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Fan X, Sun AR, Young RSE, Afara IO, Hamilton BR, Ong LJY, Crawford R, Prasadam I. Spatial analysis of the osteoarthritis microenvironment: techniques, insights, and applications. Bone Res 2024; 12:7. [PMID: 38311627 PMCID: PMC10838951 DOI: 10.1038/s41413-023-00304-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/05/2023] [Revised: 11/21/2023] [Accepted: 11/27/2023] [Indexed: 02/06/2024] Open
Abstract
Osteoarthritis (OA) is a debilitating degenerative disease affecting multiple joint tissues, including cartilage, bone, synovium, and adipose tissues. OA presents diverse clinical phenotypes and distinct molecular endotypes, including inflammatory, metabolic, mechanical, genetic, and synovial variants. Consequently, innovative technologies are needed to support the development of effective diagnostic and precision therapeutic approaches. Traditional analysis of bulk OA tissue extracts has limitations due to technical constraints, causing challenges in the differentiation between various physiological and pathological phenotypes in joint tissues. This issue has led to standardization difficulties and hindered the success of clinical trials. Gaining insights into the spatial variations of the cellular and molecular structures in OA tissues, encompassing DNA, RNA, metabolites, and proteins, as well as their chemical properties, elemental composition, and mechanical attributes, can contribute to a more comprehensive understanding of the disease subtypes. Spatially resolved biology enables biologists to investigate cells within the context of their tissue microenvironment, providing a more holistic view of cellular function. Recent advances in innovative spatial biology techniques now allow intact tissue sections to be examined using various -omics lenses, such as genomics, transcriptomics, proteomics, and metabolomics, with spatial data. This fusion of approaches provides researchers with critical insights into the molecular composition and functions of the cells and tissues at precise spatial coordinates. Furthermore, advanced imaging techniques, including high-resolution microscopy, hyperspectral imaging, and mass spectrometry imaging, enable the visualization and analysis of the spatial distribution of biomolecules, cells, and tissues. Linking these molecular imaging outputs to conventional tissue histology can facilitate a more comprehensive characterization of disease phenotypes. This review summarizes the recent advancements in the molecular imaging modalities and methodologies for in-depth spatial analysis. It explores their applications, challenges, and potential opportunities in the field of OA. Additionally, this review provides a perspective on the potential research directions for these contemporary approaches that can meet the requirements of clinical diagnoses and the establishment of therapeutic targets for OA.
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Affiliation(s)
- Xiwei Fan
- Centre for Biomedical Technologies, Queensland University of Technology, Brisbane, QLD, Australia
- School of Mechanical, Medical & Process Engineering, Queensland University of Technology, Brisbane, QLD, Australia
| | - Antonia Rujia Sun
- Centre for Biomedical Technologies, Queensland University of Technology, Brisbane, QLD, Australia
- School of Mechanical, Medical & Process Engineering, Queensland University of Technology, Brisbane, QLD, Australia
| | - Reuben S E Young
- Central Analytical Research Facility, Queensland University of Technology, Brisbane, QLD, Australia
- Molecular Horizons, University of Wollongong, Wollongong, NSW, Australia
| | - Isaac O Afara
- Department of Technical Physics, University of Eastern Finland, Kuopio, Finland
- School of Electrical Engineering and Computer Science, Faculty of Engineering, Architecture and Information Technology, University of Queensland, Brisbane, QLD, Australia
| | - Brett R Hamilton
- Centre for Microscopy and Microanalysis, University of Queensland, Brisbane, QLD, Australia
| | - Louis Jun Ye Ong
- Centre for Biomedical Technologies, Queensland University of Technology, Brisbane, QLD, Australia
- School of Mechanical, Medical & Process Engineering, Queensland University of Technology, Brisbane, QLD, Australia
| | - Ross Crawford
- Centre for Biomedical Technologies, Queensland University of Technology, Brisbane, QLD, Australia
- The Prince Charles Hospital, Brisbane, QLD, Australia
| | - Indira Prasadam
- Centre for Biomedical Technologies, Queensland University of Technology, Brisbane, QLD, Australia.
- School of Mechanical, Medical & Process Engineering, Queensland University of Technology, Brisbane, QLD, Australia.
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2
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Zelger P, Brunner A, Zelger B, Willenbacher E, Unterberger SH, Stalder R, Huck CW, Willenbacher W, Pallua JD. Deep learning analysis of mid-infrared microscopic imaging data for the diagnosis and classification of human lymphomas. JOURNAL OF BIOPHOTONICS 2023; 16:e202300015. [PMID: 37578837 DOI: 10.1002/jbio.202300015] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/18/2023] [Revised: 07/19/2023] [Accepted: 08/09/2023] [Indexed: 08/15/2023]
Abstract
The present study presents an alternative analytical workflow that combines mid-infrared (MIR) microscopic imaging and deep learning to diagnose human lymphoma and differentiate between small and large cell lymphoma. We could show that using a deep learning approach to analyze MIR hyperspectral data obtained from benign and malignant lymph node pathology results in high accuracy for correct classification, learning the distinct region of 3900 to 850 cm-1 . The accuracy is above 95% for every pair of malignant lymphoid tissue and still above 90% for the distinction between benign and malignant lymphoid tissue for binary classification. These results demonstrate that a preliminary diagnosis and subtyping of human lymphoma could be streamlined by applying a deep learning approach to analyze MIR spectroscopic data.
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Affiliation(s)
- P Zelger
- University Hospital of Hearing, Voice and Speech Disorders, Medical University of Innsbruck, Innsbruck, Austria
| | - A Brunner
- Institute of Pathology, Neuropathology and Molecular Pathology, Medical University of Innsbruck, Innsbruck, Austria
| | - B Zelger
- Institute of Pathology, Neuropathology and Molecular Pathology, Medical University of Innsbruck, Innsbruck, Austria
| | - E Willenbacher
- University Hospital of Internal Medicine V, Hematology & Oncology, Medical University of Innsbruck, Innsbruck, Austria
| | - S H Unterberger
- Institute of Material-Technology, Leopold-Franzens University Innsbruck, Innsbruck, Austria
| | - R Stalder
- Institute of Mineralogy and Petrography, Leopold-Franzens University Innsbruck, Innsbruck, Austria
| | - C W Huck
- Institute of Analytical Chemistry and Radiochemistry, Innsbruck, Austria
| | - W Willenbacher
- University Hospital of Internal Medicine V, Hematology & Oncology, Medical University of Innsbruck, Innsbruck, Austria
- Oncotyrol, Centre for Personalized Cancer Medicine, Innsbruck, Austria
| | - J D Pallua
- University Hospital for Orthopedics and Traumatology, Medical University of Innsbruck, Innsbruck, Austria
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Arakelyan M, Spagnuolo G, Iaculli F, Dikopova N, Antoshin A, Timashev P, Turkina A. Minimization of Adverse Effects Associated with Dental Alloys. MATERIALS (BASEL, SWITZERLAND) 2022; 15:7476. [PMID: 36363067 PMCID: PMC9658402 DOI: 10.3390/ma15217476] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 09/21/2022] [Revised: 10/17/2022] [Accepted: 10/21/2022] [Indexed: 06/16/2023]
Abstract
Metal alloys are one of the most popular materials used in current dental practice. In the oral cavity, metal structures are exposed to various mechanical and chemical factors. Consequently, metal ions are released into the oral fluid, which may negatively affect the surrounding tissues and even internal organs. Adverse effects associated with metallic oral appliances may have various local and systemic manifestations, such as mouth burning, potentially malignant oral lesions, and local or systemic hypersensitivity. However, clear diagnostic criteria and treatment guidelines for adverse effects associated with dental alloys have not been developed yet. The present comprehensive literature review aims (1) to summarize the current information related to possible side effects of metallic oral appliances; (2) to analyze the risk factors aggravating the negative effects of dental alloys; and (3) to develop recommendations for diagnosis, management, and prevention of pathological conditions associated with metallic oral appliances.
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Affiliation(s)
- Marianna Arakelyan
- Therapeutic Dentistry Department, Institute for Dentistry, Sechenov University, 119991 Moscow, Russia
| | - Gianrico Spagnuolo
- Department of Neurosciences, Reproductive and Odontostomatological Sciences, University of Naples “Federico II”, 80138 Napoli, Italy
| | - Flavia Iaculli
- Department of Neurosciences, Reproductive and Odontostomatological Sciences, University of Naples “Federico II”, 80138 Napoli, Italy
| | - Natalya Dikopova
- Therapeutic Dentistry Department, Institute for Dentistry, Sechenov University, 119991 Moscow, Russia
| | - Artem Antoshin
- Institute for Regenerative Medicine, Sechenov University, 119991 Moscow, Russia
- World-Class Research Center “Digital Biodesign and Personalized Healthcare”, Sechenov University, 119991 Moscow, Russia
| | - Peter Timashev
- Institute for Regenerative Medicine, Sechenov University, 119991 Moscow, Russia
- World-Class Research Center “Digital Biodesign and Personalized Healthcare”, Sechenov University, 119991 Moscow, Russia
- Chemistry Department, Lomonosov Moscow State University, 119234 Moscow, Russia
| | - Anna Turkina
- Therapeutic Dentistry Department, Institute for Dentistry, Sechenov University, 119991 Moscow, Russia
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Laimer J, Bruckmoser E, Helten T, Kofler B, Zelger B, Brunner A, Zelger B, Huck CW, Tappert M, Rogge D, Schirmer M, Pallua JD. Hyperspectral imaging as a diagnostic tool to differentiate between amalgam tattoos and other dark pigmented intraoral lesions. JOURNAL OF BIOPHOTONICS 2021; 14:e202000424. [PMID: 33210464 DOI: 10.1002/jbio.202000424] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/21/2020] [Revised: 11/13/2020] [Accepted: 11/15/2020] [Indexed: 06/11/2023]
Abstract
The goal of this project is to identify any in-depth benefits and drawbacks in the diagnosis of amalgam tattoos and other pigmented intraoral lesions using hyperspectral imagery collected from amalgam tattoos, benign, and malignant melanocytic neoplasms. Software solutions capable of classifying pigmented lesions of the skin already exist, but conventional red, green and blue images may be reaching an upper limit in their performance. Emerging technologies, such as hyperspectral imaging (HSI) utilize more than a hundred, continuous data channels, while also collecting data in the infrared. A total of 18 paraffin-embedded human tissue specimens of dark pigmented intraoral lesions (including the lip) were analyzed using visible and near-infrared (VIS-NIR) hyperspectral imagery obtained from HE-stained histopathological slides. Transmittance data were collected between 450 and 900 nm using a snapshot camera mounted to a microscope with a halogen light source. VIS-NIR spectra collected from different specimens, such as melanocytic cells and other tissues (eg, epithelium), produced distinct and diagnostic spectra that were used to identify these materials in several regions of interest, making it possible to distinguish between intraoral amalgam tattoos (intramucosal metallic foreign bodies) and melanocytic lesions of the intraoral mucosa and the lip (each with P < .01 using the independent t test). HSI is presented as a diagnostic tool for the rapidly growing field of digital pathology. In this preliminary study, amalgam tattoos were reliably differentiated from melanocytic lesions of the oral cavity and the lip.
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Affiliation(s)
- Johannes Laimer
- University Hospital for Craniomaxillofacial and Oral Surgery, Medical University of Innsbruck, Innsbruck, Austria
| | | | - Tom Helten
- University Hospital for Craniomaxillofacial and Oral Surgery, Medical University of Innsbruck, Innsbruck, Austria
| | - Barbara Kofler
- University Hospital of Otorhinolaryngology, Medical University of Innsbruck, Innsbruck, Austria
| | - Bettina Zelger
- Institute of Pathology, Neuropathology and Molecular Pathology, Medical University of Innsbruck, Innsbruck, Austria
| | - Andrea Brunner
- Institute of Pathology, Neuropathology and Molecular Pathology, Medical University of Innsbruck, Innsbruck, Austria
| | - Bernhard Zelger
- University Hospital for Dermatology, Venereology and Allergology, Medical University of Innsbruck, Innsbruck, Austria
| | - Christian W Huck
- Institute of Analytical Chemistry and Radiochemistry, Leopold Franzens University of Innsbruck, Innsbruck, Austria
| | - Michelle Tappert
- Hyperspectral Intelligence Inc., Gibsons, British Columbia, Canada
| | - Derek Rogge
- Hyperspectral Intelligence Inc., Gibsons, British Columbia, Canada
| | - Michael Schirmer
- Department of Internal Medicine, Clinic II, Medical University of Innsbruck, Innsbruck, Austria
| | - Johannes D Pallua
- Institute of Pathology, Neuropathology and Molecular Pathology, Medical University of Innsbruck, Innsbruck, Austria
- University Hospital for Orthopedics and Traumatology, Medical University of Innsbruck, Innsbruck, Austria
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Afara IO, Shaikh R, Nippolainen E, Querido W, Torniainen J, Sarin JK, Kandel S, Pleshko N, Töyräs J. Characterization of connective tissues using near-infrared spectroscopy and imaging. Nat Protoc 2021; 16:1297-1329. [PMID: 33462441 DOI: 10.1038/s41596-020-00468-z] [Citation(s) in RCA: 24] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/18/2020] [Accepted: 11/20/2020] [Indexed: 02/06/2023]
Abstract
Near-infrared (NIR) spectroscopy is a powerful analytical method for rapid, non-destructive and label-free assessment of biological materials. Compared to mid-infrared spectroscopy, NIR spectroscopy excels in penetration depth, allowing intact biological tissue assessment, albeit at the cost of reduced molecular specificity. Furthermore, it is relatively safe compared to Raman spectroscopy, with no risk of laser-induced photothermal damage. A typical NIR spectroscopy workflow for biological tissue characterization involves sample preparation, spectral acquisition, pre-processing and analysis. The resulting spectrum embeds intrinsic information on the tissue's biomolecular, structural and functional properties. Here we demonstrate the analytical power of NIR spectroscopy for exploratory and diagnostic applications by providing instructions for acquiring NIR spectra, maps and images in biological tissues. By adapting and extending this protocol from the demonstrated application in connective tissues to other biological tissues, we expect that a typical NIR spectroscopic study can be performed by a non-specialist user to characterize biological tissues in basic research or clinical settings. We also describe how to use this protocol for exploratory study on connective tissues, including differentiating among ligament types, non-destructively monitoring changes in matrix formation during engineered cartilage development, mapping articular cartilage proteoglycan content across bovine patella and spectral imaging across the depth-wise zones of articular cartilage and subchondral bone. Depending on acquisition mode and experiment objectives, a typical exploratory study can be completed within 6 h, including sample preparation and data analysis.
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Affiliation(s)
- Isaac O Afara
- Department of Applied Physics, University of Eastern Finland, Kuopio, Finland.
- School of Information Technology and Electrical Engineering, The University of Queensland, Brisbane, Queensland, Australia.
| | - Rubina Shaikh
- Department of Applied Physics, University of Eastern Finland, Kuopio, Finland
- Diagnostic Imaging Centre, Kuopio University Hospital, Kuopio, Finland
| | - Ervin Nippolainen
- Department of Applied Physics, University of Eastern Finland, Kuopio, Finland
| | - William Querido
- Department of Bioengineering, Temple University, Philadelphia, PA, USA
| | - Jari Torniainen
- Department of Applied Physics, University of Eastern Finland, Kuopio, Finland
| | - Jaakko K Sarin
- Diagnostic Imaging Centre, Kuopio University Hospital, Kuopio, Finland
| | - Shital Kandel
- Department of Bioengineering, Temple University, Philadelphia, PA, USA
| | - Nancy Pleshko
- Department of Bioengineering, Temple University, Philadelphia, PA, USA
| | - Juha Töyräs
- Department of Applied Physics, University of Eastern Finland, Kuopio, Finland
- School of Information Technology and Electrical Engineering, The University of Queensland, Brisbane, Queensland, Australia
- Diagnostic Imaging Centre, Kuopio University Hospital, Kuopio, Finland
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