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European Journal of Nuclear Medicine and Molecular Imaging

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Open Access 01-04-2019 | Original Article

The diagnostic accuracy of ¹⁸F-FDG PET/CT in diagnosing fracture-related infections

Authors: Justin V. C. Lemans, Monique G. G. Hobbelink, Frank F. A. IJpma, Joost D. J. Plate, Janna van den Kieboom, Paul Bosch, Luke P. H. Leenen, Moyo C. Kruyt, Andor W. J. M. Glaudemans, Geertje A. M. Govaert

Published in: European Journal of Nuclear Medicine and Molecular Imaging | Issue 4/2019

Abstract

Purpose

¹⁸F-Fluorodeoxyglucose positron emission tomography (¹⁸F-FDG PET/CT) is frequently used to diagnose fracture-related infections (FRIs), but its diagnostic performance in this field is still unknown. The aims of this study were: (1) to assess the diagnostic performance of qualitative assessment of ¹⁸F-FDG PET/CT scans in diagnosing FRI, (2) to establish the diagnostic performance of standardized uptake values (SUVs) extracted from ¹⁸F-FDG PET/CT scans and to determine their associated optimal cut-off values, and (3) to identify variables that predict a false-positive (FP) or false-negative (FN) ¹⁸F-FDG PET/CT result.

Methods

This retrospective cohort study included all patients with suspected FRI undergoing ¹⁸F-FDG PET/CT between 2011 and 2017 in two level-1 trauma centres. Two nuclear medicine physicians independently reassessed all ¹⁸F-FDG PET/CT scans. The reference standard consisted of the result of at least two deep, representative microbiological cultures or the presence/absence of clinical confirmatory signs of FRI (AO/EBJIS consensus definition) during a follow-up of at least 6 months. Diagnostic performance in terms of sensitivity, specificity, positive predictive value (PPV) and negative predictive value (NPV) was calculated. Additionally, SUVs were measured on ¹⁸F-FDG PET/CT scans. Volumes of interest were drawn around the suspected and corresponding contralateral areas to obtain absolute values and ratios between suspected and contralateral areas. A multivariable logistic regression analysis was also performed to identify the most important predictor(s) of FP or FN ¹⁸F-FDG PET/CT results.

Results

The study included 156 ¹⁸F-FDG PET/CT scans in 135 patients. Qualitative assessment of ¹⁸F-FDG PET/CT scans showed a sensitivity of 0.89, specificity of 0.80, PPV of 0.74, NPV of 0.91 and diagnostic accuracy of 0.83. SUVs on their own resulted in lower diagnostic performance, but combining them with qualitative assessments yielded an AUC of 0.89 compared to an AUC of 0.84 when considering only the qualitative assessment results (p = 0.007). ¹⁸F-FDG PET/CT performed <1 month after surgery was found to be the independent variable with the highest predictive value for a false test result, with an absolute risk of 46% (95% CI 27–66%), compared with 7% (95% CI 4–12%) in patients with ¹⁸F-FDG PET/CT performed 1–6 months after surgery.

Conclusion

Qualitative assessment of ¹⁸F-FDG PET/CT scans had a diagnostic accuracy of 0.83 and an excellent NPV of 0.91 in diagnosing FRI. Adding SUV measurements to qualitative assessment provided additional accuracy in comparison to qualitative assessment alone. An interval between surgery and ¹⁸F-FDG PET/CT of <1 month was associated with a sharp increase in false test results.

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Title: The diagnostic accuracy of 18F-FDG PET/CT in diagnosing fracture-related infections
Authors: Justin V. C. Lemans
Monique G. G. Hobbelink
Frank F. A. IJpma
Joost D. J. Plate
Janna van den Kieboom
Paul Bosch
Luke P. H. Leenen
Moyo C. Kruyt
Andor W. J. M. Glaudemans
Geertje A. M. Govaert
Publication date: 01-04-2019
Publisher: Springer Berlin Heidelberg
Published in: European Journal of Nuclear Medicine and Molecular Imaging / Issue 4/2019
Print ISSN: 1619-7070
Electronic ISSN: 1619-7089
DOI: https://doi.org/10.1007/s00259-018-4218-6

Keynote webinar | Spotlight on sleep in brain health

Springer Medicine

The diagnostic accuracy of ¹⁸F-FDG PET/CT in diagnosing fracture-related infections

Abstract

Purpose

Methods

Results

Conclusion

Keynote webinar | Spotlight on sleep in brain health

Springer Medicine

Abstract

Purpose

Methods

Results

Conclusion

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