The DOI matches its Crossref record; 1 of the 1 references it cites were found in a registry or an index.
68Ga-FAPI PET/CT: Tracer Uptake in 28 Different Kinds of Cancer
Open accessAbstract
The recent development of quinoline-based PET tracers that act as fibroblast-activation-protein inhibitors (FAPIs) demonstrated promising preclinical and clinical results. FAP is overexpressed by cancer-associated fibroblasts of several tumor entities. Here, we quantify the tumor uptake on 68Ga-FAPI PET/CT of various primary and metastatic tumors to identify the most promising indications for future application. Methods:68Ga-FAPI PET/CT scans were requested by various referring physicians according to individual clinical indications that were considered insufficiently covered by 18F-FDG PET/CT or other imaging modalities. All PET/CT was performed 1 h after injection of 122–312 MBq of 68Ga-FAPI-04. We retrospectively identified 80 patients with histopathologically proven primary tumors or metastases or radiologically unequivocal metastatic lesions of histologically proven primary tumors. Tumor uptake was quantified by SUVmax and SUVmean (60% isocontour). Results: Eighty patients with 28 different tumor entities (54 primary tumors and 229 metastases) were evaluated. The highest average SUVmax (>12) was found in sarcoma, esophageal, breast, cholangiocarcinoma, and lung cancer. The lowest 68Ga-FAPI uptake (average SUVmax < 6) was observed in pheochromocytoma, renal cell, differentiated thyroid, adenoid cystic, and gastric cancer. The average SUVmax of hepatocellular, colorectal, head–neck, ovarian, pancreatic, and prostate cancer was intermediate (SUV 6–12). SUV varied across and within all tumor entities. Because of low background in muscle and blood pool (SUVmax < 2), the tumor-to-background contrast ratios were more than 3-fold in the intermediate and more than 6-fold in the high-intensity uptake group. Conclusion: Several highly prevalent cancers presented with remarkably high uptake and image contrast on 68Ga-FAPI PET/CT. The high and rather selective tumor uptake may open up new applications for noninvasive tumor characterization, staging examinations, or radioligand therapy.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
Kauhanen, S. P., Komar, G., Seppänen, M. P., Dean, K. I., Minn, H. R., Kajander, S. A., Rinta-Kiikka, I., Alanen, K., Borra, R. J., Puolakkainen, P. A., et al. (2009) · Annals of Surgery · doi:10.1097/sla.0b013e3181b2fafa · Cited by 317
Cited by
Targeting of activated fibroblasts for imaging and therapy
Lindner, T., Loktev, A., Giesel, F., Kratochwil, C., Altmann, A., & Haberkorn, U. (2019) · EJNMMI Radiopharmacy and Chemistry · doi:10.1186/s41181-019-0069-0 · Cited by 205
Self-citationBiological determinants of PSMA expression, regulation and heterogeneity in prostate cancer
Bakht, M. K., & Beltran, H. (2025) · Nature Reviews Urology · doi:10.1038/s41585-024-00900-z · Cited by 158
Radiotheranostics in oncology: Making precision medicine possible
Aboagye, E. O., Barwick, T. D., & Haberkorn, U. (2023) · CA: A Cancer Journal for Clinicians · doi:10.3322/caac.21768 · Cited by 131
Self-citationNuclear medicine and molecular imaging advances in the 21st century
Vaz, S. C., Oliveira, F., Herrmann, K., & Veit-Haibach, P. (2020) · The British Journal of Radiology · doi:10.1259/bjr.20200095 · Cited by 86
Wang, L., Wang, Y., Wang, J., Xiao, M., Xi, X.-Y., Chen, B.-X., Su, Y., Zhang, Y., Xie, B., Dong, Z., et al. (2023) · Radiology · doi:10.1148/radiol.221052 · Cited by 73
Metadata
- Authors
- Kratochwil, C., Flechsig, P., Lindner, T., Abderrahim, L., Altmann, A., Mier, W., Adeberg, S., Rathke, H., Röhrich, M., Winter, H., Plinkert, P. K., Marme, F., Lang, M., Kauczor, H.-U., Jäger, D., Debus, J., Haberkorn, U., & Giesel, F. L.
- Venue
- Journal of Nuclear Medicine
- Publisher
- Society of Nuclear Medicine
- Published
- 2019-04-06
- Volume
- 60
- Issue
- 6
- Pages
- 801-805
- ISSN
- 0161-5505 (ISSN-L)
- 2159-662X
- OpenAlex
- W2930582547
- Cited by
- 1,464
- References
- 1
- FWCI
- 52.33
- Type
- journal article
- Language
- en
- Open access
- bronze
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: 68Ga-FAPI PET/CT: Tracer Uptake in 28 Different Kinds of Cancer. https://app.cochat.ai/papers/10.2967/jnumed.119.227967
- The paper
- Kratochwil, C., Flechsig, P., Lindner, T., Abderrahim, L., Altmann, A., Mier, W., Adeberg, S., Rathke, H., Röhrich, M., Winter, H., Plinkert, P. K., Marme, F., Lang, M., Kauczor, H.-U., Jäger, D., Debus, J., Haberkorn, U., & Giesel, F. L. (2019). 68Ga-FAPI PET/CT: Tracer Uptake in 28 Different Kinds of Cancer. Journal of Nuclear Medicine. https://doi.org/10.2967/jnumed.119.227967
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.