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DOI 10.1016/j.diii.2016.09.004

Медицинская библиотека · Diagnostic and interventional imaging · 2016

Apparent diffusion coefficient measurement of ovarian stroma: A potential tool for the diagnosis of polycystic ovary syndrome.

Samanci C, Alis D, Ustabasioglu F E, Ozmen E, Ucar A K, Aslan M, Habibi H A, Bakan S, Ozcabi B, Evliyaoğlu S O, Adaletli I

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Аннотация

PURPOSE: The purpose of this study was to assess the diagnostic value of measuring the apparent diffusion coefficient (ADC) of ovarian stroma in polycystic ovary syndrome (PCOS).

MATERIALS AND

METHODS

This study was approved by the institutional review board and informed consent was obtained from each women. A total of 17 women (mean age, 22.2 years±5.1 [SD]; range, 16-33 years) with a diagnosis of PCOS according to the Androgen Excess and PCOS Society criteria and 18 healthy women (mean age, 22.8 years±5.2 [SD]; range, 16-31 years) who served as a control group were included in this prospective study. ADC values of the ovarian stroma during the early follicular phase were calculated by two observers in the two groups. Comparisons were performed using the Student t-test.

RESULTS

The mean ADC value in woman with PCOS (1.29±0.27×10-3 mm2/s; range: 0.59×10-3 - 1.88×10-3 mm2/s) was significantly lower than that in the control group (1.48±0.17×10-3 mm2/s; range: 1.12×10-3 - 1.86×10-3 mm2/s) (P<0.001). The ADC cutoff value for the determination of PCOS with maximum accuracy was 1.38×10-3 mm2/s (AUC: 0.720; 95% CI: 0.597, 0.843), yielding 78% sensitivity and 62.9% specificity.

CONCLUSION

ADC values of ovarian stroma are lower in patients with PCOS than in control subjects. ADC measurement of ovarian stroma in women with PCOS might help improve the diagnosis of PCOS.

Для цитирования: Samanci C, Alis D, Ustabasioglu F E, Ozmen E, Ucar A K, Aslan M, Habibi H A, Bakan S, Ozcabi B, Evliyaoğlu S O, Adaletli I. Apparent diffusion coefficient measurement of ovarian stroma: A potential tool for the diagnosis of polycystic ovary syndrome.. Diagnostic and interventional imaging. 2016. DOI: 10.1016/j.diii.2016.09.004.

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