Diagnostic Performance and Prognostic Value of PET/CT with Different Tracers for Brain Tumors: A Systematic Review of Published Meta-Analyses
Abstract
:1. Introduction
2. Methods
3. Results
3.1. Evaluation of Suspicious Primary Brain Tumor
3.1.1. 18F-FDG
3.1.2. 11C-Methionine
3.1.3. 18F-FET
3.1.4. 18F-FDOPA
3.2. Glioma Grading
3.2.1. 18F-FDG
3.2.2. 11C-Methionine
3.2.3. 18F-FET
3.2.4. 18F-FDOPA
3.3. Delineation of Gliomas
3.4. Diagnosis of Recurrent Brain Tumors
3.4.1. 18F-FDG
3.4.2. 11C-Methionine
3.4.3. 18F-FET
3.4.4. 18F-FDOPA
3.4.5. 18F-FLT
3.4.6. 18C-Choline
3.5. Diagnosis of Brain Metastases
3.6. Diagnosis of Recurrent Brain Metastases
3.7. Diagnosis of Primary Central Nervous System Lymphoma (PCNSL)
3.8. Prognostic Value In Patients With Glioma
4. Discussion
Author Contributions
Funding
Conflicts of Interest
Appendix A
References
- Treglia, G.; Sadeghi, R.; Del Sole, A.; Giovanella, L. Diagnostic performance of PET/CT with tracers other than F-18-FDG in oncology: An evidence-based review. Clin. Transl. Oncol. 2014, 16, 770–775. [Google Scholar] [CrossRef] [PubMed]
- Muoio, B.; Giovanella, L.; Treglia, G. Recent Developments of 18F-FET PET in Neuro-oncology. Curr. Med. Chem. 2018, 25, 3061–3073. [Google Scholar] [CrossRef] [PubMed]
- Treglia, G. Diagnostic Performance of 18F-FDG PET/CT in Infectious and Inflammatory Diseases according to Published Meta-Analyses. Contrast Media Mol. Imaging 2019, 2019. [Google Scholar] [CrossRef] [PubMed]
- Mattoli, M.V.; Treglia, G.; Trevisi, G.; Muoio, B.; Cason, E. Usefulness of 11C-Methionine Positron Emission Tomography in Differential Diagnosis between Recurrent Tumours and Radiation Necrosis in Patients with Glioma: An Overview. Open Neurosurg. J. 2012, 5, 8–11. [Google Scholar] [CrossRef]
- Bell, C.; Dowson, N.; Puttick, S.; Gal, Y.; Thomas, P.; Fay, M.; Smith, J.; Rose, S. Increasing feasibility and utility of (18) F-FDOPA PET for the management of glioma. Nucl. Med. Biol. 2015, 42, 788–795. [Google Scholar] [CrossRef]
- Bertagna, F.; Biasiotto, G.; Giubbini, R. The role of F-18-fluorothymidine PET in oncology. Clin. Transl. Imaging 2013, 1, 77–97. [Google Scholar] [CrossRef] [Green Version]
- Treglia, G.; Giovannini, E.; Di Franco, D.; Calcagni, M.L.; Rufini, V.; Picchio, M.; Giordano, A. The role of positron emission tomography using carbon-11 and fluorine-18 choline in tumors other than prostate cancer: A systematic review. Ann. Nucl. Med. 2012, 26, 451–461. [Google Scholar] [CrossRef]
- Xiao, J.; Jin, Y.; Nie, J.; Chen, F.; Ma, X. Diagnostic and grading accuracy of (18) F-FDOPA PET and PET/CT in patients with gliomas: A systematic review and meta-analysis. BMC Cancer 2019, 19. [Google Scholar] [CrossRef] [PubMed]
- Kim, S.J.; Ryul Shim, S. Diagnostic value of radiolabeled amino acid PET for detection of pseudoprogression of brain tumor after treatment: A meta-analysis. Nucl. Med. Commun. 2019, 40, 965–972. [Google Scholar] [CrossRef] [PubMed]
- Zhang, Q.; Gao, X.; Wei, G.; Qiu, C.; Qu, H.; Zhou, X. Prognostic Value of MTV, SUVmax and the T/N Ratio of PET/CT in Patients with Glioma: A Systematic Review and Meta-Analysis. J. Cancer 2019, 10, 1707–1716. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Katsanos, A.H.; Alexiou, G.A.; Fotopoulos, A.D.; Jabbour, P.; Kyritsis, A.P.; Sioka, C. Performance of 18F-FDG, 11C-Methionine, and 18F-FET PET for Glioma Grading: A Meta-analysis. Clin. Nucl. Med. 2019. [Google Scholar] [CrossRef] [PubMed]
- Furuse, M.; Nonoguchi, N.; Yamada, K.; Shiga, T.; Combes, J.D.; Ikeda, N.; Kawabata, S.; Kuroiwa, T.; Miyatake, S.I. Radiological diagnosis of brain radiation necrosis after cranial irradiation for brain tumor: A systematic review. Radiat. Oncol. 2019, 14. [Google Scholar] [CrossRef] [PubMed]
- Suh, C.H.; Kim, H.S.; Jung, S.C.; Choi, C.G.; Kim, S.J. Comparison of MRI and PET as Potential Surrogate Endpoints for Treatment Response After Stereotactic Radiosurgery in Patients with Brain Metastasis. AJR Am. J. Roentgenol. 2018, 211, 1332–1341. [Google Scholar] [CrossRef] [PubMed]
- Gao, L.; Xu, W.; Li, T.; Zheng, J.; Chen, G. Accuracy of 11C-choline positron emission tomography in differentiating glioma recurrence from radiation necrosis: A systematic review and meta-analysis. Medicine 2018, 97. [Google Scholar] [CrossRef]
- Kim, Y.I.; Kim, Y.; Lee, J.Y.; Jang, S.J. Prognostic Value of the Metabolic and Volumetric Parameters of (11) C-Methionine Positron-Emission Tomography for Gliomas: A Systematic Review and Meta-Analysis. AJNR Am. J. Neuroradiol. 2018, 39, 1629–1634. [Google Scholar] [CrossRef]
- Yu, J.; Zheng, J.; Xu, W.; Weng, J.; Gao, L.; Tao, L.; Liang, F.; Zhang, J. Accuracy of (18) F-FDOPA Positron Emission Tomography and (18) F-FET Positron Emission Tomography for Differentiating Radiation Necrosis from Brain Tumor Recurrence. World Neurosurg. 2018, 114, 1211–1224. [Google Scholar] [CrossRef] [PubMed]
- Li, H.; Deng, L.; Bai, H.X.; Sun, J.; Cao, Y.; Tao, Y.; States, L.J.; Farwell, M.D.; Zhang, P.; Xiao, B.; et al. Diagnostic Accuracy of Amino Acid and FDG-PET in Differentiating Brain Metastasis Recurrence from Radionecrosis after Radiotherapy: A Systematic Review and Meta-Analysis. AJNR Am. J. Neuroradiol. 2018, 39, 280–288. [Google Scholar] [CrossRef]
- Xu, W.; Gao, L.; Shao, A.; Zheng, J.; Zhang, J. The performance of 11C-Methionine PET in the differential diagnosis of glioma recurrence. Oncotarget 2017, 8, 91030–91039. [Google Scholar] [CrossRef] [Green Version]
- Falk Delgado, A.; Falk Delgado, A. Discrimination between primary low-grade and high-grade glioma with (11) C-methionine PET: A bivariate diagnostic test accuracy meta-analysis. Br. J. Radiol. 2018, 91. [Google Scholar] [CrossRef]
- Yang, Y.; He, M.Z.; Li, T.; Yang, X. MRI combined with PET-CT of different tracers to improve the accuracy of glioma diagnosis: A systematic review and meta-analysis. Neurosurg. Rev. 2019, 42, 185–195. [Google Scholar] [CrossRef]
- Verburg, N.; Hoefnagels, F.W.A.; Barkhof, F.; Boellaard, R.; Goldman, S.; Guo, J.; Heimans, J.J.; Hoekstra, O.S.; Jain, R.; Kinoshita, M.; et al. Diagnostic Accuracy of Neuroimaging to Delineate Diffuse Gliomas within the Brain: A Meta-Analysis. AJNR Am. J. Neuroradiol. 2017, 38, 1884–1891. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Zou, Y.; Tong, J.; Leng, H.; Jiang, J.; Pan, M.; Chen, Z. Diagnostic value of using 18F-FDG PET and PET/CT in immunocompetent patients with primary central nervous system lymphoma: A systematic review and meta-analysis. Oncotarget 2017, 8, 41518–41528. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Yang, M.; Sun, J.; Bai, H.X.; Tao, Y.; Tang, X.; States, L.J.; Zhang, Z.; Zhou, J.; Farwell, M.D.; Zhang, P.; et al. Diagnostic accuracy of SPECT, PET, and MRS for primary central nervous system lymphoma in HIV patients: A systematic review and meta-analysis. Medicine (Baltimore) 2017, 96. [Google Scholar] [CrossRef] [PubMed]
- Li, Y.; Jin, G.; Su, D. Comparison of Gadolinium-enhanced MRI and 18FDG PET/PET-CT for the diagnosis of brain metastases in lung cancer patients: A meta-analysis of 5 prospective studies. Oncotarget 2017, 8, 35743–35749. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Dunet, V.; Pomoni, A.; Hottinger, A.; Nicod-Lalonde, M.; Prior, J.O. Performance of 18F-FET versus 18F-FDG-PET for the diagnosis and grading of brain tumors: Systematic review and meta-analysis. Neuro Oncol. 2016, 18, 426–434. [Google Scholar] [CrossRef] [PubMed]
- Li, Z.; Yu, Y.; Zhang, H.; Xu, G.; Chen, L. A meta-analysis comparing 18F-FLT PET with 18F-FDG PET for assessment of brain tumor recurrence. Nucl. Med. Commun. 2015, 36, 695–701. [Google Scholar] [CrossRef] [PubMed]
- Wang, X.; Hu, X.; Xie, P.; Li, W.; Li, X.; Ma, L. Comparison of magnetic resonance spectroscopy and positron emission tomography in detection of tumor recurrence in posttreatment of glioma: A diagnostic meta-analysis. Asia Pac. J. Clin. Oncol. 2015, 11, 97–105. [Google Scholar] [CrossRef] [PubMed]
- Zhao, C.; Zhang, Y.; Wang, J. A meta-analysis on the diagnostic performance of (18) F-FDG and (11) C-methionine PET for differentiating brain tumors. AJNR Am. J. Neuroradiol. 2014, 35, 1058–1065. [Google Scholar] [CrossRef] [PubMed]
- Deng, S.M.; Zhang, B.; Wu, Y.W.; Zhang, W.; Chen, Y.Y. Detection of glioma recurrence by 11C-methionine positron emission tomography and dynamic susceptibility contrast-enhanced magnetic resonance imaging: A meta-analysis. Nucl. Med. Commun. 2013, 34, 758–766. [Google Scholar] [CrossRef]
- Nihashi, T.; Dahabreh, I.J.; Terasawa, T. Diagnostic accuracy of PET for recurrent glioma diagnosis: A meta-analysis. AJNR Am. J. Neuroradiol. 2013, 34, 944–950. [Google Scholar] [CrossRef] [PubMed]
- Dunet, V.; Rossier, C.; Buck, A.; Stupp, R.; Prior, J.O. Performance of 18F-fluoro-ethyl-tyrosine (18F-FET) PET for the differential diagnosis of primary brain tumor: A systematic review and Metaanalysis. J. Nucl. Med. 2012, 53, 207–214. [Google Scholar] [CrossRef] [PubMed]
- Law, I.; Albert, N.L.; Arbizu, J.; Boellaard, R.; Drzezga, A.; Galldiks, N.; la Fougère, C.; Langen, K.J.; Lopci, E.; Lowe, V.; et al. Joint EANM/EANO/RANO practice guidelines/SNMMI procedure standards for imaging of gliomas using PET with radiolabelled amino acids and [(18)F] FDG: Version 1.0. Eur. J. Nucl. Med. Mol. Imaging 2019, 46, 540–557. [Google Scholar] [CrossRef] [PubMed]
- Sadeghi, R.; Treglia, G. Systematic reviews and meta-analyses of diagnostic studies: A practical guideline. Clin. Transl. Imaging 2017, 5, 83–87. [Google Scholar] [CrossRef]
- Treglia, G.; Sadeghi, R. Meta-analyses and systematic reviews on PET and PET/CT in oncology: The state of the art. Clin. Transl. Imaging 2013, 1, 73–75. [Google Scholar] [CrossRef]
- Galldiks, N.; Albert, N.L.; Sommerauer, M.; Grosu, A.L.; Ganswindt, U.; Law, I.; Preusser, M.; Le Rhun, E.; Vogelbaum, M.A.; Zadeh, G.; et al. PET imaging in patients with meningioma-report of the RANO/PET Group. Neuro Oncol. 2017, 19, 1576–1587. [Google Scholar] [CrossRef]
- Sasikumar, A.; Kashyap, R.; Joy, A.; Charan Patro, K.; Bhattacharya, P.; Reddy Pilaka, V.K.; Oommen, K.E.; Pillai, M.R.A. Utility of 68Ga-PSMA-11 PET/CT in Imaging of Glioma-A Pilot Study. Clin. Nucl. Med. 2018, 43, 304–309. [Google Scholar] [CrossRef]
- Michaud, L.; Beattie, B.J.; Akhurst, T.; Dunphy, M.; Zanzonico, P.; Finn, R.; Mauguen, A.; Schöder, H.; Weber, W.A.; Lassman, A.B.; et al. (18) F-Fluciclovine ((18) F-FACBC) PET imaging of recurrent brain tumors. Eur. J. Nucl. Med. Mol. Imaging 2019. [Google Scholar] [CrossRef]
- Kamson, D.O.; Juhász, C.; Buth, A.; Kupsky, W.J.; Barger, G.R.; Chakraborty, P.K.; Muzik, O.; Mittal, S. Tryptophan PET in pretreatment delineation of newly-diagnosed gliomas: MRI and histopathologic correlates. J. Neurooncol. 2013, 112, 121–132. [Google Scholar] [CrossRef] [Green Version]
- Heinzel, A.; Stock, S.; Langen, K.J.; Müller, D. Cost-effectiveness analysis of FET PET-guided target selection for the diagnosis of gliomas. Eur. J. Nucl. Med. Mol. Imaging 2012, 39, 1089–1096. [Google Scholar] [CrossRef]
- Heinzel, A.; Stock, S.; Langen, K.J.; Müller, D. Cost-effectiveness analysis of amino acid PET-guided surgery for supratentorial high-grade gliomas. J. Nucl. Med. 2012, 53, 552–558. [Google Scholar] [CrossRef]
- Heinzel, A.; Müller, D.; Langen, K.J.; Blaum, M.; Verburg, F.A.; Mottaghy, F.M.; Galldiks, N. The use of O-(2-18F-fluoroethyl)-L-tyrosine PET for treatment management of bevacizumab and irinotecan in patients with recurrent high-grade glioma: A cost-effectiveness analysis. J. Nucl. Med. 2013, 54, 1217–1222. [Google Scholar] [CrossRef] [PubMed]
- Heinzel, A.; Müller, D.; Yekta-Michael, S.S.; Ceccon, G.; Langen, K.J.; Mottaghy, F.M.; Wiesmann, M.; Kocher, M.; Hattingen, E.; Galldiks, N. O-(2-18F-fluoroethyl)-L-tyrosine PET for evaluation of brain metastasis recurrence after radiotherapy: An effectiveness and cost-effectiveness analysis. Neuro Oncol. 2017, 19, 1271–1278. [Google Scholar] [CrossRef] [PubMed]
Indication | Tracer | Authors | Year | Articles Included | Patients Included | Sensitivity (95% CI) | Specificity (95% CI) | LR + (95% CI) | LR − (95% CI) | DOR (95% CI) |
---|---|---|---|---|---|---|---|---|---|---|
Evaluation of Suspicious Primary Brain Tumor | 18F-FDG | Zhao et al. [28] | 2014 | 3 | 127 | 43% (28–59) | 74% (49–90) | 1.7 (0.6–4.8) | 0.77 (0.48–1.24) | NR |
Dunet et al. [25] | 2016 | 5 | 119 | 38% (27–50) | 86% (31–99) | 2.7 (0.3–27.8) | 0.72 (0.47–1.11) | 4 (0–58) | ||
11C-methionine | Zhao et al. [28] | 2014 | 2 | 85 | 95% (85–98) | 83% (65–93) | 5.5 (2.5–12.2) | 0.07 (0.02–0.2) | NR | |
18F-FET | Dunet et al. [31] | 2012 | 5 | 224 | 82% (74–88) | 76% (44–92) | 3.4 (1.2–9.5) | 0.24 (0.14–0.39) | 14 (3–60) | |
Dunet et al. [25] | 2016 | 5 | 119 | 94% (79–98) | 88% (37–99) | 8.1 (0.8–80.6) | 0.07 (0.02–0.30) | 113 (4–2975) | ||
18F-FDOPA | Xiao et al. [8] | 2019 | 5 | 46 | 71% (54–85) | 86% (42–100) | 3.7 (0.9–15.8) | 0.36 (0.19–0.68) | 10.88 (1.57–75.31) | |
Glioma Grading | 18F-FDG | Dunet et al. [25] | 2016 | 2 | 63 | 60% (mean TBR ≥1.4) 72% (max TBR ≥1.8) | 91% (mean TBR ≥1.4) 73% (max TBR ≥1.8) | NR | NR | NR |
Katsanos et al. [11] | 2019 | 13 | 680 | 63% (51–74) | 89% (73–95) | 5.2 (2.1–13) | 0.42 (0.29–0.6) | 12.4 (3.86–39.8) | ||
11C-methionine | Falk Delgado et al. [19] | 2018 | 13 | 241 | 80% (66–88) | 72% (62–81) | NR | NR | NR | |
Katsanos et al. [11] | 2019 | 8 | 191 | 94% (79–98) | 55% (32–77) | 2.1 (1.25–3.5) | 0.11 (0.03–0.37) | 18.25 (4.73–70.5) | ||
18F-FET | Dunet et al. [25] | 2016 | 2 | 63 | 88% (mean TBR ≥2) 80% (max TBR ≥3) | 73% (mean TBR ≥2) 82% (max TBR ≥3) | NR | NR | NR | |
Katsanos et al. [11] | 2019 | 7 | 259 | 88% (82–93) | 57% (40–73) | 2.1 (1.4–3.15) | 0.2 (0.11–0.37) | 10.16 (3.9–26.5) | ||
18F-FDOPA | Xiao et al. [8] | 2019 | 7 | 219 | 88% (81–93) | 73% (64–81) | 2.9 (2.2–3.85) | 0.16 (0.08–0.36) | 25.87 (10.53–63.54) | |
Glioma Delineation | 11C-methionine | Verburg et al. [21] | 2017 | 5 | NR | [HGG] 93.7% | [HGG] 61.3% | NR | NR | [HGG] 26.6 |
Diagnosis of Recurrent Brain Tumor | 18F-FDG | Nihashi et al. [30] | 2013 | 16 | NR | 77% (66–85) | 78% (54–91) | 3.4 (1.6–7.5) | 0.3 (0.21–0.43) | NR |
Zhao et al. [28] | 2014 | 20 | 643 | 75% (67–81) | 79% (66–88) | 3.5 (2.2–5.7) | 0.32 (0.25–0.41) | NR | ||
Li et al. [26] | 2015 | 22 | NR | 78% (69–85) | 77% (66–85) | 3.3 (2.2–5) | 0.29 (0.20–0.42) | 12 (6–22) | ||
Wang et al. [27] | 2015 | 12 | 418 | 70% (64–75) | 88% (80–93) | 4 (2.1–7.5) | 0.38 (0.29–0.51) | NR | ||
Furuse et al. [12] | 2019 | 9 | 327 | 81% (67–90) | 72% (64–79) | NR | NR | NR | ||
11C-methionine | Nihashi et al. [30] | 2013 | 7 | NR | [HGG] 70% (50–84) | [HGG] 93% (44–100) | [HGG] 10.3 (0.8–139.4) | [HGG] 0.32 (0.18–0.57) | NR | |
Deng et al. [29] | 2013 | 11 | 244 | 87% (81–91.8) | 81.3% (71.5–88.8) | 4.35 (2.8–6.8) | 0.19 (0.13–0.29) | 21.86 (10.7–44.5) | ||
Zhao et al. [28] | 2014 | 8 | 238 | 92% (83–97) | 87% (75–93) | 6.8 (3.4–13.7) | 0.09 (0.04–0.21) | NR | ||
Wang et al. [27] | 2015 | 6 | 156 | 85% (76–91) | 83% (71–92) | 4.4 (2.5–7.7) | 0.22 (0.13–0.35) | NR | ||
Xu et al. [18] | 2017 | 29 | 899 | 88% (85–91) | 85% (80–89) | 5.3 (3.3–8.7) | 0.16 (0.11–0.23) | 35.3 (22.9–54.4) | ||
Furuse et al. [12] | 2019 | 8 | 333 | 81% (73–87) | 81% (74–87) | NR | NR | NR | ||
18F-FET | Yu et al. [16] | 2018 | 27 | NR | 82% (79–84) | 80% (76–83) | 3.9 (3.0–5.1) | 0.21 (0.17–0.27) | 23.03 (14.42–36.77) | |
Furuse et al. [12] | 2019 | 3 | 138 | 91% (79–97) | 95% (61–99) | NR | NR | NR | ||
18F-FDOPA | Yu et al. [16] | 2018 | 21 | NR | 85% (81–88) | 77% (74–81) | 3.4 (2.8–4.3) | 0.21 (0.16–0.29) | 21.7 (12.61–37.33) | |
Xiao et al. [8] | 2019 | 13 | 318 | 92% (88–95) | 76% (66–85) | 2.9 (2–4.1) | 0.13 (0.07–0.23) | 29.65 (13–09–67–15) | ||
AA * | Kim et al. [9] | 2019 | 6 | 212 | 89% (82–94) | 88% (76–94) | 7.3 (3.6–14.7) | 0.12 (0.07–0.21) | 60 (23–152) | |
18F-FLT | Li et al. [26] | 2015 | 5 | NR | 82% (51–95) | 76% (50–91) | 3.5 (1.6–7.7) | 0.24 (0.08–0.70) | 15 (4–56) | |
11C-choline | Gao et al. [14] | 2018 | 6 | 118 | 87% (78–93) | 82% (69–91) | 4.9 (2.6–9.1) | 0.16 (0.09–0.29) | 35.5 (11.7–107.7) | |
Diagnosis of Brain Metastases | 18F-FDG | Li et al. [24] | 2017 | 5 | 941 | 21% (13–32) | 100% (99–100) | 184.7 (24.8–1374) | 0.79 (0.70–0.89) | 235 (31–1799) |
Diagnosis of Recurrent Brain Metastases | 18F-FDG | Li et al. [17] | 2018 | 6 | NR | 85% (77–94) | 90% (83–96) | NR | NR | NR |
Suh et al. [13] | 2018 | 5 | NR | 83% (74–92) | 88% (81–95) | NR | NR | NR | ||
Furuse et al. [12] | 2019 | 3 | NR | 91% (73–97) | 80% (60–91) | NR | NR | NR | ||
11C-methionine | Li et al. [17] | 2018 | 2 | NR | 86% (74–97) | 79% (66–93) | NR | NR | NR | |
Furuse et al. [12] | 2019 | 4 | NR | 79% (67–87) | 76% (61–87) | NR | NR | NR | ||
18F-FET | Li et al. [17] | 2018 | 5 | NR | 83% (76–91) | 89% (83–95) | NR | NR | NR | |
Yu et al. [16] | 2018 | 4 | NR | 80% (76–84) | 79% (75–83) | 3.9 | 0.24 | 19 | ||
18F-FDOPA | Li et al. [17] | 2018 | 2 | NR | 86% (74–97) | 88% (79–97) | NR | NR | NR | |
Yu et al. [16] | 2018 | 2 | NR | 78% (73–82) | 75% (71–89) | 3 | 0.31 | 11 | ||
AA * | Suh et al. [13] | 2018 | 7 | NR | 84% (79–90) | 85% (80–91) | NR | NR | NR | |
Diagnosis of PCNSL | 18F-FDG | Zhou et al. [22] | 2017 | 8 | 129 | 88% (80–94) | 86% (73–94) | 4 (2.3–6.9) | 0.11 (0.04–0.32) | 33.4 (10.4–107.3) |
Yang et al. [23] | 2017 | 6 | 108 | NR | NR | NR | NR | NR |
© 2019 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).
Share and Cite
Treglia, G.; Muoio, B.; Trevisi, G.; Mattoli, M.V.; Albano, D.; Bertagna, F.; Giovanella, L. Diagnostic Performance and Prognostic Value of PET/CT with Different Tracers for Brain Tumors: A Systematic Review of Published Meta-Analyses. Int. J. Mol. Sci. 2019, 20, 4669. https://doi.org/10.3390/ijms20194669
Treglia G, Muoio B, Trevisi G, Mattoli MV, Albano D, Bertagna F, Giovanella L. Diagnostic Performance and Prognostic Value of PET/CT with Different Tracers for Brain Tumors: A Systematic Review of Published Meta-Analyses. International Journal of Molecular Sciences. 2019; 20(19):4669. https://doi.org/10.3390/ijms20194669
Chicago/Turabian StyleTreglia, Giorgio, Barbara Muoio, Gianluca Trevisi, Maria Vittoria Mattoli, Domenico Albano, Francesco Bertagna, and Luca Giovanella. 2019. "Diagnostic Performance and Prognostic Value of PET/CT with Different Tracers for Brain Tumors: A Systematic Review of Published Meta-Analyses" International Journal of Molecular Sciences 20, no. 19: 4669. https://doi.org/10.3390/ijms20194669