Longitudinal acquisition repeatability of MRI radiomics features: An ACR MRI phantom study on two MRI scanners using a 3D T1W TSE sequence. Issue 3 (2nd February 2021) - Wong, Oi Lei
Abstract : Purpose: The purpose of this study was to quantitatively assess the longitudinal acquisition repeatability of MRI radiomics features in a three‐dimensional (3D) T1‐weighted (T1W) TSE sequence via a well‐controlled prospective phantom study. Methods: Thirty consecutive daily datasets of an ACR‐MRI phantom were acquired on two 1.5T MRI simulators using a 3D T1W TSE sequence. Images were blindly segmented by two observers. Post‐acquisition processing was minimized but an intensity discretization (fixed bin size of 25). One hundred and one radiomics features (shape n = 12; first order n = 16; texture n = 73) were extracted. Longitudinal repeatability of each feature was evaluated by Pearson correlation and coefficient of variance (CV68% ). Interobserver feature value agreement was also quantified using intraclass correlation coefficient (ICC) and Bland–Altman analysis. A most repeatable radiomics feature set on both scanners was determined by feature coefficient of variance (CV68% <5%), ICC (>0.75), and the ratio of the interobserver difference to the interobserver mean δ<5%. Results: No trend of radiomics feature value changed with time. Longitudinal feature repeatability CV68% ranged 0.01–38.60% (mean/median: 12.5%/9.9%), and 0.01–40.47%, (8.49%/7.34%) on the scanners A and B. Shape features exhibited significantly better repeatability than first‐order and texture features (all P < 0.01). Significant longitudinal repeatability difference was observed in texture features ( P < 0.001) between the two scanners, but not in shape and first‐order features ( P > 0.30). First‐order and texture features had smaller interobserver‐dependent variation than acquisition‐dependent variation. They also showed good interobserver agreement on both scanners (A:ICC = 0.80 ± 0.23; B:ICC = 0.80 ± 0.22), independent of acquisition repeatability. The repeatable radiomics features in common on both scanners, including 12 shape features, 0 first‐order features, and 3 texture features, were determined as the most repeatable MRI radiomics feature set. Conclusions: Radiomics features exhibited heterogeneous longitudinal repeatability, while the shape features were the most repeatable, in this phantom study with a 3D T1W TSE acquisition. The most repeatable radiomics feature set derived in this study should be helpful for the selection of reliable radiomics features in the future clinical use.