Comparison of Different Diagnostic Criteria of 68Ga-Pentixafor PET/CT for the Classification of Primary Aldosteronism
X.-G. Zhang, Ying Song, Ying Jing, Jinbo Hu, Hang Shen, Aipin Zhang, Wenwen He, Zhengping Feng, Yi Yang, Hua Pang, Qifu Li, Shumin Yang, Chongqing Primary Aldosteronism Study (CONPASS) Group, Mei Mei, Suxin Luo, Kangla Liao, Yao Zhang, Yunfeng He, Yihong He, Ming Xiao, Bin Peng
Abstract
CONTEXT: 68Ga-Pentixafor positron emission tomography/computed tomography (PET/CT) is an emerging method for the classification diagnosis primary aldosteronism (PA). However, the diagnosis criteria are still controversial. OBJECTIVE: To compare the accuracy of different criteria of 68Ga-Pentixafor PET/CT in the classification diagnosis of PA. METHODS: This was a retrospective study at a tertiary hospital in China. Patients with PA who had undergone PET/CT and had classification diagnosis of unilateral PA (UPA) or bilateral PA (BPA) based on surgery or adrenal venous sampling were included. Area under the receiver operating characteristic curve (AUC), specificity, and sensitivity were used to analyze the accuracy of the lateralization index (LI) based on adrenal maximum standardized uptake value (SUVmax), dominant side SUVmax adjusted by liver, dominant side of SUVmax, and visual analysis. RESULTS: A total of 208 patients with PA (including 128 UPA and 80 BPA) were analyzed. The AUCs for diagnosing UPA using LI and visual analysis were both 0.82, higher than that of the dominant side of SUVmax (0.72) and dominant side SUVmax adjusted by liver (0.71). Visual analysis showed a sensitivity of 0.73 and a specificity of 0.88. The LI cutoff of 1.50 resulted in the highest Youden index of 0.59, with a sensitivity of 0.68 and a specificity of 0.91. When the LI cutoff was increased to 1.65, the sensitivity reduced to 0.61, while the specificity increased to 0.96. CONCLUSION: Both LI and visual analysis could be used for interpretation the results of 68Ga-Pentixafor PET/CT; nevertheless, visual analysis is more sensitive, and LI is more advantageous in specificity.