Conclusions
The combination of functional 18F-FDG-PET/MRI parameters and molecular determination of YY1 could represent a novel integrated approach to predict synchronous metastatic disease with more accuracy than 18F-FDG-PET/MRI alone.
Methods
The study enrolled suspected n = 217 BC patients that underwent 18F-FDG-PET/MRI scans. The analysis retrospectively included n = 55 subjects. n = 40 were BC patients and n = 15 imaging-negative female individuals were healthy subjects (HS). Standard radiomics parameters were extracted from PET/MRI image. RNA was obtained from peripheral blood mononuclear cells and YY1 expression level was evaluated by real time reverse transcription polymerase chain reactions (qRT-PCR). An enzyme-linked immuosorbent assay (ELISA) was used to determine the amount of YY1 serum protein. Statistical comparison between subgroups was evaluated by Mann-Whitney U and Spearman's tests.
Purpose
Detection of breast cancer (BC) metastasis at the early stage is important for the assessment of BC progression status. Image analysis represents a valuable tool for the management of oncological patients. Our preliminary study combined imaging parameters from hybrid 18F-FDG-PET/MRI and the expression level of the transcriptional factor Yin Yang 1 (YY1) for the detection of early metastases.
Results
Radiomics showed a significant positive correlation between Greg-level co-occurrence matrix (GLCM) and standardized uptake value maximum (SUVmax) (r = 0.8 and r = 0.8 respectively) in BC patients. YY1 level was significant overexpressed in estrogen receptor (ER)-positive/progesteron receptor-positive/human epidermal growth factor receptor2-negative (ER+/PR+/HER2-) subtype of BC patients with synchronous metastasis (SM) at primary diagnosis compared to metachronous metastasis (MM) and HS (p < 0.001) and correlating significantly with 18F-FDG-uptake parameter (SUVmax) (r = 0.48). Conclusions: The combination of functional 18F-FDG-PET/MRI parameters and molecular determination of YY1 could represent a novel integrated approach to predict synchronous metastatic disease with more accuracy than 18F-FDG-PET/MRI alone.