Clinical, Radiologic and Cytologic Predictors of Malignancy in Pediatric Thyroid Nodules: Insights From a 26-Year Cohort Study - Top-Institutions - MDSpire

Predictive Factors for Malignancy in Pediatric Thyroid Nodules: A Comprehensive Analysis from a 26-Year Cohort Study on Clinical, Radiologic, and Cytologic Aspects

  • By

  • Maxime Gest-Laurent

  • Adrien Nguyen Quoc

  • Christine Lefevre

  • Laura González-Briceño

  • Caroline Thalassinos

  • Isabelle Flechtner

  • Dulanjalee Kariyawasam

  • Yamina Dassa

  • Magali Viaud

  • Dinane Samara-Boustani

  • Graziella Pinto

  • Hervé Monpeyssen

  • Sabine Sarnacki

  • Vincent Couloigner

  • Michel Polak

  • Athanasia Stoupa

  • July 6, 2026

Share

Top Institutions in Oncology

Brief introduction explaining scope and methodology.

  • #1

    Necker Children's University Hospital
    Necker Children's University Hospital

    Paris, France

    Key Differentiators

    • Pediatric Endocrinology

  • #2

    Assistance Publique-Hôpitaux de Paris
    Assistance Publique-Hôpitaux de Paris

    Paris, France

    Key Differentiators

    • Pediatric Endocrinology

  • #3

    University Medical Center
    University Medical Center

    Unknown, Unknown

    Key Differentiators

    • Pediatric Endocrinology

  • #4

    University of Pisa
    University of Pisa

    Pisa, Italy

    Key Differentiators

    • Pediatric Endocrinology

Original Source(s)

Clinical, Radiologic and Cytologic Predictors of Malignancy in Pediatric Thyroid Nodules: Insights From a 26-Year Cohort Study

  • by Maxime Gest-Laurent, Adrien Nguyen Quoc, Christine Lefevre, Laura González-Briceño, Caroline Thalassinos, Isabelle Flechtner, Dulanjalee Kariyawasam, Yamina Dassa, Magali Viaud, Dinane Samara-Boustani, Graziella Pinto, Hervé Monpeyssen, Sabine Sarnacki, Vincent Couloigner, Michel Polak, Athanasia Stoupa

  • July 6, 2026

Related Content

Global research landscape and hotspots of paraptosis: a multi-database bibliometric analysis with a focused literature review

Predicting cancer treatment outcomes using machine learning enabled clinical decision support systems

Editorial: Navigating the landscape of IDH-mutant gliomas: advances in diagnosis, therapeutic management, and long-term monitoring