The value of multimodal functional magnetic resonance imaging in differentiating p53abn from p53wt endometrial carcinoma

Abstract

Background Endometrial carcinoma (EC) is the sixth most common cancer in women. P53 gene expression in patients with endometrial cancer can predict the efficacy and prognosis of patients with neoadjuvant therapy. Purpose To explore the value of multimodal magnetic resonance imaging (MRI) in differentiating p53 abnormal (p53abn) from p53 wild-type (p53wt) EC. Material and Methods Data from 47 EC patients, including 14 p53abn cases and 33 p53wt cases, were retrospectively analyzed. The preoperative MRI sequences included amide proton transfer weighted (APTw) imaging, T2 mapping, mDIXON-Quant imaging and diffusion-weighted imaging (DWI). After post-processing, APT, T2, transverse relaxation rate (R2*), fat fraction (FF) and apparent diffusion coefficient (ADC) maps were obtained. The APT, T2, R2*, FF and ADC values for lesions of the two groups of cases were measured by two observers who were blind to the pathological data. Results The APT value and R2* value in the p53abn group were higher than those in the p53wt group, while the ADC value was lower (all P < 0.05). There was no statistically significant difference in T2 value and FF value between the two groups (all P > 0.05). The area under curve of APT, R2*, ADC and combined APT + R2*+ADC values for identification of p53abn and p53wt EC were 0.739, 0.689, 0.718 and 0.820, respectively (all P > 0.05). Conclusion APTw, mDIXON-Quant and DWI techniques can be usedfor quantitative identification of p53abn and p53wt EC. The multimodal MRI provides a new way for preoperative quantitative evaluation of EC molecular typing, which has certain clinical application value.

Predictive Value of Magnetic Resonance Imaging in Risk Stratification and Molecular Classification of Endometrial Cancer

“…For patients with mutant TP53 whose tumors exhibit elevated VEGF, antiangiogenic therapy with bevacizumab may hold particular promise [ 45 ]. However, the use of imaging biomarkers for predicting TP53 mutations is still in its infancy, and further development and validation are needed [ 46 , 47 ].…”