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Cancers
Special Issues
Updates on Thyroid Cancer
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Updates on Thyroid Cancer

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

Deadline for manuscript submissions: 30 July 2025 | Viewed by 1403

Special Issue Editors

Dr. Kwangsoon Kim

E-Mail Website
Guest Editor
Department of Surgery, College of Medicine, The Catholic University of Korea, Seoul 06591, Republic of Korea
Interests: thyroid; thyroid cancer; surgery
Special Issues, Collections and Topics in MDPI journals
Dr. Ja Seong Bae

E-Mail Website
Guest Editor Assistant
Department of Surgery, College of Medicine, The Catholic University of Korea, Seoul 06591, Republic of Korea
Interests: thyroidectomy; prognosis of thyroid cancer; diagnosis of thyroid cancer

Special Issue Information

Dear Colleagues,

Thyroid cancer remains a dynamic field, with ongoing research contributing to significant advancements in our understanding, diagnosis, and treatment of this disease. This Special Issue aims to gather the latest findings and perspectives from leading experts in the field, focusing on key updates and novel approaches in thyroid cancer research. We welcome original research articles, comprehensive reviews, and insightful case studies that explore the epidemiology, molecular biology, innovative diagnostic techniques, and cutting-edge therapeutic strategies for thyroid cancer. Special emphasis will be placed on emerging trends such as personalized medicine, targeted therapies, and the role of artificial intelligence in improving patient outcomes. By compiling this collection, we aim to provide a valuable resource for clinicians, researchers, and healthcare professionals, offering a comprehensive overview of the current state of thyroid cancer research and future directions in this field.

Dr. Kwangsoo Kim
Dr. Ja Seong Bae
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Cancers is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2900 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • thyroid cancer
  • surgery
  • updates
  • diagnosis
  • molecular biology
  • personalized medicine
  • artificial intelligence
  • novel therapeutic strategies
  • patient outcomes

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Published Papers (2 papers)

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Research

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10 pages, 3811 KiB  
Article
Zirconia Implants Indicated Better Stability After Exposure to Radioiodine-131 Therapy Used for Differentiated Thyroid Cancer
by Alexandru Mester, Doina Piciu, Marioara Moldovan, Codruta Sarosi, Stanca Cuc, Ioan Petean, Cristina Moisescu-Pop, Andra Piciu, Florin Onisor and Simion Bran
Cancers 2025, 17(4), 678; https://doi.org/10.3390/cancers17040678 - 17 Feb 2025
Viewed by 545
Abstract
Background: Advancements in therapeutic approaches and standard medical interventions have significantly improved the prognosis of patients with differentiated thyroid cancer. However, uncertainties remain regarding the optimal timing and protocols for dental implant placement in patients undergoing radioiodine-131 (I-131) therapy. Debates continue about the [...] Read more.
Background: Advancements in therapeutic approaches and standard medical interventions have significantly improved the prognosis of patients with differentiated thyroid cancer. However, uncertainties remain regarding the optimal timing and protocols for dental implant placement in patients undergoing radioiodine-131 (I-131) therapy. Debates continue about the potential effects of radiation on osseointegration dynamics and implant viability. This in vitro study assessed the impact of radiodiodine-131 (I-131) used for differentiated thyroid cancer on the structure of zirconia and titanium implants. Methods: A total of 60 implants were utilized, with distribution into two cohorts: titanium implants (Ti, n = 30) and zirconia implants (Zr, n = 30). Subsequently, the Ti and Zr implants were immersed in I-131 solution and retrieved at specified time intervals: 0, 6, 12, 24, 48 h, and 8 days post irradiation. The analyses used to characterize the structure of the implants were radioactivity, scanning electron microscopy, atomic force microscopy, roughness, and Vickers hardness assessment. Results: The findings indicate that the zirconia implants exhibited minimal ultra-structural topographic changes after irradiation. Notable topographical changes and debris deposition on zirconia surfaces became evident after 24 h, with cumulative effects observed after 192 h. The titanium implants, on the other hand, showed surface alterations beginning at 12 h of exposure. Significant changes, including erosive patterns and substantial debris deposits, occurred after 48 and 192 h, leading to increased surface roughness by 24 h. Implants exposed for 12 and 24 h formed a statistically significant group, indicating the onset of surface alteration accumulation. The erosion debris confirmed the surface alterations induced by radioiodine-131 exposure. Conclusions: Overall, the Zr implants demonstrated greater stability compared to the Ti implants following radioiodine-131 exposure. Full article
(This article belongs to the Special Issue Updates on Thyroid Cancer)
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Review

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27 pages, 7733 KiB  
Review
Machine Learning for Thyroid Cancer Detection, Presence of Metastasis, and Recurrence Predictions—A Scoping Review
by Irina-Oana Lixandru-Petre, Alexandru Dima, Madalina Musat, Mihai Dascalu, Gratiela Gradisteanu Pircalabioru, Florina Silvia Iliescu and Ciprian Iliescu
Cancers 2025, 17(8), 1308; https://doi.org/10.3390/cancers17081308 - 12 Apr 2025
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Abstract
Thyroid Cancer (TC) is one of the most prevalent endocrine malignancies, with early detection being critical for patient management. The motivation for integrating Machine Learning (ML) in thyroid cancer research stems from the limitations of conventional diagnostic and monitoring approaches, as ML offers [...] Read more.
Thyroid Cancer (TC) is one of the most prevalent endocrine malignancies, with early detection being critical for patient management. The motivation for integrating Machine Learning (ML) in thyroid cancer research stems from the limitations of conventional diagnostic and monitoring approaches, as ML offers transformative potential for reducing human errors and improving prediction outcomes for diagnostic accuracy, risk stratification, treatment options, recurrence prognosis, and patient quality of life. This scoping review maps existing literature on ML applications in TC, particularly those leveraging clinical data, Electronic Medical Records (EMRs), and synthesized findings. This study analyzed 1231 papers, evaluated 203 full-text articles, selected 21 articles, and detailed three themes: (1) malignancy prediction and nodule classification; (2) other metastases derived from TC prediction; and (3) recurrence and survival prediction. This work examined the case studies’ characteristics and objectives and identified key trends and challenges in ML-driven TC research. Finally, this scoping review addressed the limitations of related and highlighted directions to enhance the clinical potential of ML in this domain while emphasizing its capability to transform TC patient care into advanced precision medicine. Full article
(This article belongs to the Special Issue Updates on Thyroid Cancer)
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