Published January 2020 | Version v1
Journal article

MRI-based radiomics nomogram may predict the response to induction chemotherapy and survival in locally advanced nasopharyngeal carcinoma

  • 1. Department of Radiation Oncology, Xijing Hospital, Air Force Medical University, Xi'an (China)
  • 2. Life Sciences Research Center, School of Life Sciences and Technology, Xidian University, Xi'an (China)
  • 3. Department of Radiology, Xijing Hospital, Air Force Medical University, Xi'an (China)

Description

To establish and validate a radiomics nomogram for prediction of induction chemotherapy (IC) response and survival in nasopharyngeal carcinoma (NPC) patients. One hundred twenty-three NPC patients (100 in training and 23 in validation cohort) with multi-MR images were enrolled. A radiomics nomogram was established by integrating the clinical data and radiomics signature generated by support vector machine. The radiomics signature consisting of 19 selected features from the joint T1-weighted (T1-WI), T2-weighted (T2-WI), and contrast-enhanced T1-weighted MRI images (T1-C) showed good prognostic performance in terms of evaluating IC response in two cohorts. The radiomics nomogram established by integrating the radiomics signature with clinical data outperformed clinical nomogram alone (C-index in validation cohort, 0.863 vs 0.549; p < 0.01). Decision curve analysis demonstrated the clinical utility of the radiomics nomogram. Survival analysis showed that IC responders had significant better PFS (progression-free survival) than non-responders (3-year PFS 84.81% vs 39.75%, p < 0.001). Low-risk groups defined by radiomics signature had significant better PFS than high-risk groups (3-year PFS 76.24% vs 48.04%, p < 0.05). Multiparametric MRI-based radiomics could be helpful for personalized risk stratification and treatment in NPC patients receiving IC.

Availability note (English)

Available from: http://dx.doi.org/10.1007/s00330-019-06211-x

Additional details

Identifiers

Publishing Information

Journal Title
European Radiology
Journal Volume
30
Journal Issue
1
Journal Page Range
p. 537-546
ISSN
0938-7994
CODEN
EURAE3