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Updated: Jun 17, 2026

A 3D Organotypic Melanoma Spheroid Skin Model
Published on: May 18, 2018
A Scoring System Based on [ 18 F]PFPN PET and Clinical Features for Predicting Prognosis in Patients With Mucosal
Zhi Lin1,2, Cheng Tang1,2, Yuan Feng1,3
1Department of Nuclear Medicine, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology.
Purpose:
This study aims to establish a prognostic prediction system for mucosal melanoma patients by integrating melanocyte-targeting PET with clinical parameters.
Patients And Methods:
A retrospective study was conducted on primary mucosal melanoma patients who underwent [ 18 F]PFPN PET scans between January 2021 and April 2024. Researchers manually delineated all lesions on the [ 18 F]PFPN PET images and recorded the imaging features. Kaplan-Meier survival analysis, Cox regression, and stepwise regression were used to analyze prognosis and construct the prediction model.
Results:
Fifty patients (mean age 60.5±8.8 y) were included, with a median follow-up of 13 months (1-39 mo) and an average survival of 14.62 months. Multivariate analysis showed that lower Whole-body Melanotic Tumor Volume (WBMTV), earlier stage, younger age, immunotherapy, and head and neck or vulvar subtypes were associated with longer overall survival (OS, P <0.05). A simplified prognostic scoring system was developed based on 5 variables: stage (not detected or I/II/III/IV: 0/5/10/15 points), age (<60/≥60: 0/10), WBMTV (<1.52/≥1.52: 0/10), immunotherapy (yes/no: 0/5), and subtype (head and neck or vulva/others: 0/10). Patients were stratified into low (0-19), intermediate (20-29), and high-risk (30-50) groups. The model's concordance index was 0.85, outperforming the clinical staging (0.76). OS declined progressively from low-risk to high-risk groups, with 1-year survival from 100% to 74.6% and 3-year survival from 100% to 0%.
Conclusions:
[ 18 F]PFPN PET provides an accurate assessment of mucosal melanoma burden, and a prognostic model combining [ 18 F]PFPN PET features and clinical data offers reliable stratification of patient outcomes.

