Table 2. Summary of human radiomics studies using ICC for image reconstruction.
| First author, year | Disease | Patient number/feature number/ICC sample size | Reconstruction factors | Satisfactory feature rate | ICC threshold |
|---|---|---|---|---|---|
| CT | |||||
| Ahn et al., 2019 (60) | Liver lesion and renal cyst | 1,462/11/1,462 | Inter-method | NE | 0.75 |
| Kolossváry et al., 2019 (61) | Vascular disease | 60/171/60 | Inter-method | ~97.04% | 0.9 |
| Koo et al., 2017 (62) | Lung cancer | 194/10/194 | Reconstruction intervals | ~70% | 0.8 |
| Lee et al., 2019 (63) | Lung nodule | 194 patients (260 scans) /252/114 patients (180 scans) | Voxel size | 9.13% | 0.7 |
| Ligero et al., 2021 (31) | Colorectal/kidney disease | 43 (97 liver mets)/93/43 (97 liver mets) | Voxel size | 48.40–78.49% | 0.8 |
| Slice spacing | 43.01–86.02% | 0.8 | |||
| Slice thickness | 75.25–88.17% | 0.8 | |||
| Convolution kernel | 55.92–97.85% | 0.8 | |||
| Prayer et al., 2021 (32) | Lung disease | 60/86/60 | Reconstruction kernel and slice thickness, | NE | NE |
| Vuong et al., 2020 (33) | Lung cancer | 124/1,404/23 | Convolution kernel | 17.20% | 0.9 |
| Yamashita et al., 2020 (34) | Pancreatic cancer | 37/266/37 | Voxel size | NE | 0.8 |
| MRI | |||||
| Suter et al., 2020 (64) | GBM | 63+76/8,327/19 | K-space subsampling | NE | 0.85 |
| PET | |||||
| Altazi et al., 2017 (65) | Cervical cancer | 88/79/8 | Inter-method | NE | NA |
| van Velden et al., 2016 (66) | Lung cancer | 11/105/11 | Inter-method | 63% (segmentation or reconstruction) | 0.9 |
NA, not available or not clear; NE, could not be simply extracted due to comprehensive results, see the reference for detail; liver mets, liver metastases; GBM, glioblastoma multiforme.