Predictive value of 18F-FDG PET/CT in molecular subtyping for triple-negative breast cancer
Objective To explore the predictive value of 18F-FDG PET/CT in molecular subtyping of triple-negative breast cancer.Methods A retrospective analysis was performed on the clinical and imaging data of 227 breast cancer patients who underwent 18 F-FDG PET/CT examination in the Tianjin Medical University Cancer Institute & Hospital from January 1,2010 to December 31,2022.Based on the expression levels of estrogen receptor(ER),progesterone receptor(PR),and human epidermal growth factor receptor 2(HER-2)in the primary breast cancer,the patients were categorized into two groups:triple-negative breast cancer(TNBC)and non-TNBC.Radiomic features were extracted from images of both groups,and a radiomic model was constructed to predict the molecular subtype of the TNBC groups.In addition,the clinical data,CT morphological features,and PET metabolic parameters of both groups were compared to determine the indicators with statistically significant differences and develop a comprehensive radiomic model combined with clinical characteristics.Results Compared to the non-TNBC group,the TNBC groups exhibited more significant invasiveness in terms of tumor diameter,margins,ipsilateral axillary lymph node metastasis,invasion of neighboring skin or papillae,and PET metabolic parameters(t=-3.19;x2=7.30,8.10,5.34;t=3.80,3.30,3.42,P＜0.05).The constructed 18F-FDG PET/CT radiomic model proved effective in predicting the molecular subtype of the TNBC group,and the receiver operating characteristic(ROC)curve showed an area under the curve(AUC)of 0.83(95％CI 0.78-0.88),an accuracy of 75.9％,a sensitivity of 74.5％,and a specificity of 77.2％.In contrast,the constructed comprehensive radiomic model displayed an AUC of 0.86(95％CI 0.81-0.90),an accuracy of 77.2％,a sensitivity of 78.6％,and a specificity of 75.9％.Conclusions 18F-FDG PET/CT plays an important role in predicting molecular subtypes of TNBC.The constructed radiomic model and comprehensive radiomic model can further enhance the prediction efficacy of PET metabolic parameters and accelerate the development of accurate treatment protocols in clinical practice,thus improving the prognosis of breast cancer.
Triple-negative breast cancerMolecular subtype18F-FDG PET/CTMetabolic parameterRadiomics
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