1
|
Bae H, Rodewald M, Meyer-Zedler T, Bocklitz TW, Matz G, Messerschmidt B, Press AT, Bauer M, Guntinas-Lichius O, Stallmach A, Schmitt M, Popp J. Feasibility studies of multimodal nonlinear endoscopy using multicore fiber bundles for remote scanning from tissue sections to bulk organs. Sci Rep 2023; 13:13779. [PMID: 37612362 PMCID: PMC10447453 DOI: 10.1038/s41598-023-40944-6] [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: 06/08/2023] [Accepted: 08/18/2023] [Indexed: 08/25/2023] Open
Abstract
Here, we report on the development and application of a compact multi-core fiber optical probe for multimodal non-linear imaging, combining the label-free modalities of Coherent Anti-Stokes Raman Scattering, Second Harmonic Generation, and Two-Photon Excited Fluorescence. Probes of this multi-core fiber design avoid moving and voltage-carrying parts at the distal end, thus providing promising improved compatibility with clinical requirements over competing implementations. The performance characteristics of the probe are established using thin cryo-sections and artificial targets before the applicability to clinically relevant samples is evaluated using ex vivo bulk human and porcine intestine tissues. After image reconstruction to counteract the data's inherently pixelated nature, the recorded images show high image quality and morpho-chemical conformity on the tissue level compared to multimodal non-linear images obtained with a laser-scanning microscope using a standard microscope objective. Furthermore, a simple yet effective reconstruction procedure is presented and demonstrated to yield satisfactory results. Finally, a clear pathway for further developments to facilitate a translation of the multimodal fiber probe into real-world clinical evaluation and application is outlined.
Collapse
Affiliation(s)
- Hyeonsoo Bae
- Leibniz Institute of Photonic Technology (Leibniz IPHT), Member of Leibniz Health Technologies, Member of the Leibniz Centre for Photonics in Infection Research (LPI), PO Box 100239, 07702, Jena, Germany
- Institute of Physical Chemistry and Abbe Center of Photonics, Friedrich-Schiller University Jena, Helmholtzweg 4, 07743, Jena, Germany
- Center for Sepsis Control and Care (CSCC), Jena University Hospital, Erlanger Allee 101, 07747, Jena, Germany
| | - Marko Rodewald
- Leibniz Institute of Photonic Technology (Leibniz IPHT), Member of Leibniz Health Technologies, Member of the Leibniz Centre for Photonics in Infection Research (LPI), PO Box 100239, 07702, Jena, Germany
- Institute of Physical Chemistry and Abbe Center of Photonics, Friedrich-Schiller University Jena, Helmholtzweg 4, 07743, Jena, Germany
| | - Tobias Meyer-Zedler
- Leibniz Institute of Photonic Technology (Leibniz IPHT), Member of Leibniz Health Technologies, Member of the Leibniz Centre for Photonics in Infection Research (LPI), PO Box 100239, 07702, Jena, Germany
- Institute of Physical Chemistry and Abbe Center of Photonics, Friedrich-Schiller University Jena, Helmholtzweg 4, 07743, Jena, Germany
| | - Thomas W Bocklitz
- Institute of Physical Chemistry and Abbe Center of Photonics, Friedrich-Schiller University Jena, Helmholtzweg 4, 07743, Jena, Germany
| | - Gregor Matz
- GRINTECH GmbH, Schillerstraße 1, 07745, Jena, Germany
| | | | - Adrian T Press
- Center for Sepsis Control and Care (CSCC), Jena University Hospital, Erlanger Allee 101, 07747, Jena, Germany
- Department of Anesthesiology and Intensive Care Medicine, Jena University Hospital, Am Klinikum 1, 07747, Jena, Germany
- Medical Faculty, Friedrich-Schiller University Jena, Kastanienstr. 1, 07747, Jena, Germany
| | - Michael Bauer
- Center for Sepsis Control and Care (CSCC), Jena University Hospital, Erlanger Allee 101, 07747, Jena, Germany
- Department of Anesthesiology and Intensive Care Medicine, Jena University Hospital, Am Klinikum 1, 07747, Jena, Germany
| | - Orlando Guntinas-Lichius
- Department of Otorhinolaryngology, Jena University Hospital, Am Klinikum 1, 07747, Jena, Germany
| | - Andreas Stallmach
- Department of Internal Medicine IV, Jena University Hospital, Am Klinikum 1, 07747, Jena, Germany
| | - Michael Schmitt
- Institute of Physical Chemistry and Abbe Center of Photonics, Friedrich-Schiller University Jena, Helmholtzweg 4, 07743, Jena, Germany
| | - Juergen Popp
- Leibniz Institute of Photonic Technology (Leibniz IPHT), Member of Leibniz Health Technologies, Member of the Leibniz Centre for Photonics in Infection Research (LPI), PO Box 100239, 07702, Jena, Germany.
- Institute of Physical Chemistry and Abbe Center of Photonics, Friedrich-Schiller University Jena, Helmholtzweg 4, 07743, Jena, Germany.
| |
Collapse
|
2
|
Higginson JA, Breik O, Thompson AH, Ashrafian H, Hardman JC, Takats Z, Paleri V, Dhanda J. Diagnostic accuracy of intraoperative margin assessment techniques in surgery for head and neck squamous cell carcinoma: A meta-analysis. Oral Oncol 2023; 142:106419. [PMID: 37178655 DOI: 10.1016/j.oraloncology.2023.106419] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/17/2023] [Revised: 04/18/2023] [Accepted: 05/04/2023] [Indexed: 05/15/2023]
Abstract
BACKGROUND Positive margins following head and neck squamous cell carcinoma (HNSCC) surgery lead to significant morbidity and mortality. Existing Intraoperative Margin Assessment (IMA) techniques are not widely used due to limitations in sampling technique, time constraints and resource requirements. We performed a meta-analysis of the diagnostic performance of existing IMA techniques in HNSCC, providing a benchmark against which emerging techniques may be judged. METHODS The study was conducted according to Preferred Reporting Items for Systematic Reviews and Meta-analyses (PRISMA) reporting guidelines. Studies were included if they reported diagnostic metrics of techniques used during HNSCC surgery, compared with permanent histopathology. Screening, manuscript review and data extraction was performed by multiple independent observers. Pooled sensitivity and specificity were estimated using the bivariate random effects model. RESULTS From an initial 2344 references, 35 studies were included for meta-analysis. Sensitivity (Sens), specificity (Spec), diagnostic odds ratio (DOR) and area under the receiver operating characteristic curve (AUROC) were calculated for each group (n, Sens, Spec, DOR, AUROC): frozen section = 13, 0.798, 0.991, 309.8, 0.976; tumour-targeted fluorescence (TTF) = 5, 0.957, 0.827, 66.4, 0.944; optical techniques = 10, 0.919, 0.855, 58.9, 0.925; touch imprint cytology = 3, 0.925, 0.988, 51.1, 0.919; topical staining = 4, 0.918, 0.759, 16.4, 0.833. CONCLUSIONS Frozen section and TTF had the best diagnostic performance. Frozen section is limited by sampling error. TTF shows promise but involves administration of a systemic agent. Neither is currently in widespread clinical use. Emerging techniques must demonstrate competitive diagnostic accuracy whilst allowing rapid, reliable, cost-effective results.
Collapse
Affiliation(s)
| | - Omar Breik
- School of Dentristy, University of Queensland, Australia
| | | | | | - John C Hardman
- International Centre for Recurrent Head and Neck Cancer, The Royal Marsden NHS Foundation Trust, UK
| | | | - Vinidh Paleri
- International Centre for Recurrent Head and Neck Cancer, The Royal Marsden NHS Foundation Trust, UK; Institute of Cancer Research, UK
| | - Jagtar Dhanda
- Department of Surgery, Brighton and Sussex Medical School, UK
| |
Collapse
|
3
|
Schmitt M, Meyer-Zedler T, Guntinas-Lichius O, Popp J. [Multimodal spectroscopic imaging : A new, powerful tool for intraoperative tumor diagnostics]. CHIRURGIE (HEIDELBERG, GERMANY) 2022; 93:948-955. [PMID: 35925143 DOI: 10.1007/s00104-022-01663-2] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Accepted: 05/19/2022] [Indexed: 06/15/2023]
Abstract
BACKGROUND The increasing number of cancer cases requires new imaging approaches for intraoperative tumor characterization. OBJECTIVE Utilization of new optical/photonic methods in combination with artificial intelligence (AI) approaches to address urgent challenges in clinical pathology in terms of intraoperative computational spectral histopathology. METHODS Multimodal nonlinear imaging by combining the spectroscopic methods coherent anti-Stokes Raman scattering (CARS), two-photon excited autofluorescence (TPEF), fluorescence lifetime imaging microscopy (FLIM), and second harmonic generation (SHG). RESULTS By using multimodal spectroscopic imaging, tissue morphochemistry, i.e., its morphology and molecular structure can be visualized in a label-free manner. The multimodal images can be automatically analyzed using AI-based image analysis approaches. For clinical application in terms of frozen section diagnostics or in vivo use, the presented multimodal imaging approach can be translated into a compact microscope or endoscopic probe concepts. CONCLUSIONS The synergistic combination of spectroscopic imaging modalities in combination with automated data analysis has great potential for fast and precise tumor diagnostics e.g., in terms of precise surgical guidance in laser or robotic surgery. Overall, intraoperative multimodal spectroscopic imaging may represent an innovative advancement for tumor diagnostics in the future, directly leading to improved patient care and significant cost savings.
Collapse
Affiliation(s)
- Michael Schmitt
- Institut für Physikalische Chemie und Abbe Center of Photonics, Friedrich-Schiller-Universität Jena, Jena, Deutschland
| | - Tobias Meyer-Zedler
- Leibniz Institut für Photonische Technologien, Mitglied Leibniz Gesundheitstechnologien, Albert-Einstein-Str. 9, 07745, Jena, Deutschland
| | - Orlando Guntinas-Lichius
- Klinik und Poliklinik für Hals-. Nasen- und Ohrenheilkunde, Universitätsklinikum Jena, Jena, Deutschland
| | - Juergen Popp
- Institut für Physikalische Chemie und Abbe Center of Photonics, Friedrich-Schiller-Universität Jena, Jena, Deutschland.
- Leibniz Institut für Photonische Technologien, Mitglied Leibniz Gesundheitstechnologien, Albert-Einstein-Str. 9, 07745, Jena, Deutschland.
| |
Collapse
|
4
|
CARS Imaging Advances Early Diagnosis of Cardiac Manifestation of Fabry Disease. Int J Mol Sci 2022; 23:ijms23105345. [PMID: 35628155 PMCID: PMC9142043 DOI: 10.3390/ijms23105345] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/12/2022] [Revised: 05/05/2022] [Accepted: 05/08/2022] [Indexed: 12/12/2022] Open
Abstract
Vibrational spectroscopy can detect characteristic biomolecular signatures and thus has the potential to support diagnostics. Fabry disease (FD) is a lipid disorder disease that leads to accumulations of globotriaosylceramide in different organs, including the heart, which is particularly critical for the patient’s prognosis. Effective treatment options are available if initiated at early disease stages, but many patients are late- or under-diagnosed. Since Coherent anti-Stokes Raman (CARS) imaging has a high sensitivity for lipid/protein shifts, we applied CARS as a diagnostic tool to assess cardiac FD manifestation in an FD mouse model. CARS measurements combined with multivariate data analysis, including image preprocessing followed by image clustering and data-driven modeling, allowed for differentiation between FD and control groups. Indeed, CARS identified shifts of lipid/protein content between the two groups in cardiac tissue visually and by subsequent automated bioinformatic discrimination with a mean sensitivity of 90–96%. Of note, this genotype differentiation was successful at a very early time point during disease development when only kidneys are visibly affected by globotriaosylceramide depositions. Altogether, the sensitivity of CARS combined with multivariate analysis allows reliable diagnostic support of early FD organ manifestation and may thus improve diagnosis, prognosis, and possibly therapeutic monitoring of FD.
Collapse
|
5
|
Zhang C, Aldana-Mendoza JA. Coherent Raman scattering microscopy for chemical imaging of biological systems. JPHYS PHOTONICS 2021. [DOI: 10.1088/2515-7647/abfd09] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/01/2023] Open
Abstract
Abstract
Coherent Raman scattering (CRS) processes, including both the coherent anti-Stokes Raman scattering and stimulated Raman scattering, have been utilized in state-of-the-art microscopy platforms for chemical imaging of biological samples. The key advantage of CRS microscopy over fluorescence microscopy is label-free, which is an attractive characteristic for modern biological and medical sciences. Besides, CRS has other advantages such as higher selectivity to metabolites, no photobleaching, and narrow peak width. These features have brought fast-growing attention to CRS microscopy in biological research. In this review article, we will first briefly introduce the history of CRS microscopy, and then explain the theoretical background of the CRS processes in detail using the classical approach. Next, we will cover major instrumentation techniques of CRS microscopy. Finally, we will enumerate examples of recent applications of CRS imaging in biological and medical sciences.
Collapse
|
6
|
Pradhan P, Meyer T, Vieth M, Stallmach A, Waldner M, Schmitt M, Popp J, Bocklitz T. Computational tissue staining of non-linear multimodal imaging using supervised and unsupervised deep learning. BIOMEDICAL OPTICS EXPRESS 2021; 12:2280-2298. [PMID: 33996229 PMCID: PMC8086483 DOI: 10.1364/boe.415962] [Citation(s) in RCA: 14] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/30/2020] [Revised: 01/28/2021] [Accepted: 02/17/2021] [Indexed: 05/24/2023]
Abstract
Hematoxylin and Eosin (H&E) staining is the 'gold-standard' method in histopathology. However, standard H&E staining of high-quality tissue sections requires long sample preparation times including sample embedding, which restricts its application for 'real-time' disease diagnosis. Due to this reason, a label-free alternative technique like non-linear multimodal (NLM) imaging, which is the combination of three non-linear optical modalities including coherent anti-Stokes Raman scattering, two-photon excitation fluorescence and second-harmonic generation, is proposed in this work. To correlate the information of the NLM images with H&E images, this work proposes computational staining of NLM images using deep learning models in a supervised and an unsupervised approach. In the supervised and the unsupervised approach, conditional generative adversarial networks (CGANs) and cycle conditional generative adversarial networks (cycle CGANs) are used, respectively. Both CGAN and cycle CGAN models generate pseudo H&E images, which are quantitatively analyzed based on mean squared error, structure similarity index and color shading similarity index. The mean of the three metrics calculated for the computationally generated H&E images indicate significant performance. Thus, utilizing CGAN and cycle CGAN models for computational staining is beneficial for diagnostic applications without performing a laboratory-based staining procedure. To the author's best knowledge, it is the first time that NLM images are computationally stained to H&E images using GANs in an unsupervised manner.
Collapse
Affiliation(s)
- Pranita Pradhan
- Institute of Physical Chemistry and Abbe Center of Photonics, Friedrich-Schiller-University, Jena, Germany
- Leibniz Institute of Photonic Technology, Member of Leibniz Health Technologies Jena, Germany
| | - Tobias Meyer
- Leibniz Institute of Photonic Technology, Member of Leibniz Health Technologies Jena, Germany
| | - Michael Vieth
- Institute of Pathology, Klinikum Bayreuth, Bayreuth, Germany
| | - Andreas Stallmach
- Department of Internal Medicine IV (Gastroenterology, Hepatology, and Infectious Diseases), Jena University Hospital, Jena, Germany
| | - Maximilian Waldner
- Erlangen Graduate School in Advanced Optical Technologies (SAOT), Friedrich-Alexander University of Erlangen-Nuremberg, 91052 Erlangen, Germany
- Medical Department 1, Friedrich-Alexander University of Erlangen-Nuremberg, Erlangen, Germany
| | - Michael Schmitt
- Institute of Physical Chemistry and Abbe Center of Photonics, Friedrich-Schiller-University, Jena, Germany
| | - Juergen Popp
- Institute of Physical Chemistry and Abbe Center of Photonics, Friedrich-Schiller-University, Jena, Germany
- Leibniz Institute of Photonic Technology, Member of Leibniz Health Technologies Jena, Germany
| | - Thomas Bocklitz
- Institute of Physical Chemistry and Abbe Center of Photonics, Friedrich-Schiller-University, Jena, Germany
- Leibniz Institute of Photonic Technology, Member of Leibniz Health Technologies Jena, Germany
| |
Collapse
|
7
|
Ramya AN, Arya JS, Madhukrishnan M, Shamjith S, Vidyalekshmi MS, Maiti KK. Raman Imaging: An Impending Approach Towards Cancer Diagnosis. Chem Asian J 2021; 16:409-422. [PMID: 33443291 DOI: 10.1002/asia.202001340] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/23/2020] [Revised: 01/11/2021] [Indexed: 12/18/2022]
Abstract
In accordance with the recent studies, Raman spectroscopy is well experimented as a highly sensitive analytical and imaging technique in biomedical research, mainly for various disease diagnosis including cancer. In comparison with other imaging modalities, Raman spectroscopy facilitate numerous assistances owing to its low background signal, immense spatial resolution, high chemical specificity, multiplexing capability, excellent photo stability and non-invasive detection capability. In cancer diagnosis Raman imaging intervened as a promising investigative tool to provide molecular level information to differentiate the cancerous vs non-cancerous cells, tissues and even in body fluids. Anciently, spontaneous Raman scattering is very feeble due to its low signal intensity and long acquisition time but new advanced techniques like coherent Raman scattering (CRS) and surface enhanced Raman scattering (SERS) gradually superseded these issues. So, the present review focuses on the recent developments and applications of Raman spectroscopy-based imaging techniques for cancer diagnosis.
Collapse
Affiliation(s)
- Adukkadan N Ramya
- Chemical Sciences and Technology Division (CSTD), CSIR-National Institute for Interdisciplinary Science and Technology (CSIR-NIIST), Thiruvananthapuram, 695019, Kerala, India.,Academy of Scientific and Innovative Research (AcSIR), Ghaziabad, 201002, India
| | - Jayadev S Arya
- Chemical Sciences and Technology Division (CSTD), CSIR-National Institute for Interdisciplinary Science and Technology (CSIR-NIIST), Thiruvananthapuram, 695019, Kerala, India.,Academy of Scientific and Innovative Research (AcSIR), Ghaziabad, 201002, India
| | - Murali Madhukrishnan
- Chemical Sciences and Technology Division (CSTD), CSIR-National Institute for Interdisciplinary Science and Technology (CSIR-NIIST), Thiruvananthapuram, 695019, Kerala, India.,Academy of Scientific and Innovative Research (AcSIR), Ghaziabad, 201002, India
| | - Shanmughan Shamjith
- Chemical Sciences and Technology Division (CSTD), CSIR-National Institute for Interdisciplinary Science and Technology (CSIR-NIIST), Thiruvananthapuram, 695019, Kerala, India.,Academy of Scientific and Innovative Research (AcSIR), Ghaziabad, 201002, India
| | - Murukan S Vidyalekshmi
- Chemical Sciences and Technology Division (CSTD), CSIR-National Institute for Interdisciplinary Science and Technology (CSIR-NIIST), Thiruvananthapuram, 695019, Kerala, India.,Academy of Scientific and Innovative Research (AcSIR), Ghaziabad, 201002, India
| | - Kaustabh K Maiti
- Chemical Sciences and Technology Division (CSTD), CSIR-National Institute for Interdisciplinary Science and Technology (CSIR-NIIST), Thiruvananthapuram, 695019, Kerala, India.,Academy of Scientific and Innovative Research (AcSIR), Ghaziabad, 201002, India
| |
Collapse
|
8
|
Beletkaia E, Dashtbozorg B, Jansen RG, Ruers TJM, Offerhaus HL. Nonlinear multispectral imaging for tumor delineation. JOURNAL OF BIOMEDICAL OPTICS 2020; 25:JBO-200100RR. [PMID: 32885620 PMCID: PMC7470215 DOI: 10.1117/1.jbo.25.9.096001] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 04/23/2020] [Accepted: 08/21/2020] [Indexed: 06/11/2023]
Abstract
SIGNIFICANCE In breast-preserving tumor surgery, the inspection of the excised tissue boundaries for tumor residue is too slow to provide feedback during the surgery. The discovery of positive margins requires a new surgery which is difficult and associated with low success. If the re-excision could be done immediately this is believed to improve the success rate considerably. AIM Our aim is for a fast microscopic analysis that can be done directly on the excised tissue in or near the operating theatre. APPROACH We demonstrate the combination of three nonlinear imaging techniques at selected wavelengths to delineate tumor boundaries. We use hyperspectral coherent anti-Stokes Raman scattering (CARS), second harmonic generation (SHG), and two-photon excited fluorescence (TPF) on excised patient tissue. RESULTS We show the discriminatory power of each of the signals and demonstrate a sensitivity of 0.87 and a specificity of 0.95 using four CARS wavelengths in combination with SHG and TPF. We verify that the information is independent of sample treatment. CONCLUSIONS Nonlinear multispectral imaging can be used to accurately determine tumor boundaries. This demonstration using microscopy in the epi-direction directly on thick tissue slices brings this technology one step closer to clinical implementation.
Collapse
Affiliation(s)
- Elena Beletkaia
- Netherlands Cancer Institute, Department of Surgery, Amsterdam, Netherlands
| | - Behdad Dashtbozorg
- Netherlands Cancer Institute, Department of Surgery, Amsterdam, Netherlands
| | - Rubin G. Jansen
- University of Twente, Faculty of Science and Technology, Enschede, Netherlands
| | - Theo J. M. Ruers
- Netherlands Cancer Institute, Department of Surgery, Amsterdam, Netherlands
- University of Twente, Faculty of Science and Technology, Enschede, Netherlands
| | - Herman L. Offerhaus
- University of Twente, Faculty of Science and Technology, Enschede, Netherlands
| |
Collapse
|
9
|
Meyer T, Ackermann R, Kammel R, Schmitt M, Nolte S, Tünnermann A, Popp J. CARS-imaging guidance for fs-laser ablation precision surgery. Analyst 2020; 144:7310-7317. [PMID: 31686084 DOI: 10.1039/c9an01545k] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/18/2023]
Abstract
Due to ageing populations the number of tumors is increasing worldwide. Successful surgical treatment requires complete resection of tumors to reduce recurrence rates. To reach this goal, novel methods combining in vivo tumor and tumor margin detection with low invasive precision surgical tools are needed. Coherent anti-Stokes Raman scattering (CARS) imaging is a highly promising optical tool for visualizing tumors based on characteristic changes in tissue morphology and molecular composition, while fs-laser ablation is to date the most precise surgical tool established in ophthalmology. In this contribution, CARS imaging has been combined with fs-laser ablation as a new approach for image-guided precision surgery for the first time. CARS guided fs-ablation has been applied to ablate brain, liver, skin, muscular and vascular tissues with μm-precision using sub-100 fs pulses of μJ level. We demonstrate superior imaging performance and contrast as well as detection of tissue margins by coherent Raman microscopy in comparison to laser reflectance imaging. The combination of CARS-image-guided tissue ablation is a promising tool for minimally invasive surgeries particularly in the vicinity of functional structures in the future.
Collapse
Affiliation(s)
- Tobias Meyer
- Institute of Physical Chemistry and Abbe Center of Photonics, Friedrich-Schiller-Universität Jena, Albert-Einstein-Straße 6, D-07745 Jena, Germany.
| | | | | | | | | | | | | |
Collapse
|
10
|
Bocklitz T, Silge A, Bae H, Rodewald M, Legesse FB, Meyer T, Popp J. Non-invasive Imaging Techniques: From Histology to In Vivo Imaging : Chapter of Imaging in Oncology. Recent Results Cancer Res 2020; 216:795-812. [PMID: 32594407 DOI: 10.1007/978-3-030-42618-7_25] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/19/2022]
Abstract
In this chapter, we will introduce and review molecular-sensitive imaging techniques, which close the gap between ex vivo and in vivo analysis. In detail, we will introduce spontaneous Raman spectral imaging, coherent anti-Stokes Raman scattering (CARS), stimulated Raman scattering (SRS), second-harmonic generation (SHG) and third-harmonic generation (THG), two-photon excited fluorescence (TPEF), and fluorescence lifetime imaging (FLIM). After reviewing these imaging techniques, we shortly introduce chemometric methods and machine learning techniques, which are needed to use these imaging techniques in diagnostic applications.
Collapse
Affiliation(s)
- Thomas Bocklitz
- University of Jena, IPC, Helmholtzweg 4, 07743, Jena, Germany.
| | - Anja Silge
- University of Jena, IPC, Helmholtzweg 4, 07743, Jena, Germany
| | - Hyeonsoo Bae
- University of Jena, IPC, Helmholtzweg 4, 07743, Jena, Germany
| | - Marko Rodewald
- University of Jena, IPC, Helmholtzweg 4, 07743, Jena, Germany
| | | | - Tobias Meyer
- University of Jena, IPC, Helmholtzweg 4, 07743, Jena, Germany
| | - Jürgen Popp
- University of Jena, IPC, Helmholtzweg 4, 07743, Jena, Germany.
| |
Collapse
|
11
|
Ali N, Quansah E, Köhler K, Meyer T, Schmitt M, Popp J, Niendorf A, Bocklitz T. Automatic label‐free detection of breast cancer using nonlinear multimodal imaging and the convolutional neural network ResNet50. TRANSLATIONAL BIOPHOTONICS 2019. [DOI: 10.1002/tbio.201900003] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/24/2022] Open
Affiliation(s)
- Nairveen Ali
- Institute of Physical Chemistry and Abbe Center of Photonics (IPC)Friedrich‐Schiller‐University Jena Germany
- Leibniz Institute of Photonic Technology (Leibniz‐IPHT), Member of Leibniz Research Alliance 'Health Technologies' Jena Germany
| | - Elsie Quansah
- Institute of Physical Chemistry and Abbe Center of Photonics (IPC)Friedrich‐Schiller‐University Jena Germany
- Leibniz Institute of Photonic Technology (Leibniz‐IPHT), Member of Leibniz Research Alliance 'Health Technologies' Jena Germany
| | - Katarina Köhler
- Institut für Histologie, Zytologie und molekulare Diagnostik, Pathologie Hamburg‐West GmbH Hamburg Germany
| | - Tobias Meyer
- Institute of Physical Chemistry and Abbe Center of Photonics (IPC)Friedrich‐Schiller‐University Jena Germany
- Leibniz Institute of Photonic Technology (Leibniz‐IPHT), Member of Leibniz Research Alliance 'Health Technologies' Jena Germany
| | - Michael Schmitt
- Institute of Physical Chemistry and Abbe Center of Photonics (IPC)Friedrich‐Schiller‐University Jena Germany
- Leibniz Institute of Photonic Technology (Leibniz‐IPHT), Member of Leibniz Research Alliance 'Health Technologies' Jena Germany
| | - Jürgen Popp
- Institute of Physical Chemistry and Abbe Center of Photonics (IPC)Friedrich‐Schiller‐University Jena Germany
- Leibniz Institute of Photonic Technology (Leibniz‐IPHT), Member of Leibniz Research Alliance 'Health Technologies' Jena Germany
- Center for Sepsis Control and Care (CSCC)Jena University Hospital Jena Germany
- InfectoGnostics, Forschungscampus Jena Jena Germany
| | - Axel Niendorf
- Institut für Histologie, Zytologie und molekulare Diagnostik, Pathologie Hamburg‐West GmbH Hamburg Germany
| | - Thomas Bocklitz
- Institute of Physical Chemistry and Abbe Center of Photonics (IPC)Friedrich‐Schiller‐University Jena Germany
- Leibniz Institute of Photonic Technology (Leibniz‐IPHT), Member of Leibniz Research Alliance 'Health Technologies' Jena Germany
| |
Collapse
|
12
|
Krafft C, Popp J. Medical needs for translational biophotonics with the focus on Raman‐based methods. TRANSLATIONAL BIOPHOTONICS 2019. [DOI: 10.1002/tbio.201900018] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/22/2022] Open
Affiliation(s)
| | - Jürgen Popp
- Leibniz Institute of Photonic Technology Jena Germany
- Institute of Physical Chemistry and Abbe Center of PhotonicsFriedrich Schiller University Jena Jena Germany
| |
Collapse
|
13
|
Multimodal Nonlinear Microscopy for Therapy Monitoring of Cold Atmospheric Plasma Treatment. MICROMACHINES 2019; 10:mi10090564. [PMID: 31454918 PMCID: PMC6780561 DOI: 10.3390/mi10090564] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 07/29/2019] [Revised: 08/19/2019] [Accepted: 08/21/2019] [Indexed: 02/07/2023]
Abstract
Here we report on a non-linear spectroscopic method for visualization of cold atmospheric plasma (CAP)-induced changes in tissue for reaching a new quality level of CAP application in medicine via online monitoring of wound or cancer treatment. A combination of coherent anti-Stokes Raman scattering (CARS), two-photon fluorescence lifetime imaging (2P-FLIM) and second harmonic generation (SHG) microscopy has been used for non-invasive and label-free detection of CAP-induced changes on human skin and mucosa samples. By correlation with histochemical staining, the observed local increase in fluorescence could be assigned to melanin. CARS and SHG prove the integrity of the tissue structure, visualize tissue morphology and composition. The influence of plasma effects by variation of plasma parameters e.g., duration of treatment, gas composition and plasma source has been evaluated. Overall quantitative spectroscopic markers could be identified for a direct monitoring of CAP-treated tissue areas, which is very important for translating CAPs into clinical routine.
Collapse
|
14
|
Heuke S, Unger K, Khadir S, Belkebir K, Chaumet PC, Rigneault H, Sentenac A. Coherent anti-Stokes Raman Fourier ptychography. OPTICS EXPRESS 2019; 27:23497-23514. [PMID: 31510626 PMCID: PMC6825601 DOI: 10.1364/oe.27.023497] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/22/2019] [Revised: 06/25/2019] [Accepted: 06/25/2019] [Indexed: 05/16/2023]
Abstract
We present a theoretical and numerical study of coherent anti-Stokes Raman scattering Fourier ptychography microscopy (CARS-FPM), a scheme that has not been considered so far in the previously reported CARS wide-field imaging schemes. In this approach, the distribution of the Raman scatterer density of the sample is reconstructed numerically from CARS images obtained under various angles of incidences of the pump or Stokes beam. Our inversion procedure is based on an accurate vectorial model linking the CARS image to the sample and yields both the real and imaginary parts of the susceptibility, the latter giving access to the Raman information, with an improved resolution.
Collapse
Affiliation(s)
- Sandro Heuke
- Aix Marseille Univ, CNRS, Centrale Marseille, Institut Fresnel, Marseille,
France
| | - Kevin Unger
- Aix Marseille Univ, CNRS, Centrale Marseille, Institut Fresnel, Marseille,
France
| | - Samira Khadir
- Aix Marseille Univ, CNRS, Centrale Marseille, Institut Fresnel, Marseille,
France
| | - Kamal Belkebir
- Aix Marseille Univ, CNRS, Centrale Marseille, Institut Fresnel, Marseille,
France
| | - Patrick C. Chaumet
- Aix Marseille Univ, CNRS, Centrale Marseille, Institut Fresnel, Marseille,
France
| | - Hervé Rigneault
- Aix Marseille Univ, CNRS, Centrale Marseille, Institut Fresnel, Marseille,
France
| | - Anne Sentenac
- Aix Marseille Univ, CNRS, Centrale Marseille, Institut Fresnel, Marseille,
France
| |
Collapse
|
15
|
Yarbakht M, Pradhan P, Köse-Vogel N, Bae H, Stengel S, Meyer T, Schmitt M, Stallmach A, Popp J, Bocklitz TW, Bruns T. Nonlinear Multimodal Imaging Characteristics of Early Septic Liver Injury in a Mouse Model of Peritonitis. Anal Chem 2019; 91:11116-11121. [DOI: 10.1021/acs.analchem.9b01746] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/06/2023]
Affiliation(s)
- Melina Yarbakht
- Leibniz Institute of Photonic Technology, Member of Leibniz Health Technology, 07745 Jena, Germany
| | - Pranita Pradhan
- Institute of Physical Chemistry and Abbe Center of Photonics, Friedrich-Schiller University, 07743 Jena, Germany
- Leibniz Institute of Photonic Technology, Member of Leibniz Health Technology, 07745 Jena, Germany
| | | | - Hyeonsoo Bae
- Leibniz Institute of Photonic Technology, Member of Leibniz Health Technology, 07745 Jena, Germany
| | | | - Tobias Meyer
- Institute of Physical Chemistry and Abbe Center of Photonics, Friedrich-Schiller University, 07743 Jena, Germany
- Leibniz Institute of Photonic Technology, Member of Leibniz Health Technology, 07745 Jena, Germany
| | - Michael Schmitt
- Institute of Physical Chemistry and Abbe Center of Photonics, Friedrich-Schiller University, 07743 Jena, Germany
- Leibniz Institute of Photonic Technology, Member of Leibniz Health Technology, 07745 Jena, Germany
| | | | - Jürgen Popp
- Institute of Physical Chemistry and Abbe Center of Photonics, Friedrich-Schiller University, 07743 Jena, Germany
- Leibniz Institute of Photonic Technology, Member of Leibniz Health Technology, 07745 Jena, Germany
| | - Thomas Wilhelm Bocklitz
- Institute of Physical Chemistry and Abbe Center of Photonics, Friedrich-Schiller University, 07743 Jena, Germany
- Leibniz Institute of Photonic Technology, Member of Leibniz Health Technology, 07745 Jena, Germany
| | - Tony Bruns
- Department of Medicine III, University Hospital RWTH Aachen, 52074 Aachen, Germany
| |
Collapse
|
16
|
Zhang L, Wu Y, Zheng B, Su L, Chen Y, Ma S, Hu Q, Zou X, Yao L, Yang Y, Chen L, Mao Y, Chen Y, Ji M. Rapid histology of laryngeal squamous cell carcinoma with deep-learning based stimulated Raman scattering microscopy. Theranostics 2019; 9:2541-2554. [PMID: 31131052 PMCID: PMC6526002 DOI: 10.7150/thno.32655] [Citation(s) in RCA: 75] [Impact Index Per Article: 15.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/29/2018] [Accepted: 03/25/2019] [Indexed: 02/06/2023] Open
Abstract
Maximal resection of tumor while preserving the adjacent healthy tissue is particularly important for larynx surgery, hence precise and rapid intraoperative histology of laryngeal tissue is crucial for providing optimal surgical outcomes. We hypothesized that deep-learning based stimulated Raman scattering (SRS) microscopy could provide automated and accurate diagnosis of laryngeal squamous cell carcinoma on fresh, unprocessed surgical specimens without fixation, sectioning or staining. Methods: We first compared 80 pairs of adjacent frozen sections imaged with SRS and standard hematoxylin and eosin histology to evaluate their concordance. We then applied SRS imaging on fresh surgical tissues from 45 patients to reveal key diagnostic features, based on which we have constructed a deep learning based model to generate automated histologic results. 18,750 SRS fields of views were used to train and cross-validate our 34-layered residual convolutional neural network, which was used to classify 33 untrained fresh larynx surgical samples into normal and neoplasia. Furthermore, we simulated intraoperative evaluation of resection margins on totally removed larynxes. Results: We demonstrated near-perfect diagnostic concordance (Cohen's kappa, κ > 0.90) between SRS and standard histology as evaluated by three pathologists. And deep-learning based SRS correctly classified 33 independent surgical specimens with 100% accuracy. We also demonstrated that our method could identify tissue neoplasia at the simulated resection margins that appear grossly normal with naked eyes. Conclusion: Our results indicated that SRS histology integrated with deep learning algorithm provides potential for delivering rapid intraoperative diagnosis that could aid the surgical management of laryngeal cancer.
Collapse
Affiliation(s)
- Lili Zhang
- State Key Laboratory of Surface Physics and Department of Physics, Fudan University, Shanghai 200433, China
- Human Phenome Institute, Multiscale Research Institute of Complex Systems, Key Laboratory of Micro and Nano Photonic Structures (Ministry of Education), Fudan University, Shanghai 200433, China
| | - Yongzheng Wu
- State Key Laboratory of Surface Physics and Department of Physics, Fudan University, Shanghai 200433, China
| | - Bin Zheng
- Department of Otolaryngology, Zhejiang Provincial People's Hospital, People's Hospital of Hangzhou Medical College, Hangzhou 310014, China
| | - Lizhong Su
- Department of Otolaryngology, Zhejiang Provincial People's Hospital, People's Hospital of Hangzhou Medical College, Hangzhou 310014, China
| | - Yuan Chen
- Department of Pathology, Zhejiang Provincial People's Hospital, People's Hospital of Hangzhou Medical College, Hangzhou 310014, China
| | - Shuang Ma
- Department of Pathology, Zhejiang Provincial People's Hospital, People's Hospital of Hangzhou Medical College, Hangzhou 310014, China
| | - Qinqin Hu
- Department of Pathology, Zhejiang Provincial People's Hospital, People's Hospital of Hangzhou Medical College, Hangzhou 310014, China
| | - Xiang Zou
- Department of Neurosurgery, Department of Pancreatic Surgery, Huashan Hospital, Fudan University, Shanghai 200040, China
| | - Lie Yao
- Department of Neurosurgery, Department of Pancreatic Surgery, Huashan Hospital, Fudan University, Shanghai 200040, China
| | - Yinlong Yang
- Department of Breast Surgery, Fudan University Shanghai Cancer Center; Department of Oncology, Shanghai Medical College; Fudan University, Shanghai 200040, China
| | - Liang Chen
- Department of Neurosurgery, Department of Pancreatic Surgery, Huashan Hospital, Fudan University, Shanghai 200040, China
| | - Ying Mao
- Department of Neurosurgery, Department of Pancreatic Surgery, Huashan Hospital, Fudan University, Shanghai 200040, China
| | - Yan Chen
- State Key Laboratory of Surface Physics and Department of Physics, Fudan University, Shanghai 200433, China
| | - Minbiao Ji
- State Key Laboratory of Surface Physics and Department of Physics, Fudan University, Shanghai 200433, China
- Human Phenome Institute, Multiscale Research Institute of Complex Systems, Key Laboratory of Micro and Nano Photonic Structures (Ministry of Education), Fudan University, Shanghai 200433, China
| |
Collapse
|
17
|
Rodner E, Bocklitz T, von Eggeling F, Ernst G, Chernavskaia O, Popp J, Denzler J, Guntinas-Lichius O. Fully convolutional networks in multimodal nonlinear microscopy images for automated detection of head and neck carcinoma: Pilot study. Head Neck 2018; 41:116-121. [PMID: 30548511 DOI: 10.1002/hed.25489] [Citation(s) in RCA: 16] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/21/2017] [Revised: 03/11/2018] [Accepted: 07/05/2018] [Indexed: 12/18/2022] Open
Abstract
BACKGROUND A fully convolutional neural networks (FCN)-based automated image analysis algorithm to discriminate between head and neck cancer and noncancerous epithelium based on nonlinear microscopic images was developed. METHODS Head and neck cancer sections were used for standard histopathology and co-registered with multimodal images from the same sections using the combination of coherent anti-Stokes Raman scattering, two-photon excited fluorescence, and second harmonic generation microscopy. The images analyzed with semantic segmentation using a FCN for four classes: cancer, normal epithelium, background, and other tissue types. RESULTS A total of 114 images of 12 patients were analyzed. Using a patch score aggregation, the average recognition rate and an overall recognition rate or the four classes were 88.9% and 86.7%, respectively. A total of 113 seconds were needed to process a whole-slice image in the dataset. CONCLUSION Multimodal nonlinear microscopy in combination with automated image analysis using FCN seems to be a promising technique for objective differentiation between head and neck cancer and noncancerous epithelium.
Collapse
Affiliation(s)
- Erik Rodner
- Department of Computer Science, Friedrich Schiller University, Jena, Germany.,Corporate Research and Technology, Carl Zeiss AG, Jena, Germany
| | - Thomas Bocklitz
- Institute of Physical Chemistry and Abbe Center of Photonics, Friedrich Schiller University, Jena, Germany.,Leibniz Institute of Photonic Technology, Jena, Germany
| | - Ferdinand von Eggeling
- Institute of Physical Chemistry and Abbe Center of Photonics, Friedrich Schiller University, Jena, Germany.,Leibniz Institute of Photonic Technology, Jena, Germany.,Department of Otorhinolaryngology, Jena University Hospital, Jena, Germany
| | - Günther Ernst
- Department of Otorhinolaryngology, Jena University Hospital, Jena, Germany
| | | | - Jürgen Popp
- Institute of Physical Chemistry and Abbe Center of Photonics, Friedrich Schiller University, Jena, Germany.,Leibniz Institute of Photonic Technology, Jena, Germany
| | - Joachim Denzler
- Department of Computer Science, Friedrich Schiller University, Jena, Germany
| | | |
Collapse
|
18
|
Hoffmann F, Umbreit C, Krüger T, Pelzel D, Ernst G, Kniemeyer O, Guntinas-Lichius O, Berndt A, von Eggeling F. Identification of Proteomic Markers in Head and Neck Cancer Using MALDI-MS Imaging, LC-MS/MS, and Immunohistochemistry. Proteomics Clin Appl 2018; 13:e1700173. [PMID: 30411850 DOI: 10.1002/prca.201700173] [Citation(s) in RCA: 27] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/13/2018] [Revised: 10/29/2018] [Indexed: 12/12/2022]
Abstract
PURPOSE The heterogeneity of squamous cell carcinoma tissue greatly complicates diagnosis and individualized therapy. Therefore, characterizing the heterogeneity of tissue spatially and identifying appropriate biomarkers is crucial. MALDI-MS imaging (MSI) is capable of analyzing spatially resolved tissue biopsies on a molecular level. EXPERIMENTAL DESIGN MALDI-MSI is used on snap frozen and formalin-fixed and paraffin-embedded (FFPE) tissue samples from patients with head and neck cancer (HNC) to analyze m/z values localized in tumor and nontumor regions. Peptide identification is performed using LC-MS/MS and immunohistochemistry (IHC). RESULTS In both FFPE and frozen tissue specimens, eight characteristic masses of the tumor's epithelial region are found. Using LC-MS/MS, the peaks are identified as vimentin, keratin type II, nucleolin, heat shock protein 90, prelamin-A/C, junction plakoglobin, and PGAM1. Lastly, vimentin, nucleolin, and PGAM1 are verified with IHC. CONCLUSIONS AND CLINICAL RELEVANCE The combination of MALDI-MSI, LC-MS/MS, and subsequent IHC furnishes a tool suitable for characterizing the molecular heterogeneity of tissue. It is also suited for use in identifying new representative biomarkers to enable a more individualized therapy.
Collapse
Affiliation(s)
- Franziska Hoffmann
- Department of Otorhinolaryngology, Jena University Hospital, Jena, Germany
| | - Claudia Umbreit
- Department of Otorhinolaryngology, Jena University Hospital, Jena, Germany.,Institute of Forensic Medicine, Section Pathology, Jena University Hospital, Jena, Germany
| | - Thomas Krüger
- Department of Molecular and Applied Microbiology, Leibniz Institute for Natural Product Research and Infection Biology, Hans Knöll Institute, Jena, Germany
| | - Daniela Pelzel
- Department of Otorhinolaryngology, Jena University Hospital, Jena, Germany
| | - Günther Ernst
- Department of Otorhinolaryngology, Jena University Hospital, Jena, Germany
| | - Olaf Kniemeyer
- Department of Molecular and Applied Microbiology, Leibniz Institute for Natural Product Research and Infection Biology, Hans Knöll Institute, Jena, Germany
| | | | - Alexander Berndt
- Institute of Forensic Medicine, Section Pathology, Jena University Hospital, Jena, Germany
| | - Ferdinand von Eggeling
- Department of Otorhinolaryngology, Jena University Hospital, Jena, Germany.,Institute of Physical Chemistry, Friedrich Schiller University, Jena, Germany
| |
Collapse
|
19
|
Heuke S, Sarri B, Audier X, Rigneault H. Simultaneous dual-channel stimulated Raman scattering microscopy demultiplexed at distinct modulation frequencies. OPTICS LETTERS 2018; 43:3582-3585. [PMID: 30067629 DOI: 10.1364/ol.43.003582] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/06/2023]
Abstract
To increase the information per pixel in stimulated Raman scattering (SRS) microscopy as well as to correct from artifacts, it is valuable to acquire images at two different Raman shifts. We present a three-color SRS approach acquiring two perfectly registered SRS images where both pump beams are modulated at distinct frequencies while demodulating the Stokes beam. Our implementation uses two optical parametric oscillators that can be tuned to an almost arbitrary energy difference of Raman shifts, allowing investigation of fingerprint resonances simultaneously to CH-stretch vibrations.
Collapse
|
20
|
Krafft C, von Eggeling F, Guntinas-Lichius O, Hartmann A, Waldner MJ, Neurath MF, Popp J. Perspectives, potentials and trends of ex vivo and in vivo optical molecular pathology. JOURNAL OF BIOPHOTONICS 2018; 11:e201700236. [PMID: 28971622 DOI: 10.1002/jbio.201700236] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/23/2017] [Revised: 09/21/2017] [Accepted: 09/26/2017] [Indexed: 06/07/2023]
Abstract
It is pivotal for medical applications, such as noninvasive histopathologic characterization of tissue, to realize label-free and molecule-specific representation of morphologic and biochemical composition in real-time with subcellular spatial resolution. This unmet clinical need requires new approaches for rapid and reliable real-time assessment of pathologies to complement established diagnostic tools. Photonic imaging combined with digitalization offers the potential to provide the clinician the requested information both under in vivo and ex vivo conditions. This report summarizes photonic approaches and their use in combination with image processing, machine learning and augmented virtual reality that might solve current challenges in modern medicine. Details are given for pathology, intraoperative diagnosis in head and neck cancer and endoscopic diagnosis in gastroenterology.
Collapse
Affiliation(s)
| | - Ferdinand von Eggeling
- Leibniz Institute of Photonic Technology, Jena, Germany
- Institute of Physical Chemistry and Abbe Center of Photonics, University Jena, Germany
- Department of Otorhinolaryngology, Jena University Hospital, Jena, Germany
- Jena Biophotonic and Imaging Laboratory, Jena, Germany
| | | | - Arndt Hartmann
- Institute of Pathology, University Erlangen-Nürnberg, Erlangen-Nürnberg, Germany
| | - Maximilian J Waldner
- Department of Medicine, University Hospital Erlangen-Nürnberg, Erlangen-Nürnberg, Germany
| | - Markus F Neurath
- Department of Medicine, University Hospital Erlangen-Nürnberg, Erlangen-Nürnberg, Germany
| | - Jürgen Popp
- Leibniz Institute of Photonic Technology, Jena, Germany
- Institute of Physical Chemistry and Abbe Center of Photonics, University Jena, Germany
- Jena Biophotonic and Imaging Laboratory, Jena, Germany
| |
Collapse
|
21
|
Integration of 3D multimodal imaging data of a head and neck cancer and advanced feature recognition. BIOCHIMICA ET BIOPHYSICA ACTA-PROTEINS AND PROTEOMICS 2017; 1865:946-956. [DOI: 10.1016/j.bbapap.2016.08.018] [Citation(s) in RCA: 21] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/05/2016] [Revised: 08/03/2016] [Accepted: 08/27/2016] [Indexed: 12/14/2022]
|
22
|
Krafft C, Schmitt M, Schie IW, Cialla-May D, Matthäus C, Bocklitz T, Popp J. Label-Free Molecular Imaging of Biological Cells and Tissues by Linear and Nonlinear Raman Spectroscopic Approaches. Angew Chem Int Ed Engl 2017; 56:4392-4430. [PMID: 27862751 DOI: 10.1002/anie.201607604] [Citation(s) in RCA: 145] [Impact Index Per Article: 20.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/05/2016] [Revised: 11/04/2016] [Indexed: 12/20/2022]
Abstract
Raman spectroscopy is an emerging technique in bioanalysis and imaging of biomaterials owing to its unique capability of generating spectroscopic fingerprints. Imaging cells and tissues by Raman microspectroscopy represents a nondestructive and label-free approach. All components of cells or tissues contribute to the Raman signals, giving rise to complex spectral signatures. Resonance Raman scattering and surface-enhanced Raman scattering can be used to enhance the signals and reduce the spectral complexity. Raman-active labels can be introduced to increase specificity and multimodality. In addition, nonlinear coherent Raman scattering methods offer higher sensitivities, which enable the rapid imaging of larger sampling areas. Finally, fiber-based imaging techniques pave the way towards in vivo applications of Raman spectroscopy. This Review summarizes the basic principles behind medical Raman imaging and its progress since 2012.
Collapse
Affiliation(s)
- Christoph Krafft
- Leibniz-Institut für Photonische Technologien, Albert-Einstein-Strasse 9, 07745, Jena, Germany
| | - Michael Schmitt
- Institut für Physikalische Chemie und Abbe Center für Photonics, Friedrich Schiller Universität Jena, Helmholtzweg 4, 07743, Jena, Germany
| | - Iwan W Schie
- Leibniz-Institut für Photonische Technologien, Albert-Einstein-Strasse 9, 07745, Jena, Germany
| | - Dana Cialla-May
- Leibniz-Institut für Photonische Technologien, Albert-Einstein-Strasse 9, 07745, Jena, Germany.,Institut für Physikalische Chemie und Abbe Center für Photonics, Friedrich Schiller Universität Jena, Helmholtzweg 4, 07743, Jena, Germany
| | - Christian Matthäus
- Leibniz-Institut für Photonische Technologien, Albert-Einstein-Strasse 9, 07745, Jena, Germany.,Institut für Physikalische Chemie und Abbe Center für Photonics, Friedrich Schiller Universität Jena, Helmholtzweg 4, 07743, Jena, Germany
| | - Thomas Bocklitz
- Leibniz-Institut für Photonische Technologien, Albert-Einstein-Strasse 9, 07745, Jena, Germany.,Institut für Physikalische Chemie und Abbe Center für Photonics, Friedrich Schiller Universität Jena, Helmholtzweg 4, 07743, Jena, Germany
| | - Jürgen Popp
- Leibniz-Institut für Photonische Technologien, Albert-Einstein-Strasse 9, 07745, Jena, Germany.,Institut für Physikalische Chemie und Abbe Center für Photonics, Friedrich Schiller Universität Jena, Helmholtzweg 4, 07743, Jena, Germany
| |
Collapse
|
23
|
Chernavskaia O, Heuke S, Vieth M, Friedrich O, Schürmann S, Atreya R, Stallmach A, Neurath MF, Waldner M, Petersen I, Schmitt M, Bocklitz T, Popp J. Beyond endoscopic assessment in inflammatory bowel disease: real-time histology of disease activity by non-linear multimodal imaging. Sci Rep 2016; 6:29239. [PMID: 27406831 PMCID: PMC4942779 DOI: 10.1038/srep29239] [Citation(s) in RCA: 35] [Impact Index Per Article: 4.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/12/2016] [Accepted: 06/14/2016] [Indexed: 01/19/2023] Open
Abstract
Assessing disease activity is a prerequisite for an adequate treatment of inflammatory bowel diseases (IBD) such as Crohn’s disease and ulcerative colitis. In addition to endoscopic mucosal healing, histologic remission poses a promising end-point of IBD therapy. However, evaluating histological remission harbors the risk for complications due to the acquisition of biopsies and results in a delay of diagnosis because of tissue processing procedures. In this regard, non-linear multimodal imaging techniques might serve as an unparalleled technique that allows the real-time evaluation of microscopic IBD activity in the endoscopy unit. In this study, tissue sections were investigated using the non-linear multimodal microscopy combination of coherent anti-Stokes Raman scattering (CARS), two-photon excited auto fluorescence (TPEF) and second-harmonic generation (SHG). After the measurement a gold-standard assessment of histological indexes was carried out based on a conventional H&E stain. Subsequently, various geometry and intensity related features were extracted from the multimodal images. An optimized feature set was utilized to predict histological index levels based on a linear classifier. Based on the automated prediction, the diagnosis time interval is decreased. Therefore, non-linear multimodal imaging may provide a real-time diagnosis of IBD activity suited to assist clinical decision making within the endoscopy unit.
Collapse
Affiliation(s)
- Olga Chernavskaia
- Leibniz Institute of Photonic Technology, Jena, Germany.,Institute of Physical Chemistry and Abbe Center of Photonics, Friedrich-Schiller-University, Jena, Germany
| | - Sandro Heuke
- Leibniz Institute of Photonic Technology, Jena, Germany.,Institute of Physical Chemistry and Abbe Center of Photonics, Friedrich-Schiller-University, Jena, Germany
| | - Michael Vieth
- Institute of Pathology, Klinikum Bayreuth, Bayreuth, Germany
| | - Oliver Friedrich
- Institute of Medical Biotechnology, Friedrich-Alexander University of Erlangen-Nuremberg, Erlangen, Germany.,Erlangen Graduate School in Advanced Optical Technologies (SAOT), Friedrich-Alexander University of Erlangen-Nuremberg
| | - Sebastian Schürmann
- Institute of Medical Biotechnology, Friedrich-Alexander University of Erlangen-Nuremberg, Erlangen, Germany.,Erlangen Graduate School in Advanced Optical Technologies (SAOT), Friedrich-Alexander University of Erlangen-Nuremberg
| | - Raja Atreya
- Medical Department 1, Friedrich-Alexander University of Erlangen-Nuremberg, Erlangen, Germany
| | - Andreas Stallmach
- Department of Internal Medicine IV (Gastroenterology, Hepatology, and Infectious Diseases), Jena University Hospital, Jena, Germany
| | - Markus F Neurath
- Erlangen Graduate School in Advanced Optical Technologies (SAOT), Friedrich-Alexander University of Erlangen-Nuremberg.,Medical Department 1, Friedrich-Alexander University of Erlangen-Nuremberg, Erlangen, Germany
| | - Maximilian Waldner
- Erlangen Graduate School in Advanced Optical Technologies (SAOT), Friedrich-Alexander University of Erlangen-Nuremberg.,Medical Department 1, Friedrich-Alexander University of Erlangen-Nuremberg, Erlangen, Germany
| | - Iver Petersen
- Institute of Pathology, Jena University Hospital, Jena, Germany
| | - Michael Schmitt
- Institute of Physical Chemistry and Abbe Center of Photonics, Friedrich-Schiller-University, Jena, Germany
| | - Thomas Bocklitz
- Leibniz Institute of Photonic Technology, Jena, Germany.,Institute of Physical Chemistry and Abbe Center of Photonics, Friedrich-Schiller-University, Jena, Germany
| | - Jürgen Popp
- Leibniz Institute of Photonic Technology, Jena, Germany.,Institute of Physical Chemistry and Abbe Center of Photonics, Friedrich-Schiller-University, Jena, Germany
| |
Collapse
|