Comparison of the Volumetric and Radiomics Findings of 18F-FDG PET/CT Images with Immunohistochemical Prognostic Factors in Local/locally Advanced Breast Cancer
Overview
Affiliations
Objective: The aim of this study was to determine the change in volumetric and radiomics parameters of fluorine-18 fluorodeoxyglucose (F-FDG) PET/computed tomography (CT) imaging in local/locally advanced cancer patients according to immunohistochemical findings.
Patients And Methods: A total of 72 patients who were diagnosed with local/locally advanced breast cancer and then examined by F-FDG PET/CT for staging were included in this study. Immunohistochemical prognostic factors [estrogen receptor (ER), progesterone receptor (PR), human epidermal growth factor receptor 2 (Her-2), p53 mutation, Ki-67 proliferation index] and histological grades were determined. Standardized uptake value (SUV)-based, volume-based, and radiomics findings were obtained from F-FDG PET/CT images.
Results: In cases of ER and PR negativity, Her-2 positivity, presence of the p53 mutation, and Ki-67 index of at least 20% patients, total volumetric parameters were significantly higher in paired comparisons. The results of the ER-negative group were significantly higher than those of ER-positive patients in GLRLM_GLNU, GLRLM_RLNU, GLZLM_GLNU, and GLZLM_ZLNU comparisons. In grade 3 patients, mean SUV, maximum SUV, and GLRLM_LRHGE values were higher than those of grade 2 patients. SUV and volumetric parameters were significantly higher in patients with Ki-67 index of at least 20% than those with less than 20%. Maximum SUV, breast tumor lesion glycolysis values, and entropy in nuclear polymorphism in the 3+ patient group were found to be higher compared with the 2+ patient group. Moreover, patients with mitosis 3+ had significantly higher breast metabolic tumor volume, breast tumor lesion glycolysis, and kurtosis values than the 1+ group.
Conclusion: ER negativity, triple negativity, high tumor grade, and high nuclear polymorphism were associated with tumor heterogeneity. With respect to ER negativity, PR negativity, high tumor grade, high mitosis number, high Ki-67 index, Her-2 positivity, and the presence of p53 mutation, an increased tumor load were observed. In addition to immunohistochemical parameters, the use of radiomics data is believed to contribute to breast cancer management.
Zheng X, Huang Y, Lin Y, Zhu T, Zou J, Wang S EJNMMI Res. 2023; 13(1):105.
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Travaglio Morales D, Huerga Cabrerizo C, Losantos Garcia I, Coronado Poggio M, Cordero Garcia J, Lopez Llobet E Diagnostics (Basel). 2023; 13(22).
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Yang H, Lin J, Liu H, Yao J, Lin Q, Wang J Insights Imaging. 2023; 14(1):130.
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Wang H, Zha H, Du Y, Li C, Zhang J, Ye X Front Oncol. 2023; 13:1170729.
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Urso L, Manco L, Castello A, Evangelista L, Guidi G, Castellani M Int J Mol Sci. 2022; 23(21).
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