Positron emission tomography/magnetic resonance imaging for the diagnosis and differentiation of pancreatic tumors.

NUCLEAR MEDICINE COMMUNICATIONS(2020)

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摘要
Objective This retrospective study aimed to evaluate the diagnostic efficiency of simultaneous positron emission tomography/magnetic resonance imaging (PET/MR) in differentiating the benign and malignant of pancreatic tumors as well as the differentiation of pancreatic cancer. Methods A total of 62 patients with suspected pancreatic tumors, diagnosed by PET/MR examinations, were collected in this study. These patients were divided into benign group and malignant group. The characteristics of the morphological MR, apparent diffusion coefficient (ADC), the mean of standardized uptake value (SUVmean), maximum values of standardized uptake value (SUVmax), in lesions were measured, and the novel parameters SUVpeak/ADC and SUVmax/ADC were constructed. The diagnostic efficiency for differentiating the benign and malignant lesions was analyzed by receiver operating characteristic (ROC) curve, and the diagnosis efficiency for the differentiation of pancreatic cancer was analyzed by Spearman correlation analysis. Results In differentiating the benign and malignant of pancreatic tumors, the diagnostic efficiency increased in the order of SUVpeak (AUROC: 0.760), SUVmax (AUROC: 0.774), T1T2 (AUROC: 0.789), ADC (AUROC: 0.817), SUVpeak/ADC (AUROC: 0.836), SUVmax/ADC (AUROC: 0.847). There was no significant correlation for SUVmax, SUVpeak, ADC, SUVpeak/ADC, and SUVmax/ADC with the differentiation of pancreatic cancer (P > 0.05). Besides, T1T2 was not significantly correlated to the differentiation of pancreatic cancer (P = 0.026, r = -0.406). Conclusion The integration of PET/MR imaging could be used to efficiently diagnose whether the pancreatic tumor was benign or malignant. The SUVmax/ADC was the most efficient metric, while it could not help in the differentiation of pancreatic cancer.
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关键词
apparent diffusion coefficient,pancreatic cancer,PET,MR,standardized uptake value
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