Combination of snapshot hyperspectral retinal imaging and optical coherence tomography to identify Alzheimer's disease patients

被引:45
作者
Lemmens, Sophie [1 ,2 ,3 ]
Van Craenendonck, Toon [3 ]
Van Eijgen, Jan [1 ,2 ,3 ]
De Groef, Lies [4 ]
Bruffaerts, Rose [5 ,6 ]
de Jesus, Danilo Andrade [2 ]
Charle, Wouter [7 ]
Jayapala, Murali [7 ]
Sunaric-Megevand, Gordana [8 ]
Standaert, Arnout [3 ]
Theunis, Jan [3 ]
Van Keer, Karel [1 ,2 ]
Vandenbulcke, Mathieu [9 ]
Moons, Lieve [4 ]
Vandenberghe, Rik [5 ,6 ,10 ]
De Boever, Patrick [3 ,11 ,12 ]
Stalmans, Ingeborg [1 ,2 ]
机构
[1] Univ Hosp UZ Leuven, Dept Ophthalmol, Herestr 49, B-3000 Leuven, Belgium
[2] Katholieke Univ Leuven, Res Grp Ophthalmol, Biomed Sci Grp, Dept Neurosci, Herestr 49, B-3000 Leuven, Belgium
[3] VITO Flemish Inst Technol Res, Hlth Unit, Boeretang 200, B-2400 Mol, Belgium
[4] Katholieke Univ Leuven, Neural Circuit Dev & Regenerat Res Grp, Dept Biol, Naamsestr 61, B-3000 Leuven, Belgium
[5] Katholieke Univ Leuven, Dept Neurosci, Lab Cognit Neurol, Herestr 49, B-3000 Leuven, Belgium
[6] Univ Hosp UZ Leuven, Dept Neurol, Herestr 49, B-3000 Leuven, Belgium
[7] IMEC, Kapeldreef 75, B-3001 Leuven, Belgium
[8] Mem A Rothschild, Clin Res Ctr, 22 Chemin Beau Soleil, CH-1208 Geneva, Switzerland
[9] Univ Hosp Leuven, Div Psychiat, Herestr 49, B-3000 Leuven, Belgium
[10] Alzheimer Res Ctr KU Leuven, Leuven Brain Inst, Herestr 49, B-3000 Leuven, Belgium
[11] Hasselt Univ, Ctr Environm Sci, B-3590 Diepenbeek, Belgium
[12] Univ Antwerp, Dept Biol, Univ Pl 1, B-2610 Antwerp, Belgium
基金
欧盟地平线“2020”;
关键词
Retina; Brain; Neurodegeneration; Cognitive impairment; Alzheimer’ s disease; Amyloid-beta (Aβ Hyperspectral imaging; Machine learning; Biomarker; FIBER LAYER THICKNESS; DEGENERATION; ABNORMALITIES; DIAGNOSIS; AMYLOIDOPATHY; BIOMARKERS; SEVERITY; EYES;
D O I
10.1186/s13195-020-00715-1
中图分类号
R74 [神经病学与精神病学];
学科分类号
摘要
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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页数:13
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