Evaluating the use of synthetic T1-w images in new T2 lesion detection in multiple sclerosis

MRI; Deep learning; Multiple sclerosis

Detalles Bibliográficos
Autores: Valencia, Liliana, Clèrigues Garcia, Albert, Salem, Mostafa, Oliver, Arnau, Rovira Cañellas, Alex, Valverde, Sergi, Llado, Xavier
Tipo de recurso: artículo
Estado:Versión publicada
Fecha de publicación:2022
País:España
Institución:Varias* (Consorci de Biblioteques Universitáries de Catalunya, Centre de Serveis Científics i Acadèmics de Catalunya)
Repositorio:Recercat. Dipósit de la Recerca de Catalunya
OAI Identifier:oai:recercat.cat:11351/8516
Acceso en línea:https://hdl.handle.net/11351/8516
http://hdl.handle.net/11351/8516
Access Level:acceso abierto
Palabra clave:Esclerosi múltiple - Tractament
Cervell - Imatgeria
DISEASES::Nervous System Diseases::Autoimmune Diseases of the Nervous System::Demyelinating Autoimmune Diseases, CNS::Multiple Sclerosis
Other subheadings::Other subheadings::/therapy
ANATOMY::Nervous System::Central Nervous System::Brain
Other subheadings::Other subheadings::Other subheadings::/diagnostic imaging
ENFERMEDADES::enfermedades del sistema nervioso::enfermedades autoinmunitarias del sistema nervioso::enfermedades autoinmunes desmielinizantes del SNC::esclerosis múltiple
Otros calificadores::Otros calificadores::/terapia
ANATOMÍA::sistema nervioso::sistema nervioso central::encéfalo
Otros calificadores::Otros calificadores::Otros calificadores::/diagnóstico por imagen
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oai_identifier_str oai:recercat.cat:11351/8516
network_acronym_str ES
network_name_str España
repository_id_str
dc.title.none.fl_str_mv Evaluating the use of synthetic T1-w images in new T2 lesion detection in multiple sclerosis
title Evaluating the use of synthetic T1-w images in new T2 lesion detection in multiple sclerosis
spellingShingle Evaluating the use of synthetic T1-w images in new T2 lesion detection in multiple sclerosis
Valencia, Liliana
Esclerosi múltiple - Tractament
Cervell - Imatgeria
DISEASES::Nervous System Diseases::Autoimmune Diseases of the Nervous System::Demyelinating Autoimmune Diseases, CNS::Multiple Sclerosis
Other subheadings::Other subheadings::/therapy
ANATOMY::Nervous System::Central Nervous System::Brain
Other subheadings::Other subheadings::Other subheadings::/diagnostic imaging
ENFERMEDADES::enfermedades del sistema nervioso::enfermedades autoinmunitarias del sistema nervioso::enfermedades autoinmunes desmielinizantes del SNC::esclerosis múltiple
Otros calificadores::Otros calificadores::/terapia
ANATOMÍA::sistema nervioso::sistema nervioso central::encéfalo
Otros calificadores::Otros calificadores::Otros calificadores::/diagnóstico por imagen
title_short Evaluating the use of synthetic T1-w images in new T2 lesion detection in multiple sclerosis
title_full Evaluating the use of synthetic T1-w images in new T2 lesion detection in multiple sclerosis
title_fullStr Evaluating the use of synthetic T1-w images in new T2 lesion detection in multiple sclerosis
title_full_unstemmed Evaluating the use of synthetic T1-w images in new T2 lesion detection in multiple sclerosis
title_sort Evaluating the use of synthetic T1-w images in new T2 lesion detection in multiple sclerosis
dc.creator.none.fl_str_mv Valencia, Liliana
Clèrigues Garcia, Albert
Salem, Mostafa
Oliver, Arnau
Rovira Cañellas, Alex
Valverde, Sergi
Llado, Xavier
author Valencia, Liliana
author_facet Valencia, Liliana
Clèrigues Garcia, Albert
Salem, Mostafa
Oliver, Arnau
Rovira Cañellas, Alex
Valverde, Sergi
Llado, Xavier
author_role author
author2 Clèrigues Garcia, Albert
Salem, Mostafa
Oliver, Arnau
Rovira Cañellas, Alex
Valverde, Sergi
Llado, Xavier
author2_role author
author
author
author
author
author
dc.contributor.none.fl_str_mv Institut Català de la Salut
[Valencia L, Clèrigues A, Oliver A, Lladó X] Research Institute of Computer Vision and Robotics, University of Girona, Girona, Spain. [Valverde S] Tensor Medical, Girona, Spain. [Salem M] Research Institute of Computer Vision and Robotics, University of Girona, Girona, Spain. Department of Computer Science, Faculty of Computers and Information, Assiut University, Asyut, Egypt. [Rovira À] L’Institut de Diagnòstic per la Imatge (IDI), Servei de Radiologia, Vall d'Hebron Hospital Universitari, Barcelona, Spain
Vall d'Hebron Barcelona Hospital Campus
dc.subject.none.fl_str_mv Esclerosi múltiple - Tractament
Cervell - Imatgeria
DISEASES::Nervous System Diseases::Autoimmune Diseases of the Nervous System::Demyelinating Autoimmune Diseases, CNS::Multiple Sclerosis
Other subheadings::Other subheadings::/therapy
ANATOMY::Nervous System::Central Nervous System::Brain
Other subheadings::Other subheadings::Other subheadings::/diagnostic imaging
ENFERMEDADES::enfermedades del sistema nervioso::enfermedades autoinmunitarias del sistema nervioso::enfermedades autoinmunes desmielinizantes del SNC::esclerosis múltiple
Otros calificadores::Otros calificadores::/terapia
ANATOMÍA::sistema nervioso::sistema nervioso central::encéfalo
Otros calificadores::Otros calificadores::Otros calificadores::/diagnóstico por imagen
topic Esclerosi múltiple - Tractament
Cervell - Imatgeria
DISEASES::Nervous System Diseases::Autoimmune Diseases of the Nervous System::Demyelinating Autoimmune Diseases, CNS::Multiple Sclerosis
Other subheadings::Other subheadings::/therapy
ANATOMY::Nervous System::Central Nervous System::Brain
Other subheadings::Other subheadings::Other subheadings::/diagnostic imaging
ENFERMEDADES::enfermedades del sistema nervioso::enfermedades autoinmunitarias del sistema nervioso::enfermedades autoinmunes desmielinizantes del SNC::esclerosis múltiple
Otros calificadores::Otros calificadores::/terapia
ANATOMÍA::sistema nervioso::sistema nervioso central::encéfalo
Otros calificadores::Otros calificadores::Otros calificadores::/diagnóstico por imagen
description MRI; Deep learning; Multiple sclerosis
publishDate 2022
dc.date.none.fl_str_mv 2022
2022
2022
dc.type.none.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
format article
status_str publishedVersion
dc.identifier.none.fl_str_mv https://hdl.handle.net/11351/8516
http://hdl.handle.net/11351/8516
url https://hdl.handle.net/11351/8516
http://hdl.handle.net/11351/8516
dc.language.none.fl_str_mv Inglés
language_invalid_str_mv Inglés
dc.relation.none.fl_str_mv Frontiers in Neuroscience;16
https://doi.org/10.3389/fnins.2022.954662
dc.rights.none.fl_str_mv Attribution 4.0 International
http://creativecommons.org/licenses/by/4.0/
info:eu-repo/semantics/openAccess
rights_invalid_str_mv Attribution 4.0 International
http://creativecommons.org/licenses/by/4.0/
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.publisher.none.fl_str_mv Frontiers Media
publisher.none.fl_str_mv Frontiers Media
dc.source.none.fl_str_mv Scientia
reponame:Recercat. Dipósit de la Recerca de Catalunya
instname:Varias* (Consorci de Biblioteques Universitáries de Catalunya, Centre de Serveis Científics i Acadèmics de Catalunya)
instname_str Varias* (Consorci de Biblioteques Universitáries de Catalunya, Centre de Serveis Científics i Acadèmics de Catalunya)
reponame_str Recercat. Dipósit de la Recerca de Catalunya
collection Recercat. Dipósit de la Recerca de Catalunya
repository.name.fl_str_mv
repository.mail.fl_str_mv
_version_ 1869407179734253568
spelling Evaluating the use of synthetic T1-w images in new T2 lesion detection in multiple sclerosisValencia, LilianaClèrigues Garcia, AlbertSalem, MostafaOliver, ArnauRovira Cañellas, AlexValverde, SergiLlado, XavierEsclerosi múltiple - TractamentCervell - ImatgeriaDISEASES::Nervous System Diseases::Autoimmune Diseases of the Nervous System::Demyelinating Autoimmune Diseases, CNS::Multiple SclerosisOther subheadings::Other subheadings::/therapyANATOMY::Nervous System::Central Nervous System::BrainOther subheadings::Other subheadings::Other subheadings::/diagnostic imagingENFERMEDADES::enfermedades del sistema nervioso::enfermedades autoinmunitarias del sistema nervioso::enfermedades autoinmunes desmielinizantes del SNC::esclerosis múltipleOtros calificadores::Otros calificadores::/terapiaANATOMÍA::sistema nervioso::sistema nervioso central::encéfaloOtros calificadores::Otros calificadores::Otros calificadores::/diagnóstico por imagenMRI; Deep learning; Multiple sclerosisResonancia magnética; Aprendizaje profundo; Esclerosis múltipleRessonància magnètica; Aprenentatge profund; Esclerosi múltipleThe assessment of disease activity using serial brain MRI scans is one of the most valuable strategies for monitoring treatment response in patients with multiple sclerosis (MS) receiving disease-modifying treatments. Recently, several deep learning approaches have been proposed to improve this analysis, obtaining a good trade-off between sensitivity and specificity, especially when using T1-w and T2-FLAIR images as inputs. However, the need to acquire two different types of images is time-consuming, costly and not always available in clinical practice. In this paper, we investigate an approach to generate synthetic T1-w images from T2-FLAIR images and subsequently analyse the impact of using original and synthetic T1-w images on the performance of a state-of-the-art approach for longitudinal MS lesion detection. We evaluate our approach on a dataset containing 136 images from MS patients, and 73 images with lesion activity (the appearance of new T2 lesions in follow-up scans). To evaluate the synthesis of the images, we analyse the structural similarity index metric and the median absolute error and obtain consistent results. To study the impact of synthetic T1-w images, we evaluate the performance of the new lesion detection approach when using (1) both T2-FLAIR and T1-w original images, (2) only T2-FLAIR images, and (3) both T2-FLAIR and synthetic T1-w images. Sensitivities of 0.75, 0.63, and 0.81, respectively, were obtained at the same false-positive rate (0.14) for all experiments. In addition, we also present the results obtained when using the data from the international MSSEG-2 challenge, showing also an improvement when including synthetic T1-w images. In conclusion, we show that the use of synthetic images can support the lack of data or even be used instead of the original image to homogenize the contrast of the different acquisitions in new T2 lesions detection algorithms.AC holds an FPI grant from the Ministerio de Ciencia, Innovación y Universidades with reference number PRE2018-083507. This work has been supported by DPI2020-114769RB-I00 from the Ministerio de Ciencia, Innovación y Universidades. The authors gratefully acknowledge the support of the NVIDIA Corporation with their donation of the TITAN X GPU used in this research. This work has been also supported by ICREA Academia Program.Frontiers MediaInstitut Català de la Salut[Valencia L, Clèrigues A, Oliver A, Lladó X] Research Institute of Computer Vision and Robotics, University of Girona, Girona, Spain. [Valverde S] Tensor Medical, Girona, Spain. [Salem M] Research Institute of Computer Vision and Robotics, University of Girona, Girona, Spain. Department of Computer Science, Faculty of Computers and Information, Assiut University, Asyut, Egypt. [Rovira À] L’Institut de Diagnòstic per la Imatge (IDI), Servei de Radiologia, Vall d'Hebron Hospital Universitari, Barcelona, SpainVall d'Hebron Barcelona Hospital Campus202220222022info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionapplication/pdfhttps://hdl.handle.net/11351/8516http://hdl.handle.net/11351/8516Scientiareponame:Recercat. Dipósit de la Recerca de Catalunyainstname:Varias* (Consorci de Biblioteques Universitáries de Catalunya, Centre de Serveis Científics i Acadèmics de Catalunya)InglésFrontiers in Neuroscience;16https://doi.org/10.3389/fnins.2022.954662Attribution 4.0 Internationalhttp://creativecommons.org/licenses/by/4.0/info:eu-repo/semantics/openAccessoai:recercat.cat:11351/85162026-05-29T05:05:01Z
score 15,81155

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