18 F-FDG PET/CT在三阴性乳腺癌分子分型诊断中的价值

目的 探究¹⁸F-氟脱氧葡萄糖-正电子体层扫描成像(¹⁸F-FDG PET/CT)在三阴性乳腺癌分子分型诊断中的价值。方法 回顾性分析2010年1月1日至2022年12月31日在天津医科大学肿瘤医院行¹⁸F-FDG PET/CT检查的227例乳腺癌患者的临床和影像学资料,根据乳腺癌原发灶雌激素受体(ER)、孕激素受体(PR)及人表皮生长因子受体2(HER-2)表达状态将患者分为三阴性乳腺癌和非三阴性乳腺癌两组;基于PET图像和CT图像,提取影像组学特征,构建影像组学模型用于预测三阴性乳腺癌的分子分型;并比较两组患者的临床资料、CT形态学特征和PET代谢参数的差异,筛选出差异有统计学意义的指标,建立联合临床特征的综合性影像组学模型。结果 与非三阴性乳腺癌相比,三阴性乳腺癌在肿瘤直径、边缘、合并同侧腋下淋巴结转移、累犯邻近皮肤乳头及PET代谢参数等方面表现出更显著的侵袭性(t=-3.19,χ²=7.30、8.10、5.34,t=3.80、3.30、3.42,P＜ 0.05)。构建的¹⁸F-FDG PET/CT影像组学模型能够有效预测三阴性乳腺癌的分子分型,受试者工作特征(ROC)曲线分析显示,曲线下面积(AUC)为0.83(95%CI 0.78~0.88),预测准确度为75.9%,灵敏度为74.5%,特异度为77.2%。构建的综合性影像组学模型AUC为0.86(95%CI 0.81~0.90),预测准确度为77.2%,灵敏度为78.6%,特异度为75.9%。结论 ¹⁸F-FDG PET/CT在三阴性乳腺癌分子分型诊断中发挥重要价值,构建的影像组学模型和综合性影像组学模型进一步提高了PET代谢参数的预测效能,有助于临床上尽早制定准确的治疗方案,从而改善患者预后。

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 ¹⁸F-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; χ² = 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.