Predicting malignancy in patients with adrenal tumors using (18)F-FDG-PET/CT SUVmax Journal Article


Authors: Vos, E. L.; Grewal, R. K.; Russo, A. E.; Reidy-Lagunes, D.; Untch, B. R.; Gavane, S. C.; Boucai, L.; Geer, E.; Gopalan, A.; Chou, J. F.; Capanu, M.; Strong, V. E.
Article Title: Predicting malignancy in patients with adrenal tumors using (18)F-FDG-PET/CT SUVmax
Abstract: Background and Objectives: 18F-fluorodeoxyglucose positron emission tomography/computed tomography (18F-FDG-PET/CT) parameters may help distinguish malignant from benign adrenal tumors, but few have been externally validated or determined based on definitive pathological confirmation. We determined and validated a threshold for 18F-FDG-PET/CT maximum standard uptake value (SUVmax) in patients who underwent adrenalectomy for a nonfunctional tumor. Methods: Database review identified patients with 18F-FDG-PET/CT images available (training cohort), or only SUVmax values (validation cohort). Discriminative accuracy was assessed by area under the curve (AUC), and the optimal cutoff value estimated by maximally selected Wilcoxon rank statistics. Results: Of identified patients (n = 171), 86 had adrenal metastases, 20 adrenal cortical carcinoma, and 27 adrenal cortical adenoma. In the training cohort (n = 96), SUVmax was significantly higher in malignant versus benign tumors (median 8.3 vs. 3.0, p <.001), with an AUC of 0.857. Tumor size did not differ. The optimal cutoff SUVmax was 4.6 (p <.01). In the validation cohort (n = 75), this cutoff had a sensitivity of 75% and specificity 55%. Conclusions: 18F-FDG-PET/CT SUVmax was associated with malignancy. Validation indicated that SUVmax ≥ 4.6 was suggestive of malignancy, while lower values did not reliably predict benign tumor. © 2020 Wiley Periodicals LLC
Keywords: adrenal metastasis; incidentaloma; predictive tool; adrenal cortical carcinoma; adrenal cortical adenoma
Journal Title: Journal of Surgical Oncology
Volume: 122
Issue: 8
ISSN: 0022-4790
Publisher: Wiley Blackwell  
Date Published: 2020-12-15
Start Page: 1821
End Page: 1826
Language: English
DOI: 10.1002/jso.26203
PUBMED: 32914407
PROVIDER: scopus
PMCID: PMC7793554
DOI/URL:
Notes: Article -- Export Date: 4 January 2021 -- Source: Scopus
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MSK Authors
  1. Joanne Fu-Lou Chou
    333 Chou
  2. Ravinder K Grewal
    82 Grewal
  3. Marinela Capanu
    388 Capanu
  4. Diane Lauren Reidy
    294 Reidy
  5. Anuradha Gopalan
    417 Gopalan
  6. Somali C Gavane
    24 Gavane
  7. Vivian Strong
    268 Strong
  8. Brian Untch
    65 Untch
  9. Laura   Boucai
    48 Boucai
  10. Ashley Elizabeth Russo
    18 Russo
  11. Eliza Brevoort Geer
    50 Geer
  12. Elvira Lise Vos
    26 Vos