The relationship between 18F-FDG PET/CT parameters and histopathological-immunohistochemical properties in breast cancer
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https://doi.org/10.26900/hsq.2122Keywords:
Breast cancer, 18F-FDG PET/CT, standardized uptake value (SUVmax), metabolic tumor volume (MTV), total lesion glycolysis (TLG)Abstract
In this study, it is aimed to determine the correlation between histopathologic-immunohistochemical factors, tumor subtypes and fluorine-18-fluorodeoxyglucose positron emission tomography/computed tomography (18F-FDG PET/CT) parameters such standardized uptake value (SUVmax), metabolic tumor volume (MTV), total lesion glycolysis (TLG) in breast cancer (BC). Initial PET/CT examination of 110 histopathologically proven BC patients (age ranging 27-92, mean age 56.18 ± 14.59) were included in this retrospective study. The relationship between histopathological-immunohistochemical factors, tumor subtypes and PET/CT parameters were analyzed by regression analysis. The mean SUV max value of 110 breast tumors was 7.73 ± 5.62 (range 1.4 - 34.15). Histological subtypes were; invasive ductal carcinoma (n:94, 85.5%), invasive lobular carcinoma (n=6, 5.5%) and other types (n=10, 9.1%). The distribution of BC subtypes was as follows; Luminal A (Lum A) (n=38; 34.5%), Luminal B (Lum B) (n=56; 50.9%), HER2-positive (n=3; 2.7%) and Triple Negative (TN) (n=13; 11.8%). Univariate regression analysis revealed significantly higher SUV max values in ductal carcinomas than lobular carcinomas (p=0.03). SUVmax values of the Lum B, HER2 positive and TN groups were higher than Lum A group (p=0.03, p<0.001, p<0.001 respectively). Univariate regression analyses also showed that the MTV and TLG values of TN group were significantly higher than Lum A group (p=0.011, p=0.007, respectively). In multivariate regression analyses, no significant difference was observed in above mentioned groups. MTV, TLG and SUVmax values significantly correlated with histopathological-immunohistochemical factors and tumor subtypes in BC. So that, these parameters can be used to predict the tumors’ behavior.
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