The magnetic resonance images and maps of bovine ovaries acquired at defined phases of follicular development and regression were studied to determine whether magnetic resonance image attributes of the follicular antrum reflect the physiological status of dominant and subordinate ovarian follicles. Ovariectomies were performed at day 3 of wave one, day 6 of wave one, day 1 of wave two and at >/= day 17 after ovulation. The timings of ovariectomies were selected to acquire growing, early static, late static and regressing follicles of the first wave and preovulatory follicles of the ovulatory wave. Pre-selection and subordinate follicles were also available for analysis. Serum samples were taken on the day of ovariectomy and follicular fluid samples were taken after imaging. Numerical pixel value and pixel heterogeneity in a spot representing approximately 95% of the follicular antrum were quantified in T(1)- and T(2)-weighted images. T(1) and T(2) relaxation rates (T(1) and T(2)), proton density, apparent diffusion coefficients and their heterogeneities were determined from the computed magnetic resonance maps. The antra of early atretic dominant follicles showed higher T(2)-weighted mean pixel value (P < 0.008) and heterogeneity (P < 0. 01) and lower T(2) heterogeneity (P < 0.008) than growing follicles. Subordinate follicles in the presence of a preovulatory dominant follicle had higher T(1), T(1) heterogeneity, proton density, proton density heterogeneity, and lower mean pixel value in T(1)-weighted images than subordinate follicles of the anovulatory wave (P < 0.04). T(1) relaxation rate heterogeneity and proton density heterogeneity were positively correlated with follicular fluid oestradiol concentration (r = 0.4 and 0.3; P < 0.04). T(2) relaxation rate heterogeneity was positively correlated with follicular fluid progesterone concentration (r = 0.4; P < 0.008). Quantitative differences in magnetic resonance image attributes of the antrum observed among phases of follicular development and regression coincided with changes in the ability of the dominant follicle to produce steroid hormones and ovulate, and thus were indicative of physiological status and follicular health.
An automated approach for the optimised estimation of breast density with Dixon methods
