Abstract
BACKGROUND AND AIM: To evaluate the diagnostic value of integrated F-fluorodeoxyglucose (FDG) positron emission tomography and computed tomography (PET/CT) to discriminate malignant from benign ovarian tumors. METHODS: One hundred and eight women suspected of having ovarian cancer underwent preoperative FDG-PET/CT scans. FDG uptake was quantified by calculating the maximum standardized uptake value (SUVmax) of each tumor. The receiver operating characteristic curve was drawn to determine the optimal cut-off values of SUVmax that would best discriminate between benign and malignant tumors. Histopathologic results served as the reference standard. We assessed the association between SUVmax and with International Federation of Gynecology and Obsterics stage in borderline and malignant tumors, using one-factor analysis of variance and an unpaired t test with Bonferoni correction. RESULTS: The SUVmax of benign (n=26), borderline (n=12) and malignant (n=73) lesions was 2.00±1.02, 2.72±1.04, and 7.55±4.29, respectively. Although there were significant differences between benign and malignant, and borderline and malignant lesions (P<0.0001), there was no significant difference between benign and borderline lesions. Using an SUVmax cutoff of 2.55, the sensitivity, specificity and accuracy of FDG-PET/CT scanning to detect malignant or borderline tumors were 82.4, 76.9, and 81.1%, respectively. The SUVmax of stage I (n=35), stage II (n=8), stage III (n=34) and stage IV (n=8) was 3.59±2.32, 5.18±1.34, 8.72±2.69, and 15.05±3.77, respectively, and significant differences were observed between SUVmax values and the various International Federation of Gynecology and Obsterics stage (P<0.0001). CONCLUSION: FDG-PET/CT scanning has a high diagnostic value in differentiating between malignant and benign tumors, and a low diagnostic value in differentiating between borderline and benign tumors.
| Original language | English |
|---|---|
| Pages (from-to) | 549-553 |
| Number of pages | 5 |
| Journal | Nuclear medicine communications |
| Volume | 32 |
| Issue number | 7 |
| DOIs | |
| Publication status | Published - 07-2011 |
| Externally published | Yes |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 3 Good Health and Well-being
All Science Journal Classification (ASJC) codes
- Radiology Nuclear Medicine and imaging
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