Hu Fan, Zhang Xiao, Shu Hua, Wang Xiaoli, Feng Shuqian, Hu Mengmeng, Lan Xiaoli, Qin Chunxia
Department of Nuclear Medicine, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology Wuhan 430022, Hubei, China.
Hubei Key Laboratory of Molecular Imaging Wuhan 430022, Hubei, China.
Am J Nucl Med Mol Imaging. 2023 Dec 25;13(6):269-278. eCollection 2023.
The aim was to utilize three segmentation methods on F-FDG PET/CT and PET/MR images of pancreatic neoplasm patients, and further compare the effectiveness in differentiating benign from malignant, TNM-stage and prognosis. We conducted a retrospective analysis of 51 patients with pancreatic neoplasm who had undergone F-FDG PET/CT and PET/MR before treatment. The patients were categorized into malignant and benign groups. For each patient, the lesion was segmented by 3 thresholds and we recorded TNM-stage, treatment strategy, time to death, and the performance status of survivors. We used receiver operating characteristic (ROC) analysis to compare the diagnostic performance of different threshold delineations between benign and malignant, as well as TNM-stage of adenocarcinoma patients. The optimal model of prognostic value was also assessed by Cox proportional hazards regression analysis and Kaplan-Meier survival analysis. For both PET/CT and PET/MR, SUV had the best diagnostic efficacy in identifying malignant tumors. The background method of PET/MR exhibited the outstanding performance in M-stage (sensitivity/specificity, 92.90%/88.20%), with the weighted factor being whole-body total lesion glycolysis (WBTLG). In multivariate analysis, WBTLG (Exp [B] = 1.009; = 0.009), and surgery (Exp [B] = 15.542; = 0.008) were independent predictive factors associated with prognosis. This study found that SUV from PET/CT had the best diagnostic efficacy in identifying malignancy, while PET/MR showed higher specificity and accuracy for M-stage. The treatment strategy and WBTLG were independent prognostic factors in pancreatic neoplasm patients. PET/MR using the background method was identified as the optimal predictive model for prognosis.
目的是对胰腺肿瘤患者的F-FDG PET/CT和PET/MR图像应用三种分割方法,并进一步比较在区分良恶性、TNM分期和预后方面的有效性。我们对51例在治疗前接受过F-FDG PET/CT和PET/MR检查的胰腺肿瘤患者进行了回顾性分析。将患者分为恶性组和良性组。对每位患者,通过3种阈值对病变进行分割,并记录TNM分期、治疗策略、死亡时间和幸存者的功能状态。我们使用受试者操作特征(ROC)分析来比较良性和恶性之间不同阈值划定的诊断性能,以及腺癌患者的TNM分期。还通过Cox比例风险回归分析和Kaplan-Meier生存分析评估了预后价值的最佳模型。对于PET/CT和PET/MR,SUV在识别恶性肿瘤方面具有最佳诊断效能。PET/MR的背景方法在M期表现出色(敏感性/特异性,92.90%/88.20%),加权因子为全身总病变糖酵解(WBTLG)。在多变量分析中,WBTLG(Exp[B]=1.009;P=0.009)和手术(Exp[B]=15.542;P=0.008)是与预后相关的独立预测因素。本研究发现,PET/CT的SUV在识别恶性肿瘤方面具有最佳诊断效能,而PET/MR对M期显示出更高的特异性和准确性。治疗策略和WBTLG是胰腺肿瘤患者的独立预后因素。采用背景方法的PET/MR被确定为预后的最佳预测模型。