Author | N | Modality/features (software applied) | # features selected | Model type | Outcome measures | Validation | Result/comment |
---|---|---|---|---|---|---|---|
Huynh [24] | 113 | CT:1605 (in-house software) | 12 + clinical | Survival analysis, cc-index | Recurrence, Distant mets., OS | Single institution cross validation | Risk for recurrence: no significant features Risk for dist. metastases: 1 sign. Feature OS: 4 significant features, cc = 0.67 |
92 | CT: 219 (Definiens Developer) | 8–68 + clinical + semantic | ROC-analysis | Recurrence, RFS, OS | Single institution cross-validation | Risk stratification: AUC = 0.69–0.75 | |
Zhang [58] | 112 | CT: 30 (ProCanVAS) | dependent on model | 8 models: Random forest GLM, SVM etc | Recurrence, Distal failure, OS | Single institution cross validation | Risk stratification: AUC = 0.60–0.77 |
Yu [34] | 442 | CT: 12 (IBEX) | 2 | Random survival forests | Regional recurrence, OS | Single institution test set: 67% | OS risk stratification: p = 0.017 Recurrence risk stratification: p < 0.05 2 sign. features: kurtosis, homogeneity |
Li [30] | 110 | CT + FDG-PET (learned by model) | from model | Kernelled support tensor machine | Distant failure | Single institution test set: 30% | Risk stratification: AUC = 0.80 |
Oikonomou [31] | 150 | CT + FDG-PET 2 × 21 (ProCanVAS) | 6–8, 4 from PCA | PCA, logistic regression | Local control, Distant control, DSS, OS | Single institution cross validation | Risk stratification: p = 0.004–0.02 features: heterogeneity and morphology |
Starkov [32] | 116 | CT: 2D-textures from solid core and GGO | 2–30 | Cox regression lasso | PFS, distant failure | Single institution cross validation | Risk stratification: p = 0.03 dependent on wavelet filtering |
Lafata [26] | 70 | CT: 43 | 2 | Logistic regression regularized | Local recurrence | none | Risk stratification: p = 0.048 features: density |
Franceschini [23] | 102 | CT: 41 (LifeX) | 4–6 | Cox regression elastic net, back selection | Nodal relapse, PFS, DSS | Single institution Test set: 32% | Nodal Relapse: accuracy = 85% PFS: 53 vs.45 months features: heterogeneity |
Lou [59] | 944* | CT | learned by model | CNN, Multivariate competing risk | Local recurrence | Multi institution test set: 10% | Risk stratification: p < 0.002 |
Baek [21] | 122 | CT + FDG-PET 2 × 55,296 | Features from k-medoids pool | CNN (U-Net) logistic regression | OS | Independent institution test set: 21% | Risk stratification: AUC = 0.87 |