Comparison of 68Ga-DOTANOC and 18F-FDG PET-CT Scans in the Evaluation of Primary Tumors and Lymph Node Metastasis in Patients With Rectal Neuroendocrine Tumors

Author:

Zhou Zhihao,Wang Zhixiong,Zhang Bing,Wu Yanzhang,Li Guanghua,Wang Zhao

Abstract

BackgroundLymph node metastasis of rectal neuroendocrine tumors (RNETs) predicts poor prognosis. However, the assessment of lymph node metastasis remains a challenge. It has been reported that 68Ga-DOTANOC and 18F-FDG PET-CT scans could be employed in the work-up of rectal neuroendocrine tumors (RNETs). This study aimed to assess both tracers’ ability to identify primary tumors and lymph node (LN) metastasis in RNETs.MethodsA total of 537 patients with RNETs were enrolled from January 2014 to January 2021. Both 68Ga-DOTANOC and 18F-FDG PET-CT scans were used to evaluate primary tumors and LN group metastasis. PET images were evaluated through visual and semiquantitative assessment. Receiver Operating Characteristics (ROC) curve analysis was used to investigate the performance of SUVmax of 68Ga-DOTANOC and 18F-FDG PET in predicting LN group metastasis.ResultsFifty-two patients with preoperative 68Ga-DOTANOC with 18F-FDG PET-CT scans underwent endoscopic biopsy or dissection of the primary tumor, while 11 patients underwent rectal surgery together with regional LN dissection. For primary tumors, 68Ga-DOTANOC had a sensitivity of 89.58% and a positive predictive value (PPV) of 95.56% through visual assessment, while 18F-FDG PET-CT showed 77.08% sensitivity and 97.37% PPV. For the prediction of LN group metastasis, 68Ga-DOTANOC PET-CT had 77.78% sensitivity and 91.67% specificity, while 18F-FDG PET-CT had 38.89% sensitivity and 100% specificity according to visual assessment. The area under the ROC curves (AUC) for 68Ga-DOTANOC PET/CT was 0.852 (95%CI:0.723-0.981) with an optimal SUVmax cut-off value of 2.25, while the AUC for 18F-FDG PET were 0.664 (95%CI:0.415-0.799) with an optimal SUVmax cut-off value of 1.05.ConclusionsThis study showed that 68Ga-DOTANOC PET-CT was a promising tool for detecting LN metastasis in RNETs with high sensitivity and specificity in visual assessment and semiquantitative assessment, which was better than 18F-FDG PET-CT.

Funder

Natural Science Foundation of Guangdong Province

Publisher

Frontiers Media SA

Subject

Endocrinology, Diabetes and Metabolism

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