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Evaluation of Clostridium difficile Infection with PET/CT Imaging in a Mouse Model

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Abstract

Purpose

Existing clinical or microbiological scores are not sensitive enough to obtain prompt identification of patients at risk of complicated Clostridium difficile infection (CDI). Our aim was to use a CDI animal model to evaluate 2-deoxy-2-[18F]fluoro-D-glucose positron emission tomography ([18F]FDG-PET) as a marker of severe course of infection.

Procedures

CDI was induced with cefoperazone for 10 days followed by clindamycin 1 day before C. difficile inoculation. Mice were divided into wild type (n = 6), antibiotic without infection (AC n = 4), h001-infected (n = 5, ribotype 001), and h027-infected (n = 5, ribotype 027). Two days after inoculation, [18F]FDG-PET was acquired. Weight, general animal condition, and survival were monitored daily for 9 days.

Results

h001 group showed symptoms for 4 days with 0 % mortality and a similar colon uptake than control animals (h001 0.52 ± 0.20, WT 0.42 ± 0.07, and AC 0.36 ± 0.06). The h027 group showed symptoms up to 7 days, with 66.7 % of mortality 4 days after infection, and significantly higher colon uptake (0.93 ± 0.38, p < 0.05). Clinical score was associated to colon and cecum uptake (rho = 0.78, p = 0.0001) (rho = 0.73, p = 0.0003).

Conclusion

High toxin producer ribotype 027 induced more severe CDI infections, correlating with higher colon and cecum [18F]FDG uptake. Colon uptake may purportedly serve as early predictor of CDI severity.

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References

  1. Bartlett JG (2002) Clinical practice. Antibiotic-associated diarrhea. N Engl J Med 346:334–339

    Article  Google Scholar 

  2. Henrich TJ, Krakower D, Bitton A, Yokoe DS (2009) Clinical risk factors for severe Clostridium difficile-associated disease. Emerg Infect Dis 15:415–422

    Article  Google Scholar 

  3. Hensgens MP, Dekkers OM, Goorhuis A et al (2013) Predicting a complicated course of Clostridium difficile infection at the bedside. Clin Microbiol Infect

  4. Lungulescu OA, Cao W, Gatskevich E, Tlhabano L, Stratidis JG (2011) CSI: a severity index for Clostridium difficile infection at the time of admission. J Hosp Infect 79:151–154

    Article  CAS  Google Scholar 

  5. McFarland LV, Surawicz CM, Rubin M et al (1999) Recurrent Clostridium difficile disease: epidemiology and clinical characteristics. Infect Control Hosp Epidemiol 20:43–50

    Article  CAS  Google Scholar 

  6. Reigadas E, Alcala L, Marin M et al (2015) Missed diagnosis of Clostridium difficile infection; a prospective evaluation of unselected stool samples. J Inf Secur 70:264–272

    CAS  Google Scholar 

  7. Debast SB, Bauer MP, Kuijper EJ (2014) European Society of Clinical Microbiology and Infectious Diseases: update of the treatment guidance document for Clostridium difficile infection. Clin Microbiol Infect 20(Suppl 2):1–26

    Article  CAS  Google Scholar 

  8. Crobach MJ, Planche T, Eckert C et al (2016) European Society of Clinical Microbiology and Infectious Diseases: update of the diagnostic guidance document for Clostridium difficile infection. Clin Microbiol Infect 22(Suppl 4):S63–S81

    Article  Google Scholar 

  9. Reigadas E, Alcala L, Marin M et al (2017) Clinical, immunological and microbiological predictors of poor outcome in Clostridium difficile infection. Diagn Microbiol Infect Dis 88:330–334

    Article  CAS  Google Scholar 

  10. Poli A, Di Matteo S, Bruno GM et al (2015) Economic burden of Clostridium difficile in five hospitals of the Florence health care system in Italy. Risk Manag Healthc Policy 8:207–213

    PubMed  PubMed Central  Google Scholar 

  11. Kawamoto S, Horton KM, Fishman EK (1999) Pseudomembranous colitis: spectrum of imaging findings with clinical and pathologic correlation. Radiographics 19:887–897

    Article  CAS  Google Scholar 

  12. Ash L, Baker ME, O'Malley CM Jr, Gordon SM, Delaney CP, Obuchowski NA (2006) Colonic abnormalities on CT in adult hospitalized patients with Clostridium difficile colitis: prevalence and significance of findings. AJR Am J Roentgenol 186:1393–1400

    Article  Google Scholar 

  13. Belmares J, Gerding DN, Parada JP et al (2007) Outcome of metronidazole therapy for Clostridium difficile disease and correlation with a scoring system. J Inf Secur 55:495–501

    Google Scholar 

  14. Best EL, Freeman J, Wilcox MH (2012) Models for the study of Clostridium difficile infection. Gut Microbes 3:145–167

    Article  Google Scholar 

  15. Hutton ML, Mackin KE, Chakravorty A, Lyras D (2014) Small animal models for the study of Clostridium difficile disease pathogenesis. FEMS Microbiol Lett 352:140–149

    Article  CAS  Google Scholar 

  16. Jelicks LA, Lisanti MP, Machado FS, Weiss LM, Tanowitz HB, Desruisseaux MS (2013) Imaging of small-animal models of infectious diseases. Am J Pathol 182:296–304

    Article  Google Scholar 

  17. Theriot CM, Koumpouras CC, Carlson PE, Bergin II, Aronoff DM, Young VB (2011) Cefoperazone-treated mice as an experimental platform to assess differential virulence of Clostridium difficile strains. Gut Microbes 2:326–334

    Article  Google Scholar 

  18. Pawlowski SW, Calabrese G, Kolling GL, Platts-Mills J, Freire R, AlcantaraWarren C, Liu B, Sartor RB, Guerrant RL (2010) Murine model of Clostridium difficile infection with aged gnotobiotic C57BL/6 mice and a BI/NAP1 strain. J Infect Dis 202:1708–1712

    Article  CAS  Google Scholar 

  19. Chen X, Katchar K, Goldsmith JD, Nanthakumar N, Cheknis A, Gerding DN, Kelly CP (2008) A mouse model of Clostridium difficile-associated disease. Gastroenterology 135:1984–1992

    Article  Google Scholar 

  20. Abella M, Vaquero JJ, Sisniega A, Pascau J, Udías A, García V, Vidal I, Desco M (2012) Software architecture for multi-bed FDK-based reconstruction in X-ray CT scanners. Comput Methods Prog Biomed 107:218–232

    Article  CAS  Google Scholar 

  21. Wang Y, Seidel J, Tsui BM et al (2006) Performance evaluation of the GE healthcare eXplore VISTA dual-ring small-animal PET scanner. J Nucl Med 47:1891–1900

    PubMed  Google Scholar 

  22. Cussó L, Desco M (2018) Suppression of 18F-FDG signal in the bladder on small animal PET-CT. PLoS One 13:e0205610

    Article  Google Scholar 

  23. Shelby RD, Tengberg N, Conces M et al (2019) Development of a standardized scoring system to assess a murine model of Clostridium difficile colitis. J Investig Surg:1–9

  24. Davies KA, Ashwin H, Longshaw CM, et al (2016) Diversity of Clostridium difficile PCR ribotypes in Europe: results from the European, multicentre, prospective, biannual, point-prevalence study of Clostridium difficile infection in hospitalised patients with diarrhoea (EUCLID), 2012 and 2013. Euro Surveill 21: ISSN 1560-7917

  25. Warny M, Pepin J, Fang A, Killgore G, Thompson A, Brazier J, Frost E, McDonald LC (2005) Toxin production by an emerging strain of Clostridium difficile associated with outbreaks of severe disease in North America and Europe. Lancet 366:1079–1084

    Article  CAS  Google Scholar 

  26. Dresler J, Krutova M, Fucikova A, Klimentova J, Hruzova V, Duracova M, Houdkova K, Salovska B, Matejkova J, Hubalek M, Pajer P, Pisa L, Nyc O (2017) Analysis of proteomes released from in vitro cultured eight Clostridium difficile PCR ribotypes revealed specific expression in PCR ribotypes 027 and 176 confirming their genetic relatedness and clinical importance at the proteomic level. Gut Pathog 9:45

    Article  Google Scholar 

  27. Crook DW, Walker AS, Kean Y, Weiss K, Cornely OA, Miller MA, Esposito R, Louie TJ, Stoesser NE, Young BC, Angus BJ, Gorbach SL, Peto TE, Study 003/004 Teams (2012) Fidaxomicin versus vancomycin for Clostridium difficile infection: meta-analysis of pivotal randomized controlled trials. Clin Infect Dis 55(Suppl 2):S93–S103

  28. Palau-Davila L, Lara-Medrano R, Negreros-Osuna AA et al (2016) Efficacy of computed tomography for the prediction of colectomy and mortality in patients with clostridium difficile infection. Ann Med Surg (Lond) 12:101–105

    Article  Google Scholar 

  29. Kestler M, Munoz P, Rodriguez-Creixems M, Rotger A, Jimenez-Requena F, Mari A, Orcajo J, Hernandez L, Alonso JC, Bouza E, in collaboration with the Group for the Management of Infectious Endocarditis (GAME) (2014) Role of 18F-FDG PET in patients with infectious endocarditis. J Nucl Med 55:1093–1098

    Article  CAS  Google Scholar 

  30. Revest M, Patrat-Delon S, Devillers A, Tattevin P, Michelet C (2014) Contribution of 18fluoro-deoxyglucose PET/CT for the diagnosis of infectious diseases. Med Mal Infect 44:251–260

    Article  CAS  Google Scholar 

  31. Fujitani S, George WL, Murthy AR (2011) Comparison of clinical severity score indices for Clostridium difficile infection. Infect Control Hosp Epidemiol 32:220–228

    Article  Google Scholar 

  32. Figh ML, Zoog ESL, Moore RA, Dart BW 4th, Heath G, Butler RM, Gao C, Kong JC, Stanley JD (2017) External validation of Velazquez-Gomez severity score index and ATLAS scores and the identification of risk factors associated with mortality in Clostridium difficile infections. Am Surg 83:1347–1351

    PubMed  Google Scholar 

  33. van Beurden YH, Hensgens MPM, Dekkers OM, le Cessie S, Mulder CJJ, Vandenbroucke-Grauls CMJE (2017) External validation of three prediction tools for patients at risk of a complicated course of Clostridium difficile infection: disappointing in an outbreak setting. Infect Control Hosp Epidemiol 38:897–905

    Article  Google Scholar 

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Acknowledgments

We thank Alexandra de Francisco, Yolanda Sierra, and María de la Jara Felipe for their excellent work with animal preparation and imaging protocols and Ana Villarejo for her help on data acquisition and processing.

Funding

This work was partially supported by the Spanish Ministerio de Ciencia, Innovación y Universidades (ISCIII grants PI13/00687 and PIE16/00055) and co-funded by European Regional Development Fund (ERDF), “A way of making Europe.” It was also supported by the Comunidad de Madrid (S2017/BMD-3867 RENIM-CM) and co-funded with European structural and investment funds. The CNIC is supported by the Ministerio de Ciencia, Innovación y Universidades, and the Pro CNIC Foundation and is a Severo Ochoa Center of Excellence (SEV-2015-0505).

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Author notes

  1. L. Cussó and E. Reigadas contributed equally to this work.

Authors and Affiliations

  1. Departamento de Bioingeniería e Ingeniería Aeroespacial, Universidad Carlos III de Madrid, Avenida de la Universidad 30, 28911, Leganés, Madrid, Spain

    L. Cussó & Manuel Desco

  2. Instituto de Investigación Sanitaria Gregorio Marañón, Madrid, Spain

    L. Cussó, E. Reigadas, P. Muñoz, Manuel Desco & E. Bouza

  3. Centro de Investigación Biomédica en Red de Salud Mental (CIBERSAM), Madrid, Spain

    L. Cussó & Manuel Desco

  4. Centro Nacional de Investigaciones Cardiovasculares (CNIC), Madrid, Spain

    L. Cussó & Manuel Desco

  5. Department of Clinical Microbiology and Infectious Diseases, Hospital General Universitario Gregorio Marañón, Madrid, Spain

    E. Reigadas, P. Muñoz & E. Bouza

  6. Medicine Department, School of Medicine, Universidad Complutense de Madrid (UCM), Madrid, Spain

    E. Reigadas, P. Muñoz & E. Bouza

  7. CIBER de Enfermedades Respiratorias (CIBERES CB06/06/0058), Madrid, Spain

    P. Muñoz & E. Bouza

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  1. L. Cussó
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  2. E. Reigadas
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  4. Manuel Desco
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Correspondence to Manuel Desco.

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Cussó, L., Reigadas, E., Muñoz, P. et al. Evaluation of Clostridium difficile Infection with PET/CT Imaging in a Mouse Model. Mol Imaging Biol 22, 587–592 (2020). https://doi.org/10.1007/s11307-019-01408-4

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