The Role of Molecular Imaging in Patients with Brain Metastases: A Literature Review
Abstract
:Simple Summary
Abstract
1. Introduction
2. Methods
3. [18F]-FDG
4. Amino Acid Radiotracers
4.1. [11C]-MET
4.2. [18F]-FET
4.3. [18F]-DOPA
5. Other Radiotracers
6. Future Perspectives
6.1. Radiomics
6.2. Therapy with Immune Checkpoint Inhibitors
6.3. Theranostics
6.4. Novel Targeted Therapies and PET Imaging
7. Conclusions
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Acknowledgments
Conflicts of Interest
References
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Authors | Year | Study Design | Primary Malignancy | Patients M/F | Aim | Comments |
---|---|---|---|---|---|---|
Krüger et al. [15] | 2011 | P | Lung cancer | 104 (77/27) | To compare MRI and PET/CT for diagnosis BM | PET/CT showed a sensitivity of 27%, with a high number of false positive for BM |
Bochev et al. [16] | 2012 | P | Solid neoplasms | 2502 (NR) | To assess the role of PET/CT for detecting BM | PET/CT detected BM in 1% of all patients |
Manohar et al. [17] | 2013 | R | Solid neoplasms | 5110 (3322/1788) | To assess the role of PET/CT for detecting BM | PET/CT detected BM in only 0.7% of cases |
Nia et al. [18] | 2017 | R | NSCLC | 227 (NR) | To assess the role of follow-up PET/CT for detecting BM | Only 5/227 patients were found to have BM |
Saito et al. [19] | 2021 | R | T1-T2 N0 NSCLC | 466 (272/194) | To assess the frequency of BM | Screening of brain by PET/CT is unnecessary in patients with early stage NSCLC |
Li et al. [20] | 2017 | Meta-analysis | Lung cancer | 941 (NR) | To compare MRI and PET/CT for diagnosis BM | Gadolinium-enhanced MRI had higher sensitivity than PET/CT |
Oldan et al. [21] | 2020 | R | Melanoma | 212 (NR) | To evaluate at what size BM are detectable by PET/CT | Lesions over about 2 cm were detectable by PET/CT |
Lee et al. [22] | 2008 | R | Lung cancer | 48 (31/17) | To compare FDG uptake between NSCLC and SCLC BM | NSCLC BM were more frequently hypermetabolic than those from SCLC |
Meric et al. [23] | 2015 | R | BM, CNS lymphomas, gliomas | 76 (37/39) | To characterize the nature of brain masses | SUVmax and Tmax:Wmimax seem useful parameters to discriminate brain masses |
Purandare et al. [24] | 2017 | R | GBM, CNS lymphoma, BM | 106 (70/36) | To characterize the nature of brain masses | CNS lymphomas showed higher metabolic activity than GBM and BM |
Wang et al. [25] | 2006 | R | BM, gliomas | 117 (58/59) | To differentiate between recurrence and radionecrosis | PET/CT demonstrated: PPV 96% NPV 56% |
Torrens et al. [26] | 2016 | R | BM, glioblastoma | 16 (11/5) | To differentiate between recurrence and radionecrosis co-registering PET/CT and MRI | PET/MRI co-registration determined: Sensitivity 65% Specificity 100% |
Horky et al. [27] | 2011 | R | Solid neoplasms | 32 (10/22) | Dual phase PET/CT to differentiate recurrence from radionecrosis | Variation of L/GM > 0.19 between early and delayed: Sensitivity 955% Specificity 100% Accuracy 96% |
Hatzoglou et al. [28] | 2016 | P | BM, gliomas | 53 (35/18) | To differentiate between recurrence and radionecrosis using PET/CT and DCE MRI | Vp ratio = 2.1 showed highest accuracy: Sensitivity 92% Specificity 77% |
Leiva-Salinas et al. [29] | 2019 | R | BM | 85 (37/48) | To determinate if PET/MRI predicts recurrence after radiosurgery | Relative SUV = 1.75: Sensitivity 87% Specificity 32% |
Authors | Year | Study Design | RP | Primary Malignancy | Patients M/F | Aim | Comments |
---|---|---|---|---|---|---|---|
Minamoto et al. [32] | 2015 | R | [11C]-MET | BM and gliomas | 70 (38/32) | To differentiate between recurrence and radionecrosis | Visual analysis was comparable to quantitative assessment by L/Nmax and L/Nmean |
Govaerts et al. [33] | 2021 | R | [11C]-MET | Solid neoplasms | 26 (13/13) | To differentiate between recurrence and radionecrosis | SUVmax of 3.9 was the best parameter: AUC = 0.834 sensitivity 78.6% specificity 70.6% PPV 74.3% NPV 75.3% |
Yomo et al. [34] | 2017 | P | [11C]-MET | Solid neoplasms | 32 (19/13) | To differentiate between recurrence and radionecrosis | LNR of 1.40 showed: AUC 0.84 sensitivity 82% specificity 75% |
Matsuo et al. [35] | 2009 | P | [11C]-MET | Solid neoplasms | 19 (14/5) | To delineate and to compare target volumes with MRI | Tumor volume on PET imaging was significantly larger than that on MRI for lesions >0.5 mL |
Momose et al. [36] | 2014 | R | [11C]-MET | NR | 88 (48/40) | To differentiate between recurrence and radionecrosis | [11C]-MET-PET was predictive for longer OS after stereotactic radiosurgery |
Rottenburger et al. [37] | 2011 | P | [11C]-MET, [11C]-choline | Solid neoplasms | 8 (NR) | To compare [11C]-MET and [11C]-choline PET | [11C]-choline showed a higher LNR |
Tran et al. [38] | 2020 | P | [11C]-MET, [11C]PBR28 | Melanoma, NSCLC | 5 (3/2) | To compare [11C]-MET and [11C]PBR28 PET | [11C]PBR28 was not a valid biomarker to detect radionecrosis |
Cicuendez et al. [39] | 2015 | P | [11C]-MET | NR, gliomas | 43 (24/19) | To evaluate [11C]-MET uptake and relationship with histopathological grade | T/C was higher in BM and high grade gliomas; T/C < 1.9 was associated with longer OS |
Unterrainer et al. [42] | 2017 | R | [18F]-FET | Solid neoplasms | 30 (NR) | To evaluate the uptake characteristics of untreated BM | All BM > 1cm were [18F]-FET positive |
Galldiks et al. [43] | 2012 | P | [18F]-FET | Solid neoplasms | 31 (5/26) | To differentiate between recurrence and radionecrosis | TBRmax of 2.55: AUC 0.822 sensitivity 79% specificity 76% TBRmean of 1.95: AUC 0.851 sensitivity 74% specificity 90% |
Ceccon et al. [44] | 2017 | R | [18F]-FET | Solid neoplasms | 62 (14/48) | To role of dynamic PET scan to differentiate recurrence from radiation injury | TBRmean > 1.95 + a slope < 0.37 SUV/ h: accuracy 88% sensitivity 83% specificity 93% |
Kebir et al. [45] | 2016 | R | [18F]-FET | melanoma | 5 (NR) | To evaluate pseudoprogression in patients treated with ICI | TBRmax was higher in patients with true progression (5.4 vs. 2.5), as well as time to peak was significantly shorter (17 min vs. 45 min) |
Romagna et al. [46] | 2016 | R | [18F]-FET | Solid neoplasms | 22 (11/11) | To differentiate between recurrence and radionecrosis | TBRmax of 2.15 and TBRmean of 1.95: AUC 0.84 sensitivity 86% specificity 79% TBRs + decreasing TAC: AUC 0.79 sensitivity 91% specificity 83% |
Grosu et al. [47] | 2011 | P | [18F]-FET, [11C]-MET | Solid neoplasms, gliomas | 42 (NR) | To compare [18F]-FET and [11C]-MET uptake in gliomas and BM; To compare volumes between PET and MRI | [18F]-FET and [11C]-MET strongly correlated; Both radiotracers: sensitivity 91% specificity 100% |
Gempt et al. [48] | 2015 | R | [18F]-FET | Solid neoplasms | 41 (NR) | To delineate and to compare target volumes with MRI | Tumor volumes by [18F]-FET and MRI were only partially overlapped |
Papin-Michault [31] | 2016 | R | [18F]-DOPA | Solid neoplasms, non-tumoral tissue | 67 BM 53 control | LAT-1 and CD68 expression in BM | LAT-1 expression level and [18F]-DOPA uptake were significantly correlated |
Lizarraga et al. [50] | 2014 | R | [18F]-DOPA | Solid neoplasms | 32 (26/6) | To differentiate between recurrence and radionecrosis | Visual scoring ≥ 2: sensitivity 81% specificity 84% |
Cicone et al. [51] | 2015 | R | [18F]-DOPA | Solid neoplasms | 42 (NR) | To differentiate between recurrence and radionecrosis and to compare with MRI | SUVLmax/Bkgrmax of 1.59: sensitivity 90% specificity 92% |
Cicone et al. [52] | 2021 | P | [18F]-DOPA | Solid neoplasms | 30 (13/17) | To characterize the long-term metabolic evolution of radionecrosis | rSUV of 1.92: sensitivity 90% specificity 96% |
Humbert et al. [53] | 2019 | P | [18F]-DOPA | Solid neoplasms, glioblastoma | 106 | To evaluate the impact of [18F]-DOPA on the therapeutic decision | For suspicions of tumor recurrence, [18F]-DOPA improved diagnostic accuracy for both BM and glioblastomas |
Authors | Year | Study Design | RF | Primary Malignancy | Patients (M/F) | Aim | Comments |
---|---|---|---|---|---|---|---|
Kamson et al. [54] | 2013 | P | [11C]-AMT | Solid neoplasms, glioblastoma | 36 (20/16) | To discriminate between BM and glioblastomas | BM had lower tumoral SUVs, lower mean tumor/cortex SUVratio, and tumor/cortex VD′-ratio |
Xu et al. [55] | 2018 | P | [18F]-FGln | Solid neoplasms, gliomas | 14 (7/7) | To compare [18F]-Fgln and [18F]-FDG | Detection rates for BM [18F]-Fgln 82% [18F]-FDG 37% |
Yu et al. [56] | 2015 | P | [18F]-Alfatide II | Solid neoplasms, gliomas | 9 (5/4) | To compare [18F]-Alfatide II and [18F]-FDG | All 20 brain lesions were visualized by [18F]-Alfatide II, while only 10 by [18F]-FDG, and 13 by CT. |
Grkovski et al. [58] | 2020 | P | [18F]-choline | Solid neoplasms | 14 (NR) | To evaluate [18F]-choline uptake correlation from surgical samples with pathologic evidence of recurrent tumor | Surgical samples with viable tumor had higher uptake than those without tumor, although inflammation and gliosis also increase the uptake |
Morikawa et al. [59] | 2021 | P | [18F]-FLT | Breast | 15 (NR) | To assess early response to sorafenib and whole-brain radiation therapy | [18F]-FLT seems a valid imaging tool for early response assessment |
O’Sullivan et al. [59] | 2016 | P | [18F]-FLT | Breast | 10 (NR) | To evaluate therapy response | A total of 52% of target lesions showed a reduction in [18F]-FLT SUV ≥20% after treatment |
Allen et al. [61] | 2012 | P | [18F]-ML-10 | Solid neoplasms | 10 (NR) | To evaluate therapy response after radiation therapy | High correlation between early changes on [18F]-ML-10 PET and later changes on MRI |
Øen et al. [62] | 2022 | R | [18F]-fluciclovine | Solid neoplasms | 18 (11/7) | To compare diagnostic accuracy for tumor recurrence between PET/MRI and MRI alone | PET volumes correlated and were comparable in size with those from MRI, but were only partially congruent |
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Urso, L.; Bonatto, E.; Nieri, A.; Castello, A.; Maffione, A.M.; Marzola, M.C.; Cittanti, C.; Bartolomei, M.; Panareo, S.; Mansi, L.; et al. The Role of Molecular Imaging in Patients with Brain Metastases: A Literature Review. Cancers 2023, 15, 2184. https://doi.org/10.3390/cancers15072184
Urso L, Bonatto E, Nieri A, Castello A, Maffione AM, Marzola MC, Cittanti C, Bartolomei M, Panareo S, Mansi L, et al. The Role of Molecular Imaging in Patients with Brain Metastases: A Literature Review. Cancers. 2023; 15(7):2184. https://doi.org/10.3390/cancers15072184
Chicago/Turabian StyleUrso, Luca, Elena Bonatto, Alberto Nieri, Angelo Castello, Anna Margherita Maffione, Maria Cristina Marzola, Corrado Cittanti, Mirco Bartolomei, Stefano Panareo, Luigi Mansi, and et al. 2023. "The Role of Molecular Imaging in Patients with Brain Metastases: A Literature Review" Cancers 15, no. 7: 2184. https://doi.org/10.3390/cancers15072184
APA StyleUrso, L., Bonatto, E., Nieri, A., Castello, A., Maffione, A. M., Marzola, M. C., Cittanti, C., Bartolomei, M., Panareo, S., Mansi, L., Lopci, E., Florimonte, L., & Castellani, M. (2023). The Role of Molecular Imaging in Patients with Brain Metastases: A Literature Review. Cancers, 15(7), 2184. https://doi.org/10.3390/cancers15072184