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Insights into Imaging

Table 4 Univariate and multivariate regression analysis of the radiological features

From: Exploring a multiparameter MRI–based radiomics approach to predict tumor proliferation status of serous ovarian carcinoma

Characteristics

Univariate regression analysis

Multivariate regression analysis

OR

95% CI

p Value

OR

95% CI

p Value

Distribution

 Unilateral

1

     

 Bilateral

0.719

0.293–1.717

0.461

N/A

N/A

N/A

Lobulated ovarian mass

 NO

1

     

 Yes

0.967

0.045–10.845

1

N/A

N/A

N/A

Angiogenesis of ovarian mass

 No

1

     

 Yes

1.22

0.237–5.344

0.794

N/A

N/A

N/A

Size of ovarian mass (cm)

 ≤ 7.4

1

     

 > 7.4

0.906

0.802–1.019

0.104

N/A

N/A

N/A

Homogeneous solid in ovarian mass

 No

1

  

1

  

 Yes

23.94

7.859–86.448

< 0.01

22.15

6.7–73.21

< 0.01

Peritoneum/mesentery nodules

 No

1

     

 Yes

2.07

0.790–5.430

0.135

N/A

N/A

N/A

Metastases of distant parenchymal organs

 No

1

     

 Yes

2.01

0.572–9.443

0.312

N/A

N/A

N/A

Retro-peritoneal lymphadenopathy

 No

1

     

 Yes

1.66

0.570–5.569

0.375

N/A

N/A

N/A

Amount of ascites

 None/ small

1

     

 Middle/large

1.30

0.541–3.129

0.551

N/A

N/A

N/A

  1. Chi-square test FIGO the International Federation of Gynecology and Obstetrics, CA-125 carbohydrate antigen 125, HE4 human epididymis protein 4, NLR neutrophil-to-lymphocyte ratio, OR odds ratio, 95% CI 95% confidence interval
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