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Lemmens S, Van Craenendonck T, Van Eijgen J, De Groef L, Bruffaerts R, de Jesus DA, Charle W, Jayapala M, Sunaric-Mégevand G, Standaert A, Theunis J, Van Keer K, Vandenbulcke M, Moons L, Vandenberghe R, De Boever P, Stalmans I. Combination of snapshot hyperspectral retinal imaging and optical coherence tomography to identify Alzheimer's disease patients. Alzheimers Res Ther 2020; 12:144. [PMID: 33172499 PMCID: PMC7654576 DOI: 10.1186/s13195-020-00715-1] [Citation(s) in RCA: 21] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/06/2020] [Accepted: 10/22/2020] [Indexed: 12/14/2022]
Abstract
INTRODUCTION The eye offers potential for the diagnosis of Alzheimer's disease (AD) with retinal imaging techniques being explored to quantify amyloid accumulation and aspects of neurodegeneration. To assess these changes, this proof-of-concept study combined hyperspectral imaging and optical coherence tomography to build a classification model to differentiate between AD patients and controls. METHODS In a memory clinic setting, patients with a diagnosis of clinically probable AD (n = 10) or biomarker-proven AD (n = 7) and controls (n = 22) underwent non-invasive retinal imaging with an easy-to-use hyperspectral snapshot camera that collects information from 16 spectral bands (460-620 nm, 10-nm bandwidth) in one capture. The individuals were also imaged using optical coherence tomography for assessing retinal nerve fiber layer thickness (RNFL). Dedicated image preprocessing analysis was followed by machine learning to discriminate between both groups. RESULTS Hyperspectral data and retinal nerve fiber layer thickness data were used in a linear discriminant classification model to discriminate between AD patients and controls. Nested leave-one-out cross-validation resulted in a fair accuracy, providing an area under the receiver operating characteristic curve of 0.74 (95% confidence interval [0.60-0.89]). Inner loop results showed that the inclusion of the RNFL features resulted in an improvement of the area under the receiver operating characteristic curve: for the most informative region assessed, the average area under the receiver operating characteristic curve was 0.70 (95% confidence interval [0.55, 0.86]) and 0.79 (95% confidence interval [0.65, 0.93]), respectively. The robust statistics used in this study reduces the risk of overfitting and partly compensates for the limited sample size. CONCLUSIONS This study in a memory-clinic-based cohort supports the potential of hyperspectral imaging and suggests an added value of combining retinal imaging modalities. Standardization and longitudinal data on fully amyloid-phenotyped cohorts are required to elucidate the relationship between retinal structure and cognitive function and to evaluate the robustness of the classification model.
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Affiliation(s)
- Sophie Lemmens
- Department of Ophthalmology, University Hospitals UZ Leuven, Herestraat 49, 3000 Leuven, Belgium
- Department of Neurosciences, Research Group Ophthalmology, KU Leuven, Biomedical Sciences Group, Herestraat 49, 3000 Leuven, Belgium
- VITO (Flemish Institute for Technological Research), Health Unit, Boeretang 200, 2400 Mol, Belgium
| | - Toon Van Craenendonck
- VITO (Flemish Institute for Technological Research), Health Unit, Boeretang 200, 2400 Mol, Belgium
| | - Jan Van Eijgen
- Department of Ophthalmology, University Hospitals UZ Leuven, Herestraat 49, 3000 Leuven, Belgium
- Department of Neurosciences, Research Group Ophthalmology, KU Leuven, Biomedical Sciences Group, Herestraat 49, 3000 Leuven, Belgium
- VITO (Flemish Institute for Technological Research), Health Unit, Boeretang 200, 2400 Mol, Belgium
| | - Lies De Groef
- Neural Circuit Development and Regeneration Research Group, Department of Biology, KU Leuven, Naamsestraat 61, 3000 Leuven, Belgium
| | - Rose Bruffaerts
- Laboratory for Cognitive Neurology, Department of Neurosciences, KU Leuven, Herestraat 49, 3000 Leuven, Belgium
- Department of Neurology, University Hospitals UZ Leuven, Herestraat 49, 3000 Leuven, Belgium
| | - Danilo Andrade de Jesus
- Department of Neurosciences, Research Group Ophthalmology, KU Leuven, Biomedical Sciences Group, Herestraat 49, 3000 Leuven, Belgium
| | | | | | - Gordana Sunaric-Mégevand
- Clinical Research Center, Mémorial A. de Rothschild, 22 Chemin Beau Soleil, 1208 Geneva, Switzerland
| | - Arnout Standaert
- VITO (Flemish Institute for Technological Research), Health Unit, Boeretang 200, 2400 Mol, Belgium
| | - Jan Theunis
- VITO (Flemish Institute for Technological Research), Health Unit, Boeretang 200, 2400 Mol, Belgium
| | - Karel Van Keer
- Department of Ophthalmology, University Hospitals UZ Leuven, Herestraat 49, 3000 Leuven, Belgium
- Department of Neurosciences, Research Group Ophthalmology, KU Leuven, Biomedical Sciences Group, Herestraat 49, 3000 Leuven, Belgium
| | - Mathieu Vandenbulcke
- Division of Psychiatry, University Hospitals Leuven, Herestraat 49, 3000 Leuven, Belgium
| | - Lieve Moons
- Neural Circuit Development and Regeneration Research Group, Department of Biology, KU Leuven, Naamsestraat 61, 3000 Leuven, Belgium
| | - Rik Vandenberghe
- Laboratory for Cognitive Neurology, Department of Neurosciences, KU Leuven, Herestraat 49, 3000 Leuven, Belgium
- Department of Neurology, University Hospitals UZ Leuven, Herestraat 49, 3000 Leuven, Belgium
- Alzheimer Research Center KU Leuven, Leuven Brain Institute, Herestraat 49, 3000 Leuven, Belgium
| | - Patrick De Boever
- VITO (Flemish Institute for Technological Research), Health Unit, Boeretang 200, 2400 Mol, Belgium
- Hasselt University, Center of Environmental Sciences, Agoralaan, 3590 Diepenbeek, Belgium
- Department of Biology, University of Antwerp, Universiteitsplein 1, 2610 Wilrijk, Belgium
| | - Ingeborg Stalmans
- Department of Ophthalmology, University Hospitals UZ Leuven, Herestraat 49, 3000 Leuven, Belgium
- Department of Neurosciences, Research Group Ophthalmology, KU Leuven, Biomedical Sciences Group, Herestraat 49, 3000 Leuven, Belgium
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