| 1 | Maximum standardized uptake value on PET/CT in preoperative assessment of lymph node metastasis from thoracic esophageal squamous cell carcinoma显示文摘The presence of lymph node metastasis is an important prognostic factor for patients with esophageal cancer.Accurate assessment of lymph nodes in thoracic esophageal carcinoma is essential for selecting appropriate treatment and forecasting disease progression.Positron emission tomography combined with computed tomography(PET/CT)is becoming an important tool in the workup of esophageal carcinoma.Here,we evaluated the effectiveness of the maximum standardized uptake value(SUVmax)in assessing lymph node metastasis in esophageal squamous cell carcinoma(ESCC)prior to surgery.Fifty-nine surgical patients with pathologically confirmed thoracic ESCC were retrospectively studied.These patients underwent radical esophagectomy with pathologic evaluation of lymph nodes.They all had18F-FDG PET/CT scans in their preoperative staging procedures.None had a prior history of cancer.The pathologic status and PET/CT SUVmax of lymph nodes were collected to calculate the receiver operating characteristic(ROC)curve and to determine the best cutoff value of the PET/CT SUVmax to distinguish benign from malignant lymph nodes.Lymph node data from 27 others were used for the validation.A total of 323 lymph nodes including 39 metastatic lymph nodes were evaluated in the training cohort,and 117lymph nodes including 32 metastatic lymph nodes were evaluated in the validation cohort.The cutoff point of the SUVmax for lymph nodes was 4.1,as calculated by ROC curve(sensitivity,80%;specificity,92%;accuracy,90%).When this cutoff value was applied to the validation cohort,a sensitivity,a specificity,and an accuracy of 81%,88%,and 86%,respectively,were obtained.These results suggest that the SUVmax of lymph nodes predicts malignancy.Indeed,when an SUVmax of 4.1 was used instead of 2.5,FDG-PET/CT was more accurate in assessing nodal metastasis. | Amos JM Ela Bella Ya-Rui Zhang Wei Fan Kong-Jia Luo Tie-Hua Rong Peng Lin Hong Yang Jian-Hua Fu | 2014 | Chinese Journal of Cancer2014，33，4： | 3 |
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