Authors, year | Dataset: sample size, cancer type | Time of xerostomia assessment, endpoint/scale | Imaging modality | VOI | Classifier / regression model(s) | Metric: maximum performance a |
---|---|---|---|---|---|---|
Sheikh et al. 2019 [110] | Train:216, HNSCC Test:50, HNSCC | 3-month post-RT, CTCAE v4.0 b grade ≥ 2 vs. grade 0/1 | Pre-treatment CT, T1-weighted MRI | Parotid and submandibular glands (bilateral) | Multivariable logistic regression | CV-AUC: 0.75 test-AUC: 0.70 |
Liu et al. 2019 [111] | Train:35, NPC Test:4, NPC | day of 10th and 30th RT, saliva amount (ml) over 5 min (a regression analysis) | CT at start and day of 10th RT fraction | Parotid glands (bilateral) | 8 different regression models | CV-MSE: 0.9042 (10th fraction), 0.0569 (30th fraction) test-MSE: 0.0233 (30th fraction) |
van Dijk et al. 2018 [112] | Train:68, HNSCC Test:25, HNSCC | 12 moth post-RT, patient-rated moderate-to-severe xerostomia present vs. not present | Pre-treatment T1-weighted MRI | Parotid glands, (bilateral) | Multivariable logistic regression | n/a c |
van Dijk et al. 2017 [113] | Total: 249, HNSCC | 12 moth post-RT, EORTC QLQ-H, N35 questionnaire d moderate-to-severe xerostomia vs. not present | Pre-treatment contrast CT | Parotid and submandibular glands (bilateral) | Multivariable logistic regression | n/a c |
van Dijk et al. 2018 [114] | Total: 161, HNSCC | 12-month post-RT, EORTC QLQ-H questionnaire d moderate-to-severe xerostomia present vs. not present | Pre-treatment FDG PET | Contralateral parotid gland | Multivariable logistic regression | n/a c |