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The Changing Paradigms in the Management of Thyroid Cancer

A special issue of Cancers (ISSN 2072-6694). This special issue belongs to the section "Cancer Therapy".

Deadline for manuscript submissions: closed (30 April 2026) | Viewed by 1060

Special Issue Editor


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Guest Editor
Unit of Endocrinology, Department of Clinical and Experimental Medicine, University of Pisa, 56124 Pisa, Italy
Interests: thyroid cancer; endocrine surgery; clinical endocrinology; nuclear medicine; cancer surgery; molecular endocrinology; surgical oncology; clinical trials

Special Issue Information

Dear Colleagues,

In recent years, our understanding of thyroid cancer—including the differentiated, anaplastic, and medullary subtypes—has significantly advanced, largely due to discoveries regarding the molecular mechanisms driving tumor development, proliferation, and survival. Simultaneously, thyroid cancer incidence has risen, prompting a shift toward personalized treatment approaches rather than a standardized strategy.

Active surveillance is increasingly being recognized as a viable option for managing low-risk differentiated thyroid cancers, alongside less invasive surgical techniques and selective radioiodine use. Meanwhile, new and highly selective targeted therapies are offering new hope for patients with aggressive thyroid cancers, including metastatic and anaplastic cases.

This Special Issue will explore the evolving treatment landscape, highlighting innovative therapeutic strategies that are shaping current clinical practices, as well as future treatment paradigms.

Dr. Antonio M. Matrone
Guest Editor

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Keywords

  • thyroid cancer
  • targeted therapies
  • minimally invasive surgery
  • selective radioiodine use
  • personalized treatment

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Published Papers (1 paper)

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Review

18 pages, 692 KB  
Review
From Pixels to Prediction: Developing Integrated AI Foundation Models for Personalized Thyroid Cancer Care
by Jae Hyun Park, Younghyun Park, Yong Moon Lee, Sejung Yang and Jong Ho Yoon
Cancers 2026, 18(7), 1155; https://doi.org/10.3390/cancers18071155 - 3 Apr 2026
Viewed by 650
Abstract
Background: Thyroid cancer incidence continues to rise globally, yet current diagnostic methods, reliant on ultrasound-guided fine-needle aspiration, suffer from substantial inter-observer variability and indeterminate results. Objective: This review explores the transformative potential of integrated artificial intelligence (AI) foundation models in thyroid [...] Read more.
Background: Thyroid cancer incidence continues to rise globally, yet current diagnostic methods, reliant on ultrasound-guided fine-needle aspiration, suffer from substantial inter-observer variability and indeterminate results. Objective: This review explores the transformative potential of integrated artificial intelligence (AI) foundation models in thyroid cancer management. We propose a paradigm shift using foundation models—large-scale, multimodal architectures pre-trained on diverse datasets—to bridge the gap between initial pixels and long-term prognostic prediction. Proposed Models: We introduce two integrated conceptual frameworks: ThyroSight-Prognos for high-precision assessment in specialized tertiary settings and SonoPredict-AI for cost-effective screening in primary care. Key Innovations: By synthesizing data from ultrasound, pathology (WSI), genomics, and clinical parameters through explainable AI (XAI), these models aim to reduce unnecessary surgeries and personalize treatment pathways. Challenges and Outlook: This paper addresses critical implementation challenges, including data heterogeneity, hardware requirements, and regulatory trust, ultimately providing a strategic blueprint for future multi-center prospective clinical validation to revolutionize thyroid care through precision oncology. Full article
(This article belongs to the Special Issue The Changing Paradigms in the Management of Thyroid Cancer)
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