Diffusion magnetic resonance imaging data: development of methods and tools for diagnosis and treatment of brain diseases

The use of quantitative mapping of diffusion characteristics carries great potential for diagnosis and therapy of brain diseases, since it potentially allows to classify tumors, determine the degree of their malignancy, differentiate various morphological structures of tumor and non-tumor pathologie...

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Main Authors: K. A. Urazova, G. E. Gorlachev, A. P. Chernyaev, A. V. Golanov
Format: Article
Language:English
Published: Siberian State Medical University (Tomsk) 2021-07-01
Series:Бюллетень сибирской медицины
Subjects:
Online Access:https://bulletin.ssmu.ru/jour/article/view/4397
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author K. A. Urazova
G. E. Gorlachev
A. P. Chernyaev
A. V. Golanov
author_facet K. A. Urazova
G. E. Gorlachev
A. P. Chernyaev
A. V. Golanov
author_sort K. A. Urazova
collection DOAJ
description The use of quantitative mapping of diffusion characteristics carries great potential for diagnosis and therapy of brain diseases, since it potentially allows to classify tumors, determine the degree of their malignancy, differentiate various morphological structures of tumor and non-tumor pathologies (such as  tumor stroma, necrotic zones, cysts, various types of edema, etc.), and predict the course and outcome of diseases, in particular, a clinical response to treatment. Based on diffusion weighted magnetic resonance imaging (MRI), it is possible to perform 3D modeling of the white matter pathways of the brain, which is called tractography. In addition to a unique ability to visualize the location of tracts in relation to intracranial pathologies, this technology allows to build and analyze complex maps of communication networks in the brain (connectomics).The review is devoted to the discussion of the physical and technical concept of diffusion weighted MRI, the key ways of its application in tumor and non-tumor processes, and problems that complicate correct interpretation of results. Since the problem of developing software for diffusion MRI data remains relevant, this review presents our own experience in developing an application as part of a project on creating effective methods for processing diffusion MRI data and modeling white matter tracts.
format Article
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institution DOAJ
issn 1682-0363
1819-3684
language English
publishDate 2021-07-01
publisher Siberian State Medical University (Tomsk)
record_format Article
series Бюллетень сибирской медицины
spelling doaj-art-194291f4f9054f74852b6b680cf558d52025-08-20T03:02:04ZengSiberian State Medical University (Tomsk)Бюллетень сибирской медицины1682-03631819-36842021-07-0120219120110.20538/1682-0363-2021-2-191-2012797Diffusion magnetic resonance imaging data: development of methods and tools for diagnosis and treatment of brain diseasesK. A. Urazova0G. E. Gorlachev1A. P. Chernyaev2A. V. Golanov3N.N. Burdenko National Scientific and Practical Center for Neurosurgery; M.V. Lomonosov Moscow State UniversityN.N. Blokhin National Medical Research Center of OncologyM.V. Lomonosov Moscow State UniversityN.N. Burdenko National Scientific and Practical Center for NeurosurgeryThe use of quantitative mapping of diffusion characteristics carries great potential for diagnosis and therapy of brain diseases, since it potentially allows to classify tumors, determine the degree of their malignancy, differentiate various morphological structures of tumor and non-tumor pathologies (such as  tumor stroma, necrotic zones, cysts, various types of edema, etc.), and predict the course and outcome of diseases, in particular, a clinical response to treatment. Based on diffusion weighted magnetic resonance imaging (MRI), it is possible to perform 3D modeling of the white matter pathways of the brain, which is called tractography. In addition to a unique ability to visualize the location of tracts in relation to intracranial pathologies, this technology allows to build and analyze complex maps of communication networks in the brain (connectomics).The review is devoted to the discussion of the physical and technical concept of diffusion weighted MRI, the key ways of its application in tumor and non-tumor processes, and problems that complicate correct interpretation of results. Since the problem of developing software for diffusion MRI data remains relevant, this review presents our own experience in developing an application as part of a project on creating effective methods for processing diffusion MRI data and modeling white matter tracts.https://bulletin.ssmu.ru/jour/article/view/4397магнитно-резонансная томографиядиффузионно-взвешенная томографиятрактографияголовной мозгнейронауки
spellingShingle K. A. Urazova
G. E. Gorlachev
A. P. Chernyaev
A. V. Golanov
Diffusion magnetic resonance imaging data: development of methods and tools for diagnosis and treatment of brain diseases
Бюллетень сибирской медицины
магнитно-резонансная томография
диффузионно-взвешенная томография
трактография
головной мозг
нейронауки
title Diffusion magnetic resonance imaging data: development of methods and tools for diagnosis and treatment of brain diseases
title_full Diffusion magnetic resonance imaging data: development of methods and tools for diagnosis and treatment of brain diseases
title_fullStr Diffusion magnetic resonance imaging data: development of methods and tools for diagnosis and treatment of brain diseases
title_full_unstemmed Diffusion magnetic resonance imaging data: development of methods and tools for diagnosis and treatment of brain diseases
title_short Diffusion magnetic resonance imaging data: development of methods and tools for diagnosis and treatment of brain diseases
title_sort diffusion magnetic resonance imaging data development of methods and tools for diagnosis and treatment of brain diseases
topic магнитно-резонансная томография
диффузионно-взвешенная томография
трактография
головной мозг
нейронауки
url https://bulletin.ssmu.ru/jour/article/view/4397
work_keys_str_mv AT kaurazova diffusionmagneticresonanceimagingdatadevelopmentofmethodsandtoolsfordiagnosisandtreatmentofbraindiseases
AT gegorlachev diffusionmagneticresonanceimagingdatadevelopmentofmethodsandtoolsfordiagnosisandtreatmentofbraindiseases
AT apchernyaev diffusionmagneticresonanceimagingdatadevelopmentofmethodsandtoolsfordiagnosisandtreatmentofbraindiseases
AT avgolanov diffusionmagneticresonanceimagingdatadevelopmentofmethodsandtoolsfordiagnosisandtreatmentofbraindiseases