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This study examines the accuracy of CTseg segmentation software to diagnose Alzheimer's disease dementia and other dementias using routine CT scans from a New Zealand memory service. Analyzing 168 scans (89 with dementia and 79 without dementia) the software segmented the brain to produce total brain volume and hippocampal volume. CTseg-derived total brain volume (sensitivity 72%, specificity 58%) and hippocampal volume (sensitivity 71%, specificity 62%) were reasonably effective at differentiating dementia from non-dementia at time of diagnosis. Our findings suggest that CTseg automated volumetric analysis has some potential to aid dementia diagnosis in real-world clinical settings.
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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC12095946 | PMC |
http://dx.doi.org/10.1177/25424823251332448 | DOI Listing |
J Alzheimers Dis Rep
May 2025
School of Medicine, Faculty of Medical and Health Sciences, The University of Auckland, Auckland, New Zealand.
This study examines the accuracy of CTseg segmentation software to diagnose Alzheimer's disease dementia and other dementias using routine CT scans from a New Zealand memory service. Analyzing 168 scans (89 with dementia and 79 without dementia) the software segmented the brain to produce total brain volume and hippocampal volume. CTseg-derived total brain volume (sensitivity 72%, specificity 58%) and hippocampal volume (sensitivity 71%, specificity 62%) were reasonably effective at differentiating dementia from non-dementia at time of diagnosis.
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