Quantitative 18F-FDG PET-CT scan characteristics correlate with tuberculosis treatment response.
18F-FDG
Mycobacterium tuberculosis
PET-CT
Quantified lung analysis
Quantitative imaging analysis
Tuberculosis
Tuberculosis treatment response
Journal
EJNMMI research
ISSN: 2191-219X
Titre abrégé: EJNMMI Res
Pays: Germany
ID NLM: 101560946
Informations de publication
Date de publication:
10 Feb 2020
10 Feb 2020
Historique:
received:
11
09
2019
accepted:
09
01
2020
entrez:
11
2
2020
pubmed:
11
2
2020
medline:
11
2
2020
Statut:
epublish
Résumé
There 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. Quantified 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. Quantification 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.
Sections du résumé
BACKGROUND
BACKGROUND
There 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.
RESULTS
RESULTS
Quantified 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.
CONCLUSIONS
CONCLUSIONS
Quantification 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.
Identifiants
pubmed: 32040770
doi: 10.1186/s13550-020-0591-9
pii: 10.1186/s13550-020-0591-9
pmc: PMC7010890
doi:
Types de publication
Journal Article
Langues
eng
Pagination
8Subventions
Organisme : Medical Research Council
ID : MR/P028071/1
Pays : United Kingdom
Organisme : International Collaborations in Infectious disease Research (ICIDR)
ID : 5U01IA115619/03
Organisme : European and Developing Countries Clinical Trials Partnership
ID : CDF1576
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