Role of 18F FDG-PET-CT in Fever and Inflammation of Unknown Origin
Abstract
1. Introduction
2. Methodology
3. Results
4. Discussion
5. Study Limitations
6. Conclusions and Future Directions
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Conflicts of Interest
Abbreviations
FUO | Fever of unknown origin |
IUO | Inflammation of unknown origin |
FDG | Fluorodeoxyglucose |
PET-CT | Positron emission tomography/computed tomography |
PPV | positive predictive value |
NPV | negative predictive value |
NR | not reported |
TP | True positive |
TN | True negative |
R | Retrospective |
P | Prospective |
A | Ambispective |
References
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First Author | Year | Patients n. | Population | Study Type | Final Diagnosis |
---|---|---|---|---|---|
Jaruskova [14] | 2006 | 94 | FUO | R | NR |
Bleeker-Rovers [15] | 2006 | 70 | FUO | P | 0.50 |
Keidar [16] | 2008 | 48 | FUO | P | 0.60 |
Balink [17] | 2009 | 68 | FUO | R | 0.65 |
Federici [18] | 2010 | 14 | FUO/IUO | R | 0.71 |
Ferda [19] | 2010 | 48 | FUO | R | 0.92 |
Kei [20] | 2010 | 12 | FUO | R | 0.58 |
Ergül [21] | 2011 | 24 | FUO | R | 0.54 |
Kubota [22] | 2011 | 81 | FUO | R | 0.75 |
Pelosi [23] | 2011 | 24 | FUO | R | 0.71 |
Sheng [24] | 2011 | 48 | FUO | R | 0.75 |
Rosenbaum [25] | 2011 | 24 | FUO | R | 1.00 |
Becerra Nakayo [26] | 2012 | 20 | FUO | R | NR |
Crouzet [27] | 2012 | 79 | FUO | R | 0.77 |
Kim [28] | 2012 | 48 | FUO | R | 0.85 |
Pedersen [29] | 2012 | 22 | FUO | R | 0.60 |
Manohar [30] | 2013 | 103 | FUO | R | 0.67 |
Balink [31] | 2014 | 140 | IUO | R | 0.74 |
Buch-Olsen [32] | 2014 | 57 | FUO | R | 0.91 |
Tokmak [33] | 2014 | 25 | FUO | R | 0.92 |
Balink [34] | 2015 | 498 | FUO/IUO | R | 0.66 |
Gafter-Gvili [35] | 2015 | 112 | FUO | R | 0.74 |
Singh [36] | 2015 | 47 | FUO | P | 0.53 |
Bouter [37] | 2016 | 72 | FUO/IUO | R | 0.83 |
Pereira [38] | 2016 | 76 | FUO | R | 0.93 |
Hung [39] | 2017 | 58 | FUO | P | 0.79 |
Abdelrahman [40] | 2018 | 27 | FUO | P | 0.92 |
Garcia-Vicente [41] | 2018 | 67 | FUO | R | 0.88 |
Schönau [42] | 2018 | 240 | FUO/IUO | P | 0.79 |
Wang [43] | 2019 | 376 | FUO/IUO | R | 0.91 |
Wang [44] | 2020 | 147 | FUO/IUO | P | 0.88 |
Georga [45] | 2020 | 50 | FUO | R | 0.78 |
Zhu [46] | 2020 | 89 | FUO/IUO | R | 0.74 |
Kubota [47] | 2021 | 128 | FUO | P | 0.72 |
Letertre [48] | 2021 | 44 | FUO | R | 0.70 |
MuldersManders [49] | 2021 | 104 | FUO/IUO | R | 0.65 |
Bilici Salman [50] | 2021 | 97 | IUO | R | 0.90 |
Mahajna [51] | 2021 | 128 | FUO | R | 0.74 |
Das [52] | 2021 | 43 | FUO | R | 0.74 |
Yadav [53] | 2021 | 51 | FUO | P | 0.88 |
Buchritis [54] | 2021 | 303 | FUO | R | 0.72 |
Chen [55] | 2022 | 524 | FUO | P | 0.91 |
Chen [56] | 2022 | 326 | FUO/IUO | R | 0.91 |
Holubar [57] | 2022 | 317 | IUO | R | 0.72 |
Ogut [58] | 2022 | 58 | FUO/IUO | R | 0.90 |
Ly [59] | 2022 | 103 | FUO/IUO | P | 0.56 |
Weitzer [60] | 2022 | 300 | FUO/IUO | R | 0.84 |
Becker KK [61] | 2024 | 77 | FUO/IUO | R | 1.00 |
Fathala [62] | 2024 | 105 | FUO | R | 1.00 |
Khan [63] | 2024 | 573 | FUO | A | 0.38 |
Liu [64] | 2024 | 40 | FUO | R | 1.00 |
Kobayashi [65] | 2024 | 45 | FUO/IUO | R | 0.71 |
Koreli [66] | 2025 | 30 | FUO/IUO | R | 0.50 |
Yu [67] | 2025 | 284 | FUO | R | 0.69 |
Greuez [68] | 2025 | 93 | FUO/IUO | R | 0.59 |
First Author | Clinical Helpfulness | Sensitivity | Specificity | PPV | NPV |
---|---|---|---|---|---|
Jaruskova [14] | 0.36 | NR | NR | NR | NR |
Bleeker-Rovers [15] | 0.33 (TP) | 0.88 | 0.77 | 0.70 | 0.92 |
Keidar [16] | 0.90 (TP + TN) | 1.00 | 0.81 | 0.81 | 1.00 |
Balink [17] | 0.56 (TP) | 1.00 | 0.90 | 0.93 | 1.00 |
Federici * [18] | 0.50 (TP) | 0.70 | 0.75 | 0.88 | 0.5 |
Ferda [19] | 0.77 | 0.97 | 0.75 | NR | NR |
Kei [20] | 0.42 (TP) | NR | NR | NR | NR |
Ergül [21] | 0.63 | 0.92 | 0.45 | 0.63 | 1.0 |
Kubota [22] | 0.54 | 0.81 | 0.75 | NR | NR |
Pelosi * [23] | 0.87 (TP + TN) | 0.50 | 0.50 | 0.85 | 0.85 |
Sheng [24] | 0.67 | 0.89 | 0.33 | 0.80 | 0.50 |
Rosenbaum [25] | 1.00 (TP + TN) | NR | NR | NR | NR |
Becerra Nakayo [26] | 0.55 (TP) | 0.78 | 0.83 | 0.92 | 0.62 |
Crouzet [27] | 0.19 | 0.98 | 0.87 | NR | NR |
Kim [28] | 0.56 | 0.92 | 0.23 | NR | NR |
Pedersen * [29] | 0.83 | 0.67 | 0.71 | 0.83 | 0.50 |
Manohar [30] | 0.60 | 0.90 | 0.97 | 0.98 | 0.83 |
Balink [31] | 0.51 | 0.94 | 0.83 | 0.93 | 0.77 |
Buch-Olsen [32] | 0.75 (TP + TN) | NR | NR | NR | NR |
Tokmak [33] | 0.60 (TP) | 0.94 | 0.80 | NR | NR |
Balink [34] | 0.59 (TP) | 0.89 | 0.89 | 0.94 | 0.80 |
Gafter-Gvili [35] | 0.66 | 0.72 | 0.58 | 0.74 | 0.54 |
Singh [36] | 0.38 (TP) | NR | NR | NR | NR |
Bouter [37] | 0.65 (TP) | 0.81 | 0.86 | NR | NR |
Pereira [38] | 0.61 | 0.77 | 0.31 | 0.61 | 0.50 |
Hung [39] | 0.72 | 0.79 | 0.56 | 0.83 | 0.50 |
Abdelrahman [40] | 0.85 (TP) | 0.95 | 0.67 | 0.96 | 0.67 |
Garcia-Vicente [41] | 0.52 | 0.84 | 0.31 | NR | NR |
Schönau [42] | 0.57 (TP) | 0.91 | 0.22 | 0.65 | 0.62 |
Wang [43] | 0.90 | NR | NR | NR | NR |
Wang [44] | 0.58 | 0.88 | 0.15 | 0.59 | 0.47 |
Georga [45] | 0.72 (TP) | 0.94 | 0.50 | 0.86 | 0.75 |
Zhu [46] | 0.74 (TP + TN) | 0.84 | 0.26 | NR | NR |
Kubota [47] | 0.33 (TP) | 0.45 | 0.40 | 0.67 | NR |
Letertre [48] | 0.44 | 0.85 | 0.37 | 0.58 | 0.70 |
MuldersManders [49] | 0.45 | NR | NR | NR | NR |
Bilici Salman [50] | 0.61 (TP) | 0.67 | 1.00 | 1.00 | 0.26 |
Mahajna [51] | 0.48 (TP) | 0.70 | 0.37 | 0.70 | 0.34 |
Das [52] | 0.91 (TP + TN) | 0.77 | 0.33 | 0.83 | 0.25 |
Yadav [53] | 0.63 | NR | NR | NR | NR |
Buchritis [54] | 0.26 | 0.89 | 0.81 | NR | NR |
Chen [55] | 0.91 | NR | NR | NR | NR |
Chen [56] | 0.96 | NR | NR | NR | NR |
Holubar [57] | 0.75 (TP + TN) | 0.84 | 0.62 | 0.77 | 0.72 |
Ogut [58] | 0.72 (TP + TN) | 0.88 | 0.37 | 0.79 | 0.55 |
Ly [59] | 0.19 (TP) | 0.36 | 0.81 | NR | NR |
Weitzer [60] | 0.54 (TP) | 0.80 | 0.90 | NR | NR |
Becker KK [61] | 0.61 (TP + TN) | NR | NR | NR | NR |
Fathala [62] | 0.72 (TP + TN) | 0.72 | 0.29 | 0.68 | 0.33 |
Khan [63] | 0.16 (TP) | NR | NR | NR | NR |
Liu [64] | 0.98 | 0.93 | 0.62 | 0.83 | 0.80 |
Kobayashi [65] | 0.64 | 0.91 | 0.38 | 0.78 | 0.62 |
Koreli [66] | 0.50 (TP) | 1.00 | 0.33 | 0.60 | 1.00 |
Yu [67] | 0.48 | 0.79 | 0.61 | 0.76 | 0.63 |
Greuez [68] | 0.31 | NR | NR | NR | NR |
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Romano Gargarella, E.; Vocaturo, F.; Guarneri, A.; Calcagni, M.L.; Leccisotti, L. Role of 18F FDG-PET-CT in Fever and Inflammation of Unknown Origin. J. Clin. Med. 2025, 14, 5861. https://doi.org/10.3390/jcm14165861
Romano Gargarella E, Vocaturo F, Guarneri A, Calcagni ML, Leccisotti L. Role of 18F FDG-PET-CT in Fever and Inflammation of Unknown Origin. Journal of Clinical Medicine. 2025; 14(16):5861. https://doi.org/10.3390/jcm14165861
Chicago/Turabian StyleRomano Gargarella, Elena, Flaminia Vocaturo, Andrea Guarneri, Maria Lucia Calcagni, and Lucia Leccisotti. 2025. "Role of 18F FDG-PET-CT in Fever and Inflammation of Unknown Origin" Journal of Clinical Medicine 14, no. 16: 5861. https://doi.org/10.3390/jcm14165861
APA StyleRomano Gargarella, E., Vocaturo, F., Guarneri, A., Calcagni, M. L., & Leccisotti, L. (2025). Role of 18F FDG-PET-CT in Fever and Inflammation of Unknown Origin. Journal of Clinical Medicine, 14(16), 5861. https://doi.org/10.3390/jcm14165861