Artificial intelligence-based rapid brain volumetry substantially improves differential diagnosis in dementia

Jan Rudolph*, Johannes Rueckel, Jörg Döpfert, Wen Xin Ling, Jens Opalka, Christian Brem, Nina Hesse, Maria Ingenerf, Vanessa Koliogiannis, Olga Solyanik, Boj F Hoppe, Hanna Zimmermann, Wilhelm Flatz, Robert Forbrig, Maximilian Patzig, Boris-Stephan Rauchmann, Robert Perneczky, Oliver Peters, Josef Priller, Anja SchneiderKlaus Fliessbach, Andreas Hermann, Jens Wiltfang, Frank Jessen, Emrah Düzel, Katharina Buerger, Stefan Teipel, Christoph Laske, Matthis Synofzik, Annika Spottke, Michael Ewers, Peter Dechent, John-Dylan Haynes, Johannes Levin, Thomas Liebig, Jens Ricke, Michael Ingrisch, Sophia Stoecklein

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

Abstract

INTRODUCTION: This study evaluates the clinical value of a deep learning-based artificial intelligence (AI) system that performs rapid brain volumetry with automatic lobe segmentation and age- and sex-adjusted percentile comparisons.

METHODS: Fifty-five patients-17 with Alzheimer's disease (AD), 18 with frontotemporal dementia (FTD), and 20 healthy controls-underwent cranial magnetic resonance imaging scans. Two board-certified neuroradiologists (BCNR), two board-certified radiologists (BCR), and three radiology residents (RR) assessed the scans twice: first without AI support and then with AI assistance.

RESULTS: AI significantly improved diagnostic accuracy for AD (area under the curve -AI: 0.800, +AI: 0.926, p < 0.05), with increased correct diagnoses ( p < 0.01) and reduced errors ( p < 0.03). BCR and RR showed notable performance gains (BCR: p < 0.04; RR: p < 0.02). For the diagnosis FTD, overall consensus ( p < 0.01), BCNR ( p < 0.02), and BCR ( p < 0.05) recorded significantly more correct diagnoses.

DISCUSSION: AI-assisted volumetry improves diagnostic performance in differentiating AD and FTD, benefiting all reader groups, including BCNR.

HIGHLIGHTS: 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.

Original languageEnglish
Pages (from-to)e70037
JournalAlzheimer's & Dementia: Diagnosis, Assessment & Disease Monitoring
Volume16
Issue number4
DOIs
Publication statusPublished - 11 Dec 2024

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