Radiomics Analysis of Multiparametric MRI Evaluates the Pathological Features of Cervical Squamous Cell Carcinoma

Robust parameters to evaluate pathological aggressiveness are needed to provide individualized therapy for cervical cancer patients.

To investigate the radiomics analysis of multiparametric MRI to evaluate tumor grade, lymphovascular space invasion (LVSI), and lymph node (LN) metastasis of cervical squamous cell carcinoma (CSCC).

Retrospective.

Fifty-six patients with histopathologically confirmed CSCC.

3T, axial T₂ and T₂ with fat suppression (FS), diffusion-weighted imaging (DWI) (multi-b values), axial dynamic contrast enhanced (DCE) MRI (8 sec temporal resolution).

Regions of interest were drawn around the tumor on each axial slice and fused to generate the whole tumor volume. Sixty-six radiomics features were derived from each image sequence, including axial T₂ and T₂ FS, ADC maps, and K_trans , V_e , and V_p maps from DCE MRI.

A univariate analysis was performed to assess each parameter's association with tumor grade and the presence of lymphovascular space invasion (LVSI) and lymph node (LN) metastasis. A principal component analysis was employed for dimension reduction and to generate new discriminative valuables. Using logistic regression, a discriminative model of each parameter was built and a receiver operating characteristic curve (ROC) was generated.

The area under the ROC curve (AUC) of anatomical, diffusion, and permeability parameters in discriminating the presence of LVSI ranged from 0.659 to 0.814, with V_e showing the best discriminative value. The AUC in discriminating the presence of LN metastasis and distinguishing tumor grade ranged from 0.747 to 0.850, 0.668 to 0.757, with ADC and V_e showing the best discriminative value, respectively.

Functional maps exhibit better discriminative values than anatomical images for discriminating the pathological features of CSCC, with ADC maps showing the best discrimination performance for LN metastasis and V_e maps showing the best discriminative value for LVSI and tumor grade.

3 Technical Efficacy: Stage 2 J. Magn. Reson. Imaging 2019;49:1141-1148.