Recently, the group of Image Guided Surgery and Therapy (IGST) led by Prof. GAO Xin at Suzhou Institute of Biomedical Engineering and Technology (SIBET) proposed a preoperative radiomic model for noninvasively evaluation of tumor biological characteristics.

Traditionally, molecular markers for clinical expression of tumors need to be invasively sampled by surgery or needle biopsy, which can only be collected in a single position. This cannot fully describe the temporal and spatial heterogeneity of tumor tissues, and the patient is in pain while taking the sample.

In this study, magnetic resonance imaging data and tumor biological characteristics of 345 patients with rectal cancer were acquired (including immunohistochemical parameters such as Ki-67 and HER-2, lymph node metastasis, KRAS-2 gene mutation, and tumor differentiation).

Data from 197 patients were used to develop the biological characteristics evaluation models. Radiomic features were extracted from MP-MRI and then refined for reproducibility and redundancy.

Two feature selection methods and three classification methods were used. A non-invasive evaluation model for rectal cancer tumors was constructed.

The results show that the model has a good evaluation effect on tumor biological characteristics (AUC=0.651-0.720, Fig.1). The model can assess the tumor biological characteristics based on the MRI images (Fig.2).

Therefore, our tumor evaluation model based on radionomics, which can non-invasive, real-time, repeatedly obtain tumor information, has an important application prospect.

These works entitled "Preoperative Radiomic Signature based on Multiparametric Magnetic Resonance Imaging for Noninvasively Evaluation of Biological Characteristics in Rectal Cancer" were published in European Radiology. 

Fig 1. The receiver operating characteristic curves of radiomic signatures: (a) HER-2, (b) Ki-67, (c) tumor differentiation, (d) KRAS-2, and (e) lymph node metastasis. For lymph node metastasis, the ROC curves of integrated evaluation model were also plotted. (Image by XIA Wei)

Fig 2. Preoperative images obtained by multiparametric magnetic resonance imaging and radiomic signature scores of patients with rectal cancer with different biological characteristics. (Image by XIA Wei)