Current status and future perspectives of radiomics in hepatocellular carcinoma

Table 1 Summary of the studies that evaluated radiomics to preoperatively predict hepatocellular cholangiocarcinoma histology

Ref.	Country	n	Imaging modality	Endpoint	Segmentation	ROI/VOI	No. of readers	Main results	Validation
Wang et al[92], 2022	China	196	MRI	cHCC-CC vs HCC	Manual, intratumoral	ROI	1	AUC (delayed phase MRI): 0.91	None
Liu et al[24], 2021	Canada	85	MRI and CT	cHCC-CC vs HCC vs CC	Manual, intratumoral	ROI	2	AUC (MRI): 0.77-0.81. AUC (CT): 0.71-0.81	Cross-validation
Lewis et al[25], 2019	United States	63	MRI	cHCC-CC vs HCC vs CC	Manual, intratumoral	VOI	2	AUC (LI-RADS and male gender): 0.90	None
Nie et al[27], 2020	China	156	CT	HCC vs FNH	Manual, intratumoral	ROI	2	AUC (radiomics): 0.96 training, 0.87 validation. AUC (radiomics + clinical factors): 0.98 training, 0.92 validation	None
Wu et al[28], 2019	China	369	MRI	HCC vs hemangioma	Manual, intratumoral	ROI	2	AUC: 0.86 training, 0.89 testing	None
Mokrane et al[29], 2020	United States	178	CT	HCC diagnosis	Manual, intratumoral	VOI	2	AUC: 0.70 training, 0.66 validation	External
Brancato et al[34], 2022	Italy	38	MRI	Tumor grade	Manual, intratumoral	VOI	1	AUC: 0.89	None
Gao et al[93], 2018	China	Training: 125. Validation: 45	MRI	Tumor grade	Manual, intratumoral	N/A	N/A	AUC: 0.83 training, 0.74 validation	None
Wu et al[30], 2019	China	Training: 125. Validation: 45	MRI	Tumor grade	Manual, intratumoral	ROI	1	AUC: 0.83 training, 0.74 validation	Internal
Zhou et al[94], 2017	China	46	MRI	Tumor grade	Manual, intratumoral	ROI	1	AUC: 0.83-0.92	None
Mao et al[31], 2022	China	Training: 85. Validation: 37	MRI	Tumor grade	Manual, intratumoral	ROI	2	AUC: 0.97 training, 0.94 validation	Internal
Chen et al[33], 2021	China	Training: 112. Validation: 49	CT	Tumor grade	Manual, intratumoral	VOI	2	AUC: 0.90 training, 0.94 validation	Internal
Yang et al[95], 2019	China	Training: 146. Validation: 62	Gadoxetic acid-enhanced MRI	MVI	Manual, intratumoral	ROI	2 (consensus)	AUC: 0.94 training, 0.86 validation	Internal
Xu et al[39], 2019	China	495	CT	MVI	Semi-automatic, intratumoral and peritumoral	VOI	3	AUC: 0.91 training, 0.89 validation	Internal
Feng et al[40], 2019	China	160	Gadoxetic acid-enhanced MRI	MVI	Manual, intratumoral and peritumoral	VOI	3	AUC: 0.85 training, 0.83 validation	Internal
Zheng et al[41], 2017	United States	120	CT	MVI	Semi-automatic	ROI	1	AUC: 0.80	None
Bakr et al[96], 2017	United States	28	CT	MVI	Manual, intratumoral	ROI	4	AUC: 0.76	None
Ma et al[97], 2019	China	157	CT	MVI	Manual, intratumoral	VOI	1	AUC (portal venous phase CT): 0.79	Cross-validation

AUC: Area under the curve; cHCC-CC: Combined hepatocellular cholangiocarcinoma; CT: Computed tomography; FNH: Focal nodular hyperplasia; HCC: Hepatocellular carcinoma; MRI: Magnetic resonance imaging; MVI: Microvascular invasion; ROI: Region of interest; VOI: Volume of interest.

Table 2 Summary of the studies that evaluated radiomics models to predict genetic profile in patients with hepatocellular cholangiocarcinoma

Ref.	Country	n	Imaging modality	Endpoint	Segmentation	ROI/VOI	No. of readers	Main results	Validation
Xia et al[98], 2018	China	38	CT	Association with gene expression profile	Manual, intratumoral	ROI	1	Individual textural features predicted gene modules	No
Wu et al[44], 2022	China	Training: 120. Validation: 52	CT	Ki-67 expression	Manual, intratumoral	VOI	2	AUC: 0.85 (training), 0.74 (validation)	Internal
Li et al[45], 2019	China	83	MRI	Ki-67 expression	Manual, intratumoral	ROI	2	Some features were associated, no model	No
Ye et al[47], 2019	China	89	MRI	Ki-67 expression	Manual, intratumoral	VOI	2	C-index: 0.878	No
Fan et al[46], 2021	China	Training: 103. Validation: 48	MRI	Ki-67 expression	Manual, intratumoral	VOI	2	AUC: 0.88 (training), 0.80 (validation)	Internal
Hu et al[48], 2022	China	Training: 87. Validation: 21	MRI	Ki-67 expression	Manual, intratumoral	ROI	1	AUC: 0.90 (training), 0.83 (validation)	Internal
Wang et al[50], 2019	China	78	MRI	CK19 positivity	Manual, intra- and peritumoral	ROI	1	AUC: 0.76	No
Chen et al[51], 2021	China	Training: 102. Validation: 19	MRI	CK19 positivity	Manual, intratumoral	ROI	2	AUC: 0.82 (training), 0.78 (external validation)	Internal and external
Yang et al[52], 2021	China (multi-center)	Training: 143. Validation: 75	MRI	CK19 positivity	Manual, intratumoral	ROI	2	AUC: 0.85 (training), 0.79 (external validation)	Internal and external
Wu et al[55], 2019	China	63	CT	P53 mutation status	Manual, intratumoral	ROI	2	AUC: 0.62-0.79	No
Li et al[99], 2022	China	92	MRI	Gene signatures associated with disease recurrence	Manual, intratumoral	ROI	2	MRI radiomics features could help quantify GOLM1, SETD7, and RND1 expression levels	Internal
Liao et al[56], 2022	China	Training: 86. Validation: 46	CT	Somatic mutations of the PI3K signaling pathway	Manual, intratumoral and peritumoral	VOI	2	AUC: 0.74 (training), 0.73 (external validation)	Internal and external
Che et al[60], 2022	China	Training: 69. Validation: 30	CT	β-arrestin1 phosphorylation	Manual, intratumoral	ROI	1	AUC: 0.89 (training), 0.74 (validation)	Internal

AUC: Area under the curve; CT: Computed tomography; MRI: Magnetic resonance imaging; ROI: Region of interest; VOI: Volume of interest; CK19: Cytokeratin 19; PI3K: P53, and phosphatidylinositol-3 kinase.

Table 3 Summary of the studies that assessed radiomics to predict recurrence and treatment response in patient with hepatocellular cholangiocarcinoma who underwent surgery, liver transplantation or locoregional treatment

Ref.	Country	n	Imaging modality	Endpoint	Treatment type	Segmentation	ROI/VOI	No. of readers	Main results	Validation
Hui et al[100], 2018	Singapore	50	MRI	Recurrence	Hepatic resection	Manual, intratumoral	ROI	3	AUC: 0.78-0.84	None
Kim et al[65], 2019	South Korea	Training: 128. Validation: 39	MRI	Recurrence	Hepatic resection	Semiautomatic, intra- and peritumoral	VOI	2	C-index: 0.716	Internal
Zhao et al[101], 2021	China	Training: 78. Validation: 35	MRI	Recurrence	Hepatic resection	Manual, intratumoral	VOI	2	AUC: 0.83 (training), 0.77 (validation)	Internal
Zhou et al[68], 2017	China	215	CT	Recurrence	Hepatic resection	Manual, intratumoral	ROI	2	AUC: 0.84 (combined model)	None
Ji et al[64], 2020	China	Internal: 177. External: 118	CT	Recurrence	Hepatic resection	Manual, intratumoral	VOI	1	AUC: 0.77 (internal), 0.78 (external)	External
Guo et al[69], 2019	China	Training: 93. Validation: 40	CT	Recurrence	Liver transplant	Semiautomatic, intratumoral	ROI	1	AUC: 0.79 (training), 0.79 (validation)	Internal
Shan et al[66], 2019	China	Training: 109. Validation: 47	CT	Recurrence	Hepatic resection or ablation	Manual, intra- and peritumoral	ROI	2	AUC: 0.80 (training), 0.79 (validation)	Internal
Zheng et al[79], 2018	China	Training: 212. Validation: 107	CT	Recurrence and survival	Hepatic resection	Manual, intratumoral	ROI	2	AUC: 0.64 (training), 0.59 (validation)	Internal
Song et al[67], 2020	China	Training: 110. Validation: 74	MRI	Recurrence	TACE	Semiautomatic, intra- and peritumoral	VOI	2	C-index: 0.82	Internal
Lv et al[71], 2021	China	Training: 40. Validation: 18	MRI	Recurrence	RFA	Semiautomatic, intratumoral	VOI	2	AUC: 0.94 (training), 0.82 (validation)	Internal
Sun et al[70], 2020	China	Training: 67. Validation: 17	MRI	Recurrence	TACE	Manual (intratumoral)	VOI	2	AUC: 0.71-0.79	Internal
Cai et al[75], 2019	China	Training: 80. Validation: 32	CT	Liver failure	Hepatic resection	Semiautomatic, intratumoral	ROI	2	AUC: 0.82 (training), 0.76 (validation)	Internal
Zhu et al[76], 2020	China	101	MRI	Liver failure	Hepatic resection	Manual, entire liver	ROI	2	AUC: 0.81-0.89	None
Ivanics et al[73], 2021	Canada	88	CT	Treatment response	TACE	Manual, intratumoral	VOI	1	AUC: 0.70-0.87	None
Kong et al[72], 2021	China	Training: 69. Validation: 30	MRI	Treatment response	TACE	Manual, intratumoral	VOI	2	AUC: 0.81 (training), 0.87 (validation)	Internal
Chen et al[63], 2021	China	Training: 355. Internal: 118. External: 122	CT	Treatment response	TACE	Semiautomatic, intra- and peritumoral	ROI	2	AUC: 0.94 (internal), 0.90 (external)	Internal and external
Horvat et al[74], 2021	Brazil	34	MRI	Treatment response	RFA	Manual, intratumoral	VOI	1	AUC: 0.76	None

AUC: Area under the curve; CT: Computed tomography; MRI: Magnetic resonance imaging; RFA: Radiofrequency ablation; ROI: Region of interest; TACE: Transarterial chemoembolization; VOI: Volume of interest.

Table 4 Summary of the studies that evaluated radiomics to predict survival in patients with hepatocellular cholangiocarcinoma

Ref.	Country	n	Imaging modality	Endpoint	Treatment type	Segmentation	ROI/VOI	No. of readers	Main results	Validation
Kiryu et al[77], 2017	Japan	122	CT	Survival	Hepatic resection	Manual, intra- and peritumoral	ROI	1	OS and DFS were significantly different between 2 rad score groups	None
Xu et al[39], 2019	China	Training: 350. Validation: 145	CT	Survival	Hepatic resection	Semiautomatic, intratumoral	VOI	3	AUC: 0.91 (training), 0.81 (validation)	Internal
Akai et al[78], 2018	Japan	127	CT	Survival	Hepatic resection	Manual, intratumoral	ROI	1	OS and DFS were significantly different between 2 rad score groups	None
Kim et al[80], 2018	South Korea	88	CT	Survival	TACE	Manual, intratumoral	ROI	1	Combined clinical and radiomics score was a better predictor of survival	None
Blanc-Durand et al[81], 2018	Switzerland	47	18F-FDG PET-CT	Survival	TARE	Semiautomatic, whole liver	VOI	N/A	PFS-Rad Score and OS-Rad Score were independent negative predictors	None
Petukhova-Greenstein et al[82], 2022	United States	65	MRI	Survival	RFA	Semiautomatic, intra- and peritumoral	VOI	2	OS was significantly different between 2 rad score groups	None
Zheng et al[79], 2018	China	Training: 212. Validation: 107	CT	Survival	Hepatic resection	Manual, intratumoral	ROI	2	AUC: 0.71 (training and validation)	Internal

AUC: Area under the curve; CT: Computed tomography; DFS: Disease-fee survival; MRI: Magnetic resonance imaging; OS: Overall survival; PFS: Progression-free survival; RFA: Radiofrequency ablation; ROI: Region of interest; TACE: Transarterial chemoembolization; TARE: Transarterial radioembolization; VOI: Volume of interest; PET: Positron emission tomography.

Table 5 Summary of the studies that assessed reproducibility of hepatocellular cholangiocarcinoma textural features

Ref.	Country	n	Imaging modality	Segmentation	Segmentation software	ROI/VOI	No. of readers	Intra-reader reproducibility	Inter-reader reproducibility	Other reproducibility
Duan et al[88], 2022	China	19	CT, MRI	Manual, intra- and peritumoral	3D-Slicer	ROI	2 (1 radiologist and 1 radiation oncologist)	Features with ICC ≥ 0.75 in both tumoral and peritumoral tissue greatest in MR	Features with ICC ≥ 0.75 in both tumoral and peritumoral tissue greatest in MR	N/A
Zhang et al[102], 2022	China	90 (31 HCC)	MRI	Manual, intratumoral	ITK-SNAP	ROI and VOI	2 radiologists	N/A	ICC > 0.8 used	N/A
Carbonell et al[89], 2022	United States	55 (16 HCC)	MRI	Manual, intratumoral and liver parenchyma	Olea sphere 3.0, Olea Medical	ROI for normal liver, VOI for HCC	2 radiologists	N/A	CCC: 0.80-0.99	For test-retest (same MRI system, 2 different MRI exams): ICC: 0.53-0.99; and in liver parenchyma: ICC: 0.53-0.73. For inter-platform reproducibility (MRI systems from 2 different vendors): CCC: 0.58-0.99
Park et al[103], 2022	South Korea	249	CT	Manual followed by automatic segmentation, intratumoral	MEDIP PRO	ROI and VOI	1 radiologist	For VOI: Manual: ICC 0.594-0.998 for FO, 0.764-0.997 for shape, and 0.190-0.926 for SO; DL-AS: ICC > 0.75 for all. For ROI: Manual: 0.698-0.997 for FO, 0.556-0.997 for shape, and 0.341-0.935 for SO; DL-AS ICC > 0.75 for all	N/A
Haniff et al[104], 2021	Malaysia	30	MRI	Manual and semi-automatic, intratumoral	3D-Slicer	VOI	Manual: 4 readers. Semi-automatic: 2 readers	N/A	Manual segmentation: ICC 0.897. Semi-automatic segmentation: ICC 0.952	NA
Ibrahim et al[90], 2021	Germany	61 patients, 104 lesions	CT	Manual, intratumoral	MIM software	ROI	1 nonradiologist revised by radiologist	N/A	N/A	Across different contrast imaging phases: 25% of extracted features had CCC > 0.9 across arterial and portal venous phases
Hu et al[105], 2021	China	30	CT	Manual, intratumoral	MaZda software	ROI	2 radiologists	ICC > 0.7	ICC > 0.7	N/A
Mao et al[32], 2020	China	30	CT	Manual, intratumoral	ITK-SNAP	ROI	2 radiologists	N/A	ICC ≥ 0.8	N/A
Hu et al[106], 2020	China	50	CT	Semi-automatic, peritumoral	Not mentioned	ROI	2 radiologists	N/A	ICC > 0.6	N/A
Qiu et al[107], 2019	China	26	CT	Manual and semi-automatic, intratumoral	GrowCut and GraphCut	ROI	Manual: 5 radiation oncologists. Semi-automatic: 2 radiation oncologists	N/A	ICC ≥ 0.75 in 69% of features extracted from manual segmentation, 73% from GraphCut, and 79% from GrowCut	Across different centers: Poor reproducibility of CT-based peritumoral-radiomics model
Zhang et al[108], 2019	China	46 (34 HCC)	MRI	Manual, intratumoral	MIM software	VOI	1 radiologist	N/A	N/A	Across different b-values: radiomic features extracted from b = 0, 20, 50, 100, 200 s/mm2 and b = 1000 s/mm2 and nearby b-values DWIs showed a high reproducibility (ICC ≥ 0.8)
Feng et al[40], 2019	China	160 (110)	MRI	Manual, intra- and peritumoral	ITK-SNAP	VOI	3 radiologists	85% ICC ≥ 0.8	82% ICC ≥ 0.8	N/A
Perrin et al[91], 2018	United States	38 (6 HCC)	CT	Semi-automatic, intratumoral and liver parenchyma	Scout Liver	VOI	1 research fellow under supervision of radiologist	N/A	N/A	Across different contrast injection rates, pixel resolutions, and scanner models: Number of reproducible radiomic features (CCC > 0.9) decreased with variations in contrast injection rate, pixel resolution, and scanner model

CT: Computed tomography; MRI: Magnetic resonance imaging; ROI: Region of interest; VOI: Volume of interest; TACE: Transarterial chemoembolization; ICC: Intraclass correlation coefficient; DWI: Diffusion-weighted imaging; CCC: Concordance correlation coefficient; HCC: Hepatocellular carcinoma; N/A: Not applicable; FO: First order; SO: Second order; DL-AS: Deep learning-based auto-segmentation.