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An algorithmic approach to structural imaging in dementia
Accurate and timely diagnosis of dementia is important to guide management and provide appropriate information and support to patients and families. Currently, with the exception of individuals with genetic mutations, postmortem examination of brain tissue remains the only definitive means of establ...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BMJ Publishing Group
2014
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4033032/ https://www.ncbi.nlm.nih.gov/pubmed/24133287 http://dx.doi.org/10.1136/jnnp-2013-306285 |
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author | Harper, Lorna Barkhof, Frederik Scheltens, Philip Schott, Jonathan M Fox, Nick C |
author_facet | Harper, Lorna Barkhof, Frederik Scheltens, Philip Schott, Jonathan M Fox, Nick C |
author_sort | Harper, Lorna |
collection | PubMed |
description | Accurate and timely diagnosis of dementia is important to guide management and provide appropriate information and support to patients and families. Currently, with the exception of individuals with genetic mutations, postmortem examination of brain tissue remains the only definitive means of establishing diagnosis in most cases, however, structural neuroimaging, in combination with clinical assessment, has value in improving diagnostic accuracy during life. Beyond the exclusion of surgical pathology, signal change and cerebral atrophy visible on structural MRI can be used to identify diagnostically relevant imaging features, which provide support for clinical diagnosis of neurodegenerative dementias. While no structural imaging feature has perfect sensitivity and specificity for a given diagnosis, there are a number of imaging characteristics which provide positive predictive value and help to narrow the differential diagnosis. While neuroradiological expertise is invaluable in accurate scan interpretation, there is much that a non-radiologist can gain from a focused and structured approach to scan analysis. In this article we describe the characteristic MRI findings of the various dementias and provide a structured algorithm with the aim of providing clinicians with a practical guide to assessing scans. |
format | Online Article Text |
id | pubmed-4033032 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2014 |
publisher | BMJ Publishing Group |
record_format | MEDLINE/PubMed |
spelling | pubmed-40330322014-06-05 An algorithmic approach to structural imaging in dementia Harper, Lorna Barkhof, Frederik Scheltens, Philip Schott, Jonathan M Fox, Nick C J Neurol Neurosurg Psychiatry Neurodegeneration Accurate and timely diagnosis of dementia is important to guide management and provide appropriate information and support to patients and families. Currently, with the exception of individuals with genetic mutations, postmortem examination of brain tissue remains the only definitive means of establishing diagnosis in most cases, however, structural neuroimaging, in combination with clinical assessment, has value in improving diagnostic accuracy during life. Beyond the exclusion of surgical pathology, signal change and cerebral atrophy visible on structural MRI can be used to identify diagnostically relevant imaging features, which provide support for clinical diagnosis of neurodegenerative dementias. While no structural imaging feature has perfect sensitivity and specificity for a given diagnosis, there are a number of imaging characteristics which provide positive predictive value and help to narrow the differential diagnosis. While neuroradiological expertise is invaluable in accurate scan interpretation, there is much that a non-radiologist can gain from a focused and structured approach to scan analysis. In this article we describe the characteristic MRI findings of the various dementias and provide a structured algorithm with the aim of providing clinicians with a practical guide to assessing scans. BMJ Publishing Group 2014-06 2013-10-16 /pmc/articles/PMC4033032/ /pubmed/24133287 http://dx.doi.org/10.1136/jnnp-2013-306285 Text en Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://group.bmj.com/group/rights-licensing/permissions This is an Open Access article distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 3.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited and the use is non-commercial. See: http://creativecommons.org/licenses/by-nc/3.0/ |
spellingShingle | Neurodegeneration Harper, Lorna Barkhof, Frederik Scheltens, Philip Schott, Jonathan M Fox, Nick C An algorithmic approach to structural imaging in dementia |
title | An algorithmic approach to structural imaging in dementia |
title_full | An algorithmic approach to structural imaging in dementia |
title_fullStr | An algorithmic approach to structural imaging in dementia |
title_full_unstemmed | An algorithmic approach to structural imaging in dementia |
title_short | An algorithmic approach to structural imaging in dementia |
title_sort | algorithmic approach to structural imaging in dementia |
topic | Neurodegeneration |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4033032/ https://www.ncbi.nlm.nih.gov/pubmed/24133287 http://dx.doi.org/10.1136/jnnp-2013-306285 |
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