dc.contributor
Institut Català de la Salut
dc.contributor
[Garcia-Ruiz A, Grussu F, Monreal-Aguero C, Ligero M, Perez-Lopez R] Radiomics Group, Vall d’Hebron Institute of Oncology (VHIO), Barcelona, Spain. [Pons-Escoda A] Radiology Department, Bellvitge University Hospital, Barcelona, Spain. Neuro-Oncology Unit, Institut d’Investigacio Biomedica de Bellvitge (IDIBELL), Barcelona, Spain. [Naval-Baudin P] Radiology Department, Bellvitge University Hospital, Barcelona, Spain. [Hermann G] Radiation Medicine Department and Applied Sciences, University of California, San Diego, La Jolla, CA, USA
dc.contributor
Vall d'Hebron Barcelona Hospital Campus
dc.contributor.author
Garcia Ruiz, Alonso
dc.contributor.author
Pons-Escoda, Albert
dc.contributor.author
Naval-Baudin, Pablo
dc.contributor.author
Monreal-Aguero, Camilo
dc.contributor.author
Hermann, Gretchen
dc.contributor.author
Grussu, Francesco
dc.contributor.author
Ligero, Marta
dc.contributor.author
Perez-Lopez, Raquel
dc.date.accessioned
2025-10-25T05:39:46Z
dc.date.available
2025-10-25T05:39:46Z
dc.date.issued
2024-03-26T10:58:50Z
dc.date.issued
2024-03-26T10:58:50Z
dc.date.issued
2024-03-19
dc.identifier
Garcia-Ruiz A, Pons-Escoda A, Grussu F, Naval-Baudin P, Monreal-Aguero C, Hermann G, et al. An accessible deep learning tool for voxel-wise classification of brain malignancies from perfusion MRI. Cell Reports Med. 2024 Mar 19;5(3):101464.
dc.identifier
https://hdl.handle.net/11351/11246
dc.identifier
10.1016/j.xcrm.2024.101464
dc.identifier.uri
http://hdl.handle.net/11351/11246
dc.description.abstract
Deep learning; Glioblastoma; Perfusion MRI
dc.description.abstract
Aprenentatge profund; Glioblastoma; Ressonància magnètica de perfusió
dc.description.abstract
Aprendizaje profundo; Glioblastoma; Resonancia magnética de perfusión
dc.description.abstract
Noninvasive differential diagnosis of brain tumors is currently based on the assessment of magnetic resonance imaging (MRI) coupled with dynamic susceptibility contrast (DSC). However, a definitive diagnosis often requires neurosurgical interventions that compromise patients' quality of life. We apply deep learning on DSC images from histology-confirmed patients with glioblastoma, metastasis, or lymphoma. The convolutional neural network trained on ∼50,000 voxels from 40 patients provides intratumor probability maps that yield clinical-grade diagnosis. Performance is tested in 400 additional cases and an external validation cohort of 128 patients. The tool reaches a three-way accuracy of 0.78, superior to the conventional MRI metrics cerebral blood volume (0.55) and percentage of signal recovery (0.59), showing high value as a support diagnostic tool. Our open-access software, Diagnosis In Susceptibility Contrast Enhancing Regions for Neuro-oncology (DISCERN), demonstrates its potential in aiding medical decisions for brain tumor diagnosis using standard-of-care MRI.
dc.description.abstract
This project was supported by “La Caixa” Foundation (RTI2018-095209-B-C21) and the Spanish Ministry of Science and Innovation (FIS-G64384969). R.P.-L. is supported by the Prostate Cancer Foundation Young Investigator Award, the FERO Foundation, the CRIS Foundation Talent Award (TALENT19-05), the Instituto de Salud Carlos III Investigacion en Salud (PI21/01019), and the Asociacion Espanola Contra el Cancer (PRYCO211023SERR). F.G. was funded by the Government of Catalonia (Beatriu de Pinos 2020 00117 BP) and by the Fundacio LaCaixa (ID 100010434, code LCF/BQ/PR22/11920010). C.M. and A.P.-E. acknowledge support from the Instituto de Salud Carlos III-Investigación en Salud (PI20/00360). We would like to express our sincere appreciation to Javier Carmona for his valuable support and assistance in reviewing the manuscript.
dc.format
application/pdf
dc.relation
Cell Reports Medicine;5(3)
dc.relation
https://doi.org/10.1016/j.xcrm.2024.101464
dc.relation
info:eu-repo/grantAgreement/ES/PE2017-2020/PI21%2F01019
dc.rights
Attribution-NonCommercial-NoDerivatives 4.0 International
dc.rights
http://creativecommons.org/licenses/by-nc-nd/4.0/
dc.rights
info:eu-repo/semantics/openAccess
dc.subject
Cervell - Càncer - Imatgeria
dc.subject
Imatgeria per ressonància magnètica
dc.subject
Aprenentatge profund
dc.subject
DISEASES::Neoplasms::Neoplasms by Site::Nervous System Neoplasms::Central Nervous System Neoplasms::Brain Neoplasms
dc.subject
Other subheadings::Other subheadings::Other subheadings::/diagnostic imaging
dc.subject
PHENOMENA AND PROCESSES::Mathematical Concepts::Algorithms::Artificial Intelligence::Machine Learning::Deep Learning
dc.subject
ANALYTICAL, DIAGNOSTIC AND THERAPEUTIC TECHNIQUES, AND EQUIPMENT::Diagnosis::Diagnostic Techniques and Procedures::Diagnostic Imaging::Tomography::Magnetic Resonance Imaging
dc.subject
ANALYTICAL, DIAGNOSTIC AND THERAPEUTIC TECHNIQUES, AND EQUIPMENT::Diagnosis::Diagnostic Techniques and Procedures::Diagnostic Imaging::Radionuclide Imaging::Perfusion Imaging
dc.subject
ENFERMEDADES::neoplasias::neoplasias por localización::neoplasias del sistema nervioso::neoplasias del sistema nervioso central::neoplasias cerebrales
dc.subject
Otros calificadores::Otros calificadores::Otros calificadores::/diagnóstico por imagen
dc.subject
FENÓMENOS Y PROCESOS::conceptos matemáticos::algoritmos::inteligencia artificial::aprendizaje automático::aprendizaje profundo
dc.subject
TÉCNICAS Y EQUIPOS ANALÍTICOS, DIAGNÓSTICOS Y TERAPÉUTICOS::diagnóstico::técnicas y procedimientos diagnósticos::diagnóstico por imagen::tomografía::imagen por resonancia magnética
dc.subject
TÉCNICAS Y EQUIPOS ANALÍTICOS, DIAGNÓSTICOS Y TERAPÉUTICOS::diagnóstico::técnicas y procedimientos diagnósticos::diagnóstico por imagen::imagen radioisotópica::imágenes de perfusión
dc.title
An accessible deep learning tool for voxel-wise classification of brain malignancies from perfusion MRI
dc.type
info:eu-repo/semantics/article
dc.type
info:eu-repo/semantics/publishedVersion
