Introduction: The aim of our study to investigate relationship between 18F -fluorodeoxyglucose
PET/CT (18F-FDG PET/CT) metabolic parameters and immunohistochemical factors in breast
carcinomas.
Material and method: Patients with breast carcinomas who underwent 18F-FDG PET/CT imaging at
our department between May 2018 and November 2019 were included in this study. A total of 146
female patients were included (aged 49.1 ± 13.4years; range, 26-87 years). PET scanning was
performed in 3D mode from the skull ceiling to the middle of the thigh. Metabolic parameters such as
TLG (Total lesion glycolysis), MTV (Metabolic tumor volume) , SUVmean and SUVmax values were
calculated. We obtained the histopathological findings, including the size of invasive cancer,
histological type, histological grade, ER and PR status, epidermal growth factor receptor (HER2) and
Ki-67 of the primary tumor by reviewing the pathology reports.
Result: SUV max and SUVmean of Oestrogen receptor negative group were statistically higher than
Oestrogen receptor positive group (p=0.009). SUVmean of progesterone receptor negative group
were statistically higher than progesterone receptor positive group (p=0.05). Ki-67 of the Oestrogen
receptor negative group and progesterone receptor negative group were statistically higher than
Oestrogen receptor and progesterone receptor positive group (p=0.001, 0,001 respectively). Both
SUVmax and SUVmean of Ki-67 positive group were statistically higher than Ki-67negative group
(p=0.0001).
Conclusions: 1-SUV max, SUVmean and Ki-67 of Oestrogen receptor negative group were
statistically higher than Oestrogen receptor positive group.
2-SUVmean and Ki-67 of progesterone receptor negative group were statistically higher than
progesteron receptor positive group.
3- HER2 positive and/or triple negative breast cancers were not associated with 18F-FDG PET/CT
metabolic parameters
Primary Language | English |
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Subjects | Clinical Sciences |
Journal Section | Research |
Authors | |
Publication Date | December 30, 2019 |
Published in Issue | Year 2019 Volume: 11 Issue: 2 |
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