1
|
Shao J, Zhao X, Tang P, Chen B, Xu B, Lu H, Qin Z, Wu C. Label-free investigation of infected acute pyelonephritis tissue by FTIR microspectroscopy with unsupervised and supervised analytical methods. SPECTROCHIMICA ACTA. PART A, MOLECULAR AND BIOMOLECULAR SPECTROSCOPY 2024; 321:124753. [PMID: 38963949 DOI: 10.1016/j.saa.2024.124753] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/19/2024] [Revised: 06/13/2024] [Accepted: 06/27/2024] [Indexed: 07/06/2024]
Abstract
Acute pyelonephritis (AP) is a severe urinary tract infection (UTI) syndrome with a large population of patients worldwide. Current approaches to confirming AP are limited to urinalysis, radiological imaging methods and histological assessment. Fourier transform infrared (FTIR) microspectroscopy is a promising label-free modality that can offer information about both morphological and molecular pathologic alterations from biological tissues. Here, FTIR microspectroscopy serves to investigate renal biological histology of a rat model with AP and classify normal cortex, normal medulla and infected acute pyelonephritis tissues. The spectra were experimentally collected by FTIR with an infrared Globar source through raster scanning procedure. Unsupervised analysis methods, including integrating, clustering and principal component analysis (PCA) were performed on such spectra data to form infrared histological maps of entire kidney section. In comparison to Hematoxylin & Eosin-stained results of the adjacent tissue sections, these infrared maps were proved to enable the differentiation of the renal tissue types. The results of both integration and clustering indicated that the concentration of amide II decreases in the infected acute pyelonephritis tissues, with an increased presence of nucleic acids and lipids. By means of PCA, the infected tissue was linearly separated from normal ones by plotting confident ellipses with the score values of the first and second principal components. Moreover, supervised analysis was performed based on the supported vector machines (SVM). Normal cortex, normal medulla and infected acute pyelonephritis tissues were classified by SVM models with the best accuracy of 96.11% in testing dataset. In addition, these analytical methods were further employed on synchrotron-based FTIR spectra data and successfully form high-resolution infrared histological maps of glomerulus and necrotic cell mass. This work demonstrates that FTIR microspectroscopy will be a powerful manner to investigate AP tissue and differentiate infected tissue from normal tissue in a renal infected model system.
Collapse
Affiliation(s)
- Jingzhu Shao
- Center for Biophotonics, Institute of Medical Robotics, School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai, China
| | - Xiangyu Zhao
- Center for Biophotonics, Institute of Medical Robotics, School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai, China
| | - Ping Tang
- Center for Biophotonics, Institute of Medical Robotics, School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai, China
| | - Bo Chen
- Center for Biophotonics, Institute of Medical Robotics, School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai, China
| | - Borui Xu
- Center for Biophotonics, Institute of Medical Robotics, School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai, China
| | - Han Lu
- Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Zhen Qin
- Shanghai General Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
| | - Chongzhao Wu
- Center for Biophotonics, Institute of Medical Robotics, School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai, China; Wuhan National Laboratory for Optoelectronics, Hubei, China.
| |
Collapse
|
2
|
Bouzy P, Lyburn ID, Pinder SE, Scott R, Mansfield J, Moger J, Greenwood C, Bouybayoune I, Cornford E, Rogers K, Stone N. Exploration of utility of combined optical photothermal infrared and Raman imaging for investigating the chemical composition of microcalcifications in breast cancer. ANALYTICAL METHODS : ADVANCING METHODS AND APPLICATIONS 2023; 15:1620-1630. [PMID: 36880909 PMCID: PMC10065137 DOI: 10.1039/d2ay01197b] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 07/26/2022] [Accepted: 02/21/2023] [Indexed: 06/02/2023]
Abstract
Microcalcifications play an important role in cancer detection. They are evaluated by their radiological and histological characteristics but it is challenging to find a link between their morphology, their composition and the nature of a specific type of breast lesion. Whilst there are some mammographic features that are either typically benign or typically malignant often the appearances are indeterminate. Here, we explore a large range of vibrational spectroscopic and multiphoton imaging techniques in order to gain more information about the composition of the microcalcifications. For the first time, we validated the presence of carbonate ions in the microcalcifications by O-PTIR and Raman spectroscopy at the same time, the same location and the same high resolution (0.5 μm). Furthermore, the use of multiphoton imaging allowed us to create stimulated Raman histology (SRH) images which mimic histological images with all chemical information. In conclusion, we established a protocol for efficiently analysing the microcalcifications by iteratively refining the area of interest.
Collapse
Affiliation(s)
- Pascaline Bouzy
- School of Physics and Astronomy, University of Exeter, Exeter, UK.
| | - Iain D Lyburn
- Cranfield Forensic Institute, Cranfield University, Shrivenham, UK
- Gloucestershire Hospitals NHS Foundation Trust, UK
| | - Sarah E Pinder
- King's College London, Comprehensive Cancer Centre at Guy's Hospital, London, UK
| | - Robert Scott
- Cranfield Forensic Institute, Cranfield University, Shrivenham, UK
| | | | - Julian Moger
- School of Physics and Astronomy, University of Exeter, Exeter, UK.
| | - Charlene Greenwood
- School of Chemical and Physical Sciences, Keele University, Keele, Staffordshire, UK
| | - Ihssane Bouybayoune
- King's College London, Comprehensive Cancer Centre at Guy's Hospital, London, UK
| | | | - Keith Rogers
- Cranfield Forensic Institute, Cranfield University, Shrivenham, UK
| | - Nick Stone
- School of Physics and Astronomy, University of Exeter, Exeter, UK.
- Gloucestershire Hospitals NHS Foundation Trust, UK
| |
Collapse
|
3
|
Generation of 8–20 μm Mid-Infrared Ultrashort Femtosecond Laser Pulses via Difference Frequency Generation. PHOTONICS 2022. [DOI: 10.3390/photonics9060372] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
Mid-infrared (MIR) ultrashort laser pulses have a wide range of applications in the fields of environmental monitoring, laser medicine, food quality control, strong-field physics, attosecond science, and some other aspects. Recent years have seen great developments in MIR laser technologies. Traditional solid-state and fiber lasers focus on the research of the short-wavelength MIR region. However, due to the limitation of the gain medium, they still cannot cover the long-wavelength region from 8 to 20 µm. This paper summarizes the developments of 8–20 μm MIR ultrafast laser generation via difference frequency generation (DFG) and reviews related theoretical models. Finally, the feasibility of MIR power scaling by nonlinear-amplification DFG and methods for measuring the power of DFG-based MIR are analyzed from the author’s perspective.
Collapse
|
4
|
Yang Y, Yang Y, Liu Z, Guo L, Li S, Sun X, Shao Z, Ji M. Microcalcification-Based Tumor Malignancy Evaluation in Fresh Breast Biopsies with Hyperspectral Stimulated Raman Scattering. Anal Chem 2021; 93:6223-6231. [PMID: 33826297 DOI: 10.1021/acs.analchem.1c00522] [Citation(s) in RCA: 13] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
Abstract
Precise evaluation of breast tumor malignancy based on tissue calcifications has important practical value in the disease diagnosis, as well as the understanding of tumor development. Traditional X-ray mammography provides the overall morphologies of the calcifications but lacks intrinsic chemical information. In contrast, spontaneous Raman spectroscopy offers detailed chemical analysis but lacks the spatial profiles. Here, we applied hyperspectral stimulated Raman scattering (SRS) microscopy to extract both the chemical and morphological features of the microcalcifications, based on the spectral and spatial domain analysis. A total of 211 calcification sites from 23 patients were imaged with SRS, and the results were analyzed with a support vector machine (SVM) based classification algorithm. With optimized combinations of chemical and geometrical features of microcalcifications, we were able to reach a precision of 98.21% and recall of 100.00% for classifying benign and malignant cases, significantly improved from the pure spectroscopy or imaging based methods. Our findings may provide a rapid means to accurately evaluate breast tumor malignancy based on fresh tissue biopsies.
Collapse
Affiliation(s)
- Yifan Yang
- State Key Laboratory of Surface Physics and Department of Physics, Human Phenome Institute, Multiscale Research Institute of Complex Systems, Academy for Engineering and Technology, Key Laboratory of Micro and Nano Photonic Structures, Ministry of Education, Fudan University, Shanghai 200433, China
| | - Yinlong Yang
- Department of Breast Surgery, Fudan University Shanghai Cancer Center, Shanghai 200032, China.,Department of Oncology, Shanghai Medical College, Fudan University, Shanghai 200032, China
| | - Zhijie Liu
- State Key Laboratory of Surface Physics and Department of Physics, Human Phenome Institute, Multiscale Research Institute of Complex Systems, Academy for Engineering and Technology, Key Laboratory of Micro and Nano Photonic Structures, Ministry of Education, Fudan University, Shanghai 200433, China
| | - Li Guo
- State Key Laboratory of Surface Physics and Department of Physics, Human Phenome Institute, Multiscale Research Institute of Complex Systems, Academy for Engineering and Technology, Key Laboratory of Micro and Nano Photonic Structures, Ministry of Education, Fudan University, Shanghai 200433, China
| | - Shiping Li
- Department of Breast Surgery, Fudan University Shanghai Cancer Center, Shanghai 200032, China.,Department of Oncology, Shanghai Medical College, Fudan University, Shanghai 200032, China
| | - Xiangjie Sun
- Department of Oncology, Shanghai Medical College, Fudan University, Shanghai 200032, China.,Department of Pathology, Fudan University Shanghai Cancer Center, Shanghai 200032, China
| | - Zhiming Shao
- Department of Breast Surgery, Fudan University Shanghai Cancer Center, Shanghai 200032, China.,Department of Oncology, Shanghai Medical College, Fudan University, Shanghai 200032, China
| | - Minbiao Ji
- State Key Laboratory of Surface Physics and Department of Physics, Human Phenome Institute, Multiscale Research Institute of Complex Systems, Academy for Engineering and Technology, Key Laboratory of Micro and Nano Photonic Structures, Ministry of Education, Fudan University, Shanghai 200433, China
| |
Collapse
|
5
|
Deep-Learning-Based Active Hyperspectral Imaging Classification Method Illuminated by the Supercontinuum Laser. APPLIED SCIENCES-BASEL 2020. [DOI: 10.3390/app10093088] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/25/2023]
Abstract
Hyperspectral imaging (HSI) technology is able to provide fine spectral and spatial information of objects. It has the ability to discriminate materials and thereby has been used in a wide range of areas. However, traditional HSI strongly depends on the sunlight and hence is restricted to daytime. In this paper, a visible/near-infrared active HSI classification method illuminated by a visible/near-infrared supercontinuum laser is developed for spectra detection and objects imaging in the dark. Besides, a deep-learning-based classifier, hybrid DenseNet, is created to learn the feature representations of spectral and spatial information parallelly from active HSI data and is used for the active HSI classification. By applying the method to a selection of objects in the dark successfully, we demonstrate that with the active HSI classification method, it is possible to detect objects of interest in practical applications. Correct active HSI classification of different objects further supports the viability of the method for camouflage detection, biomedical alteration detection, cave painting mapping and so on.
Collapse
|
6
|
Capmany J, Torregrosa AJ, Maestre H. Intracavity image upconversion system with fast and flexible electro-optic image gating based on polarization-frustrated phase-matching for range-gated applications. OPTICS EXPRESS 2020; 28:1936-1953. [PMID: 32121895 DOI: 10.1364/oe.383735] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/20/2019] [Accepted: 01/03/2020] [Indexed: 06/10/2023]
Abstract
We report on a new image gating mechanism for intracavity nonlinear image upconversion systems that uses sum-frequency mixing of an external infrared image and a pump laser beam. Fast and flexible time duration gating of the upconverted image is achieved through transient electro-optic frustration of the phase-matching condition in a nonlinear crystal placed inside the cavity of the pump beam. The phase-matching condition is controlled by altering the polarization state of the laser cavity beam without interrupting laser oscillation, using a Pockels cell in one arm of an L-folded standing-wave resonator. In this way, an external image shutter mechanism is added to an image upconverter system that allows for using low shutter-speed EMCCDs (Electron Multiplying CCD) in range-gated imaging systems across the whole IR and potentially in the THz range.
Collapse
|
7
|
Toor F, Jackson S, Shang X, Arafin S, Yang H. Mid-infrared Lasers for Medical Applications: introduction to the feature issue. BIOMEDICAL OPTICS EXPRESS 2018; 9:6255-6257. [PMID: 31065426 PMCID: PMC6491011 DOI: 10.1364/boe.9.006255] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/19/2018] [Indexed: 05/25/2023]
Abstract
This feature issue contains a series of papers that report the most recent advances in the field of mid-infrared light sources used for medical applications, including tissue imaging, reconstruction, excision, and ablation. Many biomolecular compounds have strong resonances in the mid-infrared region and medicine is ideally suited to exploit this. The precision, sterility, and versatility of light in mid-infrared is opening more opportunities and this feature issue captures some of the most exciting.
Collapse
Affiliation(s)
- Fatima Toor
- Department of Electrical and Computer Engineering, University of Iowa, Iowa City, IA, 52242, USA
- Department of Physics and Astronomy, University of Iowa, Iowa City, IA, 52242, USA
- Holden Comprehensive Cancer Center - Experimental Therapeutics, University of Iowa Hospitals and Clinics, Iowa City, IA, 52242, USA
| | - Stuart Jackson
- School of Engineering, Macquarie University, Sydney, 2109, Australia
| | | | - Shamsul Arafin
- Department of Electrical and Computer Engineering, Ohio State University, Columbus, OH, 43210, USA
| | | |
Collapse
|