Magnetic resonance imaging-based radiomics model for preoperative assessment of risk stratification in endometrial cancer

Table 1 Magnetic resonance imaging scanning parameters

Sequence	TR/TE in ms	FOV in mm × mm	Matrix	Slice gap in mm	Slice thickness in mm
Axial T1WI	500/8.6	310 × 310	224 × 320	1	6
Axial T2WI	6200/95	310 × 310	307 × 384	1	6
Axial (FS)-T2WI	4000/93	310 × 310	256 × 320	1	5
Sagittal (FS)-T2WI	6000/86	240 × 240	205 × 256	1	6
Axial DWI	5000/69	327 × 245	115 × 192	1	4

DWI: Diffusion weighted imaging; FOV: Field of view; FS: Fat suppression; T1WI: T1-weighted images; T2WI: T2-weighted imaging; TE: Echo Time; TR: Repetition time.

Table 2 Characteristics of endometrial cancer patients in the training and validation cohorts

Characteristics	Training cohort	Validation cohort	P value
Number	78	34
Age in yr	58.04 ± 11.54	59.06 ± 12.04	0.367
Histological grade1			0.465
G1/G2	58	23
G3	20	11
Risk classes			1.000
Low-risk	39	17
High-risk	39	17
Histological subtype1			0.018
Endometrioid	66	22
Serous	6	5
Clear cell	4	4
Carcinosarcoma	2	3
FIGO staging			0.765
I	50	21
II	11	7
III	9	4
IV	8	2
BMI
> 24	44	19	0.959
≤ 24	34	15
Hypertension			0.812
Positive	20	8
Negative	58	26
DM			0.605
Positive	15	8
Negative	63	26
Hyperlipidemia			0.338
Positive	5	4
Negative	73	30
Menstruation			0.395
Regular	48	18
Irregular	30	16
Menopausal status
Premenopausal	57	27	0.477
Postmenopausal	21	7
Fertility			0.669
Fertility	69	31
Nonfertility	9	3
CA125			0.617
< 35 U/mL	61	28
≥ 35 U/mL	17	6
CA19-9			0.631
< 27 U/mL	67	28
≥ 27 U/mL	11	6
Family history of cancer			0.292
Positive	10	7
Negative	68	27
Drinking history			0.915
Positive	5	2
Negative	73	32
Smoking history			0.606
Positive	4	1
Negative	74	33

¹Histological grade and subtype of endometrioid adenocarcinoma from surgical specimen.

Data are n or mean ± standard deviation. FIGO: The International Federation of Gynaecology and Obstetrics; BMI: Body mass index; CA125: Cancer antigen 125; CA19-9: Cancer antigen 19-9; DM: Diabetes mellitus.

Table 3 Univariate regression analysis and multivariate regression analysis

Characteristics	Univariate regression OR (95%CI)	P value	Multivariate regression OR (95%CI)	P value
Age	Reference 1.091 (1.038-1.147)	0.000	Reference 1.10 (1.000-1.019)	0.048
BMI
> 24	Reference
≤ 24	2.333 (0.933-5.833)	0.070
Hypertension
Positive	Reference
Negative	0.438 (0.152-1.256)	0.124
Diabetes mellitus
Positive	Reference
Negative	0.848 (0.274-2.619)	0.774
Hyperlipidemia
Positive	Reference
Negative	0.649 (0.102-4.113)	0.646
Menstruation
Regular	Reference
Irregular	1.591 (0.615-4.114)	0.338
Menopausal status
Premenopausal	Reference
Postmenopausal	2.560 (0.898-7.296)	0.079
Reproductive history
Positive	Reference
Negative	0.777 (0.192-3.142)	0.724
CA125
< 35 U/mL	Reference		Reference
≥ 35 U/mL	26.435 (3.284-29.776)	0.002	1.515 (1.163-1.973)	0.003
CA19-9			Reference
< 27 U/mL	Reference		1.355 (1.030-1.783)	0.033
≥ 27 U/mL	5.550 (1.114-27.648)	0.036
Family history of cancer
Negative	Reference
Positive	1.000 (0.265-3.772)	1.000
Drinking history
Negative	Reference
Positive	4.343 (0.463-40.749)	0.199
Smoke history
Negative	Reference
Positive	0.316 (0.031-3.177)	0.328
Radscore	1.027 (1.002-1.054)	0.038	1.025 (0.990-1.060)	0.016

BMI: Body mass index; CA125: Cancer antigen 125; CA19-9: Cancer antigen 19-9; CI; Confidence interval; OR: Odds ratio.

Table 4 Outcomes of radiomics models in validation set

Algorithms	AUC (95%CI)	Accuracy	Sensitivity	Specificity
LR	0.794 (0.706-0.976)	0.794	0.765	0.824
KNN	0.893 (0.766-0.971)	0.765	0.823	0.705
DT	0.676 (0.529-0.824)	0.676	0.529	0.824
RF	0.915 (0.806-0.986)	0.824	0.824	0.824
GB	0.907 (0.792-0.979)	0.794	0.706	0.882
XGBoost	0.869 (0.739-0.965)	0.765	0.706	0.824
GBDT	0.872 (0.742-0.958)	0.765	0.647	0.882

AUC: Area under the curve; CI: Confidence interval; DT: Decision tree; GB: Gradient boosting; GBDT: Gradient boosting decision tree; KNN: K-nearest neighbor; LR: Logistic regression; RF: Random forest; XGBoost: eXtreme gradient boosting.