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Fei AT, Strand DW, Wang J. Registration of hyperspectral images and mass spectrometry data for the correlation of tissue optical spectra and molecular profiles. PROCEEDINGS OF SPIE--THE INTERNATIONAL SOCIETY FOR OPTICAL ENGINEERING 2024; 12827:1282708. [PMID: 38827822 PMCID: PMC11141327 DOI: 10.1117/12.3007718] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/05/2024]
Abstract
Hyperspectral imaging (HSI) is a label-free imaging modality that is emerging for non-invasive detection of various diseases including cancers. HSI provides high-resolution spatial images where each pixel has a spectral curve with numerous wavelength bands from the visible to infrared ranges. The rich spatial and spectral information can be used to discriminate various types of tissues and pathophysiological conditions. However, it can be difficult to explain spectral data with respect to the underline cellular and molecular mechanism. In this study, we developed an approach that registers hyperspectral images and mass spectrometry (MS) data where MS provides tissue molecular profiles. Human prostate tissues that were obtained after prostatectomy were used in the experiments. The whole prostate was first sliced every six mm. A customized hyperspectral surgical microscope was used to acquire HSI data from the sliced tissue. For MS data analysis, the sliced tissue of the prostate was divided into 51 small regions and then processed separately for each region. The immediately adjacent tissue was sliced and processed histologically for H&E staining. The MS molecular profiles were correlated with the hyperspectral images in this study.
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Affiliation(s)
| | - Douglas W Strand
- Department of Urology, The University of Texas Southwestern Medical Center, Dallas, Texas
| | - Jing Wang
- Department of Radiation Oncology, The University of Texas Southwestern Medical Center, Dallas, Texas
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In Vitro Antibody Quantification with Hyperspectral Imaging in a Large Field of View for Clinical Applications. Bioengineering (Basel) 2023; 10:bioengineering10030370. [PMID: 36978761 PMCID: PMC10045535 DOI: 10.3390/bioengineering10030370] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/22/2023] [Accepted: 03/13/2023] [Indexed: 03/19/2023] Open
Abstract
Hyperspectral imaging (HSI) is a non-invasive, contrast-free optical-based tool that has recently been applied in medical and basic research fields. The opportunity to use HSI to identify exogenous tumor markers in a large field of view (LFOV) could increase precision in oncological diagnosis and surgical treatment. In this study, the anti-high mobility group B1 (HMGB1) labeled with Alexa fluorophore (647 nm) was used as the target molecule. This is the proof-of-concept of HSI’s ability to quantify antibodies via an in vitro setting. A first test was performed to understand whether the relative absorbance provided by the HSI camera was dependent on volume at a 1:1 concentration. A serial dilution of 1:1, 10, 100, 1000, and 10,000 with phosphatase-buffered saline (PBS) was then used to test the sensitivity of the camera at the minimum and maximum volumes. For the analysis, images at 640 nm were extracted from the hypercubes according to peak signals matching the specificities of the antibody manufacturer. The results showed a positive correlation between relative absorbance and volume (r = 0.9709, p = 0.0013). The correlation between concentration and relative absorbance at min (1 µL) and max (20 µL) volume showed r = 0.9925, p < 0.0001, and r = 0.9992, p < 0.0001, respectively. These results demonstrate the HSI potential in quantifying HMGB1, hence deserving further studies in ex vivo and in vivo settings.
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Calin MA, Parasca SV. Automatic detection of basal cell carcinoma by hyperspectral imaging. JOURNAL OF BIOPHOTONICS 2022; 15:e202100231. [PMID: 34427393 DOI: 10.1002/jbio.202100231] [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: 07/27/2021] [Accepted: 08/19/2021] [Indexed: 06/13/2023]
Abstract
The purpose of this study was to test the ability of hyperspectral imaging (HSI) combined with unsupervised anomaly detectors to automatically differentiate basal cell carcinoma (BCC) from normal skin. Hyperspectral images of the face of a female patient with a BCC of the lower lip were acquired using a visible/near-infrared HSI system and two anomaly detection algorithms (Reed-Xiaoli and Reed-Xiaoli/Uniform Target hybrid anomaly detectors) were used to detect pathological tissue from normal skin. The results revealed that the receiver operating characteristic curve of the Reed-Xiaoli/Uniform Target hybrid detector was higher than that of the Reed-Xiaoli detector in the range of false positive rates between 0 and 0.8. The area under curve values were good (0.7074 and 0.8607, respectively) with Reed-Xiaoli/Uniform Target hybrid detector performing better. In conclusion, HSI combined with either of two anomaly detectors can play a promising role in the automated screening of BCC.
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Affiliation(s)
- Mihaela Antonina Calin
- Optoelectronic Methods for Biomedical Applications Department, National Institute of Research and Development for Optoelectronics INOE 2000, Magurele, Ilfov, Romania
| | - Sorin Viorel Parasca
- Plastic and Reconstructive Surgery Department, Carol Davila University of Medicine and Pharmacy, Bucharest, Romania
- Emergency Clinical Hospital for Plastic, Reconstructive Surgery and Burns, Bucharest, Romania
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Felli E, Al-Taher M, Collins T, Baiocchini A, Felli E, Barberio M, Ettorre GM, Mutter D, Lindner V, Hostettler A, Gioux S, Schuster C, Marescaux J, Diana M. Hyperspectral evaluation of hepatic oxygenation in a model of total vs. arterial liver ischaemia. Sci Rep 2020; 10:15441. [PMID: 32963333 PMCID: PMC7509803 DOI: 10.1038/s41598-020-72915-6] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/30/2020] [Accepted: 09/08/2020] [Indexed: 12/12/2022] Open
Abstract
Liver ischaemia reperfusion injury (IRI) is a dreaded pathophysiological complication which may lead to an impaired liver function. The level of oxygen hypoperfusion affects the level of cellular damage during the reperfusion phase. Consequently, intraoperative localisation and quantification of oxygen impairment would help in the early detection of liver ischaemia. To date, there is no real-time, non-invasive, and intraoperative tool which can compute an organ oxygenation map, quantify and discriminate different types of vascular occlusions intraoperatively. Hyperspectral imaging (HSI) is a non-invasive optical methodology which can quantify tissue oxygenation and which has recently been applied to the medical field. A hyperspectral camera detects the relative reflectance of a tissue in the range of 500 to 1000 nm, allowing the quantification of organic compounds such as oxygenated and deoxygenated haemoglobin at different depths. Here, we show the first comparative study of liver oxygenation by means of HSI quantification in a model of total vascular inflow occlusion (VIO) vs. hepatic artery occlusion (HAO), correlating optical properties with capillary lactate and histopathological evaluation. We found that liver HSI could discriminate between VIO and HAO. These results were confirmed via cross-validation of HSI which detected and quantified intestinal congestion in VIO. A significant correlation between the near-infrared spectra and capillary lactate was found (r = − 0.8645, p = 0.0003 VIO, r = − 0.7113, p = 0.0120 HAO). Finally, a statistically significant negative correlation was found between the histology score and the near-infrared parameter index (NIR) (r = − 0.88, p = 0.004). We infer that HSI, by predicting capillary lactates and the histopathological score, would be a suitable non-invasive tool for intraoperative liver perfusion assessment.
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Affiliation(s)
- Eric Felli
- Institute of Physiology, EA3072 Mitochondria Respiration and Oxidative Stress, University of Strasbourg, Strasbourg, France. .,IHU-Strasbourg, Institute of Image-Guided Surgery, Strasbourg, France.
| | - Mahdi Al-Taher
- IHU-Strasbourg, Institute of Image-Guided Surgery, Strasbourg, France
| | - Toby Collins
- Surgical Data Science Department, Research Institute Against Digestive Cancer (IRCAD), Strasbourg, France
| | - Andrea Baiocchini
- Department of Pathology, San Camillo Forlanini Hospital, Rome, Italy
| | - Emanuele Felli
- Department of General, Digestive, and Endocrine Surgery, University Hospital of Strasbourg, Strasbourg, France.,INSERM, Institute of Viral and Liver Disease, U1110, Strasbourg, France
| | - Manuel Barberio
- IHU-Strasbourg, Institute of Image-Guided Surgery, Strasbourg, France.,Department of Visceral, Transplant, Thoracic and Vascular Surgery, University Hospital of Leipzig, Leipzig, Germany
| | | | - Didier Mutter
- Department of General, Digestive, and Endocrine Surgery, University Hospital of Strasbourg, Strasbourg, France.,Surgical Data Science Department, Research Institute Against Digestive Cancer (IRCAD), Strasbourg, France
| | | | - Alexandre Hostettler
- Surgical Data Science Department, Research Institute Against Digestive Cancer (IRCAD), Strasbourg, France
| | - Sylvain Gioux
- ICUBE Laboratory, Photonics Instrumentation for Health, University of Strasbourg, Strasbourg, France
| | - Catherine Schuster
- INSERM, Institute of Viral and Liver Disease, U1110, Strasbourg, France.,University of Strasbourg, Strasbourg, France
| | - Jacques Marescaux
- IHU-Strasbourg, Institute of Image-Guided Surgery, Strasbourg, France.,Surgical Data Science Department, Research Institute Against Digestive Cancer (IRCAD), Strasbourg, France
| | - Michele Diana
- Institute of Physiology, EA3072 Mitochondria Respiration and Oxidative Stress, University of Strasbourg, Strasbourg, France.,IHU-Strasbourg, Institute of Image-Guided Surgery, Strasbourg, France.,Department of General, Digestive, and Endocrine Surgery, University Hospital of Strasbourg, Strasbourg, France.,Surgical Data Science Department, Research Institute Against Digestive Cancer (IRCAD), Strasbourg, France.,ICUBE Laboratory, Photonics Instrumentation for Health, University of Strasbourg, Strasbourg, France
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