疗前FDG PET—CT代谢参数与食管癌放疗预后关系初步研究

Prognostic value of FDG PET-CT metabolic parameters before treatment in patients with esophageal cancer receiving radiotherapy

目的探讨基于FDGPET—CT显像所采集的影像获取食管癌原发灶代谢参数——SUVmax、MTV、TLG及PTL对判断食管癌放疗或放疗联合治疗患者预后价值。方法选择2006—2012年在本院行PET—CT放疗定位的Ⅰ～Ⅳ期食管癌患者55例入组，分析患者性别、年龄、原发灶部位、TNM分期、SUVmax、MTV、TLG、PTL、治疗手段与预后的关系。利用ROC寻找SUVmax、MTV、TLG及PTL最佳界值，将其分为高、低值组。Kaplan—Meier法生存分析并Logrank法检验。结果全组患者中位OS时间为19．1个月（95％凹为8．1～30．1），1、2、3、4年OS率分别为59％、45％、35％、26％。SUVmax、MTV、TLG、PT低值组（SUVmax〈11．4、MTV〈8．27cm^3、TLG〈35．21、PTL〈5．8cm）有更好的预后（P=0．002、0．021、0．044、0．000）。结论疗前SUVmax、MTV、TLG、PTL对判断食管癌患者预后有一定价值，放疗前可根据这些参数对患者进行危险分层，从而制订个体化治疗方案来改善预后。

Objective To investigate the prognostic value of metabolic parameters, maximum standard uptake value （ SUVmax ）, metabolic tumour volume （ MTV ）, total lesion glycolysis （ TLG）, and PET tumor length （ PTL）, in primary lesions of esophageal cancer on FDG PET-CT imaging in patients receiving radiotherapy or combined radiotherapy. Methods A total of 55 patients with stage I-IV esophageal cancer who received PET-CT radiotherapy localization in our hospital from 2006 to 2012 were enrolled. The association of sex, age, primary lesion, TNM stage, SUVmax, MTV, TLG, PTL, and therapeutic methods with the patient＇ s prognosis was analyzed. Tim receiver operating characteristic curve was used to determine the cut-off values of SUV MTV, TLG, and PTL, and the patients were divided into higher-value group and lower-value group. The Kaplan-Meier method was used to calculate survival rates, and the log-rank test was used for survival difference analysis. Results The median overall survival （OS） time for all patients was 19. 1 months （95% CI 8. 1-30. 1）, and the 1-, 2-, 3-, and 4-year OS rates were 59%, 45%, 35%, and 26%, respectively. The group with lower values of SUVma. （〈11.4） , MTV （ 〈 8.27 cm^3 ） , TLG （ 〈35.21 ） , and PTL （ 〈5.8 cm） had better prognosis than those with higher values （ P =0. 002, 0. 021, 0. 044, and 0. 000）. Conclusions SUVmax, MTV, TLG, and PTL before treatment have certain values in predicting the prognosis of patients with esophageal cancer. Risk stratification can be performed for these patients before radiotherapy according to these parameters, in order to develop individualized treatment regimens and improve prognosis.