Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Concept Videos

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

Toronto Staging Guidelines for Wilms Tumour: The Meeting Point Between Clinicians and Epidemiologists-Results of the BENCHISTA-ITA Project.

Cancers·2026
Same author

Frequency and Prognostic Significance of Genetic Abnormalities in a Subgroup of Patients With Intermediate-Risk Neuroblastoma: A SIOPEN Study.

JCO precision oncology·2026
Same author

Pycnodysostosis: Report of Two Novel CTSK Variants in a Child.

Clinics and practice·2026
Same author

When Platelet Stimulation Becomes Marrow Stress: Rethinking Thrombopoietin Receptor Agonist Intensification in Pediatric Immune Thrombocytopenia.

Pediatric reports·2026
Same author

Expanding the scope of PI3K-δ inhibition: Leniolisib treatment in PRKCD deficiency.

Journal of human immunity·2026
Same author

Long-Term Persistence of Hepatitis A Virus Immunity in Healthcare Workers Upto 25 Years After Vaccination.

Journal of viral hepatitis·2026

Related Experiment Video

Updated: May 5, 2026

Whole-body PET/MRI of Pediatric Patients: The Details That Matter
10:02

Whole-body PET/MRI of Pediatric Patients: The Details That Matter

Published on: December 19, 2017

14.8K

Feasibility of T2-Weighted MRI Radiomics for Initial Risk Stratification in Pediatric Neuroblastoma.

Annalisa Tondo1, Irene Ferri1, Mattia Biavati1

  • 1Oncology, Hematology, and Stem Cell Transplantation, Meyer Children's Hospital IRCCS, 50139 Florence, Italy.

Children (Basel, Switzerland)
|May 4, 2026
PubMed
Summary

Magnetic resonance imaging (MRI)-based radiomics from T2-weighted scans show promise for noninvasively stratifying risk in pediatric neuroblastoma (NB). This approach could aid early diagnosis without contrast agents or advanced sequences.

Keywords:
imaging biomarkersmachine learningmagnetic resonance imagingneuroblastomapediatric oncologyradiomicsrisk stratification

More Related Videos

Magnetic Resonance Imaging Assessment of Carcinogen-induced Murine Bladder Tumors
05:19

Magnetic Resonance Imaging Assessment of Carcinogen-induced Murine Bladder Tumors

Published on: March 29, 2019

9.8K
Assessment of Chimeric Antigen Receptor T Cell-Associated Toxicities Using an Acute Lymphoblastic Leukemia Patient-Derived Xenograft Mouse Model
06:08

Assessment of Chimeric Antigen Receptor T Cell-Associated Toxicities Using an Acute Lymphoblastic Leukemia Patient-Derived Xenograft Mouse Model

Published on: February 10, 2023

1.9K

Related Experiment Videos

Last Updated: May 5, 2026

Whole-body PET/MRI of Pediatric Patients: The Details That Matter
10:02

Whole-body PET/MRI of Pediatric Patients: The Details That Matter

Published on: December 19, 2017

14.8K
Magnetic Resonance Imaging Assessment of Carcinogen-induced Murine Bladder Tumors
05:19

Magnetic Resonance Imaging Assessment of Carcinogen-induced Murine Bladder Tumors

Published on: March 29, 2019

9.8K
Assessment of Chimeric Antigen Receptor T Cell-Associated Toxicities Using an Acute Lymphoblastic Leukemia Patient-Derived Xenograft Mouse Model
06:08

Assessment of Chimeric Antigen Receptor T Cell-Associated Toxicities Using an Acute Lymphoblastic Leukemia Patient-Derived Xenograft Mouse Model

Published on: February 10, 2023

1.9K

Area of Science:

  • Radiology
  • Oncology
  • Medical Imaging

Background:

  • Pediatric neuroblastoma (NB) requires accurate initial risk stratification for effective treatment planning.
  • Current classification systems rely on clinical and molecular data, with a need for noninvasive adjuncts.

Purpose of the Study:

  • To assess the feasibility of T2-weighted MRI radiomics for initial risk stratification in pediatric neuroblastoma.
  • To explore radiomics as a noninvasive tool complementing existing NB classification systems.

Main Methods:

  • Retrospective analysis of 45 pediatric NB cases using T2-weighted MRI.
  • Extraction of 107 IBSI-compliant radiomic features from segmented tumors.
  • Evaluation of machine learning classifiers (Random Forest, XGBoost) and dimensionality reduction (PCA, LDA) with K-means clustering.

Main Results:

  • Radiomic classification achieved 77.8% test accuracy, agreeing with conventional risk stratification in 77.8% of cases.
  • Linear Discriminant Analysis (LDA) with K-means clustering yielded the highest performance (77.8% accuracy, 64.7% sensitivity, 85.7% specificity).
  • The method utilized only routine T2-weighted MRI, demonstrating workflow feasibility without contrast agents.

Conclusions:

  • T2-weighted MRI radiomics is a feasible method for noninvasive initial risk stratification in pediatric neuroblastoma.
  • Findings support further multicenter research into radiomics as an adjunctive imaging biomarker for early NB diagnosis.
  • The study highlights the potential of radiomics to enhance diagnostic workflows in pediatric oncology.