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Diagnostics
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Innovations in Thyroid Nodule and Cancer Diagnostics
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Innovations in Thyroid Nodule and Cancer Diagnostics

A special issue of Diagnostics (ISSN 2075-4418). This special issue belongs to the section "Clinical Diagnosis and Prognosis".

Deadline for manuscript submissions: 30 June 2026 | Viewed by 864

Editor

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

Special Issue Information

Dear Colleagues,

The diagnosis and management of thyroid nodules and cancer are rapidly evolving, driven by breakthroughs in imaging, molecular profiling, and artificial intelligence. This Special Issue, ‘Innovations in Thyroid Nodule and Cancer Diagnostics,’ aims to curate cutting-edge research and reviews that highlight these transformative advancements. We welcome contributions that explore novel ultrasound techniques, the integration of AI in diagnostic workflows, and refined risk stratification systems. By synthesizing the latest developments, this collection seeks to improve diagnostic accuracy, personalize patient care, and outline future directions in the field.

Dr. Kwangsoon Kim
Guest Editor

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 short communications are invited. For planned papers, a title and short abstract (about 250 words) can be sent to the Editorial Office for assessment.

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-anonymized peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Diagnostics 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 2600 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 nodule
  • thyroid cancer
  • diagnostic imaging
  • molecular diagnostics
  • ultrasound elastography
  • Fine-Needle Aspiration (FNA)
  • artificial intelligence
  • risk stratification
  • personalized medicine

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Published Papers (2 papers)

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Research

17 pages, 3523 KB  
Article
Interpretable SVM-Based Integrated Ultrasound Model for Preoperative Thyroid Nodule Subtype Classification: Improved Identification of Follicular Variant Papillary Thyroid Carcinoma
by Ran Zheng, Zhen Wang, Yongxin Li, Yuanqing Zhang and Fang Nie
Diagnostics 2026, 16(13), 1950; https://doi.org/10.3390/diagnostics16131950 (registering DOI) - 23 Jun 2026
Abstract
Background/Objectives: Preoperative differentiation among benign thyroid nodules, follicular variant papillary thyroid carcinoma (FV-PTC), and classical papillary thyroid carcinoma (C-PTC) remains clinically challenging. FV-PTC is particularly difficult to identify due to its substantial sonographic and cytological overlap with both benign nodules and other [...] Read more.
Background/Objectives: Preoperative differentiation among benign thyroid nodules, follicular variant papillary thyroid carcinoma (FV-PTC), and classical papillary thyroid carcinoma (C-PTC) remains clinically challenging. FV-PTC is particularly difficult to identify due to its substantial sonographic and cytological overlap with both benign nodules and other malignant subtypes, frequently resulting in overtreatment or delayed diagnosis. This study aimed to develop and validate an interpretable multimodal model for accurate three-class discrimination using routine ultrasound images, with a specific focus on improving the preoperative identification of FV-PTC. Methods: This retrospective study included 479 pathologically confirmed thyroid nodules from 462 patients. Conventional ultrasound features and radiomics features extracted from grayscale ultrasound and color Doppler flow imaging were used to construct three predictive models: a Conventional Ultrasound model (conventional ultrasound features only), a Radiomics model (radiomics features only), and an Integrated model (combined features). Each model was trained using four machine learning classifiers. Model performance was evaluated using the area under the receiver operating characteristic curve (AUC), accuracy, sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), and F1 score. Model interpretability was assessed using SHapley Additive exPlanations (SHAP) analysis, and clinical usefulness was evaluated using decision curve analysis (DCA). Results: The support vector machine (SVM)-based Integrated Model achieved the best overall performance. In the independent testing cohort, the AUCs were 0.853 for FV-PTC, 0.882 for C-PTC and 0.928 for benign nodules. The Integrated Model showed the greatest improvement for FV-PTC, with a ΔAUC of 0.141 compared with the Conventional Ultrasound Model. SHAP (SHapley Additive exPlanations) analysis identified wavelet-HL_gldm_Dependence and wavelet-HH_glcm_InverseVariance as the two most important radiomics predictors in both the Radiomics Model and the Integrated Model, demonstrating robust cross-model stability and high discriminative power. Conclusions: The SVM-based Integrated Model demonstrated promising performance for three-class classification of thyroid nodules and enhanced the preoperative identification of FV-PTC. This approach may provide an interpretable and noninvasive decision-support tool for refining subtype-specific risk stratification and supporting individualized clinical management. Full article
(This article belongs to the Special Issue Innovations in Thyroid Nodule and Cancer Diagnostics)
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12 pages, 546 KB  
Article
Clinical Impact of Multifocality and Bilaterality on Lymph Node Metastasis in Papillary Thyroid Microcarcinoma
by Merima Goran, Marko Buta, Srdjan Nikolic, Nada Santrac, Nikola Jeftic, Nevena Savkovic, Jovan Raketic, Zoran Kozomara, Natasa Medic-Milijic, Ana Cvetkovic, Saska Pavlovic and Ivan Markovic
Diagnostics 2026, 16(2), 208; https://doi.org/10.3390/diagnostics16020208 - 9 Jan 2026
Viewed by 576
Abstract
Objective: Papillary thyroid microcarcinoma (PTMC) often presents with multifocality and bilaterality, but the clinical significance of these features and their association with cervical lymph node metastases (LNMs) remain debated. The aim of this study was to investigate the patterns of multifocality and bilaterality [...] Read more.
Objective: Papillary thyroid microcarcinoma (PTMC) often presents with multifocality and bilaterality, but the clinical significance of these features and their association with cervical lymph node metastases (LNMs) remain debated. The aim of this study was to investigate the patterns of multifocality and bilaterality in PTMC and their association with central and lateral neck lymph node metastases. Methods: This retrospective study analyzed 254 patients with histologically confirmed PTMC treated at the Institute for Oncology and Radiology of Serbia between 2004 and 2016. All patients underwent total thyroidectomy with central and, when indicated, lateral neck dissection. Associations between multifocality, bilaterality, and cervical LNM were evaluated using appropriate statistical tests. A p-value < 0.05 was considered statistically significant. Results: Multifocal tumors were present in 40.55% of patients, with bilateral involvement in 27.17%. Cervical LNM occurred in 33.07% of patients, with 26.77% showing central and 20.08% lateral metastases. Patients with multifocal tumors were associated with significantly higher proportions of male patients (p = 0.0283), higher rates of capsular invasion (p = 0.0002), larger tumor size (p = 0.0134), and increased incidence of LNM (p = 0.0152). Bilateral tumors were associated with larger tumor size (p = 0.0004) and more frequent capsular invasion (p = 0.0248), but not with a statistically significant increase in LNM. The number of tumor foci was strongly associated with both central and lateral LNM (p < 0.001). Conclusions: Multifocality, particularly with a higher number of tumor foci, is significantly associated with more aggressive tumor features and higher rates of cervical lymph node metastases in PTMC. While bilaterality also reflects a more aggressive phenotype, it was not independently predictive of LNM. These findings underscore the importance of careful risk stratification in PTMC and suggest that multifocality should inform surgical and follow-up strategies. Full article
(This article belongs to the Special Issue Innovations in Thyroid Nodule and Cancer Diagnostics)
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