Clinical characteristics associated with the finding of thyroid cancer originating from hot nodules in patients with hyperthyroidism: a case report and systematic review of the literature

Coexistence between thyroid cancer and hyperthyroidism is rare, and most of the nodular lesions from which a malignant tumor is documented in this group of patients correspond to cold nodules. Justified by the increasing number of reports in the literature about malignant tumors diagnosed from hot nodules, a systematic review was carried out to determine possible factors associated with the diagnosis of thyroid cancer from hot nodules in patients with hyperthyroidism. The results suggest that the clinical diagnosis of toxic nodular goiter, nodular lesions of diameter > 10 mm and a histological type compatible with a follicular carcinoma, are factors that on their own increase the risk of making the diagnosis of cancer from a hot nodule.

Thyroid cancer in persons as a result of the Chernobyl accident

This study analyzed the sex and age characteristics of the incidence of thyroid cancer between residents of contaminated and not contaminated by the iodine-131 districts of Belarus in whom thyroid cancer was registered from 1986 to 2016. The analysis was carried out according to the data of the Belarusian Cancer Register and was focused on the age groups of 0-4, 5-9, 10-14, and 15-18 years old as of April 1986, i.e. at the time of the Chernobyl accident. The control group of patients was taken from the Lepel district of the Vitebsk region, which was not contaminated with iodine isotopes . The shortest latency period until the onset of the disease (16 years) was found for the 0-4 years old group. There are no significant gender differences in latency time and the age of diagnosis of thyroid cancer. In general, the incidence rates of thyroid cancer in the Brest region are higher than in the Vitebsk region, where there was practically no radioactive fallout of iodine-131. Comparison of the incidence in the Brest region with the nationwide one showed its decrease in 2006-2010, that can be explained by different latency periods of different age groups and the characteristics of radiation exposure. The data obtained supports the hypothesis of the radiation-induced nature of thyroid cancer due to the exposure of the population to radioactive iodine in April 1986.

A Systematic Review on the Role of Artificial Intelligence in Sonographic Diagnosis of Thyroid Cancer: Past, Present and Future

Thyroid cancer is common worldwide with a rapid increase in prevalence across North America in recent years. While most patients present with palpable nodules through physical examination, a large number of small and medium-sized nodules are detected by ultrasound examination. Suspicious nodules are then sent for biopsy through fine needle aspiration to determine whether the nodule is malignant. Since biopsies are invasive and sometimes inconclusive, various research groups have tried to develop computer-aided diagnosis systems aimed at characterizing thyroid nodules based on ultrasound scans. Earlier approaches along these lines relied on clinically relevant features that were manually identified by radiologists. With the recent success of Artificial Intelligence (AI), various new methods using deep learning are being developed to identify these features in thyroid ultrasound automatically. In this paper, we present a systematic review of state-of-the-art on Artificial Intelligence (AI) application in sonographic diagnosis of thyroid cancer. This review follows a methodology-based classification of the different techniques available for thyroid cancer diagnosis, from methods using feature-based models to the most recent deep learning-based approaches. In this review, we reflect on the trends and challenges of the field of sonographic diagnosis of thyroid malignancies and potential of computer-aided diagnosis to increase the impact of ultrasound applications on the future of thyroid cancer diagnosis. Machine learning will continue to play a fundamental role in the development of future thyroid cancer diagnosis frameworks.