Assessment of Radiomics Feature Repeatability and Reproducibility and Their Generalizability Across Image Modalities by Perturbation in Nasopharyngeal Carcinoma Patients

This study aims to evaluate the repeatability and reproducibility of radiomics features (RFs) under image perturbations and examine their generalizability across computed tomography (CT) and magnetic resonance (MR) images among nasopharyngeal carcinoma (NPC) patients. A total of 397 NPC patients with contrast-enhanced computed tomography (CECT), CET1-weight, and T2-weight MR images were analyzed. Image perturbation and contour randomization were implemented to the images and masks to mimic the scanning position and tumor segmentation stochasticity. A total of 1288 RFs from original, Laplacian-of-Gaussian-filtered (LoG) and wavelet-filtered images were extracted. The stability of RF was assessed by adopting median intraclass correlation coefficient (mICC) under patient subsampling. The mean absolute difference (MAD) of the mICC and the accuracy of the binarized repeatability between image datasets were adopted to evaluate its generalizability across image modalities. The MRI-based RFs showed higher stability (77.6% in CET1-w and 80.2% in T2-w with mICC ≥ 0.9), whereas the CT-based RFs were less stable (41.7% with mICC ≥ 0.9). Overall, 497 RFs (38.6%) had mICC ≥ 0.9 in all three modalities. Shape features consistently kept the highest stability in all modalities. MRI-based RFs displayed higher repeatability and reproducibility against scanning position and tumor segmentation variations than CT-based RFs. We urge caution when handling CT-based RFs and advice adopting MRI-based RFs with higher stability during feature pre-selection for stable model construction.

Duke Scholars

Author Jing Cai Radiation Oncology