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Optical Imaging for Biomedical Applications, 2nd Edition

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Special Issue Editor

Dr. Johannes Dominikus Pallua

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Department of Orthopaedics and Traumatology, Medical University of Innsbruck, Anichstraße 35, 6020 Innsbruck, Austria
Interests: osteological pathologies; bone infection diagnosis; multimodal imaging; microscopy; digital pathology; infrared spectroscopy; raman spectroscopy; FTIR imaging; NIR spectroscopy; hyperspectral imaging; MRI; CT; micro-CT; MALDI imaging; imaging-guided surgery and treatment; 3D printing; orthopedics and traumatology; pathology; forensic science; analytical chemistry; molecular biology; microbiology; quality management
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Special Issue Information

Dear Colleagues,

Optical imaging is a type of imaging technique that uses visible, ultraviolet, and infrared light to create images of soft tissue without using any harmful radiation. Unlike X-rays, which require ionizing radiation, optical imaging is a safe and non-invasive way to monitor disease progression and treatment efficacy. This technique measures multiple properties of soft tissue, which makes it beneficial for detecting early metabolic changes that indicate abnormal organ and tissue functioning. By examining how soft tissues absorb and scatter light, researchers can use optical imaging to gain enhanced information about complex diseases. Optical imaging can also be combined with other imaging techniques, such as MRI or X-rays, to better understand the disease or tissue being studied. This Special Issue, entitled “Optical Imaging for Biomedical Applications”, showcases recent advancements in developing, designing, modeling, implementing, and characterizing optical imaging techniques for biomedical applications. This Special Issue covers, but is not limited to, the topics listed below.

This is the second edition of the Special Issue “Optical Imaging for Biomedical Applications”, https://www.mdpi.com/journal/bioengineering/special_issues/EQG5W6M6ZG.

Microscopy;
Digital pathology;
Infrared spectroscopy;
Raman spectroscopy;
NIR spectroscopy;
Hyperspectral imaging;
Combinations with MRI, X-ray, CT, or micro-CT;
Advanced imaging techniques and systems;
Imaging-guided surgery and treatment;
Artificial intelligence-based computational imaging techniques for biomedical imaging;
Image processing.

Dr. Johannes Dominikus Pallua
Guest Editor

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Keywords

microscopy
digital pathology
infrared spectroscopy
Raman spectroscopy
NIR spectroscopy
hyperspectral imaging
combinations with MRI, X-ray, CT, or micro-CT
advanced imaging techniques and systems
imaging-guided surgery and treatment
artificial intelligence-based computational imaging techniques for biomedical imaging
image processing
photoacoustics
optical coherence tomography

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17 pages, 8391 KB

Open AccessArticle

Proof-of-Concept Study: Hyperspectral Imaging for Quantification of DKK-3 Expression in Oropharyngeal Carcinoma

by Theresa Mittermair, Andrea Brunner, Bettina Zelger, Rohit Arora, Christian Wolfgang Huck and Johannes Dominikus Pallua

Bioengineering 2025, 12(9), 971; https://doi.org/10.3390/bioengineering12090971 - 12 Sep 2025

Viewed by 483

Abstract

Introduction: Oral squamous cell carcinoma (OSCC) is one of the most common tumours worldwide. This study investigated the suitability of visible and near-infrared hyperspectral imaging compared to visual assessment and conventional digital image analysis for quantifying immunohistochemical staining on the example of Dickkopf-3 (DKK-3) in OSCC. Materials and methods: A retrospective analysis of TMAs containing DKK-3 stained OSCC of 50 patients was retrieved from the archives at the Institute of Pathology, Medical University of Innsbruck. TMAs were first evaluated visually, followed by digital image analysis using QuPath (version 0.3.2, open-source software). For hyperspectral imaging, six exemplary cases were selected (three cases with strong expression and three cases with weak expression) and evaluated. The collected hyperspectral images were visualised using TIVITA (Tissue Imaging System). The resulting true-colour images and the classified HSI images were then assessed using the QuPath software. The Allred score and the H-score were used for all analyses. Results: 97 tissue cores were used for visual and digital image analysis. No significant difference was found between the evaluations of visual and digital image analysis using the H-score (pWilcoxon = 0.278), and both H-scores correlated significantly with each other (p^Spearman < 0.001). Similar results were also found using the Allred score. The kappa value was 0.67, which represents a “substantial” correlation. Finally, the H-scores and Allred scores were compared for visual, digital, and HSI imaging. No significant differences were found between the three groups concerning the H-score (pWilcoxon > 0.1). Using Cohen’s Kappa, a “fair” to “moderate” correlation was observed between the three evaluations. Conclusion: Visible and near-infrared hyperspectral imaging (VIS-NIR-HSI) is a promising complementary tool for digital pathology workflows. This proof-of-concept study suggests that HSI offers the potential for more objective quantification of DKK-3 expression in oropharyngeal squamous cell carcinoma, particularly in cases with weak staining. However, given the small sample size and exploratory design, the findings should be regarded as hypothesis-generating. Future studies with larger, clinically annotated cohorts and standardised workflows are needed before any consideration of routine clinical application. Full article

(This article belongs to the Special Issue Optical Imaging for Biomedical Applications, 2nd Edition)

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