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OBJECTIVE: To study effects of overexposure to androgens and subsequent antiandrogenic treatment on brain activity during working memory processes in women with polycystic ovary syndrome (PCOS).DESIGN: In this longitudinal study, working memory function was evaluated with the use of functional magnetic resonance imaging (MRI) in women with PCOS before and after antiandrogenic treatment.SETTING: Department of reproductive medicine, university medical center.PATIENT(S): Fourteen women with PCOS and with hyperandrogenism and 20 healthy control women without any features of PCOS or other hormonal disorders.INTERVENTION(S): Antiandrogenic hormone treatment.MAIN OUTCOME MEASURE(S): Functional MRI response during a working memory task.RESULT(S): At baseline women with PCOS showed more activation than the control group within the right superior parietal lobe and the inferior parietal lobe during task (all memory conditions). Task performance (speed and accuracy) did not differ between the groups. After antiandrogenic treatment the difference in overall brain activity between the groups disappeared and accuracy in the high memory load condition of the working memory task increased in women with PCOS.CONCLUSION(S): Women with PCOS may need additional neural resources during a working memory task compared with women without PCOS, suggesting less efficient executive functioning. This inefficiency may have effects on daily life functioning of women with PCOS. Antiandrogenic treatment appears to have a beneficial effect on this area of cognitive functioning.CLINICAL TRIAL REGISTRATION NUMBER: NTR2493.

Objective: To investigate the effect of hormonal androgenic treatment on antimullerian hormone (AMH) serum levels in female-to-male (FtM) transsexuals. Polycystic ovary syndrome (PCOS) is associated with elevated AMH levels. Some hypothesize that the high AMH level is a consequence of androgen-induced excessive development of small antral follicles. However, this role of androgens is not yet clear. Design: Observational, prospective, cohort study. Setting: Tertiary academic medical center. Patient(s): Twenty-two FtM transsexuals, healthy native females receiving cross-sex hormone therapy/androgenic treatment. Intervention(s): Androgenic treatment with testosterone (T) and an aromatase inhibitor while endogenous hormone secretion was suppressed with the use of a GnRH agonist. Main Outcome Measure(s): Hormone concentrations were measured before and after androgenic treatment (administration of T and aromatase inhibitor). Measured hormones: AMH, inhibin B, T, androstenedione, DHEAS, E-2, SHBG, LH, and FSH. Result(s): AMH concentrations were significantly lower after androgenic treatment (4.4 +/- 4.4 mg/L vs. 1.4 +/- 2.1 mg/L). Androgenic treatment resulted in a strong suppression of AMH secretion over a relative short period of 16 weeks. Conclusion(s): Our data underscore the likely important role of androgens in the dynamics of folliculogenesis. It challenges the idea that androgens induce high AMH levels, which is gaining more interest nowadays as an important particular PCOS feature. This strong decline furthermore indicates that AMH must be interpreted in the context of other reproductive endocrine conditions. Clinical Trial Registration Number: NTR2493. (C) 2015 by American Society for Reproductive Medicine.

Functional magnetic resonance imaging (fMRI) analysis is usually carried out with standard software packages (e.g., FSL and SPM) implementing the General Linear Model (GLM) computation. Yet, the validity of an analysis may still largely depend on the parameterization of those tools, which has, however, received little attention from researchers. In this paper we study the influence of three of those parameters, namely (i) the size of the spatial smoothing kernel, (ii) the hemodynamic response function delay and (iii) the degrees of freedom of the fMRI-to-anatomical scan registration. In addition, two different values of acquisition parameters (echo times) are compared. The study is performed on a data set of 11 subjects, sweeping a significant range of parameters. It involves almost one CPU year and produces 1.4 Terabytes of data. Thanks to a grid deployment of the FSL FEAT application, this compute and data intensive problem can be handled and the execution time is reduced to less than a week. Results suggest that optimal parameter values for detecting activation in the amygdalae deviate from the default typically adopted in such studies. Moreover, robust results indicate no significant difference between brain activation maps obtained with the two echo times. (C) 2009 Elsevier B.V. All rights reserved