Prognostic Value of Baseline 18F-FDG PET/CT to Predict Brain Metastasis Development in Melanoma Patients
To investigate the value of 18F-FDG-PET/CT in predicting the occurrence of brain metastases in melanoma patients, in this retrospective study 201 consecutive patients with pathology-proven melanoma, between 2008 and 2021, were reviewed. Those who underwent 18F-FDG-PET/CT for initial staging were con...
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Veröffentlicht in: | Cancers 2023-12, Vol.16 (1), p.127 |
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Zusammenfassung: | To investigate the value of 18F-FDG-PET/CT in predicting the occurrence of brain metastases in melanoma patients, in this retrospective study 201 consecutive patients with pathology-proven melanoma, between 2008 and 2021, were reviewed. Those who underwent 18F-FDG-PET/CT for initial staging were considered eligible. Baseline assessment included histopathology, 18F-FDG-PET/CT, and brain MRI. Also, all patients had serial follow-ups for diagnosing brain metastasis development. Baseline 18F-FDG-PET/CT parameters were analysed using competing risk regression models to analyze their correlation with the occurrence of brain metastases. Overall, 159 patients entered the study. The median follow-up was six years. Among clinical variables, the initial M-stage and TNM-stage were significantly correlated with brain metastasis. Regarding 18F-FDG-PET/CT parameters, regional metastatic lymph node uptake values, as well as prominent SULmax (pSULmax) and prominent SUVmean (pSUVmean), were significantly correlated with the outcome. Cumulative incidences were 10% (6.3–16%), 31% (24.4–38.9%), and 35.2% (28.5–43.5%) after 1, 5, and 10 years. There were significant correlations between pSULmax (p-value < 0.001) and pSULpeak (p-value < 0.001) and the occurrence of brain metastases. The higher these values, the sooner the patient developed brain metastases. Thus, baseline 18F-FDG-PET/CT may have the potential to predict brain metastasis in melanoma patients. Those with high total metabolic activity should undergo follow-up/complementary evaluations, such as brain MRI. |
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ISSN: | 2072-6694 2072-6694 |
DOI: | 10.3390/cancers16010127 |