Table 4. Summary of human radiomics studies using ICC for image processing.
| First author, year | Disease | Patient number/feature number/ICC sample size | Image processing factors | Satisfactory feature rate | ICC threshold |
|---|---|---|---|---|---|
| CT | |||||
| Bogowicz et al., 2016 (105) | Lung cancer, HNC | 11+11/315/11+11 | HU threshold | ~35% | 0.9 |
| Voxel size resampling | ~5% | ||||
| Temporal resolution | ~30% | ||||
| Artery contouring | ~45% | ||||
| Noise threshold | ~52.5% | ||||
| Ger et al., 2018 (106) | Lung cancer HNC | 20+30/49/20+30 | Voxel size resampling | 71–79.6% | 0.9 |
| Shafiq-Ul-Hassan et al., 2018 (107) | Lung cancer | 18/24/18 | Gray level normalization | 100.00% | 0.8 |
| Lee et al., 2019 (63) | Lung nodule | 194 patients (260 scans)/252/114 patients (180 scans) | Voxel size resampling | 15% | 0.7 |
| Zwanenburg et al., 2019 (28) | Lung cancer HNC | 31+19/4,032/31+19 | Noise | 95.0–97.4% | 0.9 |
| Rotation | ~75–80% | ||||
| Translation, volume adaptation, contrast | 16.6–32.9% | ||||
| Rotation, volume adaptation, contrast | 16.8–33.3% | ||||
| Noise, translation, volume adaptation, contrast | 16.7–33.7% | ||||
| Rotation, noise, volume adaptation, contrast | 16.7–34.2% | ||||
| Other | NE | ||||
| Defeudis et al., 2020 (108) | Colorectal cancer | 14/35/14 | Standardization | ~36–60% | 0.9 |
| Park et al., 2020 (109) | Bladder cancer | 83/55/83 | SNR, and outlier inclusion | NE | 0.75 |
| MRI | |||||
| Kim et al., 2019 (110) | GBM | 167/356/167 | Pertubation | 77.20% | 0.75 |
| Li et al., 2019 (36) | Hippocampus | 60/55/60 | Normalization | ~36.36–56.36% | 0.4 |
| Schwier et al., 2019 (111) | Prostate cancer | 15/1,120/15 | Normalization | NE | 0.85 |
| Traverso et al., 2020 (95) | Cervical cancer | 81/552/81 | Normalization | NE | 0.9 |
| Fan et al., 2020 (112) | Breast cancer | 322/107/322 | Voxel size resampling | NE | 0.7 |
| Moradmand et al., 2020 (113) | GBM | 65/107/65 | Noise | 21.4% | 0.9 |
| Noise + bias field | 20.4% | ||||
| Bias field | 23.2% | ||||
| Bias field + noise | 22.5% | ||||
| Scalco et al., 2020 (43) | Prostate cancer | 14/91/14 | Normalization | ~12–14% | 0.9 |
| Shiri et al., 2020 (44) | GBM | 17/26,295,192/17 | Transformation, bias field removal | NE | 0.95 |
| Suter et al., 2020 (64) | GBM | 63+76/8,327/19 | Perturbation | 42.5% | 0.85 |
| PET | |||||
| Branchini et al., 2019 (114) | Pediatric | 21/106/21 | Activity reduction simulation | NE | 0.9 |
| Whybra et al., 2019 (115) | HNC | 441/141/441 | Voxel size resampling | 66% | 0.9 |
| PET, MRI | |||||
| Yang et al., 2020 (104) | NPC | 21/540/21 | Pixel size resampling | 55.74% (T2), 60.37% (DWI), 58.33% (PET) | 0.95 |
| Slice thickness | 24.07% (T2 and DWI), 23.89% (PET) |
NA, not available or not clear; NE, could not be simply extracted due to comprehensive results, see the reference for detail; HNC, head and neck cancer; HU, Hounsfield unit; SNR, signal-to-noise ratio; GBM, glioblastoma multiforme; NPC, nasopharyngeal carcinoma; DWI, diffusion-weighted imaging.