beltran, Caroline G. G.1, 2
  • van Zyl, Susan1, 2
  • McAnda, Shirely1, 2
  • Abrahams, Charmaine1, 2
  • Maasdorp, Elizna1, 2, 2
  • Doruyter, Alex5, 2
  • Via, Laura E.3, 5
  • Barry, Clifton E. III1, 2, 3, 5
  • Alland, David6
  • Richards, Stephanie Griffith-2
  • Ellman, Annare2
  • Peppard, Thomas7
  • Belisle, John8
  • And 5 more
  • 1 Centre of Excellence for Biomedical Tuberculosis Research and South African Medical Research Council Centre for Tuberculosis Research, Cape Town, South Africa , Cape Town (South Africa)
  • 2 Stellenbosch University, Cape Town, South Africa , Cape Town (South Africa)
  • 3 National Institute of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, MD, USA , Bethesda (United States)
  • 4 KU Leuven, Leuven, Belgium , Leuven (Belgium)
  • 5 University of Cape Town, Cape Town, South Africa , Cape Town (South Africa)
  • 6 Rutgers-New Jersey Medical School, Rutgers Biomedical and Health Sciences, Newark, NJ, USA , Newark (United States)
  • 7 Certara, Inc, Princeton, NJ, USA , Princeton (United States)
  • 8 Colorado State University, Fort Collins, CO, USA , Fort Collins (United States)
  • 9 Mater Research Institute – The University of Queensland, Translational Research Institute, Brisbane, QLD, Australia , Brisbane (Australia)
  • 10 Catalysis Foundation for Health, San Ramon, CA, USA , San Ramon (United States)
Type
Published Article
Journal
EJNMMI Research
Publisher
Springer (Biomed Central Ltd.)
Publication Date
Feb 10, 2020
Volume
10
Issue
1
Identifiers
DOI: 10.1186/s13550-020-0591-9
Source
Springer Nature
Keywords
License
Green

Abstract

BackgroundThere is a growing interest in the use of F-18 FDG PET-CT to monitor tuberculosis (TB) treatment response. Tuberculosis lung lesions are often complex and diffuse, with dynamic changes during treatment and persisting metabolic activity after apparent clinical cure. This poses a challenge in quantifying scan-based markers of burden of disease and disease activity. We used semi-automated, whole lung quantification of lung lesions to analyse serial FDG PET-CT scans from the Catalysis TB Treatment Response Cohort to identify characteristics that best correlated with clinical and microbiological outcomes.ResultsQuantified scan metrics were already associated with clinical outcomes at diagnosis and 1 month after treatment, with further improved accuracy to differentiate clinical outcomes after standard treatment duration (month 6). A high cavity volume showed the strongest association with a risk of treatment failure (AUC 0.81 to predict failure at diagnosis), while a suboptimal reduction of the total glycolytic activity in lung lesions during treatment had the strongest association with recurrent disease (AUC 0.8 to predict pooled unfavourable outcomes). During the first year after TB treatment lesion burden reduced; but for many patients, there were continued dynamic changes of individual lesions.ConclusionsQuantification of FDG PET-CT images better characterised TB treatment outcomes than qualitative scan patterns and robustly measured the burden of disease. In future, validated metrics may be used to stratify patients and help evaluate the effectiveness of TB treatment modalities.

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