AUTHOR=Zhou Xuezhi , Yi Yongju , Liu Zhenyu , Zhou Zhiyang , Lai Bingjia , Sun Kai , Li Longfei , Huang Liyu , Feng Yanqiu , Cao Wuteng , Tian Jie
TITLE=Radiomics-Based Preoperative Prediction of Lymph Node Status Following Neoadjuvant Therapy in Locally Advanced Rectal Cancer
JOURNAL=Frontiers in Oncology
VOLUME=10
YEAR=2020
URL=https://www.frontiersin.org/journals/oncology/articles/10.3389/fonc.2020.00604
DOI=10.3389/fonc.2020.00604
ISSN=2234-943X
ABSTRACT=Background and Purpose: Lymph node status is a key factor for the recommendation of organ preservation for patients with locally advanced rectal cancer (LARC) following neoadjuvant therapy but generally confirmed post-operation. This study aimed to preoperatively predict the lymph node status following neoadjuvant therapy using multiparametric magnetic resonance imaging (MRI)-based radiomic signature.
Materials and Methods: A total of 391 patients with LARC who underwent neoadjuvant therapy and TME were included, of which 261 and 130 patients were allocated to the primary cohort and the validation cohort, respectively. The tumor area, as determined by preoperative MRI, underwent radiomics analysis to build a radiomic signature related to lymph node status. Two radiologists reassessed the lymph node status on MRI. The radiomic signature and restaging results were included in a multivariate analysis to build a combined model for predicting the lymph node status. Stratified analyses were performed to test the predictive ability of the combined model in patients with post-therapeutic MRI T1-2 or T3-4 tumors, respectively.
Results: The combined model was built in the primary cohort, and predicted lymph node metastasis (LNM+) with an area under the curve of 0.818 and a negative predictive value (NPV) of 93.7% were considered in the validation cohort. Stratified analyses indicated that the combined model could predict LNM+ with a NPV of 100 and 87.8% in the post-therapeutic MRI T1-2 and T3-4 subgroups, respectively.
Conclusion: This study reveals the potential of radiomics as a predictor of lymph node status for patients with LARC following neoadjuvant therapy, especially for those with post-therapeutic MRI T1-2 tumors.