The EANM guideline on radioiodine therapy of benign thyroid disease

Factors affecting timing of hypothyroidism following radioactive iodine therapy (RAIT) for patients with Graves' disease: A 12-month observational study

BACKGROUND

This retrospective study analyzed factors influencing hypothyroidism development after radioactive iodine therapy for Graves' disease.

PATIENTS AND METHODS

Three hundred and three patients with Graves' disease treated with radioactive iodine (RAI) from 2013 to 2022 at two Egyptian hospitals were included. Data collected included demographics, lab values, thyroid imaging, RAI doses, and outcomes. Patients were followed for ≥1 year to assess hypothyroidism onset.

RESULTS

At the end of 1 year, around 79.5% of the individuals developed hypothyroidism while 12.5% continued to experience hyperthyroidism. The onset of hypothyroidism occurred earlier in those with thyroid volume (≤75.5 cm 3 ), lower thyroid weight (≤84.7 g), thyroid uptake (≤18.8%), and higher RAI dose/volume (≥0.1022 mCi/ml) ( P  < 0.001). Additionally, there was a correlation between anti-thyroid peroxidase (anti-TPO) antibodies and faster development of hypothyroidism compared to those who were negative for antibodies (2.9 vs 8.9 months, P  = 0.001). When considering factors in analysis it was found that anti-TPO antibodies were the only independent predictor, for developing hypothyroidism (hazard risk 30.47, P  < 0.001). Additionally, thyroid volume and uptake independently predicted successful treatment outcomes ( P  < 0.05).

CONCLUSION

Positive anti-TPO antibodies strongly predict hypothyroidism risk after RAI therapy for Graves' disease. Smaller thyroid size, lower uptake, and higher RAI dose/volume correlate with earlier hypothyroidism onset but are less significant predictors than anti-TPO status. Findings can guide RAI therapy personalization to optimize outcomes.

Correlation between the thyroid computed tomography value and thyroid function in hyperthyroidism: a retrospective study

OBJECTIVE

Radioiodine (I-131) therapy for hyperthyroidism is a well-established and safe treatment option. This study aimed to investigate the relationship between the computed tomography (CT) value and the function and volume of the thyroid gland by identifying the factors that induce changes in the CT value of patients with hyperthyroidism.

METHODS

This retrospective study evaluated 38 patients with Graves' disease and 10 patients with Plummer disease. To obtain the mean CT value and volume of the thyroid gland, the entire thyroid gland was set as the region of interest. A test dose of 3.7 MBq I-131 was administered before initiating I-131 therapy, and the radioiodine uptake (RIU) rate was assessed after 3, 24, 96, and 168 h. An approximate curve was plotted based on the RIU values obtained, and the effective half-life (EHL) was calculated. The correlation between the mean CT value and the volume of the thyroid gland, 24-h RIU, EHL, and the free triiodothyronine (FT3), free thyroxine (FT4), thyroid-stimulating hormone (TSH), and TSH receptor antibody (TRAb) levels was evaluated.

RESULTS

The CT value exhibited a significant positive correlation with EHL in patients with Graves' disease (r = 0.62, p < 0.0001) as well as patients with Plummer disease (r = 0.74, p < 0.05). However, it did not display any correlation with the remaining parameters.

CONCLUSION

The CT value is significantly correlated with EHL, suggesting that it reflects thyroid function and is mainly related to the factors associated with iodine discharge.

Autoimmune Thyroid Diseases

Autoimmune thyroid diseases (AITDs) include a wide spectrum of thyroid diseases affecting more commonly women than men. The most frequent forms are Graves' Disease (GD) and Hashimoto's thyroiditis / Autoimmune Thyroiditis (AIT), but there are also other immunogenic destructive forms of thyroiditis, that is, silent and postpartum thyroiditis. In the last decade, AITDs and other inflammatory thyroid diseases related to anti-tumor molecular drugs are more frequently seen due to the widespread use of tyrosine kinase inhibitors (TKIs) and immune checkpoint inhibitors (ICPIs). Autoimmune thyroiditis related to SARS-CoV-2 infection has been a novel entity in recent years. Graves' Disease and AIT may shift from hyperthyroidism to hypothyroidism, which may complicate the differential diagnosis and further treatment strategy. Moreover, all AITDs may manifest with thyrotoxicosis (a clinical condition marked with high serum levels of thyroid hormones) which has to be distinguished from hyperthyroidism (increased thyroid hormone production and secretion as a result of hyperfunctioning thyroid gland) due to different therapeutic approaches. Nuclear medicine techniques, such as radioiodine uptake (RAIU) and thyroid scintigraphy, using 99mTc- pertechnetate (Na[99mTc]TcO4) or 123-Iodine (Na[123I]I), have a crucial role in the differential diagnosis. Measurement of thyroid antibodies, e.g. thyroid peroxidase antibodies (TPO) and thyrotropin receptor antibodies (TRAb), as well as thyroid ultrasound, are complementary methods in the evaluation of thyroid disorders.

Artificial Intelligence-powered automatic volume calculation in medical images - available tools, performance and challenges for nuclear medicine

Volumetry is crucial in oncology and endocrinology, for diagnosis, treatment planning, and evaluating response to therapy for several diseases. The integration of Artificial Intelligence (AI) and Deep Learning (DL) has significantly accelerated the automatization of volumetric calculations, enhancing accuracy and reducing variability and labor. In this review, we show that a high correlation has been observed between Machine Learning (ML) methods and expert assessments in tumor volumetry; Yet, it is recognized as more challenging than organ volumetry. Liver volumetry has shown progression in accuracy with a decrease in error. If a relative error below 10 % is acceptable, ML-based liver volumetry can be considered reliable for standardized imaging protocols if used in patients without major anomalies. Similarly, ML-supported automatic kidney volumetry has also shown consistency and reliability in volumetric calculations. In contrast, AI-supported thyroid volumetry has not been extensively developed, despite initial works in 3D ultrasound showing promising results in terms of accuracy and reproducibility. Despite the advancements presented in the reviewed literature, the lack of standardization limits the generalizability of ML methods across diverse scenarios. The domain gap, i. e., the difference in probability distribution of training and inference data, is of paramount importance before clinical deployment of AI, to maintain accuracy and reliability in patient care. The increasing availability of improved segmentation tools is expected to further incorporate AI methods into routine workflows where volumetry will play a more prominent role in radionuclide therapy planning and quantitative follow-up of disease evolution.