Recent Development of Nuclear Molecular Imaging in Thyroid Cancer

Correlation between socioeconomic indices and epidemiological indices of thyroid cancer from 1990 to 2019 year: a global ecologic study

BACKGROUND

The incidence of thyroid cancer as the most common type of endocrine gland malignancy has risen more significantly than any malignancies in recent years. Estimated new cases of thyroid cancer in the United States in 2024 were 12,500 and 31,520 for men and women, respectively, and estimated deaths were 1,180 for women and 990 for men. Indices of socio-economic have been commonly used to measure the development of countries. Therefore, this study aimed to examine the correlation between indices of socioeconomic status and epidemiological indices of thyroid cancer throughout the world. In addition, this study has compared two indices of human development and a socio-demographic index.

METHOD

This worldwide ecological study used data on thyroid cancer incidence, mortality, human development index (HDI), and sociodemographic index (SDI) between 1990 and 2019 from the Global Burden of Disease (GBD). We evaluated the correlation between incidence and mortality rates with socioeconomic indices by using Pearson's correlation coefficient. Furthermore, for the first time, the generalized additive model (GAM) was employed for modeling. The statistical software R, version 4.2.2, was used to conduct all statistical analyses.

RESULTS

The correlation between the incidence of thyroid cancer and the HDI was significant and positive (r = 0.47, p-value < 0.001). While the correlation between thyroid cancer mortality and HDI was not statistically significant (r = 0.01, p-value = 0.076). Besides, the incidence of thyroid cancer was significantly positively correlated with SDI (r = 0.48, p-value < 0.001). The multiple GAM showed that for one unit increase in HDI, the risk of thyroid cancer was increased by 2.1 times (RR = 2.1, 95%CI = 2.04 to 2.19), and for one unit increase in SDI, the risk of thyroid cancer was shown to increase by 2.2 times. (RR = 2.2, 95%CI = 2.19 to 2.35).

CONCLUSION

It has been evident that countries with higher incidence of thyroid cancer display higher socioeconomic indices. While, countries with higher socioeconomic indices, report lower mortality rates. However, based on the modeling results, it can be concluded that the SDI is slightly more useful in this regard. Therefore, examining the epidemiological indices of thyroid cancer by socio-economic indices can be useful to reflect a clear image of the distribution of this cancer in each country, and can be used for planning cancer prevention strategies.

Nuclear Imaging Modalities in the Diagnosis and Management of Thyroid Cancer

In this review we have brought forward various nuclear imaging modalities used in the diagnosis, staging, and management of thyroid cancer. Thyroid cancer is the most common endocrine malignancy, accounting for approximately 3% of all new cancer diagnoses. Nuclear imaging plays an important role in the evaluation of thyroid cancer, and the use of radioiodine imaging, FDG imaging, and somatostatin receptor imaging are all valuable tools in the management of this disease. Radioiodine imaging involves the use of Iodine-123 [I-123] or Iodine-131 [I-131] to evaluate thyroid function and detect thyroid cancer. I-123 is a gamma-emitting isotope that is used in thyroid imaging to evaluate thyroid function and detect thyroid nodules. I-131 is a beta-emitting isotope that is used for the treatment of thyroid cancer. Radioiodine imaging is used to detect the presence of thyroid nodules and evaluate thyroid function. FDG imaging is a PET imaging modality that is used to evaluate the metabolic activity of thyroid cancer cells. FDG is a glucose analogue that is taken up by cells that are metabolically active, such as cancer cells. FDG PET/CT can detect primary thyroid cancer and metastatic disease, including lymph nodes and distant metastases. FDG PET/CT is also used to monitor treatment response and detect the recurrence of thyroid cancer. Somatostatin receptor imaging involves the use of radiolabeled somatostatin analogues to detect neuroendocrine tumors, including thyroid cancer. Radiolabeled somatostatin analogues, such as Indium-111 octreotide or Gallium-68 DOTATATE, are administered to the patient, and a gamma camera is used to detect areas of uptake. Somatostatin receptor imaging is highly sensitive and specific for the detection of metastatic thyroid cancer. A comprehensive search of relevant literature was done using online databases of PubMed, Embase, and Cochrane Library using the keywords "thyroid cancer," "nuclear imaging," "radioiodine imaging," "FDG PET/CT," and "somatostatin receptor imaging" to identify relevant studies to be included in this review. Nuclear imaging plays an important role in the diagnosis, staging, and management of thyroid cancer. The use of radioiodine imaging, thyroglobulin imaging, FDG imaging, and somatostatin receptor imaging are all valuable tools in the evaluation of thyroid cancer. With further research and development, nuclear imaging techniques have the potential to improve the diagnosis and management of thyroid cancer and other endocrine malignancies.

An Artificial Intelligence System for Optimizing Radioactive Iodine Therapy Dosimetry

Thyroid cancer, specifically differentiated thyroid carcinoma (DTC), is one of the most prevalent endocrine malignancies worldwide. Radioactive iodine therapy (RAIT) using I-131 has been a standard-of-care approach for DTC due to its ability to ablate remnant thyroid disease following surgery, thus reducing the risk of recurrence. It is also used for the treatment of iodine-avid metastases. RAIT dosimetry can be employed to determine the optimal treatment dose of I-131 to effectively treat cancer cells while safeguarding against undesirable radiation effects such as bone marrow toxicity or radiation pneumonitis. Conventional dosimetry protocols for RAIT, however, are complex and time-consuming, involving multiple days of imaging and blood sampling. This study explores the use of Artificial Intelligence (AI) in simplifying and optimizing RAIT. A retrospective analysis was conducted on 83 adult patients with DTC who underwent RAIT dosimetry at our institution between 1996 and 2023. The conventional MIRD-based dosimetry protocol involved imaging and blood sampling at 4, 24, 48, 72, and 96 h post-administration of a tracer activity of I-131. An AI system based on a deep-learning neural network was developed to predict the maximum permissible activity (MPA) for RAIT using only the data obtained from the initial 4, 24, and 48 h time points. The AI system predicted the MPA values with high accuracy, showing no significant difference compared to the results obtained from conventional MIRD-based analysis utilizing a paired t-test (p = 0.351, 95% CI). The developed AI system offers the potential to streamline the dosimetry process, reducing the number of imaging and blood sampling sessions while also optimizing resource allocation. Additionally, the AI approach can uncover underlying relationships in data that were previously unknown. Our findings suggest that AI-based dosimetry may be a promising method for patient-specific treatment planning in differentiated thyroid carcinoma, representing a step towards applying precision medicine for thyroid cancer. Further validation and implementation studies are warranted to assess the clinical applicability of the AI system.

Towards an era of precise diagnosis and treatment: Role of novel molecular modification-based imaging and therapy for dedifferentiated thyroid cancer

Dedifferentiated thyroid cancer is the major cause of mortality in thyroid cancer and is difficult to treat. Hence, the essential molecular mechanisms involved in dedifferentiation should be thoroughly investigated. Several studies have explored the biomolecular modifications of dedifferentiated thyroid cancer such as DNA methylation, protein phosphorylation, acetylation, ubiquitination, and glycosylation and the new targets for radiological imaging and therapy in recent years. Novel radionuclide tracers and drugs have shown attractive potential in the early diagnosis and treatment of dedifferentiated thyroid cancer. We summarized the updated molecular mechanisms of dedifferentiation combined with early detection by molecular modification-based imaging to provide more accurate diagnosis and novel therapeutics in the management of dedifferentiated thyroid cancer.

ImmunoPET: Antibody-Based PET Imaging in Solid Tumors

Immuno-positron emission tomography (immunoPET) is a molecular imaging modality combining the high sensitivity of PET with the specific targeting ability of monoclonal antibodies. Various radioimmunotracers have been successfully developed to target a broad spectrum of molecules expressed by malignant cells or tumor microenvironments. Only a few are translated into clinical studies and barely into clinical practices. Some drawbacks include slow radioimmunotracer kinetics, high physiologic uptake in lymphoid organs, and heterogeneous activity in tumoral lesions. Measures are taken to overcome the disadvantages, and new tracers are being developed. In this review, we aim to mention the fundamental components of immunoPET imaging, explore the groundbreaking success achieved using this new technique, and review different radioimmunotracers employed in various solid tumors to elaborate on this relatively new imaging modality.

Personalized Diagnosis in Differentiated Thyroid Cancers by Molecular and Functional Imaging Biomarkers: Present and Future

Personalized diagnosis can save unnecessary thyroid surgeries, in cases of indeterminate thyroid nodules, when clinicians tend to aggressively treat all these patients. Personalized diagnosis benefits from a combination of imagery and molecular biomarkers, as well as artificial intelligence algorithms, which are used more and more in our timeline. Functional imaging diagnosis such as SPECT, PET, or fused images (SPECT/CT, PET/CT, PET/MRI), is exploited at maximum in thyroid nodules, with a long history in the past and a bright future with many suitable radiotracers that could properly contribute to diagnosing malignancy in thyroid nodules. In this way, patients will be spared surgery complications, and apparently more expensive diagnostic workouts will financially compensate each patient and also the healthcare system. In this review we will summarize essential available diagnostic tools for malignant and benignant thyroid nodules, beginning with functional imaging, molecular analysis, and combinations of these two and other future strategies, including AI or NIS targeted gene therapy for thyroid carcinoma diagnosis and treatment as well.

Molecular Imaging of Galectin-1 Expression as a Biomarker of Papillary Thyroid Cancer by Using Peptide-Functionalized Imaging Probes

Thyroid cancers are the most frequent endocrine cancers and their incidence is increasing worldwide. Thyroid nodules occur in over 19–68% of the population, but only 7–15% of them are diagnosed as malignant. Diagnosis relies on a fine needle aspiration biopsy, which is often inconclusive and about 90% of thyroidectomies are performed for benign lesions. Galectin-1 has been proposed as a confident biomarker for the discrimination of malignant from benign nodules. We previously identified by phage display two peptides (P1 and P7) targeting galectin-1, with the goal of developing imaging probes for non-invasive diagnosis of thyroid cancer. The peptides were coupled to ultra-small superparamagnetic particles of iron oxide (USPIO) or to a near-infrared dye (CF770) for non-invasive detection of galectin-1 expression in a mouse model of papillary thyroid cancer (PTC, as the most frequent one) by magnetic resonance imaging and fluorescence lifetime imaging. The imaging probes functionalized with the two peptides presented comparable image enhancement characteristics. However, those coupled to P7 were more favorable, and showed decreased retention by the liver and spleen (known for their galectin-1 expression) and high sensitivity (75%) and specificity (100%) of PTC detection, which confirm the aptitude of this peptide to discriminate human malignant from benign nodules (80% sensitivity, 100% specificity) previously observed by immunohistochemistry.

Cholecystokinin-2 Receptor Targeting with Radiolabeled Peptides: Current Status and Future Directions

A wide variety of radiolabeled peptide analogs for specific targeting of cholecystokinin- 2 receptors (CCK2R) has been developed in the last decades. Peptide probes based on the natural ligands Minigastrin (MG) and Cholecystokinin (CCK) have a high potential for molecular imaging and targeted radiotherapy of different human tumors, such as Medullary Thyroid Carcinoma (MTC) and Small Cell Lung Cancer (SCLC). MG analogs with high persistent uptake in CCK2R expressing tumors have been preferably used for the development of radiolabeled peptide analogs. The clinical translation of CCK2R targeting has been prevented due to high kidney uptake or low metabolic stability of the different radiopeptides developed. Great efforts in radiopharmaceutical development have been undertaken to overcome these limitations. Various modifications in the linear peptide sequence of MG have been introduced mainly with the aim to reduce kidney retention. Furthermore, improved tumor uptake could be obtained by in situ stabilization of the radiopeptide against enzymatic degradation through coinjection of peptidase inhibitors. Recent developments focusing on the stabilization of the Cterminal receptor binding sequence (Trp-Met-Asp-Phe-NH2) have led to new radiolabeled MG analogs with highly improved tumor uptake and tumor-to-kidney ratio. In this review, all the different aspects in the radiopharmaceutical development of CCK2R targeting peptide probes are covered, giving also an overview on the clinical investigations performed so far. The recent development of radiolabeled MG analogs, which are highly stabilized against enzymatic degradation in vivo, promises to have a high impact on the clinical management of patients with CCK2R expressing tumors in the near future.