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Differentiating Glioblastomas from Solitary Brain Metastases: An Update on the Current Literature of Advanced Imaging Modalities

SIMPLE SUMMARY: The process of differentiating glioblastomas from solitary brain metastases is often difficult using traditional magnetic resonance imaging alone. In the past two decades, much progress has been made in devising advanced imaging modalities for the purpose of ascertaining more data on...

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Autores principales: Fordham, Austin-John, Hacherl, Caitlin-Craft, Patel, Neal, Jones, Keri, Myers, Brandon, Abraham, Mickey, Gendreau, Julian
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8231515/
https://www.ncbi.nlm.nih.gov/pubmed/34199151
http://dx.doi.org/10.3390/cancers13122960
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author Fordham, Austin-John
Hacherl, Caitlin-Craft
Patel, Neal
Jones, Keri
Myers, Brandon
Abraham, Mickey
Gendreau, Julian
author_facet Fordham, Austin-John
Hacherl, Caitlin-Craft
Patel, Neal
Jones, Keri
Myers, Brandon
Abraham, Mickey
Gendreau, Julian
author_sort Fordham, Austin-John
collection PubMed
description SIMPLE SUMMARY: The process of differentiating glioblastomas from solitary brain metastases is often difficult using traditional magnetic resonance imaging alone. In the past two decades, much progress has been made in devising advanced imaging modalities for the purpose of ascertaining more data on these intracranial tumors to help neuroradiologists in differentiating the two pathologies. In addition to the data provided by dynamic susceptibility contrast imaging and magnetic resonance spectroscopy, more innovative modalities now include diffusion tensor imaging and neurite orientation dispersion and density imaging. Radiomic analysis protocols and machine learning algorithms are being continually optimized to increase the accuracy of diagnosis by utilizing multiple different imaging protocols per patient. In this review, we provide an update on these advanced imaging modalities by reviewing the most up-to-date and current evidence. ABSTRACT: Differentiating between glioblastomas and solitary brain metastases proves to be a challenging diagnosis for neuroradiologists, as both present with imaging patterns consisting of peritumoral hyperintensities with similar intratumoral texture on traditional magnetic resonance imaging sequences. Early diagnosis is paramount, as each pathology has completely different methods of clinical assessment. In the past decade, recent developments in advanced imaging modalities enabled providers to acquire a more accurate diagnosis earlier in the patient’s clinical assessment, thus optimizing clinical outcome. Dynamic susceptibility contrast has been optimized for detecting relative cerebral blood flow and relative cerebral blood volume. Diffusion tensor imaging can be used to detect changes in mean diffusivity. Neurite orientation dispersion and density imaging is an innovative modality detecting changes in intracellular volume fraction, isotropic volume fraction, and extracellular volume fraction. Magnetic resonance spectroscopy is able to assist by providing a metabolic descriptor while detecting variable ratios of choline/N-acetylaspartate, choline/creatine, and N-acetylaspartate/creatine. Finally, radiomics and machine learning algorithms have been devised to assist in improving diagnostic accuracy while often utilizing more than one advanced imaging protocol per patient. In this review, we provide an update on all the current evidence regarding the identification and differentiation of glioblastomas from solitary brain metastases.
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spelling pubmed-82315152021-06-26 Differentiating Glioblastomas from Solitary Brain Metastases: An Update on the Current Literature of Advanced Imaging Modalities Fordham, Austin-John Hacherl, Caitlin-Craft Patel, Neal Jones, Keri Myers, Brandon Abraham, Mickey Gendreau, Julian Cancers (Basel) Review SIMPLE SUMMARY: The process of differentiating glioblastomas from solitary brain metastases is often difficult using traditional magnetic resonance imaging alone. In the past two decades, much progress has been made in devising advanced imaging modalities for the purpose of ascertaining more data on these intracranial tumors to help neuroradiologists in differentiating the two pathologies. In addition to the data provided by dynamic susceptibility contrast imaging and magnetic resonance spectroscopy, more innovative modalities now include diffusion tensor imaging and neurite orientation dispersion and density imaging. Radiomic analysis protocols and machine learning algorithms are being continually optimized to increase the accuracy of diagnosis by utilizing multiple different imaging protocols per patient. In this review, we provide an update on these advanced imaging modalities by reviewing the most up-to-date and current evidence. ABSTRACT: Differentiating between glioblastomas and solitary brain metastases proves to be a challenging diagnosis for neuroradiologists, as both present with imaging patterns consisting of peritumoral hyperintensities with similar intratumoral texture on traditional magnetic resonance imaging sequences. Early diagnosis is paramount, as each pathology has completely different methods of clinical assessment. In the past decade, recent developments in advanced imaging modalities enabled providers to acquire a more accurate diagnosis earlier in the patient’s clinical assessment, thus optimizing clinical outcome. Dynamic susceptibility contrast has been optimized for detecting relative cerebral blood flow and relative cerebral blood volume. Diffusion tensor imaging can be used to detect changes in mean diffusivity. Neurite orientation dispersion and density imaging is an innovative modality detecting changes in intracellular volume fraction, isotropic volume fraction, and extracellular volume fraction. Magnetic resonance spectroscopy is able to assist by providing a metabolic descriptor while detecting variable ratios of choline/N-acetylaspartate, choline/creatine, and N-acetylaspartate/creatine. Finally, radiomics and machine learning algorithms have been devised to assist in improving diagnostic accuracy while often utilizing more than one advanced imaging protocol per patient. In this review, we provide an update on all the current evidence regarding the identification and differentiation of glioblastomas from solitary brain metastases. MDPI 2021-06-13 /pmc/articles/PMC8231515/ /pubmed/34199151 http://dx.doi.org/10.3390/cancers13122960 Text en © 2021 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 Review
Fordham, Austin-John
Hacherl, Caitlin-Craft
Patel, Neal
Jones, Keri
Myers, Brandon
Abraham, Mickey
Gendreau, Julian
Differentiating Glioblastomas from Solitary Brain Metastases: An Update on the Current Literature of Advanced Imaging Modalities
title Differentiating Glioblastomas from Solitary Brain Metastases: An Update on the Current Literature of Advanced Imaging Modalities
title_full Differentiating Glioblastomas from Solitary Brain Metastases: An Update on the Current Literature of Advanced Imaging Modalities
title_fullStr Differentiating Glioblastomas from Solitary Brain Metastases: An Update on the Current Literature of Advanced Imaging Modalities
title_full_unstemmed Differentiating Glioblastomas from Solitary Brain Metastases: An Update on the Current Literature of Advanced Imaging Modalities
title_short Differentiating Glioblastomas from Solitary Brain Metastases: An Update on the Current Literature of Advanced Imaging Modalities
title_sort differentiating glioblastomas from solitary brain metastases: an update on the current literature of advanced imaging modalities
topic Review
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8231515/
https://www.ncbi.nlm.nih.gov/pubmed/34199151
http://dx.doi.org/10.3390/cancers13122960
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