Conventional and Emerging Diagnostic Approaches for Differentiated Thyroid Carcinoma

被引:2
|
作者
Kristollari, Kathelina [1 ]
Paul, Abraham Abbey [1 ]
Angel, Sagi [2 ]
Marks, Robert S. [1 ,3 ]
机构
[1] Bengurion Univ Negev, Avram & Stella Goldstein Goren Dept Biotechnol Eng, IL-84105 Beer Sheva, Israel
[2] Picodya Technol Ltd, IL-7670402 Rehovot, Israel
[3] Bengurion Univ Negev, Ilse Katz Ctr Nanoscale Sci & Technol, IL-84105 Beer Sheva, Israel
关键词
differentiated thyroid carcinoma; diagnostics; biomarkers; point-of-care testing; FINE-NEEDLE-ASPIRATION; MANAGEMENT GUIDELINES; MUTATION ANALYSIS; LC-MS/MS; CANCER; IMMUNOHISTOCHEMISTRY; CALCITONIN; FNA; BIOSENSORS; ACCURACY;
D O I
10.3390/chemosensors12110229
中图分类号
O65 [分析化学];
学科分类号
070302 ; 081704 ;
摘要
Differentiated thyroid carcinoma (DTC) is among the most prevalent endocrine cancers. The diagnosis of DTC has witnessed tremendous progress in terms of technological advancement and clinical operational guidelines. DTC diagnostics have evolved significantly over centuries, from early clinical examinations to modern molecular testing and imaging modalities. The diagnosis and management of DTC are currently dependent on the international histological classification and identification of specific genetic abnormalities in tumor tissue, as well as the prognostic implications that can inform treatment decisions. This study goes down the memory lanes of various diagnostic methods for DTCs, highlighting recent advancements in molecular testing and point-of-care (POC) technology. Beginning with conventional methods like fine needle aspiration biopsy (FNAB), fine needle aspiration cytology (FNAC), and ultrasound (US) and moving to contemporary innovative approaches such as POC-thyroglobulin (POC-Tg) and liquid biopsy, this review showcases the current trends in DTC diagnostics. Although considerable progress has been achieved in early malignancy detection, patient stratification, prognosis, and personalized treatment, there is a need to refine the mainstay diagnostic procedures. Finally, future perspectives were provided, and emerging roles of artificial intelligence in DTC diagnostics were explored.
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页数:33
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