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Geldof F, Schrage YM, van Houdt WJ, Sterenborg HJCM, Dashtbozorg B, Ruers TJM. Toward the use of diffuse reflection spectroscopy for intra-operative tissue discrimination during sarcoma surgery. JOURNAL OF BIOMEDICAL OPTICS 2024; 29:027001. [PMID: 38361507 PMCID: PMC10869119 DOI: 10.1117/1.jbo.29.2.027001] [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: 07/06/2023] [Revised: 01/23/2024] [Accepted: 01/24/2024] [Indexed: 02/17/2024]
Abstract
Significance Accurately distinguishing tumor tissue from normal tissue is crucial to achieve complete resections during soft tissue sarcoma (STS) surgery while preserving critical structures. Incomplete tumor resections are associated with an increased risk of local recurrence and worse patient prognosis. Aim We evaluate the performance of diffuse reflectance spectroscopy (DRS) to distinguish tumor tissue from healthy tissue in STSs. Approach DRS spectra were acquired from different tissue types on multiple locations in 20 freshly excised sarcoma specimens. A k -nearest neighbors classification model was trained to predict the tissue types of the measured locations, using binary and multiclass approaches. Results Tumor tissue could be distinguished from healthy tissue with a classification accuracy of 0.90, sensitivity of 0.88, and specificity of 0.93 when well-differentiated liposarcomas were included. Excluding this subtype, the classification performance increased to an accuracy of 0.93, sensitivity of 0.94, and specificity of 0.93. The developed model showed a consistent performance over different histological subtypes and tumor locations. Conclusions Automatic tissue discrimination using DRS enables real-time intra-operative guidance, contributing to more accurate STS resections.
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Affiliation(s)
- Freija Geldof
- Netherlands Cancer Institute, Image-Guided Surgery, Department of Surgery, Amsterdam, The Netherlands
- University of Twente, Faculty of Science and Technology, Enschede, The Netherlands
| | - Yvonne M. Schrage
- Netherlands Cancer Institute, Image-Guided Surgery, Department of Surgery, Amsterdam, The Netherlands
| | - Winan J. van Houdt
- Netherlands Cancer Institute, Image-Guided Surgery, Department of Surgery, Amsterdam, The Netherlands
| | | | - Behdad Dashtbozorg
- Netherlands Cancer Institute, Image-Guided Surgery, Department of Surgery, Amsterdam, The Netherlands
| | - Theo J. M. Ruers
- Netherlands Cancer Institute, Image-Guided Surgery, Department of Surgery, Amsterdam, The Netherlands
- University of Twente, Faculty of Science and Technology, Enschede, The Netherlands
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Nazarian S, Gkouzionis I, Murphy J, Darzi A, Patel N, Peters CJ, Elson DS. Real-time classification of tumour and non-tumour tissue in colorectal cancer using diffuse reflectance spectroscopy and neural networks to aid margin assessment. Int J Surg 2024; 110:01279778-990000000-01004. [PMID: 38241421 PMCID: PMC11020003 DOI: 10.1097/js9.0000000000001102] [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: 07/26/2023] [Accepted: 01/08/2024] [Indexed: 01/21/2024]
Abstract
BACKGROUND Colorectal cancer is the third most commonly diagnosed malignancy and the second leading cause of mortality worldwide. A positive resection margin following surgery for colorectal cancer is linked with higher rates of local recurrence and poorer survival. We investigated diffuse reflectance spectroscopy (DRS) to distinguish tumour and non-tumour tissue in ex vivo colorectal specimens, to aid margin assessment and provide augmented visual maps to the surgeon in real-time. METHODS Patients undergoing elective colorectal cancer resection surgery at a London-based hospital were prospectively recruited. A hand-held DRS probe was used on the surface of freshly resected ex vivo colorectal tissue. Spectral data was acquired for tumour and non-tumour tissue. Binary classification was achieved using conventional machine learning classifiers and a convolutional neural network (CNN), which were evaluated in terms of sensitivity, specificity, accuracy and the area under the curve. RESULTS A total of 7692 mean spectra were obtained for tumour and non-tumour colorectal tissue. The CNN-based classifier was the best performing machine learning algorithm, when compared to contrastive approaches, for differentiating tumour and non-tumour colorectal tissue, with an overall diagnostic accuracy of 90.8% and area under the curve of 96.8%. Live on-screen classification of tissue type was achieved using a graduated colourmap. CONCLUSION A high diagnostic accuracy for a DRS probe and tracking system to differentiate ex vivo tumour and non-tumour colorectal tissue in real-time with on-screen visual feedback was highlighted by this study. Further in vivo studies are needed to ensure integration into a surgical workflow.
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Affiliation(s)
| | - Ioannis Gkouzionis
- Department of Surgery and Cancer
- Hamlyn Centre for Robotics Surgery, Imperial College London, London, UK
| | | | - Ara Darzi
- Department of Surgery and Cancer
- Hamlyn Centre for Robotics Surgery, Imperial College London, London, UK
| | | | | | - Daniel S. Elson
- Department of Surgery and Cancer
- Hamlyn Centre for Robotics Surgery, Imperial College London, London, UK
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3
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Saito Nogueira M, Maryam S, Amissah M, Killeen S, O'Riordain M, Andersson-Engels S. Diffuse reflectance spectroscopy for colorectal cancer surgical guidance: towards real-time tissue characterization and new biomarkers. Analyst 2023; 149:88-99. [PMID: 37994161 DOI: 10.1039/d3an00261f] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/24/2023]
Abstract
Colorectal cancer (CRC) is the third most common and second most deadly type of cancer worldwide, representing 11.3% of the diagnosed cancer cases and resulting in 10.2% (0.88 million) of the cancer related deaths in 2020. CRCs are typically detected at the late stage, which leads to high mortality and morbidity. Mortality and poor prognosis are partially caused by cancer recurrence and postoperative complications. Patient survival could be increased by improving precision in surgical resection using accurate surgical guidance tools based on diffuse reflectance spectroscopy (DRS). DRS enables real-time tissue identification for potential cancer margin delineation through determination of the circumferential resection margin (CRM), while also supporting non-invasive and label-free approaches for laparoscopic surgery to avoid short-term complications of open surgery as suitable. In this study, we have estimated the scattering properties and chromophore concentrations based on 2949 DRS measurements of freshly excised ex vivo specimens of 47 patients, and used this estimation to classify normal colorectal wall (CW), fat and tumor tissues. DRS measurements were performed with fiber-optic probes of 630 μm source-detector distance (SDD; probe 1) and 2500 μm SDD (probe 2) to measure tissue layers ∼0.5-1 mm and ∼0.5-2 mm deep, respectively. By using the 5-fold cross-validation of machine learning models generated with the classification and regression tree (CART) algorithm, we achieved 95.9 ± 0.7% sensitivity, 98.9 ± 0.3% specificity, 90.2 ± 0.4% accuracy, and 95.5 ± 0.3% AUC for probe 1. Similarly, we achieved 96.9 ± 0.8% sensitivity, 98.9 ± 0.2% specificity, 94.0 ± 0.4% accuracy, and 96.7 ± 0.4% AUC for probe 2.
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Affiliation(s)
- Marcelo Saito Nogueira
- Tyndall National Institute, Lee Maltings, Dyke Parade, Cork, T12 R5CP, Ireland.
- Department of Physics, University College Cork, College Road, Cork, T12 K8AF, Ireland
| | - Siddra Maryam
- Tyndall National Institute, Lee Maltings, Dyke Parade, Cork, T12 R5CP, Ireland.
- Department of Physics, University College Cork, College Road, Cork, T12 K8AF, Ireland
| | - Michael Amissah
- Tyndall National Institute, Lee Maltings, Dyke Parade, Cork, T12 R5CP, Ireland.
- Department of Physics, University College Cork, College Road, Cork, T12 K8AF, Ireland
| | - Shane Killeen
- Department of Surgery, Mercy University Hospital, Cork, T12 WE28, Ireland
| | - Micheal O'Riordain
- Department of Surgery, Mercy University Hospital, Cork, T12 WE28, Ireland
| | - Stefan Andersson-Engels
- Tyndall National Institute, Lee Maltings, Dyke Parade, Cork, T12 R5CP, Ireland.
- Department of Physics, University College Cork, College Road, Cork, T12 K8AF, Ireland
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4
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Li CL, Fisher CJ, Komolibus K, Grygoryev K, Lu H, Burke R, Visentin A, Andersson-Engels S. Frameworks of wavelength selection in diffuse reflectance spectroscopy for tissue differentiation in orthopedic surgery. JOURNAL OF BIOMEDICAL OPTICS 2023; 28:121207. [PMID: 37674977 PMCID: PMC10479945 DOI: 10.1117/1.jbo.28.12.121207] [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: 02/08/2023] [Revised: 08/04/2023] [Accepted: 08/08/2023] [Indexed: 09/08/2023]
Abstract
Significance Wavelength selection from a large diffuse reflectance spectroscopy (DRS) dataset enables removal of spectral multicollinearity and thus leads to improved understanding of the feature domain. Feature selection (FS) frameworks are essential to discover the optimal wavelengths for tissue differentiation in DRS-based measurements, which can facilitate the development of compact multispectral optical systems with suitable illumination wavelengths for clinical translation. Aim The aim was to develop an FS methodology to determine wavelengths with optimal discriminative power for orthopedic applications, while providing the frameworks for adaptation to other clinical scenarios. Approach An ensemble framework for FS was developed, validated, and compared with frameworks incorporating conventional algorithms, including principal component analysis (PCA), linear discriminant analysis (LDA), and backward interval partial least squares (biPLS). Results Via the one-versus-rest binary classification approach, a feature subset of 10 wavelengths was selected from each framework yielding comparable balanced accuracy scores (PCA: 94.8 ± 3.47 % , LDA: 98.2 ± 2.02 % , biPLS: 95.8 ± 3.04 % , and ensemble: 95.8 ± 3.16 % ) to those of using all features (100%) for cortical bone versus the rest class labels. One hundred percent balanced accuracy scores were generated for bone cement versus the rest. Different feature subsets achieving similar outcomes could be identified due to spectral multicollinearity. Conclusions Wavelength selection frameworks provide a means to explore domain knowledge and discover important contributors to classification in spectroscopy. The ensemble framework generated a model with improved interpretability and preserved physical interpretation, which serves as the basis to determine illumination wavelengths in optical instrumentation design.
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Affiliation(s)
- Celina L. Li
- University College Cork, Biophotonics@Tyndall, IPIC, Tyndall National Institute, Cork, Ireland
| | - Carl J. Fisher
- University College Cork, Biophotonics@Tyndall, IPIC, Tyndall National Institute, Cork, Ireland
| | - Katarzyna Komolibus
- University College Cork, Biophotonics@Tyndall, IPIC, Tyndall National Institute, Cork, Ireland
| | - Konstantin Grygoryev
- University College Cork, Biophotonics@Tyndall, IPIC, Tyndall National Institute, Cork, Ireland
| | - Huihui Lu
- University College Cork, Biophotonics@Tyndall, IPIC, Tyndall National Institute, Cork, Ireland
| | - Ray Burke
- University College Cork, Biophotonics@Tyndall, IPIC, Tyndall National Institute, Cork, Ireland
| | - Andrea Visentin
- University College Cork, School of Computer Science and Information Technology, Insight Centre for Data Analytics, Cork, Ireland
| | - Stefan Andersson-Engels
- University College Cork, Biophotonics@Tyndall, IPIC, Tyndall National Institute, Cork, Ireland
- University College Cork, Department of Physics, Cork, Ireland
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Geldof F, Witteveen M, Sterenborg HJCM, Ruers TJM, Dashtbozorg B. Diffuse reflection spectroscopy at the fingertip: design and performance of a compact side-firing probe for tissue discrimination during colorectal cancer surgery. BIOMEDICAL OPTICS EXPRESS 2023; 14:128-147. [PMID: 36698675 PMCID: PMC9841999 DOI: 10.1364/boe.476242] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/21/2022] [Revised: 11/14/2022] [Accepted: 11/14/2022] [Indexed: 06/17/2023]
Abstract
Optical technologies are widely used for tissue sensing purposes. However, maneuvering conventional probe designs with flat-tipped fibers in narrow spaces can be challenging, for instance during pelvic colorectal cancer surgery. In this study, a compact side-firing fiber probe was developed for tissue discrimination during colorectal cancer surgery using diffuse reflectance spectroscopy. The optical behavior was compared to flat-tipped fibers using both Monte Carlo simulations and experimental phantom measurements. The tissue classification performance was examined using freshly excised colorectal cancer specimens. Using the developed probe and classification algorithm, an accuracy of 0.92 was achieved for discriminating tumor tissue from healthy tissue.
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Affiliation(s)
- Freija Geldof
- Department of Surgery, Netherlands Cancer Institute, Amsterdam, The Netherlands
| | - Mark Witteveen
- Department of Surgery, Netherlands Cancer Institute, Amsterdam, The Netherlands
| | - Henricus J. C. M. Sterenborg
- Department of Surgery, Netherlands Cancer Institute, Amsterdam, The Netherlands
- Department of Biomedical Engineering and Physics, Amsterdam University Medical Center, Amsterdam, The Netherlands
| | - Theo J. M. Ruers
- Department of Surgery, Netherlands Cancer Institute, Amsterdam, The Netherlands
- Faculty of Science and Technology, University of Twente, Enschede, The Netherlands
| | - Behdad Dashtbozorg
- Department of Surgery, Netherlands Cancer Institute, Amsterdam, The Netherlands
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6
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Insights into Biochemical Sources and Diffuse Reflectance Spectral Features for Colorectal Cancer Detection and Localization. Cancers (Basel) 2022; 14:cancers14225715. [PMID: 36428806 PMCID: PMC9688116 DOI: 10.3390/cancers14225715] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/09/2022] [Revised: 11/07/2022] [Accepted: 11/09/2022] [Indexed: 11/23/2022] Open
Abstract
Colorectal cancer (CRC) is the third most common and second most deadly type of cancer worldwide. Early detection not only reduces mortality but also improves patient prognosis by allowing the use of minimally invasive techniques to remove cancer while avoiding major surgery. Expanding the use of microsurgical techniques requires accurate diagnosis and delineation of the tumor margins in order to allow complete excision of cancer. We have used diffuse reflectance spectroscopy (DRS) to identify the main optical CRC biomarkers and to optimize parameters for the integration of such technologies into medical devices. A total number of 2889 diffuse reflectance spectra were collected in ex vivo specimens from 47 patients. Short source-detector distance (SDD) and long-SDD fiber-optic probes were employed to measure tissue layers from 0.5 to 1 mm and from 0.5 to 1.9 mm deep, respectively. The most important biomolecules contributing to differentiating DRS between tissue types were oxy- and deoxy-hemoglobin (Hb and HbO2), followed by water and lipid. Accurate tissue classification and potential DRS device miniaturization using Hb, HbO2, lipid and water data were achieved particularly well within the wavelength ranges 350-590 nm and 600-1230 nm for the short-SDD probe, and 380-400 nm, 420-610 nm, and 650-950 nm for the long-SDD probe.
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7
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Witteveen M, Sterenborg HJCM, van Leeuwen TG, Aalders MCG, Ruers TJM, Post AL. Comparison of preprocessing techniques to reduce nontissue-related variations in hyperspectral reflectance imaging. JOURNAL OF BIOMEDICAL OPTICS 2022; 27:106003. [PMID: 36207772 PMCID: PMC9541333 DOI: 10.1117/1.jbo.27.10.106003] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 02/28/2022] [Accepted: 08/23/2022] [Indexed: 06/16/2023]
Abstract
SIGNIFICANCE Hyperspectral reflectance imaging can be used in medicine to identify tissue types, such as tumor tissue. Tissue classification algorithms are developed based on, e.g., machine learning or principle component analysis. For the development of these algorithms, data are generally preprocessed to remove variability in data not related to the tissue itself since this will improve the performance of the classification algorithm. In hyperspectral imaging, the measured spectra are also influenced by reflections from the surface (glare) and height variations within and between tissue samples. AIM To compare the ability of different preprocessing algorithms to decrease variations in spectra induced by glare and height differences while maintaining contrast based on differences in optical properties between tissue types. APPROACH We compare eight preprocessing algorithms commonly used in medical hyperspectral imaging: standard normal variate, multiplicative scatter correction, min-max normalization, mean centering, area under the curve normalization, single wavelength normalization, first derivative, and second derivative. We investigate conservation of contrast stemming from differences in: blood volume fraction, presence of different absorbers, scatter amplitude, and scatter slope-while correcting for glare and height variations. We use a similarity metric, the overlap coefficient, to quantify contrast between spectra. We also investigate the algorithms for clinical datasets from the colon and breast. CONCLUSIONS Preprocessing reduces the overlap due to glare and distance variations. In general, the algorithms standard normal variate, min-max, area under the curve, and single wavelength normalization are the most suitable to preprocess data used to develop a classification algorithm for tissue classification. The type of contrast between tissue types determines which of these four algorithms is most suitable.
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Affiliation(s)
- Mark Witteveen
- the Netherlands Cancer Institute, Surgical Oncology, Amsterdam, The Netherlands
- University of Twente, Science and Technology, Nanobiophysics, Enschede, The Netherlands
| | - Henricus J. C. M. Sterenborg
- the Netherlands Cancer Institute, Surgical Oncology, Amsterdam, The Netherlands
- Amsterdam UMC, University of Amsterdam, Cancer Center Amsterdam, Amsterdam Cardiovascular Sciences, Department of Biomedical Engineering and Physics, Amsterdam, The Netherlands
| | - Ton G. van Leeuwen
- Amsterdam UMC, University of Amsterdam, Cancer Center Amsterdam, Amsterdam Cardiovascular Sciences, Department of Biomedical Engineering and Physics, Amsterdam, The Netherlands
| | - Maurice C. G. Aalders
- Amsterdam UMC, University of Amsterdam, Cancer Center Amsterdam, Amsterdam Cardiovascular Sciences, Department of Biomedical Engineering and Physics, Amsterdam, The Netherlands
- University of Amsterdam, Co van Ledden Hulsebosch Center, Amsterdam, The Netherlands
| | - Theo J. M. Ruers
- the Netherlands Cancer Institute, Surgical Oncology, Amsterdam, The Netherlands
- University of Twente, Science and Technology, Nanobiophysics, Enschede, The Netherlands
| | - Anouk L. Post
- the Netherlands Cancer Institute, Surgical Oncology, Amsterdam, The Netherlands
- Amsterdam UMC, University of Amsterdam, Cancer Center Amsterdam, Amsterdam Cardiovascular Sciences, Department of Biomedical Engineering and Physics, Amsterdam, The Netherlands
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8
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Bhattacharyya N, Singh S, Mukherjee D, Das N, Chatterjee A, Adhikari A, Mondal S, Mondal P, Mallick AK, Pal SK. Picosecond-resolved fluorescence resonance energy transfer (FRET) in diffuse reflectance spectroscopy explores biologically relevant hidden molecular contacts in a non-invasive way. Phys Chem Chem Phys 2022; 24:6176-6184. [PMID: 35229087 DOI: 10.1039/d1cp05159h] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/21/2022]
Abstract
The potentiality of Förster resonance energy transfer (FRET) for studying molecular interactions inside biological tissues with improved spatial (Angström) and temporal (picosecond) resolution is well established. On the other hand, the efficacy of diffuse reflectance spectroscopy (DRS) that uses optical radiation in order to determine physiological parameters including haemoglobin, and oxygen saturation is well known. Here we have made an attempt to combine diffuse reflectance spectroscopy (DRS) with picosecond-resolved FRET in order to show improvement in the exploration of molecular contacts in biological tissue models. We define the technique as ultrafast time-resolved diffuse reflectance spectroscopy (UTRDRS). The illuminated photon of the fluorophore from the surface of the tissue-mimicking layers carries the hidden information of the molecular contact. In order to investigate the validation of the Kubelka-Munk (KM) formulism for the developed UTRDRS technique in tissue phantoms, we have studied the propagation of incandescent and picosecond-laser light through several layers of cellulose membranes. While picosecond-resolved FRET in the diffuse reflected light confirms the hidden nano-contact (4.6 nm) of two different dye layers (8-anilino-1-naphthalenesulfonic acid and Nile blue), high-resolution optical microscopy on the cross-section of the layers reveals the proximity and contacts of the layers with limited spatial resolution (∼300 nm). We have also investigated two biologically relevant molecules, namely carboxyfluorescein and haemoglobin, in tissue phantom layers in order to show the efficacy of the UTRDRS technique. Overall, our studies based on UTRDRS in tissue mimicking layers may have potential applications in non-invasive biomedical diagnosis for patients suffering from skin diseases.
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Affiliation(s)
- Neha Bhattacharyya
- Department of Radio Physics and Electronics, University of Calcutta, Kolkata 700009, India.,Technical Research Centre, S.N. Bose National Centre for Basic Sciences, Kolkata 700106, India.
| | - Soumendra Singh
- Technical Research Centre, S.N. Bose National Centre for Basic Sciences, Kolkata 700106, India.
| | - Dipanjan Mukherjee
- Department of Chemical, Biological and Macromolecular Sciences, S.N. Bose National Centre for Basic Sciences, Kolkata 700106, India
| | - Nairit Das
- Department of Electrical Engineering, Indian Institute of Technology, Kharagpur 721302, India
| | - Arka Chatterjee
- Department of Chemical, Biological and Macromolecular Sciences, S.N. Bose National Centre for Basic Sciences, Kolkata 700106, India
| | - Aniruddha Adhikari
- Department of Chemical, Biological and Macromolecular Sciences, S.N. Bose National Centre for Basic Sciences, Kolkata 700106, India
| | - Susmita Mondal
- Department of Chemical, Biological and Macromolecular Sciences, S.N. Bose National Centre for Basic Sciences, Kolkata 700106, India
| | - Pulak Mondal
- Department of Radio Physics and Electronics, University of Calcutta, Kolkata 700009, India
| | - Asim Kumar Mallick
- Department of Paediatrics, Nil Ratan Sircar Medical College and Hospital, Kolkata 700014, India
| | - Samir Kumar Pal
- Technical Research Centre, S.N. Bose National Centre for Basic Sciences, Kolkata 700106, India. .,Department of Chemical, Biological and Macromolecular Sciences, S.N. Bose National Centre for Basic Sciences, Kolkata 700106, India
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9
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Gkouzionis I, Nazarian S, Kawka M, Darzi A, Patel N, Peters CJ, Elson DS. Real-time tracking of a diffuse reflectance spectroscopy probe used to aid histological validation of margin assessment in upper gastrointestinal cancer resection surgery. JOURNAL OF BIOMEDICAL OPTICS 2022; 27:JBO-210293R. [PMID: 35106980 PMCID: PMC8804336 DOI: 10.1117/1.jbo.27.2.025001] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/16/2021] [Accepted: 01/10/2022] [Indexed: 05/27/2023]
Abstract
SIGNIFICANCE Diffuse reflectance spectroscopy (DRS) allows discrimination of tissue type. Its application is limited by the inability to mark the scanned tissue and the lack of real-time measurements. AIM This study aimed to develop a real-time tracking system to enable localization of a DRS probe to aid the classification of tumor and non-tumor tissue. APPROACH A green-colored marker attached to the DRS probe was detected using hue-saturation-value (HSV) segmentation. A live, augmented view of tracked optical biopsy sites was recorded in real time. Supervised classifiers were evaluated in terms of sensitivity, specificity, and overall accuracy. A developed software was used for data collection, processing, and statistical analysis. RESULTS The measured root mean square error (RMSE) of DRS probe tip tracking was 1.18 ± 0.58 mm and 1.05 ± 0.28 mm for the x and y dimensions, respectively. The diagnostic accuracy of the system to classify tumor and non-tumor tissue in real time was 94% for stomach and 96% for the esophagus. CONCLUSIONS We have successfully developed a real-time tracking and classification system for a DRS probe. When used on stomach and esophageal tissue for tumor detection, the accuracy derived demonstrates the strength and clinical value of the technique to aid margin assessment in cancer resection surgery.
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Affiliation(s)
- Ioannis Gkouzionis
- Imperial College London, Department of Surgery and Cancer, London, United Kingdom
- Imperial College London, Hamlyn Centre, London, United Kingdom
| | - Scarlet Nazarian
- Imperial College London, Department of Surgery and Cancer, London, United Kingdom
| | - Michal Kawka
- Imperial College London, Department of Surgery and Cancer, London, United Kingdom
| | - Ara Darzi
- Imperial College London, Department of Surgery and Cancer, London, United Kingdom
- Imperial College London, Hamlyn Centre, London, United Kingdom
| | - Nisha Patel
- Imperial College London, Department of Surgery and Cancer, London, United Kingdom
| | | | - Daniel S. Elson
- Imperial College London, Department of Surgery and Cancer, London, United Kingdom
- Imperial College London, Hamlyn Centre, London, United Kingdom
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10
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Geldof F, Dashtbozorg B, Hendriks BHW, Sterenborg HJCM, Ruers TJM. Layer thickness prediction and tissue classification in two-layered tissue structures using diffuse reflectance spectroscopy. Sci Rep 2022; 12:1698. [PMID: 35105926 PMCID: PMC8807816 DOI: 10.1038/s41598-022-05751-5] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/01/2021] [Accepted: 01/12/2022] [Indexed: 11/26/2022] Open
Abstract
During oncological surgery, it can be challenging to identify the tumor and establish adequate resection margins. This study proposes a new two-layer approach in which diffuse reflectance spectroscopy (DRS) is used to predict the top layer thickness and classify the layers in two-layered phantom and animal tissue. Using wavelet-based and peak-based DRS spectral features, the proposed method could predict the top layer thickness with an accuracy of up to 0.35 mm. In addition, the tissue types of the first and second layers were classified with an accuracy of 0.95 and 0.99. Distinguishing multiple tissue layers during spectral analyses results in a better understanding of more complex tissue structures encountered in surgical practice.
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Affiliation(s)
- Freija Geldof
- Department of Surgery, Netherlands Cancer Institute, 1066 CX, Amsterdam, The Netherlands.
| | - Behdad Dashtbozorg
- Department of Surgery, Netherlands Cancer Institute, 1066 CX, Amsterdam, The Netherlands
| | - Benno H W Hendriks
- Department of IGT and US Devices & Systems, Philips Research Laboratories, 5656 AE, Eindhoven, The Netherlands
- Department of BioMechanical Engineering, 3mE, Delft University of Technology, 2628 CD, Delft, The Netherlands
| | - Henricus J C M Sterenborg
- Department of Surgery, Netherlands Cancer Institute, 1066 CX, Amsterdam, The Netherlands
- Department of Biomedical Engineering and Physics, Amsterdam University Medical Center, 1105 AZ, Amsterdam, The Netherlands
| | - Theo J M Ruers
- Department of Surgery, Netherlands Cancer Institute, 1066 CX, Amsterdam, The Netherlands
- Faculty of Science and Technology, University of Twente, 7522 NB, Enschede, The Netherlands
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11
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Restrepo L, Murillo J, Botina D, Zarzycki A, Garzón J, Franco R, Montano J, Calderon S, Torres-Madronero MC, Marzani F, Robledo SM, Galeano J. Diffuse Reflectance Parameters of Treated Leishmaniasis Cutaneous Ulcers and Association with Histopathologies in an Animal Model: A Proof of Concept. SLAS Technol 2021; 26:667-680. [PMID: 34292085 DOI: 10.1177/24726303211030292] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
Cutaneous leishmaniasis (CL) is a parasitic disease that produces chronic skin ulcers. Although it has a worldwide presence, it is a neglected disease that still requires novel tools for its management. In order to study the use of optical tools in CL, this article presents a preliminary study of the correlation between CL histopathological and optical parameters. Optical parameters correspond to absorption and scattering coefficients obtained from diffuse reflectance spectra of treated CL in golden hamsters. Independently, histopathological data were collected from the same hamsters. As a result, after Spearman correlation and the Kruskal-Wallis test, inverse correlation was found between absorption/scattering optical parameters and inflammatory histopathological values, such as the scattering parameter related to the diameter of fibroblasts with the histopathological parameters of fibrosis, polymorphonuclear neutrophils, lymphocytes, plasmocytes, hyperplasia, and Leishmania, and the absorption parameter oxygen saturation showed a relation with the granulation tissue histopathological parameter. These correlations agree with the expected behavior of tissue composition during the healing process in CL. The results correspond to a proof of concept that shows that optical diffuse reflectance-based tools and methods could be considered as an alternative to assist in CL diagnosis and treatment follow-up.
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Affiliation(s)
- Lina Restrepo
- Instituto Tecnológico Metropolitano, Medellín, Colombia
| | - Javier Murillo
- Program for the Study and Control of Tropical Diseases-PECET, School of Medicine, University of Antioquia, Medellín, Colombia
| | - Deivid Botina
- Research group on Advance Materials and Energy MatyEr, Biomaterials and Electromedicine Laboratory, Instituto Tecnológico Metropolitano, Medellín, Colombia.,Laboratoire ImViA, Université Bourgogne Franche-Comté, Dijon Cedex, France
| | - Artur Zarzycki
- Research group on Advance Materials and Energy MatyEr, Biomaterials and Electromedicine Laboratory, Instituto Tecnológico Metropolitano, Medellín, Colombia
| | - Johnson Garzón
- Grupo de Óptica y Espectroscopía, Centro de Ciencia Básica, Universidad Pontificia Bolivariana, Medellín, Colombia
| | - Ricardo Franco
- Research group on Automatic, Electronic and Computational Science, MIRP Laboratory, Instituto Tecnológico Metropolitano, Medellín, Colombia
| | - Jaime Montano
- Program for the Study and Control of Tropical Diseases-PECET, School of Medicine, University of Antioquia, Medellín, Colombia
| | - Samuel Calderon
- Program for the Study and Control of Tropical Diseases-PECET, School of Medicine, University of Antioquia, Medellín, Colombia
| | - Maria C Torres-Madronero
- Research group on Automatic, Electronic and Computational Science, MIRP Laboratory, Instituto Tecnológico Metropolitano, Medellín, Colombia
| | - Franck Marzani
- Laboratoire ImViA, Université Bourgogne Franche-Comté, Dijon Cedex, France
| | - Sara M Robledo
- Program for the Study and Control of Tropical Diseases-PECET, School of Medicine, University of Antioquia, Medellín, Colombia
| | - July Galeano
- Research group on Advance Materials and Energy MatyEr, Biomaterials and Electromedicine Laboratory, Instituto Tecnológico Metropolitano, Medellín, Colombia
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12
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Takamatsu T, Kitagawa Y, Akimoto K, Iwanami R, Endo Y, Takashima K, Okubo K, Umezawa M, Kuwata T, Sato D, Kadota T, Mitsui T, Ikematsu H, Yokota H, Soga K, Takemura H. Over 1000 nm Near-Infrared Multispectral Imaging System for Laparoscopic In Vivo Imaging. SENSORS 2021; 21:s21082649. [PMID: 33918935 PMCID: PMC8069262 DOI: 10.3390/s21082649] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 02/25/2021] [Revised: 04/01/2021] [Accepted: 04/06/2021] [Indexed: 01/17/2023]
Abstract
In this study, a laparoscopic imaging device and a light source able to select wavelengths by bandpass filters were developed to perform multispectral imaging (MSI) using over 1000 nm near-infrared (OTN-NIR) on regions under a laparoscope. Subsequently, MSI (wavelengths: 1000–1400 nm) was performed using the built device on nine live mice before and after tumor implantation. The normal and tumor pixels captured within the mice were used as teaching data sets, and the tumor-implanted mice data were classified using a neural network applied following a leave-one-out cross-validation procedure. The system provided a specificity of 89.5%, a sensitivity of 53.5%, and an accuracy of 87.8% for subcutaneous tumor discrimination. Aggregated true-positive (TP) pixels were confirmed in all tumor-implanted mice, which indicated that the laparoscopic OTN-NIR MSI could potentially be applied in vivo for classifying target lesions such as cancer in deep tissues.
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Affiliation(s)
- Toshihiro Takamatsu
- Exploratory Oncology Research & Clinical Trial Center, National Cancer Center, Kashiwa, Chiba 277-8577, Japan;
- Research Institute for Biomedical Sciences, Tokyo University of Science, Noda, Chiba 278-8510, Japan; (K.S.); (H.T.)
- Correspondence: ; Tel.: +81-04-7133-1111
| | - Yuichi Kitagawa
- Department of Materials Science and Technology, Tokyo University of Science, Katsushika, Tokyo 162-8601, Japan; (Y.K.); (R.I.); (K.O.); (M.U.)
| | - Kohei Akimoto
- Department of Mechanical Engineering, Tokyo University of Science, Noda, Chiba 278-8510, Japan; (K.A.); (Y.E.)
| | - Ren Iwanami
- Department of Materials Science and Technology, Tokyo University of Science, Katsushika, Tokyo 162-8601, Japan; (Y.K.); (R.I.); (K.O.); (M.U.)
| | - Yuto Endo
- Department of Mechanical Engineering, Tokyo University of Science, Noda, Chiba 278-8510, Japan; (K.A.); (Y.E.)
| | - Kenji Takashima
- Department of Gastroenterology and Endoscopy, National Cancer Center Hospital East, Kashiwa, Chiba 277-8577, Japan; (K.T.); (D.S.); (T.K.); (T.M.)
| | - Kyohei Okubo
- Department of Materials Science and Technology, Tokyo University of Science, Katsushika, Tokyo 162-8601, Japan; (Y.K.); (R.I.); (K.O.); (M.U.)
| | - Masakazu Umezawa
- Department of Materials Science and Technology, Tokyo University of Science, Katsushika, Tokyo 162-8601, Japan; (Y.K.); (R.I.); (K.O.); (M.U.)
| | - Takeshi Kuwata
- Department of Pathology and Clinical Laboratories, National Cancer Center Hospital East, Kashiwa, Chiba 277-8577, Japan;
| | - Daiki Sato
- Department of Gastroenterology and Endoscopy, National Cancer Center Hospital East, Kashiwa, Chiba 277-8577, Japan; (K.T.); (D.S.); (T.K.); (T.M.)
| | - Tomohiro Kadota
- Department of Gastroenterology and Endoscopy, National Cancer Center Hospital East, Kashiwa, Chiba 277-8577, Japan; (K.T.); (D.S.); (T.K.); (T.M.)
| | - Tomohiro Mitsui
- Department of Gastroenterology and Endoscopy, National Cancer Center Hospital East, Kashiwa, Chiba 277-8577, Japan; (K.T.); (D.S.); (T.K.); (T.M.)
| | - Hiroaki Ikematsu
- Exploratory Oncology Research & Clinical Trial Center, National Cancer Center, Kashiwa, Chiba 277-8577, Japan;
- Department of Gastroenterology and Endoscopy, National Cancer Center Hospital East, Kashiwa, Chiba 277-8577, Japan; (K.T.); (D.S.); (T.K.); (T.M.)
| | - Hideo Yokota
- RIKEN Center for Advanced Photonics, Wako, Saitama 351-0198, Japan;
| | - Kohei Soga
- Research Institute for Biomedical Sciences, Tokyo University of Science, Noda, Chiba 278-8510, Japan; (K.S.); (H.T.)
- Department of Materials Science and Technology, Tokyo University of Science, Katsushika, Tokyo 162-8601, Japan; (Y.K.); (R.I.); (K.O.); (M.U.)
| | - Hiroshi Takemura
- Research Institute for Biomedical Sciences, Tokyo University of Science, Noda, Chiba 278-8510, Japan; (K.S.); (H.T.)
- Department of Mechanical Engineering, Tokyo University of Science, Noda, Chiba 278-8510, Japan; (K.A.); (Y.E.)
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13
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Nogueira MS, Maryam S, Amissah M, Lu H, Lynch N, Killeen S, O’Riordain M, Andersson-Engels S. Evaluation of wavelength ranges and tissue depth probed by diffuse reflectance spectroscopy for colorectal cancer detection. Sci Rep 2021; 11:798. [PMID: 33436684 PMCID: PMC7804163 DOI: 10.1038/s41598-020-79517-2] [Citation(s) in RCA: 21] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/10/2020] [Accepted: 12/04/2020] [Indexed: 01/29/2023] Open
Abstract
Colorectal cancer (CRC) is the third most common type of cancer worldwide and the second most deadly. Recent research efforts have focused on developing non-invasive techniques for CRC detection. In this study, we evaluated the diagnostic capabilities of diffuse reflectance spectroscopy (DRS) for CRC detection by building 6 classification models based on support vector machines (SVMs). Our dataset consists of 2889 diffuse reflectance spectra collected from freshly excised ex vivo tissues of 47 patients over wavelengths ranging from 350 and 1919 nm with source-detector distances of 630-µm and 2500-µm to probe different depths. Quadratic SVMs were used and performance was evaluated using twofold cross-validation on 10 iterations of randomized training and test sets. We achieved (93.5 ± 2.4)% sensitivity, (94.0 ± 1.7)% specificity AUC by probing the superficial colorectal tissue and (96.1 ± 1.8)% sensitivity, (95.7 ± 0.6)% specificity AUC by sampling deeper tissue layers. To the best of our knowledge, this is the first DRS study to investigate the potential of probing deeper tissue layers using larger SDD probes for CRC detection in the luminal wall. The data analysis showed that using a broader spectrum and longer near-infrared wavelengths can improve the diagnostic accuracy of CRC as well as probing deeper tissue layers.
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Affiliation(s)
- Marcelo Saito Nogueira
- grid.7872.a0000000123318773Tyndall National Institute, Lee Maltings, Dyke Parade, Cork, Ireland ,grid.7872.a0000000123318773Department of Physics, University College Cork, College Road, Cork, Ireland
| | - Siddra Maryam
- grid.7872.a0000000123318773Tyndall National Institute, Lee Maltings, Dyke Parade, Cork, Ireland ,grid.7872.a0000000123318773Department of Physics, University College Cork, College Road, Cork, Ireland
| | - Michael Amissah
- grid.7872.a0000000123318773Tyndall National Institute, Lee Maltings, Dyke Parade, Cork, Ireland ,grid.7872.a0000000123318773Department of Physics, University College Cork, College Road, Cork, Ireland
| | - Huihui Lu
- grid.7872.a0000000123318773Tyndall National Institute, Lee Maltings, Dyke Parade, Cork, Ireland
| | - Noel Lynch
- grid.411785.e0000 0004 0575 9497Department of Surgery, Mercy University Hospital, Cork, Ireland
| | - Shane Killeen
- grid.411785.e0000 0004 0575 9497Department of Surgery, Mercy University Hospital, Cork, Ireland
| | - Micheal O’Riordain
- grid.411785.e0000 0004 0575 9497Department of Surgery, Mercy University Hospital, Cork, Ireland
| | - Stefan Andersson-Engels
- grid.7872.a0000000123318773Tyndall National Institute, Lee Maltings, Dyke Parade, Cork, Ireland ,grid.7872.a0000000123318773Department of Physics, University College Cork, College Road, Cork, Ireland
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14
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Baltussen EJM, Brouwer de Koning SG, Sanders J, Aalbers AGJ, Kok NFM, Beets GL, Hendriks BHW, Sterenborg HJCM, Kuhlmann KFD, Ruers TJM. Using Diffuse Reflectance Spectroscopy to Distinguish Tumor Tissue From Fibrosis in Rectal Cancer Patients as a Guide to Surgery. Lasers Surg Med 2019; 52:604-611. [PMID: 31793012 DOI: 10.1002/lsm.23196] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 11/16/2019] [Indexed: 01/10/2023]
Abstract
BACKGROUND AND OBJECTIVES In patients with rectal cancer who received neoadjuvant (chemo)radiotherapy, fibrosis is induced in and around the tumor area. As tumors and fibrosis have similar visual and tactile feedback, they are hard to distinguish during surgery. To prevent positive resection margins during surgery and spare healthy tissue, it would be of great benefit to have a real-time tissue classification technology that can be used in vivo. STUDY DESIGN/MATERIALS AND METHODS In this study diffuse reflectance spectroscopy (DRS) was evaluated for real-time tissue classification of tumor and fibrosis. DRS spectra of fibrosis and tumor were obtained on excised rectal specimens. After normalization using the area under the curve, a support vector machine was trained using a 10-fold cross-validation. RESULTS Using spectra of pure tumor tissue and pure fibrosis tissue, we obtained a mean accuracy of 0.88. This decreased to a mean accuracy of 0.61 when tumor measurements were used in which a layer of healthy tissue, mainly fibrosis, was present between the tumor and the measurement surface. CONCLUSION It is possible to distinguish pure fibrosis from pure tumor. However, when the measurements on tumor also involve fibrotic tissue, the classification accuracy decreases. Lasers Surg. Med. © 2019 Wiley Periodicals, Inc.
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Affiliation(s)
- Elisabeth J M Baltussen
- Department of Surgery, Antoni van Leeuwenhoek Hospital, The Netherlands Cancer Institute, Amsterdam, 1066 CX, The Netherlands
| | - Susan G Brouwer de Koning
- Department of Surgery, Antoni van Leeuwenhoek Hospital, The Netherlands Cancer Institute, Amsterdam, 1066 CX, The Netherlands
| | - Joyce Sanders
- Department of Pathology, Antoni van Leeuwenhoek Hospital, The Netherlands Cancer Institute, Amsterdam, 1066 CX, The Netherlands
| | - Arend G J Aalbers
- Department of Surgery, Antoni van Leeuwenhoek Hospital, The Netherlands Cancer Institute, Amsterdam, 1066 CX, The Netherlands
| | - Niels F M Kok
- Department of Surgery, Antoni van Leeuwenhoek Hospital, The Netherlands Cancer Institute, Amsterdam, 1066 CX, The Netherlands
| | - Geerard L Beets
- Department of Surgery, Antoni van Leeuwenhoek Hospital, The Netherlands Cancer Institute, Amsterdam, 1066 CX, The Netherlands
| | - Benno H W Hendriks
- Department of In-body Systems, Philips Research, Eindhoven, 5656 AE, The Netherlands.,Department of Biomechanical Engineering, Delft University of Technology, Delft, 2600 AA, The Netherlands
| | - Henricus J C M Sterenborg
- Department of Surgery, Antoni van Leeuwenhoek Hospital, The Netherlands Cancer Institute, Amsterdam, 1066 CX, The Netherlands.,Department of Biomedical Engineering and Physics, Amsterdam University Medical Centre, University of Amsterdam, Amsterdam, 1105 AZ, The Netherlands
| | - Koert F D Kuhlmann
- Department of Surgery, Antoni van Leeuwenhoek Hospital, The Netherlands Cancer Institute, Amsterdam, 1066 CX, The Netherlands
| | - Theo J M Ruers
- Department of Surgery, Antoni van Leeuwenhoek Hospital, The Netherlands Cancer Institute, Amsterdam, 1066 CX, The Netherlands.,Faculty TNW, Group Nanobiophysics, Twente University, Enschede, 7522 NB, The Netherlands
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