TY  - JOUR
TI  - Can Radiomics Analyses in 18
F-FDG PET/CT Images of Primary
Breast Carcinoma Predict Hormone Receptor Status?
AB  - Objectives: This study aimed to investigate the role of preoperative 18
fluorine-fluorodeoxyglucose (18
F-FDG) positron emission tomography/
computed tomography (PET/CT) radiomics features and metabolic parameters of primary breast tumors in predicting hormone receptor (HR)
positivity.
Methods: A total of 153 patients with breast carcinoma who underwent preoperative18
F-FDG PET/CT were included. All PET/CT images were
retrospectively reevaluated. Radiomics features of primary breast lesions reflecting tumor heterogeneity as well as standardized uptake value (SUV)
metrics (SUVmin
, SUVmean
, SUVmax
, and SUVpeak
) and volumetric parameters such as metabolic tumor volume and total lesion glycolysis (TLG) were
extracted by commercial texture analysis software package (LIFEx; https://www.lifexsoft.org/ index.php). WEKA and SPSS were used for statistical
analysis. Binary logistic regression analysis was used to determine texture features predicting HR positivity. Accuracy, F-measure, precision, recall,
and precision-recall curve area were used as data-mining performance criteria of texture features to predict HR positivity.
Results: None of the radiomics parameters were significant in predicting HR status. Only SUV metrics and TLG were statistically important. Mean
± standard deviations for SUVmean
, SUVmax
, and SUVpeak for the HR-negative group were significantly higher than those in the HR-positive group
(6.73±4.36 vs. 5.20±3.32, p=0.027; 11.55±7.42 vs. 8.63±5.23, p=0.006; and 8.37±6.81 vs. 5.72±4.86; p=0.012). Cut-off values of SUVmean
,
SUVmax
, and SUVpeak for the prediction of HR positivity were 4.93, 8.35, and 6.02, respectively. Among data-mining methods, logistic regression
showed the best performance with accuracy of 0.762.
Conclusion: In addition to the relatively limited number of patients in this study, radiomics parameters cannot predict the HR status of primary
breast cancer. SUV levels of the HR-negative group were significantly higher than those of the HR-positive group. To clarify the role of metabolic
and radiomics parameters in predicting HR status in breast cancer, further studies involving a larger study population are needed.
AU  - BAKIRARAR, Batuhan
AU  - SOYDAL, Çiğdem
AU  - Dizbay Sak, Serpil
AU  - Kirmizi, Ayca
AU  - GÜNDÜZ, Pınar
AU  - ÖZKAN, Elgin
AU  - ARAZ, Mine
DO  - 10.4274/mirt.galenos.2022.59140
PY  - 2022
JO  - Molecular Imaging and Radionuclide Therapy
VL  - 31
IS  - 1
SN  - 2146-1414
SP  - 49
EP  - 56
DB  - TRDizin
UR  - http://search/yayin/detay/516139
ER  -