Artificial intelligence substantially improves differential diagnosis of 
dementia–added diagnostic value of rapid brain volumetry

Rudolph , J; Rückel, J; Döpfert, J; Ling, XW; Opalka, J; Brem, C; Hesse, N; Rauchmann, B; Ingenerf, M; Koliogiannis, V; Solyanik, O; Zimmermann, H; Flatz, W; Forbrig, R; Patzig, M; Peters, O; Priller, J; Schneider, A; Fließbach, K; Hermann, A; Wiltfang, J; Jessen, F; Düzel, E; Bürger, K; Teipel, S; Laske, C; Synofzik, M; Spottke, A; Ewers, M; Dechent, P; Haynes, J-D; Scheffler, K; Ricke, J; Ingrisch, M; Stöcklein, S

doi:10.1007/s00062-021-01075-5

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Artificial intelligence substantially improves differential diagnosis of dementia–added diagnostic value of rapid brain volumetry

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Scheffler, K
Department High-Field Magnetic Resonance, Max Planck Institute for Biological Cybernetics, Max Planck Society;

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引用

Rudolph, J., Rückel, J., Döpfert, J., Ling, X., Opalka, J., Brem, C., Hesse, N., Rauchmann, B., Ingenerf, M., Koliogiannis, V., Solyanik, O., Zimmermann, H., Flatz, W., Forbrig, R., Patzig, M., Peters, O., Priller, J., Schneider, A., Fließbach, K., Hermann, A., Wiltfang, J., Jessen, F., Düzel, E., Bürger, K., Teipel, S., Laske, C., Synofzik, M., Spottke, A., Ewers, M., Dechent, P., Haynes, J.-D., Scheffler, K., Ricke, J., Ingrisch, M., & Stöcklein, S. (2021). Artificial intelligence substantially improves differential diagnosis of dementia–added diagnostic value of rapid brain volumetry. Clinical Neuroradiology, 31(Supplement 1), 21-22.

引用: https://hdl.handle.net/21.11116/0000-0009-5951-8

要旨

Background: Brain volumetry is a key aspect in dementia diagnostics. We applied an artificial intelligence (AI) system based on a Convolutional Neural Network (CNN)
which aims to perform lobe-separated rapid brain volumetry (< 1/2 h) of three-dimensional T1-weighted magnetic resonance imaging (MRI) with automated segmentation as
well as comparison to age- and gender-adapted percentiles. Our aim was to quantify the added value in the differential diagnostics of dementia. Methods: A total of 55 patients–17 with confirmed diagnosis of
Alzheimer’s disease (AD), 18 with confirmed diagnosis of frontotemporal dementia (FTD) and 20 healthy controls–received T1-weighted three-dimensional magnetization prepared–rapid gradient echo (MPRAGE)
MRI.
Images were retrospectively assessed by one board-certified neuroradiologist (BCNR) and two radiology residents (RR)–one of whom had received 6 months of neuroradiology training (RR1). All
cases were evaluated in a two-step reading process–beginning without AI-support and followed by an AI-supported reading (AI tool: mdbrain version 3.3.0). For each subject, the suspected diagnostic category
(AD, FTD and healthy controls) was determined using a likelihood score (0–5), adding up to a sum of 5 for all three diagnostic categories.
Individual reader performance with and without AI support was statistically evaluated using receiver operating characteristics (ROC).
Results: AI support substantially improved AD diagnosis in all three readers. The effect was most pronounced for RR2 who had not undergone neuroradiology training (area under the curve [AUC]
without AI support [– AI]: 0.629, AI supported [+ AI]: 0.885). But, even for the BCNR, a substantial benefit was measurable (AUCs: BCNR—AI: 0.827, + AI: 0.882; RR1—AI: 0.713, + AI:
0.834). In diagnosing FTD RR2 improved with AI support (AUCs:—AI: 0.610, + AI: 0.754), while BCNR and RR1 had comparable reading performances with and without AI support (AUCs: BCNR—
AI: 0.843, + AI: 0.828; RR1—AI: 0.865, + AI: 0.868).
Discussion: Even experienced BCNR can improve their diagnostic accuracy for AD by using AI based rapid brain volumetry and comparison with the age- and gender-matched reference cohorts. In diagnosing
FTD, especially radiologists who are less experienced in dementia differential diagnosis can strongly benefit from AI support.
Conclusion: AI support in the radiological work-up of dementia patients is feasible and can substantially improve diagnostic accuracy, which might lead to earlier diagnosis and therefore optimized patient
management.