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The Quarterly Journal of Nuclear Medicine and Molecular Imaging 2021 March;65(1):72-8

DOI: 10.23736/S1824-4785.19.03137-6

Copyright © 2019 EDIZIONI MINERVA MEDICA

language: English

Differential diagnostic ability of 18F-FDG PET/CT radiomics features between renal cell carcinoma and renal lymphoma

Sha ZHU 1, 2, Hui XU 3, Chuyu SHEN 2, Yingjie WANG 2, Wenting XU 2, Shihao DUAN 2, Hanxiao CHEN 2, Xuejin OU 2, Linyan CHEN 2, Xuelei MA 4

1 Department of Urology, West China Hospital, Sichuan University, Chengdu, China; 2 West China School of Medicine, West China Hospital, Sichuan University, Chengdu, China; 3 Department of Radiology, West China Hospital, Sichuan University, Chengdu, China; 4 National Collaborative Innovation Center for Biotherapy, West China Hospital, Sichuan University, Chengdu, China



BACKGROUND: The aim of this study is to determine the differential diagnostic value of texture parameters of PET/CT on renal cell carcinoma and renal lymphoma.
METHODS: Twenty renal lymphoma and 18 renal cell carcinoma (RCC) patients were analyzed in this study. The pathological information and basic characteristics were extracted from the electronic medical record system of our hospital. We used LIFEx package to extract data from the radiomics images. Receiver operating characteristic analysis and binary logistic regression analysis was applied in determining the diagnostic accuracy of texture parameters as well as the synthetic parameter, of which the sensitivity and specificity was improved.
RESULTS: There were 14 (two in Histogram, two in Grey Level Co-occurrence Matrix, five in Grey-Level Run Length Matrix, five in Grey-Level Zone Length Matrix) out of the texture parameters showing an area under the curve (AUC) >0.7 and P<0.05. Synthesized parameters of each section showed even higher differentiation ability, with AUC varying from 0.725 to 1.000.
CONCLUSIONS: Texture analysis of 18F-FDG PET/CT could effectively differentiate between RCCs and renal lymphomas.


KEY WORDS: Renal cell carcinoma; Lymphoma; Differential diagnosis

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