Deep learning radiomics nomogram based on multi-regional features for predicting lymph node metastasis and prognosis in colorectal cancer

Table 1 Computed tomography protocols of the two centers

Center	Scanner	Field of view (cm)	Image matrix (mm)	Tube voltage (kv)	Tube current (mA)	Pixel size (mm)	Slice thickness (mm)
1	Revolution CT (256-slice)	50	512 × 512	70-140	Auto	0.977	0.625-5
	Discovery CT750 HD (Gemstone)	50	512 × 512	80/100/120/140	Auto	0.977	0.625-5
2	SOMATOM definition flash (dual-source CT)	50	512 × 512	70-140	Auto	0.977	0.625-5

CT: Computed tomography.

Table 2 Baseline characteristics of the study population, n (%)

Characteristic	Training cohort (n = 154)			Internal validation cohort (n = 66)			External validation cohort (n = 58)			P value
	LNM (n = 54)	non-LNM (n = 100)	P value	LNM (n = 29)	non-LNM (n = 37)	P value	LNM (n = 24)	non-LNM (n = 34)	P value
Sex			0.493	-		0.530	-		0.286	0.112
Male	37 (68.5)	63 (63.0)		15 (51.7)	22 (59.5)		14 (58.3)	15 (44.1)
Female	17 (31.5)	37 (37.0)		14 (48.3)	15 (40.5)		10 (41.7)	19 (55.9)
Age (years), median (IQR)	64.50 (57.00, 74.00)	69.50 (61.00,77.00)	0.054	70.00 (58.50, 72.50)	72.00 (62.50, 78.50)	0.047	66.50 (58.25, 71.00)	67.00 (62.75, 72.00)	0.448	0.203
Height (cm), median (IQR)	165.00 (160.00, 170.25)	165.00 (160.00, 170.00)	0.968	165.00 (159.00,171.00)	165.00 (158.00, 172.00)	0.801	161.50 (156.75, 170.00)	164.00 (155.00, 168.00)	0.776	0.245
Weight (kg), median (IQR)	62.00 (54.75, 68.25)	62.00 (55.00, 68.00)	0.847	65.00 (61.00, 70.00)	60.00 (53.00, 67.50)	0.108	60.50 (52.50, 69.50)	60.50 (54.50, 66.50)	0.937	0.424
BMI, median (IQR)	22.98 (20.42, 24.37)	22.63 (20.55, 24.65)	0.913	23.44 (22.22, 24.67)	22.21 (20.13, 25.37)	0.272	23.14 (20.70, 24.93)	22.99 (20.68, 24.93)	0.819	0.616
Location			0.112	-		0.375	-		0.314	0.254
RCC	21 (38.9)	23 (23.0)		6 (20.7)	8 (21.6)		6 (25.0)	6 (17.6)
LCC	14 (25.9)	31 (31.0)		9 (31.0)	17 (45.9)		8 (33.3)	7 (20.6)
RC	19 (35.2)	46 (46.0)		14 (48.3)	12 (3.24)		10 (41.7)	21 (61.8)
CRP (mg/L), median (IQR)	2.06 (0.53, 7.02)	3.19 (0.50, 11.82)	0.740	2.39 (0.63, 8.17)	5.00 (0.67, 8.43)	0.725	5.00 (0.66, 10.99)	0.87 (0.50, 8.39)	0.068	0.595
LDL (mmol/L), median (IQR)	2.13 (1.61, 2.85)	2.21 (1.85, 2.90)	0.153	2.40 (1.91, 2.98)	1.97 (1.55, 2.41)	0.041	2.07 (1.72, 2.70)	2.85 (2.24, 3.62)	0.011	0.058
CEA (ng/mL)			< 0.001	-		0.366	-		0.467	0.678
≤ 5	27 (50.0)	77 (77.0)		19 (65.5)	28 (75.7)		14 (58.3)	23 (67.6)
> 5	27 (50.0)	23 (23.0)		10 (34.5)	9 (24.3)		10 (41.7)	11 (32.4)
CA 19-9 (U/mL)			< 0.001	-		0.035	-		0.651	0.333
≤ 37	34 (63.0)	91 (91.0)		21 (72.4)	34 (91.9)		21 (87.5)	31 (91.2)
> 37	20 (37.0)	9 (9.0)		8 (27.6)	3 (8.1)		3 (12.5)	3 (8.8)

LNM: Lymph node metastasis; IQR: Interquartile range; BMI: Body mass index; RCC: Right-sided colon cancer; LCC: Left-sided colon cancer; RC: Rectal cancer; CRP: C-reactive protein; LDL: Low-density lipoprotein; CEA: Carcinoembryonic antigen; CA 19-9: Carbohydrate antigen 19-9.

Table 3 Univariate and multivariate logistic regression analysis

Variable	Univariate analysis		Multivariate analysis
	OR (95%CI)	P value	OR (95%CI)	P value
Sex
Male	1 (Ref.)	-	-	-
Female	0.782 (0.387-1.581)	0.494	-	-
Age	0.975 (0.949-1.002)	0.070	0.982 (0.953-1.012)	0.235
Height	1.009 (0.962-1.060)	0.703	-	-
Weight	0.997 (0.961-1.034)	0.865	-	-
BMI	0.972 (0.869-1.008)	0.624	-	-
Location
RCC	1 (Ref.)	-	1 (Ref)	-
LCC	0.495 (0.208-1.175)	0.111	0.552 (0.227-1.342)	0.190
RC	0.452 (0.204-1.004)	0.051	0.583 (0.228-1.492)	0.261
CRP	0.997 (0.988-1.006)	0.520	-	-
LDL	0.697 (0.445-1.094)	0.117	-	-
CEA
≤ 5	1 (Ref.)	-	1 (Ref)	-
> 5	3.348 (1.649-6.797)	< 0.001	2.597 (1.199-5.623)	0.015
CA 19-9
≤ 37	1 (Ref.)	-	1 (Ref)	-
> 37	5.948 (2.467-14.337)	< 0.001	3.704 (1.435-9.563)	0.007

OR: Odds ratios; CI: Confidence interval; BMI: Body mass index; RCC: Right-sided colon cancer; LCC: Left-sided colon cancer; RC: Rectal cancer; CRP: C-reactive protein; LDL: Low-density lipoprotein; CEA: Carcinoembryonic antigen; CA 19-9: Carbohydrate antigen 19-9.

Table 4 Comparison of the performance of three models in the training, internal validation and external validation cohorts

Cohort	Models	AUC	ACC	SEN	SPE	PPV	NPV
Training cohort	Clinical	0.703 (0.623-0.780)	0.695	0.630	0.730	0.557	0.785
	DLRR	0.935 (0.889-0.968)	0.870	0.852	0.880	0.793	0.917
	Combined	0.944 (0.905-0.973)	0.812	0.926	0.750	0.667	0.949
Internal validation cohort	Clinical	0.637 (0.527-0.751)	0.636	0.517	0.730	0.600	0.659
	DLRR	0.877 (0.789-0.951)	0.742	0.621	0.838	0.750	0.738
	Combined	0.878 (0.788-0.949)	0.773	0.793	0.757	0.719	0.824
External validation cohort	Clinical	0.624 (0.492-0.760)	0.638	0.583	0.676	0.560	0.697
	DLRR	0.849 (0.731-0.941)	0.759	0.875	0.676	0.656	0.885
	Combined	0.855 (0.737-0.946)	0.690	0.917	0.529	0.579	0.900

AUC: Area under the receiver operating characteristic curve; ACC: Accuracy; SEN: Sensitivity; SPE: Specificity; PPV: Positive predictive value; NPV: Negative predictive value; DLRR: Deep learning-radiomics integrated model.