Title |
Imaging biomarkers of dementia: recommended visual rating scales with teaching cases
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Published in |
Insights into Imaging, December 2016
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DOI | 10.1007/s13244-016-0521-6 |
Pubmed ID | |
Authors |
Lars-Olof Wahlund, Eric Westman, Danielle van Westen, Anders Wallin, Sara Shams, Lena Cavallin, Elna-Marie Larsson, From the Imaging Cognitive Impairment Network (ICINET) |
Abstract |
The diagnostic work up of dementia may benefit from structured reporting of CT and/or MRI and the use of standardised visual rating scales. We advocate a more widespread use of standardised scales as part of the workflow in clinical and research evaluation of dementia. We propose routine clinical use of rating scales for medial temporal atrophy (MTA), global cortical atrophy (GCA) and white matter hyperintensities (WMH). These scales can be used for evaluation of both CT and MRI and are efficient in routine imaging assessment in dementia, and may improve the accuracy of diagnosis. Our review provides detailed imaging examples of rating increments in each of these scales and a separate teaching file. The radiologist should relate visual ratings to the clinical assessment and other biomarkers to assist the clinician in the diagnostic decision. • Clinical dementia diagnostics would benefit from structured radiological reporting. • Standardised rating scales should be used in dementia assessment. • It is important to relate imaging findings to the clinically suspected diagnosis. |
X Demographics
Geographical breakdown
Country | Count | As % |
---|---|---|
United States | 1 | 50% |
Unknown | 1 | 50% |
Demographic breakdown
Type | Count | As % |
---|---|---|
Members of the public | 2 | 100% |
Mendeley readers
Geographical breakdown
Country | Count | As % |
---|---|---|
Unknown | 156 | 100% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Student > Ph. D. Student | 23 | 15% |
Other | 20 | 13% |
Researcher | 19 | 12% |
Student > Bachelor | 13 | 8% |
Student > Postgraduate | 13 | 8% |
Other | 28 | 18% |
Unknown | 40 | 26% |
Readers by discipline | Count | As % |
---|---|---|
Medicine and Dentistry | 64 | 41% |
Neuroscience | 22 | 14% |
Psychology | 6 | 4% |
Computer Science | 4 | 3% |
Nursing and Health Professions | 3 | 2% |
Other | 9 | 6% |
Unknown | 48 | 31% |