Dynamic contrast-enhanced magnetic resonance imaging-based radiomics for the prediction of progression-free survival in advanced nasopharyngeal carcinoma

Wen-Zhu Li; Gang Wu; Tian-Sheng Li; Gan-Mian Dai; Yu-Ting Liao; Qian-Yu Yang; Feng Chen; Wei-Yuan Huang

doi:10.3389/fonc.2022.955866

Dynamic contrast-enhanced magnetic resonance imaging-based radiomics for the prediction of progression-free survival in advanced nasopharyngeal carcinoma

Front Oncol. 2022 Oct 13:12:955866. doi: 10.3389/fonc.2022.955866. eCollection 2022.

Authors

Wen-Zhu Li¹, Gang Wu², Tian-Sheng Li¹, Gan-Mian Dai¹, Yu-Ting Liao³, Qian-Yu Yang¹, Feng Chen¹, Wei-Yuan Huang¹

Affiliations

¹ Department of Radiology, Hainan General Hospital, Hainan Affiliated Hospital of Hainan Medical University, Haikou, China.
² Department of Radiotherapy, Hainan General Hospital, Hainan Affiliated Hospital of Hainan Medical University, Haikou, China.
³ Department of Pharmaceutical Diagnostics, GE Healthcare, Guangzhou, China.

Abstract

To establish a multidimensional nomogram model for predicting progression-free survival (PFS) and risk stratification in patients with advanced nasopharyngeal carcinoma (NPC). This retrospective cross-sectional study included 156 patients with advanced NPC who underwent dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI). Radiomic features were extracted from the efflux rate constant (K^trans ) and extracellular extravascular volume (V_e ) mapping derived from DCE-MRI. Least absolute shrinkage and selection operator (LASSO) Cox regression analysis was applied for feature selection. The Radscore was constructed using the selected features with their respective weights in the LASSO Cox regression analysis. A nomogram model combining the Radscore and clinical factors was built using multivariate Cox regression analysis. The C-index was used to assess the discrimination power of the Radscore and nomogram. The Kaplan-Meier method was used for survival analysis. Of the 360 radiomic features, 28 were selected (7, 6, and 15 features extracted from K^trans , Ve, and K^trans +V_e images, respectively). The combined Radscore _k ^trans _+Ve (C-index, 0.703, 95% confidence interval [CI]: 0.571-0.836) showed higher efficacy in predicting the prognosis of advanced NPC than Radscore _k ^trans (C-index, 0.693; 95% CI, 0.560-0.826) and Radscore _Ve (C-index, 0.614; 95% CI, 0.481-0.746) did. Multivariable Cox regression analysis revealed clinical stage, T stage, and treatment with nimotuzumab as risk factors for PFS. The nomogram established by Radscore _k ^trans _+Ve and risk factors (C-index, 0.732; 95% CI: 0.599-0.864) was better than Radscore _k ^trans _+Ve in predicting PFS in patients with advanced NPC. A lower Radscore _k ^trans _+Ve (HR 3.5584, 95% CI 2.1341-5.933), lower clinical stage (hazard ratio [HR] 1.5982, 95% CI 0.5262-4.854), lower T stage (HR 1.4365, 95% CI 0.6745-3.060), and nimotuzumab (NTZ) treatment (HR 0.7879, 95% CI 0.4899-1.267) were associated with longer PFS. Kaplan-Meier analysis showed a lower PFS in the high-risk group than in the low-risk group (p<0.0001). The nomogram based on combined pretreatment DCE-MRI radiomics features, NTZ, and clinicopathological risk factors may be considered as a noninvasive imaging marker for predicting individual PFS in patients with advanced NPC.

Keywords: dynamic contrast-enhanced magnetic resonance imaging; nasopharyngeal carcinoma; nimotuzumab; progression-free survival; radiomics.