Deep learning based radiomics for gastrointestinal cancer diagnosis and treatment: A minireview

Table 5 Summary of studies using deep-learning-based radiomics for colorectal cancer

Ref.	Imaging	Study design	Study aim	DL model	Dataset	Outcomes
Wu et al[67], 2020	CT	Retrospective	Predicting KRAS status in patients with CRC	CNN	Primary cohort: 279 patients; validation cohort: 119 patients	C-index of 0.815 for the primary cohort and 0.832 for the validation cohort
Wei et al[68], 2021	CT	Retrospective	Predicting the response to chemotherapy in CRLM	ResNet10	192 patients	AUC of DLR: 0.820; AUC of HCR: 0.598
Zhang et al[69], 2021	MRI	Retrospective	Predicting the MSI status of CRC	MobileNetV2	491 patients	Accuracy: 85.4%; AUC: 0.868
Fu et al[70], 2020	MRI	Retrospective	Predicting NCRT response in patients with LARC	VGG19	43 patients	AUC of DLR: 0.73; AUC of HCR: 0.64
Liu et al[71], 2021	MRI	Retrospective	Predicting the distant metastasis of LARC patients receiving NCRT	ResNet18	235 patients	C-index of 0.747 and AUC of 0.894 in the validation cohort
Lu et al[72], 2021	CT	Retrospective	Prediction of early on-treatment response in mCRC	CNN + RNN	1028 patients	C-index: 0.649
Ding et al[73], 2020	MRI	Retrospective	Prediction of metastatic LN in CRC	Faster RCNN	545 patients	AUC for training: 0.862; AUC for validation: 0.920
Zhao et al[74], 2022	CT	Retrospective	Prediction of metastatic LN in CRC	Autoencoder	423 patients	AUC for training: 0.81; AUC for validation: 0.73; AUC for testing: 0.77
Li et al[75], 2020	MRI	Retrospective	Classification of CRC LN Metastasis images	AlexNet	3364 samples (1646 positive; 1718 negative)	Accuracy: 75.83%; AUC: 0.7941

CRC: Colorectal cancer; CT: Computed tomography; MRI: Magnetic resonance imaging; CRLM: Colorectal liver metastases; MSI: Microsatellite instability; NCRT: Neoadjuvant chemoradiotherapy; LARC: Locally advanced rectal cancer; mCRC: Metastatic colorectal cancer; LN: Lymph node; CNN: Convolutional neural network; RNN: Recurrent neural network; AUC: Area under the receiver operating characteristic curve; C-index: Harrell’s concordance index; DLR: Deep-learning-based radiomics; HCR: Handcrafted radiomics; Faster R-CNN: Faster region-based convolutional neural network.