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An algorithmic approach to structural imaging in dementia
  1. Lorna Harper1,
  2. Frederik Barkhof2,
  3. Philip Scheltens3,
  4. Jonathan M Schott1,
  5. Nick C Fox1
  1. 1Department of Neurodegenerative Disease, Dementia Research Centre, UCL Institute of Neurology, London, UK
  2. 2Department of Radiology, VU University Medical Centre, Amsterdam, Netherlands
  3. 3Department of Neurology, VU University Medical Centre, Amsterdam, Netherlands
  1. Correspondence to Professor Nick C Fox, Department of Neurodegenerative Disease, Dementia Research Centre, UCL Institute of Neurology, 8–11 Queen Square, London WC1N 3BG, UK;{at}


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.

  • MRI

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