Low iodine intake during pregnancy may cause thyroid dysfunction in pregnant women and their newborn. In the present study, iodine status among a nation-wide representative sample of Belgian pregnant women in the first and third trimester of pregnancy was determined, and determinants of iodine status were assessed 1 year after the introduction of bread fortified with iodised salt. The women were selected according to a multistage proportionate-to-size sampling design. Urine samples were collected and a general questionnaire was completed face to face with the study nurse. The median urinary iodine concentration (UIC) among pregnant women (n 1311) was 124·1 mg/l and 122·6 mg/g creatinine when corrected for urinary creatinine. The median UIC in the first trimester (118·3 mg/l) was significantly lower than that in the third trimester (131·0 mg/l) but significantly higher than among non-pregnant women (84·8 mg/l). Iodine-containing supplement intake was reported by 60·8 % of the women and 57·4 % of the women took this supplement daily. The risk of iodine deficiency was significantly higher in younger women, in women not taking iodine-containing supplements, with low consumption of milk and dairy drinks and during autumn. Women with a higher BMI had a higher risk of iodine deficiency but the risk was lower in women who reported alcohol consumption. The median UIC during pregnancy indicates iodine deficiency in Belgium and some women are at a higher risk of deficiency. The current low iodine intake in women of childbearing age precludes the correction of iodine deficiency in pregnant women supplemented with multivitamins containing 150 mg iodine as recommended.

Fortification of bread with iodized salt corrected iodine deficiency in Belgian children, but not in their mothers. To provide these women with an adequate iodine intake, the use of both iodized salt in bread and iodized instead of noniodized household salt needs to increase. Our findings suggest that the median UIC in children may not be an adequate surrogate of adults' iodine status. Therefore, monitoring iodine status should not be limited to children, but should be extended to women of child-bearing age.

Automated three-dimensional breast ultrasound (ABUS) is a valuable adjunct to x-ray mammography for breast cancer screening of women with dense breasts. High image quality is essential for proper diagnostics and computer-aided detection. We propose an automated image quality assessment system for ABUS images that detects artifacts at the time of acquisition. Therefore, we study three aspects that can corrupt ABUS images: the nipple position relative to the rest of the breast, the shadow caused by the nipple, and the shape of the breast contour on the image. Image processing and machine learning algorithms are combined to detect these artifacts based on 368 clinical ABUS images that have been rated manually by two experienced clinicians. At a specificity of 0.99, 55% of the images that were rated as low quality are detected by the proposed algorithms. The areas under the ROC curves of the single classifiers are 0.99 for the nipple position, 0.84 for the nipple shadow, and 0.89 for the breast contour shape. The proposed algorithms work fast and reliably, which makes them adequate for online evaluation of image quality during acquisition. The presented concept may be extended to further image modalities and quality aspects.

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