Noninvasive assessment of endometrial fibrosis in patients with intravoxel incoherent motion MR imaging.
Sci Rep
; 11(1): 12887, 2021 06 18.
Article
em En
| MEDLINE
| ID: mdl-34145361
Recently, few noninvasive methods have been reported to evaluate endometrial fibrosis. Our study was to investigate the feasibility of intravoxel incoherent motion (IVIM) MR imaging in the detection of endometrial fibrosis in patients with intrauterine injury. 30 patients with hysteroscopy-confirmed endometrial fibrosis and 28 healthy women were enrolled to undergo MR examination including the IVIM sequence. Endometrial thickness (ET); apparent diffusion coefficient (ADC); and IVIM parameters, including pure diffusion coefficient (D), pseudodiffusion coefficient (D*) and vascular fraction (f) were evaluated. A multivariable model combing ADC, D, and f values using binary logistic regression analysis was built to diagnose endometrial fibrosis. Endometrial fibrosis patients demonstrated lower endometrial ADC, D, f values and ET (all p < 0.05). The multivariable model, ADC, D, f values and ET performed well in diagnosing endometrial fibrosis with AUC of 0.979, 0.965, 0.920, 0.901 and 0.833, respectively. The multivariable model revealed a better diagnostic accuracy than D, f and ET (all p < 0.05). Although ADC achieved a better diagnostic value than ET (z = 2.082, p < 0.05), no difference in AUC was shown among ADC, D, and f (all p > 0.05); between ET and D (p > 0.05); and between ET and f (p > 0.05). The reproducibility of ADC, D, f and D* values in patients with endometrial fibrosis and healthy women were good to excellent (ICC: 0.614-0.951). IVIM parameters exhibit promising potential to serve as imaging biomarkers in the noninvasive assessment of endometrial fibrosis.
Texto completo:
1
Temas:
ECOS
/
Aspectos_gerais
Bases de dados:
MEDLINE
Assunto principal:
Doenças Uterinas
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Imageamento por Ressonância Magnética
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Endométrio
Tipo de estudo:
Observational_studies
/
Prognostic_studies
Limite:
Adult
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Female
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Humans
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Middle aged
Idioma:
En
Revista:
Sci Rep
Ano de publicação:
2021
Tipo de documento:
Article
País de afiliação:
China