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
. 2013 Sep;57(9):4237-4244.
doi: 10.1128/AAC.00277-13. Epub 2013 Jun 24.

Radiologic Responses in Cynomolgus Macaques for Assessing Tuberculosis Chemotherapy Regimens

Affiliations

Radiologic Responses in Cynomolgus Macaques for Assessing Tuberculosis Chemotherapy Regimens

Philana Ling Lin et al. Antimicrob Agents Chemother. 2013 Sep.

Abstract

Trials to test new drugs currently in development against tuberculosis in humans are impractical. All animal models to prioritize new regimens are imperfect, but nonhuman primates (NHPs) infected with Mycobacterium tuberculosis develop active tuberculosis (TB) disease with a full spectrum of lesion types seen in humans. Serial 2-deoxy-2-[18F]-fluoro-d-glucose (FDG) positron emission tomography (PET) with computed tomography (CT) imaging was performed on cynomolgus macaques during infection and chemotherapy with individual agents or the four-drug combination therapy most widely used globally. The size and metabolic activity of lung granulomas varied among animals and even within a single animal during development of disease. Individual granulomas within untreated animals had highly local and independent outcomes, some progressing in size and FDG uptake, while others waned, illustrating the highly dynamic nature of active TB. At necropsy, even untreated animals were found to have a proportion of sterile lesions consistent with the dynamics of this infection. A more marked reduction in overall metabolic activity in the lungs (decreased FDG uptake) was associated with effective treatment. A reduction in the size of individual lesions correlated with a lower bacterial burden at necropsy. Isoniazid treatment was associated with a transient increase in metabolic activity in individual lesions, whereas a net reduction occurred in most lesions from rifampin-treated animals. Quadruple-drug therapy resulted in the highest decrease in FDG uptake. The findings of PET-CT imaging may provide an important early correlate of the efficacy of novel combinations of new drugs that can be directly translated to human clinical trials.

PubMed Disclaimer

Figures

Fig 1
Fig 1
Lung granulomas are dynamic and independent. (A) Serial views of two granulomas in the right lower lobe (RLL) with independent changes in size and metabolic activity (yellow brightness) during early M. tuberculosis infection. (B) Granuloma size (based on the relative size of each sphere) and metabolic activity (SUV; y axis) are shown over time postinfection (x axis). Granulomas were from the same animal whose lung granulomas are depicted in panel A. Granuloma RLL 2 (purple) peaks in metabolic activity at 6 weeks postinfection, whereas granuloma RLL 1 (blue) peaks at 18 weeks postinfection. The granuloma in red increases dramatically at 18 weeks postinfection, unlike RLL 1 and RLL 2.
Fig 2
Fig 2
INH and RIF treatment reduces the bacterial burden within individual granulomas and in aggregate. (A) Granuloma bacterial burden (number of CFU per granuloma) was obtained at necropsy for control and treatment groups. Each dot is an individual granuloma. Sterile granulomas are depicted as 0 CFU and were found for 41 (of 99 total), 36 (of 43), and 33 (of 36) granulomas in the control, INH-treated, and RIF-treated animals, respectively. (B) The total bacterial burden was reduced in animals treated with INH alone and RIF alone compared to that in the controls. The CFU score reflects the overall bacterial burden within the entire animal. Each point represents the total bacterial burden of an animal. Too few data points were available for the HRZE-treated group for meaningful comparison. P values were determined by the Kruskall-Wallis test (P < 0.001) with post hoc analysis by Dunn's multiple-comparison test: *, P ≤ 0.05; **, P ≤ 0.01; ***, P ≤ 0.001.
Fig 3
Fig 3
Lesional bacterial burden correlates with size but not SUVR in control animals with active TB. (Left) The bacterial burden within a granuloma (gran) did not specifically correlate to inflammation measured by FDG PET (SUVR) (linear regression, R2 = 0.03, P = 0.07). (Right) A positive correlation between size and lesional bacterial burden was observed (linear regression, R2 = 0.244, P < 0.0001).
Fig 4
Fig 4
Treatment with INH, RIF, and HRZE results in reduced total PET activity from pretreatment levels. Total FDG uptake from the lungs was determined for each monkey before, during, and at the end of drug treatment. The y axis reflects the percent change of total SUV from pretreatment levels (100%). Each line represents an individual monkey. P values were determined by the Friedman test (P < 0.001) with post hoc analysis by Dunn's multiple-comparison test. **, P < 0.01. Too few data points were available for the HRZE-treated group for meaningful comparison.
Fig 5
Fig 5
Serial measurements of granuloma SUV and size (mm) of monkeys immediately before (pre) and at the end (post) of drug treatment. (A) The metabolic activity of individual granulomas decreases with RIF and HRZE; (B) granuloma size decreases among animals treated with RIF alone, INH alone, and HRZE. P values were determined by the Wilcoxon matched-pairs sign-rank test: ***, P ≤ 0.001; ****, P ≤ 0.0001.
Fig 6
Fig 6
Reductions in SUVRs during INH or RIF treatment are observed with low bacterial numbers per granuloma. Each point represents a single granuloma from control (n = 9 animals), RIF-treated (n = 7 animals), and INH-treated (n = 7 animals) animals. Too few samples from the HRZE-treated group were available for meaningful analysis. Note that the x axis scale (CFU per granulomas) differs between the control and treatment groups due to high bacterial numbers in the control group.

References

    1. Wallis RS, Perkins MD, Phillips M, Joloba M, Namale A, Johnson JL, Whalen CC, Teixeira L, Demchuk B, Dietze R, Mugerwa RD, Eisenach K, Ellner JJ. 2000. Predicting the outcome of therapy for pulmonary tuberculosis. Am. J. Respir. Crit. Care Med. 161(4 Pt 1):1076–1080 - PMC - PubMed
    1. Horne DJ, Royce SE, Gooze L, Narita M, Hopewell PC, Nahid P, Steingart KR. 2010. Sputum monitoring during tuberculosis treatment for predicting outcome: systematic review and meta-analysis. Lancet Infect. Dis. 10:387–394 - PMC - PubMed
    1. Hamilton CD, Stout JE, Goodman PC, Mosher A, Menzies R, Schluger NW, Khan A, Johnson JL, Vernon AN. 2008. The value of end-of-treatment chest radiograph in predicting pulmonary tuberculosis relapse. Int. J. Tuberc. Lung Dis. 12:1059–1064 - PMC - PubMed
    1. Im JG, Itoh H, Shim YS, Lee JH, Ahn J, Han MC, Noma S. 1993. Pulmonary tuberculosis: CT findings—early active disease and sequential change with antituberculous therapy. Radiology 186:653–660 - PubMed
    1. Jeong YJ, Lee KS. 2008. Pulmonary tuberculosis: up-to-date imaging and management. AJR Am. J. Roentgenol. 191:834–844 - PubMed