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Review
. 2023 Jan 5;15(2):355.
doi: 10.3390/cancers15020355.

The Emerging Role of PET/CT with PSMA-Targeting Radiopharmaceuticals in Clear Cell Renal Cancer: An Updated Systematic Review

Affiliations
Review

The Emerging Role of PET/CT with PSMA-Targeting Radiopharmaceuticals in Clear Cell Renal Cancer: An Updated Systematic Review

Alessio Rizzo et al. Cancers (Basel). .

Abstract

Background: Recent articles proposed the employment of positron emission tomography/computed tomography (PET/CT) with prostate-specific membrane antigen (PSMA)-targeting radiopharmaceuticals in clear cell renal cell carcinoma (ccRCC).

Methods: The authors performed a comprehensive literature search of studies on the performance of PET/CT with PSMA-targeting radiopharmaceuticals in ccRCC. Original articles concerning this imaging examination were included in newly diagnosed ccRCC patients and ccRCC patients with disease recurrence.

Results: A total of sixteen papers concerning the diagnostic performance of PSMA-targeted PET/CT in ccRCC (331 patients) were included in this systematic review. The included articles demonstrated an excellent detection rate of PSMA-targeting PET/CT in ccRCC.

Conclusions: PSMA-targeted PET/CT seems promising in detecting ccRCC lesions as well as in discriminating the presence of aggressive phenotypes. Prospective multicentric studies are warranted to strengthen the role of PSMA-targeting PET/CT in ccRCC.

Keywords: PET; PSMA; clear cell renal cell carcinoma; imaging; kidney; nuclear medicine; oncology.

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Conflict of interest statement

The authors declare no conflict of interest.

Figures

Figure 1
Figure 1
Comprehensive overview of the study selection process for the systematic review.
Figure 2
Figure 2
Summary of quality assessment according to the QUADAS-2 tool. The authors classified the papers included in the systematic review as a high risk or low risk of bias or applicability concerns for distinct domains listed in the ordinate axis. In contrast, the abscissa axis shows the percentage of studies. The graph indicates that about 60% of studies suffered a high risk of bias in “patient selection”, whereas a poor risk of bias was observed in “reference standard”, “index test”, and “flow and timing” domains.

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