Label-free opto-physicochemical profiling of eosinophils reveals molecular and structural signatures for EGPA diagnosis

Eosinophilic granulomatosis with polyangiitis (EGPA) is a rare disease that requires accurate diagnostic methods to overcome the limitations of current diagnostic criteria relying on clinical observation. Eosinophils from EGPA undergo dynamic changes that reflect its pathological state. Thus, physicochemical analysis of EGPA eosinophils may serve as a key diagnostic approach. In this study, eosinophils from patients with EGPA (n = 8) and healthy control group (n = 7) were analyzed using a multimodal imaging system with aligned optical diffraction tomography (ODT) and Raman spectroscopy. Given that ODT allows for physical analysis and Raman shift indicates chemical components, combining these two different analyses approaches could improve the accuracy of classification. We applied partial least squares discriminant analysis (PLS-DA) on Raman spectrum, specifically focusing on k-means clusters, corresponding to high refractive index (RI) regions identified by ODT. This process aimed to extract variable importance projection (VIP) score, to analyze key feature of Raman spectrum for chemical profiling. Chemical profiling from Raman spectrum complementarily explains the high RI value in granules. These granules enriched areas, derived from ODT physical feature with the validation of Dice-similarity Coefficient, enhanced the accuracy of EGPA prediction up to 96%. This integrated approach demonstrates the potential of multimodal profiling to enhance diagnostic precision for eosinophilic disorders. • ODT-Raman integration enables physical and chemical profiling of the same eosinophils. • High-RI regions in ODT match chemically distinct granules in Raman spectroscopy. • RI and Raman granule regions show strong spatial overlap via Dice Similarity Coefficient. • AI-based multimodal analysis reveals key EGPA-specific molecular and structural features. • The integrated ODT-Raman profiling improved classification accuracy up to 96%.

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Publication Details

Journal
Materials Today Advances
Published
2026-02-04
DOI
https://doi.org/10.1016/j.mtadv.2026.100705
Primary Topic
Spectroscopy Techniques in Biomedical and Chemical Research
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article
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article

Label-free opto-physicochemical profiling of eosinophils reveals molecular and structural signatures for EGPA diagnosis

You Sook Cho, Joon Seup Hwang, Jun Ki Kim, Chan-Gi Pack et al.
Materials Today Advances
Spectroscopy Techniques in Biomedical and Chemical Research
article

Label-free opto-physicochemical profiling of eosinophils reveals molecular and structural signatures for EGPA diagnosis

You Sook Cho, Joon Seup Hwang, Jun Ki Kim, Chan-Gi Pack, Minju Cho, Yu-ra Ha, Ji-Hyang Lee
article en

Abstract

Eosinophilic granulomatosis with polyangiitis (EGPA) is a rare disease that requires accurate diagnostic methods to overcome the limitations of current diagnostic criteria relying on clinical observation. Eosinophils from EGPA undergo dynamic changes that reflect its pathological state. Thus, physicochemical analysis of EGPA eosinophils may serve as a key diagnostic approach. In this study, eosinophils from patients with EGPA (n = 8) and healthy control group (n = 7) were analyzed using a multimodal imaging system with aligned optical diffraction tomography (ODT) and Raman spectroscopy. Given that ODT allows for physical analysis and Raman shift indicates chemical components, combining these two different analyses approaches could improve the accuracy of classification. We applied partial least squares discriminant analysis (PLS-DA) on Raman spectrum, specifically focusing on k-means clusters, corresponding to high refractive index (RI) regions identified by ODT. This process aimed to extract variable importance projection (VIP) score, to analyze key feature of Raman spectrum for chemical profiling. Chemical profiling from Raman spectrum complementarily explains the high RI value in granules. These granules enriched areas, derived from ODT physical feature with the validation of Dice-similarity Coefficient, enhanced the accuracy of EGPA prediction up to 96%. This integrated approach demonstrates the potential of multimodal profiling to enhance diagnostic precision for eosinophilic disorders. • ODT-Raman integration enables physical and chemical profiling of the same eosinophils. • High-RI regions in ODT match chemically distinct granules in Raman spectroscopy. • RI and Raman granule regions show strong spatial overlap via Dice Similarity Coefficient. • AI-based multimodal analysis reveals key EGPA-specific molecular and structural features. • The integrated ODT-Raman profiling improved classification accuracy up to 96%.

Materials Today AdvancesVol. 29
Ulsan College (KR), Asan Medical Center (KR), Seoul National University Hospital (KR), University of Ulsan (KR), Korea University (JP)
Reduced inequalities
Openalex Percentile: Top 71%
Spectroscopy Techniques in Biomedical and Chemical Research
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