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Assessment of Repeatability, Reproducibility, and Performances of T2 Mapping‐Based Radiomics Features: A Comparative Study
Author(s) -
Crombé Amandine,
Buy Xavier,
Han Fei,
Toupin Solenn,
Kind Michèle
Publication year - 2021
Publication title -
journal of magnetic resonance imaging
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.563
H-Index - 160
eISSN - 1522-2586
pISSN - 1053-1807
DOI - 10.1002/jmri.27558
Subject(s) - repeatability , reproducibility , magnetic resonance imaging , nuclear medicine , radiomics , coefficient of variation , medicine , pattern recognition (psychology) , radiology , computer science , artificial intelligence , mathematics , statistics
Background Magnetic resonance imaging (MRI)‐based radiomics features (RFs) quantify tumors radiological phenotypes but are sensitive to postprocessing parameters, including the intensity harmonization technique (IHT), while mappings enable objective quantitative assessment. Purpose To investigate whether T2 mapping could improve repeatability, reproducibility, and performances of radiomics compared to conventional T2‐weighted imaging (T2WI). Study Type Prospective. Subjects Twenty‐six healthy adults. Field Strength/Sequence Respiratory‐trigged radial turbo spin echo (TSE) multiecho T2 mapping (prototype) and conventional TSE T2WI of the abdomen were acquired twice at 1.5 T. Assessment T2 maps were reconstructed using a two‐parameter exponential fitting model. Volumes‐of‐interest (VOIs) were manually drawn in six tissues: liver, kidney, pancreas, muscle, bone, and spleen. After co‐registration, conventional T2WIs were processed with two IHTs (standardization [std] and histogram‐matching [HM]) resulting in four paired input image types: initial T2WI, T2WI std , T2WI HM , and T2‐map. VOIs were propagated to extract 45 RFs from MRI‐1 and MRI‐2 of each image type (LIFEx, v5.10). Statistical Tests Influence of the input data type on RF values was evaluated with analysis of variance. RFs test–retest repeatability and reproducibility over multiple segmentations were evaluated with intra‐class correlation coefficient (ICC). Correlations between k‐means clusters and the six tissues depending on the RFs dataset were investigated with adjusted‐Rand‐index (ARI). Results About 41 of 45 (91.1%) RFs were significantly influenced by the input image type ( P values < 0.05), which was the most influential factor on repeatability of RFs ( P ‐value < 0.05). Repeatability ICCs from T2‐map displayed intermediate values between the initial T2WI (range: 0.407–0.736) and the T2WI HM (range: 0.724–0.817). The number of RFs with interobserver and intraobserver reproducibility ICCs ≥ 0.90 was 37/45 (82.2%) for T2WI HM , 33/45 (73.3%) for T2WI std , 31/45 (68.9%) for T2 map, and 25/45 (55.6%) for the initial T2WI. T2 map provided the best tissue discrimination (ARI = 0.414 vs. 0.157 with T2WI HM ). Data Conclusion T2 mapping provided RFs with moderate to substantial repeatability and reproducibility ICCs, along with the most preserved discriminative information. Level of Evidence 1 Technical Efficacy 1