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Application of intravoxel incoherent motion imaging in the diagnosis of polycystic ovary syndrome

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ObjectiveTo evaluate the diagnostic efficacy of intravoxel incoherent motion (IVIM) parameters in ovarian stroma changes in polycystic ovary syndrome (PCOS) patients.MethodsThis prospective study included 58 PCOS patients and 60 healthy controls. Both groups underwent conventional magnetic resonance imaging (MRI) and IVIM scans. The diagnostic efficacy of IVIM parameters and conventional MRI was investigated and compared by using area under the curves (AUC). Binary logistic regression analysis, integrated discrimination improvement (IDI), and net reclassification improvement (NRI) were also used to assess the improvement in diagnosis of PCOS when combining IVIM parameters with conventional MRI features.ResultsThe apparent diffusion coefficient (ADC) and D values were significantly lower, while the D* and f values were significantly higher than the controls in the ovarian stroma in PCOS patients. The follicle number (FN) counted on the MRI showed an AUC of 0.90 (95%CI: 0.84–0.96) for differentiating PCOS from the controls, with a cutoff value of 23. The ADC value yielded the highest AUC of 0.83 (95%CI: 0.76–0.90) among the IVIM parameters, with a cutoff value of 1.04 × 10−3 mm2/s. The diagnostic performance was significantly by combining ADC and FN with an AUC of 0.94 (95%CI: 0.90–0.98). The IDI and NRI also showed improved diagnostic performance than FN alone.ConclusionThe D* and f values of the ovarian stroma in PCOS patients are significantly increased, while the ADC and D values are significantly reduced. The combination of ADC and FN can improve the diagnostic efficacy for PCOS.
Title: Application of intravoxel incoherent motion imaging in the diagnosis of polycystic ovary syndrome
Description:
ObjectiveTo evaluate the diagnostic efficacy of intravoxel incoherent motion (IVIM) parameters in ovarian stroma changes in polycystic ovary syndrome (PCOS) patients.
MethodsThis prospective study included 58 PCOS patients and 60 healthy controls.
Both groups underwent conventional magnetic resonance imaging (MRI) and IVIM scans.
The diagnostic efficacy of IVIM parameters and conventional MRI was investigated and compared by using area under the curves (AUC).
Binary logistic regression analysis, integrated discrimination improvement (IDI), and net reclassification improvement (NRI) were also used to assess the improvement in diagnosis of PCOS when combining IVIM parameters with conventional MRI features.
ResultsThe apparent diffusion coefficient (ADC) and D values were significantly lower, while the D* and f values were significantly higher than the controls in the ovarian stroma in PCOS patients.
The follicle number (FN) counted on the MRI showed an AUC of 0.
90 (95%CI: 0.
84–0.
96) for differentiating PCOS from the controls, with a cutoff value of 23.
The ADC value yielded the highest AUC of 0.
83 (95%CI: 0.
76–0.
90) among the IVIM parameters, with a cutoff value of 1.
04 × 10−3 mm2/s.
The diagnostic performance was significantly by combining ADC and FN with an AUC of 0.
94 (95%CI: 0.
90–0.
98).
The IDI and NRI also showed improved diagnostic performance than FN alone.
ConclusionThe D* and f values of the ovarian stroma in PCOS patients are significantly increased, while the ADC and D values are significantly reduced.
The combination of ADC and FN can improve the diagnostic efficacy for PCOS.

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