Recent research on AI models for predicting nCRT and chemotherapy response in the treatment of CRC
| Topic | Research | Model | Performance | Year | Reference |
|---|---|---|---|---|---|
| nCRT | EUS images of 43 LARC patients as predictive biomarkers Images pre-processed by lee, wiener, median, frost, bilateral, and wavelet filters | LR and SVM | AUC: 0.71 and 0.76 Accuracy: 70.0% and 71.5% Sensitivity: 69.8% and 80.2% (respectively) | 2022 | [51] |
CT images of 215 LARC patients Images evaluated by filtration histogram texture analysis and fractal dimension | LR | Accuracy: 82% Specificity: 89% Sensitivity: 60% | 2021 | [52] | |
| pCR prediction in 282 LARC patients (248 training and 34 validation) | ANN | AUC/accuracy/sensitivity: 0.84/0.88/0.94 respectively | 2020 | [53] | |
| pCR prediction in 6,555 non-metastatic cancer patients undergoing radical resection | LR | 92.4%/88.2%: With/without—pathological complete response (overall survival rate of 3 years) | 2019 | [54] | |
MRI of 98 patients (53/45: training test/validation set respectively) Image preprocessing by EMLMs and LOG filters | SVM, NN, BN, and KNN | Test (AUC and accuracy): 97.8% and 92.8% Validation (AUC and accuracy): 95% and 90% | 2019 | [55] | |
| MRI of 55 LARC patients to predict pCR and pNR rates | RF | 0.83: Mean of AUC | 2019 | [56] | |
| Chemotherapy | Irinotecan drug toxicity prediction in 20 metastatic CRC patients (liver function bloody tests and tumor markers) | SVM | Accuracy: 91%/76%/75% for diarrhea/leukopenia/neutropenia respectively | 2019 | [57] |
Detection of IC50 of a drug Evaluation of QSAR using NMR Analysis of 18,850 organic compounds | KNN, RF, and SVM | Above 63% accuracy | 2018 | [58] |
AUC: area under curve; NN: neural network; BN: Bayesian network; LARC: locally advanced rectal cancer; EUS: endorectal ultrasound; IC50: half maximal inhibitory concentration; LOG: Laplacian of Gaussian; NMR: nuclear magnetic resonance; CT: computed tomography; MRI: magnetic resonance imaging; pCR: pathologic complete response; EMLMs: ensemble machine learning models; pNR: pathologic non responder