Computer-aided diagnosis through medical image retrieval in radiology.

Currently, radiologists face an excessive workload, which leads to high levels of fatigue, and consequently, to undesired diagnosis mistakes. Decision support systems can be used to prioritize and help radiologists making quicker decisions. In this sense, medical content-based image retrieval systems can be of extreme utility by providing well-curated similar examples. Nonetheless, most medical content-based image retrieval systems work by finding the most similar image, which is not equivalent to finding the most similar image in terms of disease and its severity. Here, we propose an interpretability-driven and an attention-driven medical image retrieval system. We conducted experiments in a large and publicly available dataset of chest radiographs with structured labels derived from free-text radiology reports (MIMIC-CXR-JPG). We evaluated the methods on two common conditions: pleural effusion and (potential) pneumonia. As ground-truth to perform the evaluation, query/test and catalogue images were classified and ordered by an experienced board-certified radiologist. For a profound and complete evaluation, additional radiologists also provided their rankings, which allowed us to infer inter-rater variability, and yield qualitative performance levels. Based on our ground-truth ranking, we also quantitatively evaluated the proposed approaches by computing the normalized Discounted Cumulative Gain (nDCG). We found that the Interpretability-guided approach outperforms the other state-of-the-art approaches and shows the best agreement with the most experienced radiologist. Furthermore, its performance lies within the observed inter-rater variability.

Thyroid hormones and the metabolic syndrome.

BACKGROUND: Clustering of various metabolic parameters including abdominal obesity, hyperglycaemia, low high-density lipoprotein cholesterol, elevated triglycerides and hypertension have been used worldwide as metabolic syndrome to predict cardiometabolic risk. Thyroid dysfunction impacts on various levels of these components. OBJECTIVES: The purpose of the present review is to summarize available data on thyroid hormone-dependent action on components of the metabolic syndrome. METHODS: A PubMed search for any combination of hyperthyroidism, thyrotoxicosis or hypothyroidism and metabolic syndrome, blood pressure, hypertension, hyperlipidaemia, cholesterol, high-density lipoprotein cholesterol, glucose, diabetes mellitus, body weight or visceral fat was performed. We included papers and reviews published between 2000 and today but accepted also frequently cited papers before 2000. RESULTS: There is convincing evidence for a major impact of thyroid function on all components of the metabolic syndrome, reflecting profound alterations of energy homeostasis at many levels. CONCLUSION: Even though the interactions shown in animal models and man are complex, it is evident that insulin sensitivity is highest and adverse thyroid effects on the metabolic system are lowest in euthyroid conditions.