Teruel et al62
|
58 |
T1-weighted DCE-MRI |
GLCM texture features |
Entropy and sum variance were most significant in predicting stable disease vs. complete responders (AUC = 0.77) and predicting pCR (AUC = 0.69), respectively |
Thibault et al63
|
38 |
DCE-MRI |
GLCM, run length features extracted from pharmacokinetic maps |
GLCM features most predictive of therapy response |
Golden et al64
|
60 |
DCE-MRI |
GLCM texture features extracted from pharmacokinetic maps |
Pretherapy features can predict pCR and residual lymph node metastasis |
Parikh et al65
|
36 |
T2-and T1-weighted DCE-MRI |
Entropy and uniformity |
Responders to NACT showed increase in lesion homogeneity after one round of therapy |
Michoux et al66
|
69 |
T1-weighted DCE-MRI |
GLCM, run-length |
Model with three texture features and one kinetic feature identified nonresponders to NAC with 84% sensitivity |
Braman et al31
|
117 |
T1-weighted DCE-MRI |
Gabor, GLCM, Laws energy measures |
Intratumor and peritumor texture features predicted pCR with AUC = 0.78 |