SynthesisJournal of translational medicine2024
Association of radiomic features with genomic signatures in thyroid cancer: a systematic review.
Synthesis in Journal of translational medicine, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
7 citing papers in PubMed.
- Interpretable LightGBM model with SHAP analysis predicts non-excellent response to initial radioiodine therapy in differentiated thyroid carcinoma.Journal of applied clinical medical physics · 2026Article
- Article
- Hypoxia-Inducible Factor 1-α in Autoimmune Diseases-Insights from the Paradigm of Hashimoto's Thyroiditis: A Narrative Review.Medical sciences (Basel, Switzerland) · 2026Review
- Category-ComBat with distribution coefficient: a scale-adaptive harmonization algorithm for multicenter radiomic feature standardization.Frontiers in oncology · 2026Article
- Molecular Diagnostics and Personalized Therapeutics in Differentiated Thyroid Carcinoma: A Clinically Oriented Review.Diagnostics (Basel, Switzerland) · 2025Review
- Cross-regional radiomics: a novel framework for relationship-based feature extraction with validation in Parkinson's disease motor subtyping.BioData mining · 2025Article
- Thyroid Cancer: Epidemiology, Classification, Risk Factors, Diagnostic and Prognostic Markers, and Current Treatment Strategies.International journal of molecular sciences · 2025Review
Corrections and comments
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Authors and funding
7 authors.
Funding
Abstract
backgroundThere is a growing interest on the association of radiomic features with genomic signatures in oncology. Using computational methods, quantitative radiomic data are extracted from various imaging techniques and integrated with genomic information to construct predictive models aimed at advancing diagnostic strategies in cancer patient management. In this context, the aim of this systematic review was to assess the current knowledge on potential application of this association in patients with thyroid cancer (TC).
methodsA comprehensive literature review was conducted by querying three different databases (PubMed, Scopus and Embase) to identify studies published until June 2024, focusing on the potential association of radiomics and genomics in patients with TC. Pertinent data were subsequently extracted, and the methodological quality was evaluated using the A MeaSurement Tool to Assess Systematic Reviews 2 (AMSTAR 2).
resultsFrom the initial analysis, a total of 853 papers were identified. After removing duplicates and applying eligibility criteria, we ultimately evaluated 7 articles. It was observed that the most commonly utilized imaging technique for TC examination was ultrasound (US), followed by computed tomography and magnetic resonance imaging. Regarding genomic techniques, sequencing and polymerase chain reaction were the most commonly employed methods to validate genetic alterations. The association of radiomic features with genomic signatures demonstrated promising performance in predicting metastasis to the cervical lymph nodes or RET/PTC rearrangements. The effectiveness of models based on US-radiomic features in predicting BRAF
conclusionAlthough this systematic review has several limitations, primarily related to the limited amount of available literature data, the association of radiomic features with genomic signatures demonstrates a potential as non-invasive tool to enhance the accuracy and efficacy of TC diagnosis and prognosis. PROSPERO registration number: CRD42024572292.
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