Evaluation of parametrial infiltration in cervical cancer with voxel-based segmentation of integrated F-FDG PET/MRI images: A preliminary study.

Purpose: To identify parametrial infiltration (PMI) in cervical cancer with voxel-based segmentation of integrated PET/MRI images.

Method: This retrospective study enrolled 79 cervical cancer patients confirmed by pathology (FIGO stage IB to IIB) who underwent F-FDG PET/MRI prior to surgery. Region of interest (ROI) at the largest tumor level was delineated on the T2W-MR image, and the ROI was applied to PET image of the corresponding layer. Then, these images were postprocessed with segmentation and gray level calculations in the parauterine area.

Results: In total, 37 patients (46.8%) had postoperative pathology-confirmed PMI, and 42 patients (53.2%) showed no PMI. There was a moderate correlation between pathological results and the gray level values of each region (rs > 0.5, P < 0.001). According to FIGO stage, as the cervical lesions became more malignant, the gray level values gradually increased. The diagnostic results of MRI and PET/MRI were in good agreement (kappa = 0.693, P < 0.001); the accuracy (78.5%), sensitivity (64.9%) and NPV (74.5%) of PET/MRI were slightly higher than those of MRI (74.7%,59.5%,71.2%, respectively), with no statistically significant difference (P = 1.000). The diagnostic results of MRI and PET/MRI+gray level values were generally consistent (kappa = 0.475, P < 0.001); the accuracy (87.3%), sensitivity(83.8%) and NPV(86.4%) of PET/MRI+gray level values were higher than those of MRI, with statistically significant differences (all P values < 0.05).

Conclusions: It is feasible to evaluate PMI based on PET/T2W-MRI voxel segmentation and to obtain quantitative and visual indicators. PET/MRI and gray level values considered together can also improve the accuracy, sensitivity and NPV of PMI diagnosis.