Artificial intelligence–based rapid brain volumetry substantially improves differential diagnosis in dementia
Artificial intelligence (AI)-supported brain volumetry significantly improved the diagnostic accuracy for Alzheimer's disease (AD) and frontotemporal dementia (FTD), with notable performance gains across radiologists of varying expertise levels.The presented AI tool is readily clinically available and reduces brain volumetry processing time from 12 to 24 hours to under 5 minutes, with full integration into picture archiving and communication systems, streamlining the workflow and facilitating real-time clinical decision making.AI-supported rapid brain volumetry has the potential to improve early diagnosis and to improve patient management.
Authors
- Emrah Düzel (ORCID: https://orcid.org/0000-0002-0139-5388)
- Michael Ingrisch (ORCID: https://orcid.org/0000-0003-0268-9078)
- Hanna Zimmermann (ORCID: https://orcid.org/0000-0002-1476-3477)
- Nina Hesse (ORCID: https://orcid.org/0000-0003-3040-3110)
- Jens Wiltfang (ORCID: https://orcid.org/0000-0003-1492-5330)
- Robert Forbrig (ORCID: https://orcid.org/0000-0002-1054-1463)
- Maria Ingenerf
- Robert Perneczky (ORCID: https://orcid.org/0000-0003-1981-7435)
- Annika Spottke (ORCID: https://orcid.org/0000-0001-9854-2972)
- Oliver Peters (ORCID: https://orcid.org/0000-0003-0568-2998)
- Stefan Teipel (ORCID: https://orcid.org/0000-0002-3586-3194)
- Jörg Döpfert
- Maximilian Patzig (ORCID: https://orcid.org/0000-0003-0465-6923)
- Sophia Stoecklein (ORCID: https://orcid.org/0000-0003-0325-4674)
- Matthis Synofzik (ORCID: https://orcid.org/0000-0002-2280-7273)
- Boris‐Stephan Rauchmann (ORCID: https://orcid.org/0000-0003-4547-6240)
- Johannes Levin (ORCID: https://orcid.org/0000-0001-5092-4306)
- Vanessa Koliogiannis
- Boj Hoppe (ORCID: https://orcid.org/0000-0001-6248-5128)
- Michael Ewers (ORCID: https://orcid.org/0000-0001-5231-1714)
- Katharina Büerger (ORCID: https://orcid.org/0000-0002-5898-9953)
- Klaus Fließbach (ORCID: https://orcid.org/0000-0002-0183-7510)
- Christian Brem
- Josef Priller (ORCID: https://orcid.org/0000-0001-7596-0979)
- Jens Ricke (ORCID: https://orcid.org/0000-0001-8762-8594)
- Andreas Hermann (ORCID: https://orcid.org/0000-0002-7364-7791)
- J Opalka
- Thomas Liebig (ORCID: https://orcid.org/0000-0001-5640-7780)
- Jan Rudolph (ORCID: https://orcid.org/0000-0002-4849-8034)
- Johannes Rueckel
- Wilhelm H. Flatz (ORCID: https://orcid.org/0000-0002-0380-726X)
- Anja Schneider (ORCID: https://orcid.org/0000-0001-9540-8700)
- Wen Xin Ling
- John–Dylan Haynes (ORCID: https://orcid.org/0000-0003-1786-6954)
- Peter Dechent (ORCID: https://orcid.org/0009-0006-4005-3352)
- Christoph Laske
- Olga Solyanik
- Frank Jessen
Institutions
- University of Bonn (DE)
- University of Cologne (DE)
- University Hospital Bonn (DE)
- German Center for Neurodegenerative Diseases (DE)
- TUM Klinikum (DE)
- LMU Klinikum (DE)
- Medico-Academic Consultings (Germany) (DE)
- Munich Cluster for Systems Neurology (DE)
- UK Dementia Research Institute (GB)
- Cologne Excellence Cluster on Cellular Stress Responses in Aging Associated Diseases (DE)
- Hertie Institute for Clinical Brain Research (DE)
- Bernstein Center for Computational Neuroscience Berlin (DE)
- Munich Center for Machine Learning
- University of Rostock (DE)
- University of Aveiro (PT)
- University of Göttingen (DE)
- Charité - Universitätsmedizin Berlin (DE)
- Ludwig-Maximilians-Universität München (DE)
- University of Sheffield (GB)
- Otto-von-Guericke-Universität Magdeburg (DE)
- University of Edinburgh (GB)
Publication Details
- Journal
- Alzheimer s & Dementia Diagnosis Assessment & Disease Monitoring
- Published
- 2024-10-01
- DOI
- https://doi.org/10.1002/dad2.70037
- Citations
- 8
- Primary Topic
- Dementia and Cognitive Impairment Research
- Type
- article
- Field-Weighted Citation Impact
- 3.08