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Dynamic imaging in patients with tuberculosis reveals heterogeneous drug exposures in pulmonary lesions

Nature Medicine volume 26, pages 529–534 (2020)Cite this article

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Abstract

Tuberculosis (TB) is the leading cause of death from a single infectious agent, requiring at least 6 months of multidrug treatment to achieve cure1. However, the lack of reliable data on antimicrobial pharmacokinetics (PK) at infection sites hinders efforts to optimize antimicrobial dosing and shorten TB treatments2. In this study, we applied a new tool to perform unbiased, noninvasive and multicompartment measurements of antimicrobial concentration–time profiles in humans3. Newly identified patients with rifampin-susceptible pulmonary TB were enrolled in a first-in-human study4 using dynamic [11C]rifampin (administered as a microdose) positron emission tomography (PET) and computed tomography (CT). [11C]rifampin PET–CT was safe and demonstrated spatially compartmentalized rifampin exposures in pathologically distinct TB lesions within the same patients, with low cavity wall rifampin exposures. Repeat PET–CT measurements demonstrated independent temporal evolution of rifampin exposure trajectories in different lesions within the same patients. Similar findings were recapitulated by PET–CT in experimentally infected rabbits with cavitary TB and confirmed using postmortem mass spectrometry. Integrated modeling of the PET-captured concentration–time profiles in hollow-fiber bacterial kill curve experiments provided estimates on the rifampin dosing required to achieve cure in 4 months. These data, capturing the spatial and temporal heterogeneity of intralesional drug PK, have major implications for antimicrobial drug development.

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Fig. 1: First-in-human dynamic [11C]rifampin PET–CT studies in patients with TB.
Fig. 2: Heterogeneity of disease and intralesional rifampin exposure.
Fig. 3: Heterogeneous temporal changes in [11C]rifampin exposure during treatment.
Fig. 4: Effect of intralesional rifampin concentrations on treatment shortening.

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Data availability

All data generated or analyzed in this study are included in this article and its Supplementary Information.

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Acknowledgements

We thank all the patients who participated in the study. Additionally, we thank the Maryland Department of Health and Mental Hygiene for recruiting patients with TB; R. Abdallah, C. Voicu, J. Sanchez-Bautista, S. Frey and L. Shinehouse (Johns Hopkins Hospitals) for coordinating the human imaging studies; and M. Klunk for helping with the animal experiments. This work was funded by the US National Institutes of Health (grant R01-HL131829), Director’s Transformative Research Award (grant R01-EB020539) and R56-AI145435 to S.K.J.

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Authors and Affiliations

  1. Center for Infection and Inflammation Imaging Research, Johns Hopkins University School of Medicine, Baltimore, MD, USA

    Alvaro A. Ordonez, Camilo A. Ruiz-Bedoya, Allen Chen, Elizabeth W. Tucker, Lisa Pieterse & Sanjay K. Jain

  2. Center for Tuberculosis Research, Johns Hopkins University School of Medicine, Baltimore, MD, USA

    Alvaro A. Ordonez, Camilo A. Ruiz-Bedoya, Elizabeth W. Tucker, Michael E. Urbanowski, Lisa Pieterse, Maunank R. Shah & Sanjay K. Jain

  3. Department of Pediatrics, Johns Hopkins University School of Medicine, Baltimore, MD, USA

    Alvaro A. Ordonez, Camilo A. Ruiz-Bedoya & Sanjay K. Jain

  4. Center for Translational Medicine, University of Maryland School of Pharmacy, Baltimore, MD, USA

    Hechuan Wang, Jogarao V. S. Gobburu & Vijay D. Ivaturi

  5. Center for Infectious Diseases Research and Experimental Therapeutics, Baylor University Medical Center and Texas Tech University Health Sciences Center, Dallas, TX, USA

    Gesham Magombedze, Shashikant Srivastava & Tawanda Gumbo

  6. Russell H. Morgan Department of Radiology and Radiological Sciences, Johns Hopkins University School of Medicine, Baltimore, MD, USA

    Allen Chen, Martin A. Lodge, Daniel P. Holt, William B. Mathews, Robert F. Dannals, Steven P. Rowe & Sanjay K. Jain

  7. Department of Anesthesiology and Critical Care Medicine, Johns Hopkins University School of Medicine, Baltimore, MD, USA

    Elizabeth W. Tucker & Lisa Pieterse

  8. Department of Medicine, Johns Hopkins University School of Medicine, Baltimore, MD, USA

    Michael E. Urbanowski & Maunank R. Shah

  9. Vaccine and Infectious Disease Division, Fred Hutchinson Cancer Research Center, Seattle, WA, USA

    E. Fabian Cardozo

  10. Infectious Disease Pharmacokinetics Laboratory, Pharmacotherapy and Translational Research, University of Florida College of Pharmacy, Gainesville, FL, USA

    Charles A. Peloquin

Authors
  1. Alvaro A. Ordonez
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Contributions

A.A.O. and S.K.J. conceptualized and designed the study. H.W., J.V.S.G. and V.D.I. developed the pharmacokinetic models and analysis. G.M., S.S. and T.G. developed the hollow-fiber system experiments and analysis. D.P.H., W.B.M. and R.F.D. synthesized [11C]rifampin. A.A.O., C.A.R.-B., M.E.U. and L.P. performed the rabbit experiments. A.A.O., A.C., E.W.T., M.R.S. and S.K.J. recruited patients with TB and obtained their consent. A.A.O. and C.A.R.-B. analyzed the imaging data. E.F.C. developed algorithms to visualize PET data as heat map overlays. M.A.L. and S.P.R. designed the imaging protocols and provided technical expertise on image analysis. C.A.P. performed the mass spectrometry analysis. A.A.O., H.W., G.M., V.D.I. and S.K.J. analyzed the data and performed statistical analysis. A.A.O. and S.K.J. wrote the initial draft, and all coauthors edited the manuscript. S.K.J. provided funding and supervised the project.

Corresponding author

Correspondence to Sanjay K. Jain.

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Peer review information Alison Farrell was the primary editor on this article and managed its editorial process and peer review in collaboration with the rest of the editorial team.

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Extended data

Extended Data Fig. 1 Study outline and patient characteristics.

(a) Patients with pulmonary TB receiving a rifampin-based TB treatment were enrolled and 11C-rifampin PET/CT performed within 6-weeks of treatment initiation. A subset of patients (n = 2) was also imaged at least 20 weeks after starting treatment. (b) All patients were HIV negative and were receiving an oral regimen of isoniazid, rifampin, pyrazinamide, and ethambutol at the time of imaging, except for patient 5 that received moxifloxacin instead of ethambutol. Patient 7 was excluded from the study due to significant motion artifact during the 11C-rifampin PET/CT. Gender: male (M) and female (F).

Extended Data Fig. 2 Heterogeneous pulmonary lesions in different lung regions of TB patients.

(a) Transverse CT sections from the TB patients demonstrate the simultaneous presence of multiple pulmonary lesions. (b) TB lesions and cavities with different sizes (volumes) were noted in all lung regions, although there was a preference for the upper lung lobes. Data from all 12 patients is shown. (c and d) Using the CT as a reference, the volumes of interest (VOIs) were drawn and applied to the PET data. VOIs for unaffected lung were placed at the same location in the contralateral unaffected lung.

Extended Data Fig. 3 11C-Rifampin measurements in the liver and brain of TB patients.

(a) Time-activity curve of 11C-rifampin measured in the liver of patients. (b) AUC liver to plasma ratios (c) Time-activity curve of 11C-rifampin measured in the brain of patients. (d) AUC brain to plasma ratios. The red dots represent individual measurements [n = 12 VOIs (measured at 10 time-points; total 120 VOIs per organ) corresponding to the 12 patients], with the black line and grey region representing the median and interquartile range, respectively. Tissue to plasma AUCs are represented as median and interquartile range.

Extended Data Fig. 4 Intrasubject heterogeneity of 11C-rifampin exposure.

11C-Rifampin area under the concentration-time curve (AUC) obtained by integrating the area under the dynamic 11C-rifampin PET time-activity curves (middle panels) as well as the AUC ratio (tissue to plasma) (right panels) from selected patients, are shown as heatmap overlays on the CT (left panels). The dotted white lines outline the lesion/cavity. Tissue density [X-ray attenuation value (Hounsfield Unit)] obtained via CT was used to correct the corresponding PET data to represent 11C-rifampin concentrations per mass of tissue.

Extended Data Fig. 5 The rabbit model of cavitary TB mimics human disease.

(a) Scheme describing the experiments performed in the rabbit model. (b) After aerosol infection with M. tuberculosis, the rabbits developed a heterogeneous pulmonary disease similar to humans. Transverse CT sections from rabbits at week 18 post-infection are shown. (c) Noninvasive longitudinal monitoring of disease progression using CT. Cavities/lesions are indicated with red arrows. (d) Histopathological analysis of infected-rabbit tissues demonstrates acid-fast bacilli (AFB) in the necrotic areas of the granuloma and cavity wall. Surrounding fibrosis (blue regions) can be noted with Mason’s trichrome staining. Histological analyses were repeated independently four times with similar results.

Extended Data Fig. 6 11C-Rifampin PET in rabbits.

Time-activity curves for individual lesions (a) cavity walls, (b) TB lesions and (c) unaffected lung regions from M. tuberculosis-infected rabbits.

Extended Data Fig. 7 Direct tissue measurements of rifampin (mass spectrometry) in rabbits.

(a) Gross pathology demonstrating the M. tuberculosis-infected lungs and the (b) areas selected for quantification of rifampin by mass spectrometry. U, unaffected lung (white); L, lesion (blue); C, cavity wall (red). (c) Tissue concentrations of rifampin and its metabolite 25-desacetyl rifampin. ND, not detectable. The lung tissues from each rabbit were processed independently (n = 5 animals).

Extended Data Fig. 8 Rifampin concentrations in rabbit tissues before and after treatment.

All rabbits received five oral doses of rifampin prior to PET imaging to achieve steady state. No differences were identified in (a) 11C-rifampin PET AUC tissue/plasma ratios (n = 11 cavity wall lesions, 13 TB lesions, and 21 unaffected lung regions are shown), (b) absolute rifampin concentrations measured by mass spectrometry (n = 10 cavity wall lesions, 19 TB lesions, 20 unaffected lung regions, caseum from 10 lesions, and five plasma samples are shown), or (c) the tissue/plasma ratios for TB lesions using mass spectrometry quantification in animals before or after treatment (n = 10 cavity wall lesions, 19 TB lesions, 20 unaffected lung regions and caseum from 10 lesion are shown). Data represented as median ± interquartile range. Statistical comparisons performed using a one-tailed Mann-Whitney U test.

Extended Data Fig. 9 Pharmacokinetic lung-biodistribution model.

(a) Model schematic. Maximal elimination rate (Vmax), rifampin concentration at which the elimination is half-maximal (Km) and volume of distribution (Vc) of the central compartment of therapeutic dose, clearance (CLmic) and volume of distribution (Vc,mic) of the central compartment of the 11C-rifampin dose, partition coefficient for left ventricle (PCLV), unaffected lung (PCUL), pulmonary lesion (PCPL), cavity wall (PCCW), equilibration rate constant (Keq) between lung and venous plasma, equilibration rate constant (Keq-lv) between left ventricle and venous plasma, transit rate constant (Ktr), maximal increase in the enzyme production rate (Smax), rifampin concentration at which half the Smax is reached (SC50), and rate constant for the first-order degradation of the enzyme pool (kenz). (b) Individual fittings of observed (red dots) and model-predicted 11C-rifampin concentrations (black lines) in plasma and pulmonary tissues from all patients. Patient 7 was excluded from the study due to significant motion artifact during the 11C-rifampin PET/CT.

Extended Data Fig. 10 Pharmacokinetic model with observed and previously published data.

(a) Observed and model-predicted 11C-rifampin exposure AUC in plasma, unaffected lung, TB lesions and cavity walls of all patients. (b) External data digitized from these studies on TB patients receiving varying doses of intravenous rifampin were used to enrich the dataset. (c, d) Model-predicted rifampin plasma AUC24h and Cmax at steady state compared to the data previously reported by Boree et al. (Am J Respir Crit Care Med. 2015).

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Ordonez, A.A., Wang, H., Magombedze, G. et al. Dynamic imaging in patients with tuberculosis reveals heterogeneous drug exposures in pulmonary lesions. Nat Med 26, 529–534 (2020). https://doi.org/10.1038/s41591-020-0770-2

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