Kudus, Kareem
Wagner, Matthias W.
Namdar, Khashayar
Nobre, Liana
Bouffet, Eric
Tabori, Uri
Hawkins, Cynthia
Yeom, Kristen W.
Ertl-Wagner, Birgit B.
Khalvati, Farzad http://orcid.org/0000-0001-5616-8660
Funding for this research was provided by:
Fondation Brain Canada
Canadian Cancer Society
Article History
Received: 22 November 2022
Revised: 16 June 2023
Accepted: 10 August 2023
First Online: 7 October 2023
Declarations
:
: The scientific guarantor of this publication is Dr. Farzad Khalvati.
: The authors of this manuscript declare no relationships with any companies, whose products or services may be related to the subject matter of the article.
: No complex statistical methods were necessary for this paper.
: Written informed consent was waived by the Institutional Review Board.
: Institutional Review Board approval was obtained (The Hospital for Sick Children (Toronto, Ontario, Canada) and the Lucile Packard Children’s Hospital (Stanford University, Palo Alto, California).
: Some study subjects or cohorts have been previously reported in two previous papers. The first, “Radiomics of Pediatric Low-Grade Gliomas: Toward a Pretherapeutic Differentiation of BRAF-Mutated and BRAF-Fused Tumors,” ExternalRef removed, was an exploratory study that relied on 115 of our 253 patients. The second, “Dataset size sensitivity analysis of machine learning classifiers to differentiate molecular markers of pediatric low-grade gliomas based on MRI,” Oncology and Radiotherapy 16 (S1) 2022: 01–06, relied on 251 of our 253 patients. These previous studies aimed to establish a relationship between radiomics features and BRAF status, and to determine the best machine learning model on this classification task.
: • Retrospective• Diagnostic or prognostic study• Multicenter study