Skip to main page content
U.S. flag

An official website of the United States government

Dot gov

The .gov means it’s official.
Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

Https

The site is secure.
The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation
. 2025 Aug 12;93(8):e0017725.
doi: 10.1128/iai.00177-25. Epub 2025 Jun 23.

Characterizing PET CT patterns and bacterial dissemination features of tuberculosis relapse in the macaque model

Affiliations

Characterizing PET CT patterns and bacterial dissemination features of tuberculosis relapse in the macaque model

Pauline Maiello et al. Infect Immun. .

Abstract

Tuberculosis (TB) relapse after appropriate drug treatment is poorly understood but critical to developing shorter treatment regimens. Using a cynomolgus macaque model of human TB, macaques with active TB disease were treated with a short course of isoniazid and rifampin and subsequently infected with SIV. Serial clinical, microbiologic, immunologic, and position emission and computed tomography (PET CT) assessments were performed to identify risk factors of relapse. Of the 12 animals, eight developed radiologically defined relapse, including four that had clinical and/or microbiologic signs. Greater gross pathology and bacterial burden were observed in relapse animals. PET CT characteristics before, during, and at the end of the treatment were similar among relapse and non-relapse animals. We show that complete sterilization or very low Mtb burden is protective against SIV-induced TB relapse but cannot be predicted by PET CT. Using barcoded M. tuberculosis, we found that Mtb dissemination during relapse originated from both lung and thoracic lymph nodes, underscoring the importance of lymph nodes as a reservoir. By matching barcoded Mtb and serial PET CT, we also demonstrate that not every site of persistent Mtb growth after drug treatment is capable of dissemination and relapse, underscoring the complex nature of drug treatment and relapse.

Keywords: HIV; PET CT; relapse; tuberculosis.

PubMed Disclaimer

Conflict of interest statement

The authors declare no conflict of interest.

Figures

Fig 1
Fig 1
Experimental design and serial PET CT images from animals with active TB before and during treatment and relapse. (A) Experimental study design. Animals with active TB disease were given a 2-month course of isoniazid (INH) and rifampin (RIF), followed by 1 month of no drugs, after which SIV infection occurred. Serial PET CT was performed prior to, during drug treatment, before, and after SIV infection as shown above. Created with Biorender.com. (B) Serial PET CT images of TB disease in cynomolgus macaques at 4 weeks post-Mtb infection, pre-drug treatment, 8 weeks post-drug treatment, pre-SIV infection, and 4 weeks post-SIV infection. Axial images of the chest demonstrate the degree of TB-associated lung involvement and FDG activity (shown in yellow) among two animals without evidence of relapse (16414 and 16814) and animals with relapse (9615 and 30716). Purple arrow shows a consolidation, and green arrow shows a cavity. Blue and white arrows point to granulomas that appeared on the scan after SIV infection. SUV (standardized uptake value) scale bar is shown in the bottom right.
Fig 2
Fig 2
Clinical and microbiological evidence of relapse after SIV infection among radiologically defined relapse and non-relapse animals. Mtb detection refers to microbiologic evidence (Mtb detected) in either gastric aspirate (GA) or bronchoalveolar lavage (BAL) samples. *Increased respiratory effort. †Irregular respirations. Bar graphs represent the percentage of animals in each outcome group with clinical or microbiologic evidence of relapse post-SIV infection.
Fig 3
Fig 3
PET CT-defined relapse is associated with greater gross pathology at necropsy (measured by necropsy score) (A), total Mtb burden (measured as CFU, colony forming units of Mtb) (B), lung Mtb burden (C), and thoracic lymph node burden (D) compared with non-relapse animals. P-values shown were determined by the Mann-Whitney test. Each dot represents an animal, and the lines shown are medians.
Fig 4
Fig 4
PET CT characteristics prior to TB drug treatment. PET CT characteristics were similar between non-relapse (n = 4) and relapse (n = 7; one animal could not be scanned prior to drug treatment) animals that included total lung inflammation (measured using FDG activity) (A), number of involved lung lobes (B), proportion of unilateral or bilateral lung involvement (C), proportion of animals with lung consolidation as a CT feature (D), proportion of the animals with clusters of granulomas. as a feature of TB disease on PET CT (E), proportion of animals with cavitary disease on PET CT scan (F), number of FDG-avid (as a marker of inflammation) mediastinal lymph nodes (G), and proportion of animals with PET CT findings of extrapulmonary disease prior to drug treatment (H). P values are based on Mann-Whitney (A, B, G) or Fisher’s Exact (C through F, H) tests.
Fig 5
Fig 5
Distribution of barcodes by anatomical compartment. (A) Circos plots representing barcoded Mtb detected in tissues (inner track), with ribbons representing tissues containing the same barcodes. The middle track represents the timing of the sample seen on scans (pre- or post-SIV infection), and the outer track represents the anatomical compartment associated with each tissue. Distinct barcodes are represented by a different color. (B) New granulomas appear to be closer in distance to founding (seen at 4 weeks post-Mtb infection) lymph nodes (green) than founding granulomas (blue). Y-axis shows the number of granulomas sharing barcodes with founding granulomas and lymph nodes, and the x-axis shows the distance between the new granuloma and founding granuloma/lymph node.

Update of

Similar articles

Cited by

References

    1. World Health Organization . 2024. Global tuberculosis report 2024. World Health Organization, Geneva, Switzerland.
    1. Romanowski K, Balshaw RF, Benedetti A, Campbell JR, Menzies D, Ahmad Khan F, Johnston JC. 2019. Predicting tuberculosis relapse in patients treated with the standard 6-month regimen: an individual patient data meta-analysis. Thorax 74:291–297. doi: 10.1136/thoraxjnl-2017-211120 - DOI - PubMed
    1. Dobler CC, Crawford ABH, Jelfs PJ, Gilbert GL, Marks GB. 2009. Recurrence of tuberculosis in a low-incidence setting. Eur Respir J 33:160–167. doi: 10.1183/09031936.00104108 - DOI - PubMed
    1. Vega V, Rodríguez S, Van der Stuyft P, Seas C, Otero L. 2021. Recurrent TB: a systematic review and meta-analysis of the incidence rates and the proportions of relapses and reinfections. Thorax 76:494–502. doi: 10.1136/thoraxjnl-2020-215449 - DOI - PMC - PubMed
    1. Goletti D, Lindestam Arlehamn CS, Scriba TJ, Anthony R, Cirillo DM, Alonzi T, Denkinger CM, Cobelens F. 2018. Can we predict tuberculosis cure? What tools are available? Eur Respir J 52:1801089. doi: 10.1183/13993003.01089-2018 - DOI - PubMed

MeSH terms

LinkOut - more resources