The PET Imaging in the Surgical Management of Melanoma Study is a prospective nonrandomized clinical trial designed to test positron emission tomography using fluordeoxyglucose (FDG-PET) as a possible noninvasive staging technique to identify melanoma patients who may benefit from lymph node dissection or other therapies. Hypothesis: PET imaging of glucose metabolism in patients with clinically localized melanoma will provide a sensitive and specific marker for regional and distant metastatic disease. FDG-PET will be useful as an adjunct (or alternative) to surgical interrogation of lymph node basins for selection of patients for regional lymphadenectomy and other therapies.
Specific Aims : 1) To compare FDG-PET imaging of regional lymph nodes to histologic analysis of surgically mapped and biopsied or resected regional lymph node basins in patients with clinically localized cutaneous melanoma. 2) To determine if FDG-PET imaging of patients with clinically localized melanoma identifies a subset of patients with subclinical distant metastatic disease. 3) To estimate the minimum regional lymph node tumor burden necessary for FDG-PET detection. Methods: Approximately 165 patients with localized primary or recurrent cutaneous melanoma will undergo whole body FDG-PET scans to screen for metastatic disease. Patients with possible distant metastases by FDG_PET will have conformation with conventional radiologic techniques. Patients without distant metastatic disease will undergo surgical interrogation with sentinel node biopsy or lymphadenectomy of all node basins identified by lymphatic mapping to be at risk for metastatic disease. FDG-PET scans and histologic analysis of lymph node specimens will be correlated to determine sensitivity, specificity and predictive value of FDG-PET for detection of occult regional lymph node metastases. FDG-PET will be compared to conventional imaging and clinical followup for identification of occult distant metastatic disease. Minimum nodal tumor volume necessary for FDG-PET detection will be estimated using regression analysis.
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