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Radiomics-Based Preoperative Prediction of Lymph Node Status Following Neoadjuvant Therapy in Locally Advanced Rectal Cancer. | LitMetric

Radiomics-Based Preoperative Prediction of Lymph Node Status Following Neoadjuvant Therapy in Locally Advanced Rectal Cancer.

Front Oncol

Engineering Research Center of Molecular and Neuro Imaging of Ministry of Education, School of Life Science and Technology, Xidian University, Xi'an, China.

Published: May 2020

AI Article Synopsis

  • Lymph node status is crucial for deciding on organ preservation in patients with locally advanced rectal cancer (LARC) after neoadjuvant therapy, and this study explores preoperative predictions using MRI-based radiomics.
  • A total of 391 LARC patients underwent neoadjuvant therapy and total mesorectal excision (TME), with radiomics analysis performed on MRI to predict lymph node status.
  • The combined predictive model showed promising results with an area under the curve of 0.818 and high negative predictive values, particularly for certain tumor subgroups, highlighting the effectiveness of radiomics in this context.

Article Abstract

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. 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. 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. 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.

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Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7233118PMC
http://dx.doi.org/10.3389/fonc.2020.00604DOI Listing

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