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Untapped Neuroimaging Tools for Neuro-Oncology: Connectomics and Spatial Transcriptomics

SIMPLE SUMMARY: Brain imaging, specifically magnetic resonance imaging (MRI), plays a key role in the clinical and research aspects of neuro-oncology. Novel neuroimaging techniques enable the transformation of a brain MRI into a so-called average brain. This allows projects using already acquired br...

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Autores principales: Germann, Jurgen, Zadeh, Gelareh, Mansouri, Alireza, Kucharczyk, Walter, Lozano, Andres M., Boutet, Alexandre
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8833690/
https://www.ncbi.nlm.nih.gov/pubmed/35158732
http://dx.doi.org/10.3390/cancers14030464
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author Germann, Jurgen
Zadeh, Gelareh
Mansouri, Alireza
Kucharczyk, Walter
Lozano, Andres M.
Boutet, Alexandre
author_facet Germann, Jurgen
Zadeh, Gelareh
Mansouri, Alireza
Kucharczyk, Walter
Lozano, Andres M.
Boutet, Alexandre
author_sort Germann, Jurgen
collection PubMed
description SIMPLE SUMMARY: Brain imaging, specifically magnetic resonance imaging (MRI), plays a key role in the clinical and research aspects of neuro-oncology. Novel neuroimaging techniques enable the transformation of a brain MRI into a so-called average brain. This allows projects using already acquired brain MRIs to perform group analyses and draw conclusions. Once the data are in this average brain, several types of analyses can be performed. For example, determining the most vulnerable locations for certain tumor types or perhaps even the underlying circuitry and gene expression that might cause predisposition to tumor growth. This information may further our understanding of tumor behavior, leading to better patient counseling, surgery timing, and treatment monitoring. ABSTRACT: Neuro-oncology research is broad and includes several branches, one of which is neuroimaging. Magnetic resonance imaging (MRI) is instrumental for the diagnosis and treatment monitoring of patients with brain tumors. Most commonly, structural and perfusion MRI sequences are acquired to characterize tumors and understand their behaviors. Thanks to technological advances, structural brain MRI can now be transformed into a so-called average brain accounting for individual morphological differences, which enables retrospective group analysis. These normative analyses are uncommonly used in neuro-oncology research. Once the data have been normalized, voxel-wise analyses and spatial mapping can be performed. Additionally, investigations of underlying connectomics can be performed using functional and structural templates. Additionally, a recently available template of spatial transcriptomics has enabled the assessment of associated gene expression. The few published normative analyses have shown relationships between tumor characteristics and spatial localization, as well as insights into the circuitry associated with epileptogenic tumors and depression after cingulate tumor resection. The wide breadth of possibilities with normative analyses remain largely unexplored, specifically in terms of connectomics and imaging transcriptomics. We provide a framework for performing normative analyses in oncology while also highlighting their limitations. Normative analyses are an opportunity to address neuro-oncology questions from a different perspective.
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spelling pubmed-88336902022-02-12 Untapped Neuroimaging Tools for Neuro-Oncology: Connectomics and Spatial Transcriptomics Germann, Jurgen Zadeh, Gelareh Mansouri, Alireza Kucharczyk, Walter Lozano, Andres M. Boutet, Alexandre Cancers (Basel) Perspective SIMPLE SUMMARY: Brain imaging, specifically magnetic resonance imaging (MRI), plays a key role in the clinical and research aspects of neuro-oncology. Novel neuroimaging techniques enable the transformation of a brain MRI into a so-called average brain. This allows projects using already acquired brain MRIs to perform group analyses and draw conclusions. Once the data are in this average brain, several types of analyses can be performed. For example, determining the most vulnerable locations for certain tumor types or perhaps even the underlying circuitry and gene expression that might cause predisposition to tumor growth. This information may further our understanding of tumor behavior, leading to better patient counseling, surgery timing, and treatment monitoring. ABSTRACT: Neuro-oncology research is broad and includes several branches, one of which is neuroimaging. Magnetic resonance imaging (MRI) is instrumental for the diagnosis and treatment monitoring of patients with brain tumors. Most commonly, structural and perfusion MRI sequences are acquired to characterize tumors and understand their behaviors. Thanks to technological advances, structural brain MRI can now be transformed into a so-called average brain accounting for individual morphological differences, which enables retrospective group analysis. These normative analyses are uncommonly used in neuro-oncology research. Once the data have been normalized, voxel-wise analyses and spatial mapping can be performed. Additionally, investigations of underlying connectomics can be performed using functional and structural templates. Additionally, a recently available template of spatial transcriptomics has enabled the assessment of associated gene expression. The few published normative analyses have shown relationships between tumor characteristics and spatial localization, as well as insights into the circuitry associated with epileptogenic tumors and depression after cingulate tumor resection. The wide breadth of possibilities with normative analyses remain largely unexplored, specifically in terms of connectomics and imaging transcriptomics. We provide a framework for performing normative analyses in oncology while also highlighting their limitations. Normative analyses are an opportunity to address neuro-oncology questions from a different perspective. MDPI 2022-01-18 /pmc/articles/PMC8833690/ /pubmed/35158732 http://dx.doi.org/10.3390/cancers14030464 Text en © 2022 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Perspective
Germann, Jurgen
Zadeh, Gelareh
Mansouri, Alireza
Kucharczyk, Walter
Lozano, Andres M.
Boutet, Alexandre
Untapped Neuroimaging Tools for Neuro-Oncology: Connectomics and Spatial Transcriptomics
title Untapped Neuroimaging Tools for Neuro-Oncology: Connectomics and Spatial Transcriptomics
title_full Untapped Neuroimaging Tools for Neuro-Oncology: Connectomics and Spatial Transcriptomics
title_fullStr Untapped Neuroimaging Tools for Neuro-Oncology: Connectomics and Spatial Transcriptomics
title_full_unstemmed Untapped Neuroimaging Tools for Neuro-Oncology: Connectomics and Spatial Transcriptomics
title_short Untapped Neuroimaging Tools for Neuro-Oncology: Connectomics and Spatial Transcriptomics
title_sort untapped neuroimaging tools for neuro-oncology: connectomics and spatial transcriptomics
topic Perspective
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8833690/
https://www.ncbi.nlm.nih.gov/pubmed/35158732
http://dx.doi.org/10.3390/cancers14030464
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