Optical coherence tomography for identification and quantification of human airway wall layers
High-resolution computed tomography has limitations in the assessment of airway wall layers and related remodeling in obstructive lung diseases. Near infrared-based optical coherence tomography (OCT) is a novel imaging technique that combined with bronchoscopy generates highly detailed images of the...
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| Published in: | PloS one Vol. 12; no. 10; p. e0184145 |
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| Language: | English |
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05.10.2017
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| Abstract | High-resolution computed tomography has limitations in the assessment of airway wall layers and related remodeling in obstructive lung diseases. Near infrared-based optical coherence tomography (OCT) is a novel imaging technique that combined with bronchoscopy generates highly detailed images of the airway wall. The aim of this study is to identify and quantify human airway wall layers both ex-vivo and in-vivo by OCT and correlate these to histology.
Patients with lung cancer, prior to lobectomy, underwent bronchoscopy including in-vivo OCT imaging. Ex-vivo OCT imaging was performed in the resected lung lobe after needle insertion for matching with histology. Airway wall layer perimeters and their corresponding areas were assessed by two independent observers. Airway wall layer areas (total wall area, mucosal layer area and submucosal muscular layer area) were calculated.
13 airways of 5 patients were imaged by OCT. Histology was matched with 51 ex-vivo OCT images and 39 in-vivo OCT images. A significant correlation was found between ex-vivo OCT imaging and histology, in-vivo OCT imaging and histology and ex-vivo OCT imaging and in-vivo OCT imaging for all measurements (p < 0.0001 all comparisons). A minimal bias was seen in Bland-Altman analysis. High inter-observer reproducibility with intra-class correlation coefficients all above 0.90 were detected.
OCT is an accurate and reproducible imaging technique for identification and quantification of airway wall layers and can be considered as a promising minimal-invasive imaging technique to identify and quantify airway remodeling in obstructive lung diseases. |
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| AbstractList | High-resolution computed tomography has limitations in the assessment of airway wall layers and related remodeling in obstructive lung diseases. Near infrared-based optical coherence tomography (OCT) is a novel imaging technique that combined with bronchoscopy generates highly detailed images of the airway wall. The aim of this study is to identify and quantify human airway wall layers both ex-vivo and in-vivo by OCT and correlate these to histology.Patients with lung cancer, prior to lobectomy, underwent bronchoscopy including in-vivo OCT imaging. Ex-vivo OCT imaging was performed in the resected lung lobe after needle insertion for matching with histology. Airway wall layer perimeters and their corresponding areas were assessed by two independent observers. Airway wall layer areas (total wall area, mucosal layer area and submucosal muscular layer area) were calculated.13 airways of 5 patients were imaged by OCT. Histology was matched with 51 ex-vivo OCT images and 39 in-vivo OCT images. A significant correlation was found between ex-vivo OCT imaging and histology, in-vivo OCT imaging and histology and ex-vivo OCT imaging and in-vivo OCT imaging for all measurements (p < 0.0001 all comparisons). A minimal bias was seen in Bland-Altman analysis. High inter-observer reproducibility with intra-class correlation coefficients all above 0.90 were detected.OCT is an accurate and reproducible imaging technique for identification and quantification of airway wall layers and can be considered as a promising minimal-invasive imaging technique to identify and quantify airway remodeling in obstructive lung diseases. High-resolution computed tomography has limitations in the assessment of airway wall layers and related remodeling in obstructive lung diseases. Near infrared-based optical coherence tomography (OCT) is a novel imaging technique that combined with bronchoscopy generates highly detailed images of the airway wall. The aim of this study is to identify and quantify human airway wall layers both ex-vivo and in-vivo by OCT and correlate these to histology. 13 airways of 5 patients were imaged by OCT. Histology was matched with 51 ex-vivo OCT images and 39 in-vivo OCT images. A significant correlation was found between ex-vivo OCT imaging and histology, in-vivo OCT imaging and histology and ex-vivo OCT imaging and in-vivo OCT imaging for all measurements (p < 0.0001 all comparisons). A minimal bias was seen in Bland-Altman analysis. High inter-observer reproducibility with intra-class correlation coefficients all above 0.90 were detected. OCT is an accurate and reproducible imaging technique for identification and quantification of airway wall layers and can be considered as a promising minimal-invasive imaging technique to identify and quantify airway remodeling in obstructive lung diseases. Background High-resolution computed tomography has limitations in the assessment of airway wall layers and related remodeling in obstructive lung diseases. Near infrared-based optical coherence tomography (OCT) is a novel imaging technique that combined with bronchoscopy generates highly detailed images of the airway wall. The aim of this study is to identify and quantify human airway wall layers both ex-vivo and in-vivo by OCT and correlate these to histology. Methods Patients with lung cancer, prior to lobectomy, underwent bronchoscopy including in-vivo OCT imaging. Ex-vivo OCT imaging was performed in the resected lung lobe after needle insertion for matching with histology. Airway wall layer perimeters and their corresponding areas were assessed by two independent observers. Airway wall layer areas (total wall area, mucosal layer area and submucosal muscular layer area) were calculated. Results 13 airways of 5 patients were imaged by OCT. Histology was matched with 51 ex-vivo OCT images and 39 in-vivo OCT images. A significant correlation was found between ex-vivo OCT imaging and histology, in-vivo OCT imaging and histology and ex-vivo OCT imaging and in-vivo OCT imaging for all measurements (p < 0.0001 all comparisons). A minimal bias was seen in Bland-Altman analysis. High inter-observer reproducibility with intra-class correlation coefficients all above 0.90 were detected. Conclusions OCT is an accurate and reproducible imaging technique for identification and quantification of airway wall layers and can be considered as a promising minimal-invasive imaging technique to identify and quantify airway remodeling in obstructive lung diseases. High-resolution computed tomography has limitations in the assessment of airway wall layers and related remodeling in obstructive lung diseases. Near infrared-based optical coherence tomography (OCT) is a novel imaging technique that combined with bronchoscopy generates highly detailed images of the airway wall. The aim of this study is to identify and quantify human airway wall layers both ex-vivo and in-vivo by OCT and correlate these to histology. Patients with lung cancer, prior to lobectomy, underwent bronchoscopy including in-vivo OCT imaging. Ex-vivo OCT imaging was performed in the resected lung lobe after needle insertion for matching with histology. Airway wall layer perimeters and their corresponding areas were assessed by two independent observers. Airway wall layer areas (total wall area, mucosal layer area and submucosal muscular layer area) were calculated. 13 airways of 5 patients were imaged by OCT. Histology was matched with 51 ex-vivo OCT images and 39 in-vivo OCT images. A significant correlation was found between ex-vivo OCT imaging and histology, in-vivo OCT imaging and histology and ex-vivo OCT imaging and in-vivo OCT imaging for all measurements (p < 0.0001 all comparisons). A minimal bias was seen in Bland-Altman analysis. High inter-observer reproducibility with intra-class correlation coefficients all above 0.90 were detected. OCT is an accurate and reproducible imaging technique for identification and quantification of airway wall layers and can be considered as a promising minimal-invasive imaging technique to identify and quantify airway remodeling in obstructive lung diseases. High-resolution computed tomography has limitations in the assessment of airway wall layers and related remodeling in obstructive lung diseases. Near infrared-based optical coherence tomography (OCT) is a novel imaging technique that combined with bronchoscopy generates highly detailed images of the airway wall. The aim of this study is to identify and quantify human airway wall layers both ex-vivo and in-vivo by OCT and correlate these to histology.BACKGROUNDHigh-resolution computed tomography has limitations in the assessment of airway wall layers and related remodeling in obstructive lung diseases. Near infrared-based optical coherence tomography (OCT) is a novel imaging technique that combined with bronchoscopy generates highly detailed images of the airway wall. The aim of this study is to identify and quantify human airway wall layers both ex-vivo and in-vivo by OCT and correlate these to histology.Patients with lung cancer, prior to lobectomy, underwent bronchoscopy including in-vivo OCT imaging. Ex-vivo OCT imaging was performed in the resected lung lobe after needle insertion for matching with histology. Airway wall layer perimeters and their corresponding areas were assessed by two independent observers. Airway wall layer areas (total wall area, mucosal layer area and submucosal muscular layer area) were calculated.METHODSPatients with lung cancer, prior to lobectomy, underwent bronchoscopy including in-vivo OCT imaging. Ex-vivo OCT imaging was performed in the resected lung lobe after needle insertion for matching with histology. Airway wall layer perimeters and their corresponding areas were assessed by two independent observers. Airway wall layer areas (total wall area, mucosal layer area and submucosal muscular layer area) were calculated.13 airways of 5 patients were imaged by OCT. Histology was matched with 51 ex-vivo OCT images and 39 in-vivo OCT images. A significant correlation was found between ex-vivo OCT imaging and histology, in-vivo OCT imaging and histology and ex-vivo OCT imaging and in-vivo OCT imaging for all measurements (p < 0.0001 all comparisons). A minimal bias was seen in Bland-Altman analysis. High inter-observer reproducibility with intra-class correlation coefficients all above 0.90 were detected.RESULTS13 airways of 5 patients were imaged by OCT. Histology was matched with 51 ex-vivo OCT images and 39 in-vivo OCT images. A significant correlation was found between ex-vivo OCT imaging and histology, in-vivo OCT imaging and histology and ex-vivo OCT imaging and in-vivo OCT imaging for all measurements (p < 0.0001 all comparisons). A minimal bias was seen in Bland-Altman analysis. High inter-observer reproducibility with intra-class correlation coefficients all above 0.90 were detected.OCT is an accurate and reproducible imaging technique for identification and quantification of airway wall layers and can be considered as a promising minimal-invasive imaging technique to identify and quantify airway remodeling in obstructive lung diseases.CONCLUSIONSOCT is an accurate and reproducible imaging technique for identification and quantification of airway wall layers and can be considered as a promising minimal-invasive imaging technique to identify and quantify airway remodeling in obstructive lung diseases. Background High-resolution computed tomography has limitations in the assessment of airway wall layers and related remodeling in obstructive lung diseases. Near infrared-based optical coherence tomography (OCT) is a novel imaging technique that combined with bronchoscopy generates highly detailed images of the airway wall. The aim of this study is to identify and quantify human airway wall layers both ex-vivo and in-vivo by OCT and correlate these to histology. Methods Patients with lung cancer, prior to lobectomy, underwent bronchoscopy including in-vivo OCT imaging. Ex-vivo OCT imaging was performed in the resected lung lobe after needle insertion for matching with histology. Airway wall layer perimeters and their corresponding areas were assessed by two independent observers. Airway wall layer areas (total wall area, mucosal layer area and submucosal muscular layer area) were calculated. Results 13 airways of 5 patients were imaged by OCT. Histology was matched with 51 ex-vivo OCT images and 39 in-vivo OCT images. A significant correlation was found between ex-vivo OCT imaging and histology, in-vivo OCT imaging and histology and ex-vivo OCT imaging and in-vivo OCT imaging for all measurements (p < 0.0001 all comparisons). A minimal bias was seen in Bland-Altman analysis. High inter-observer reproducibility with intra-class correlation coefficients all above 0.90 were detected. Conclusions OCT is an accurate and reproducible imaging technique for identification and quantification of airway wall layers and can be considered as a promising minimal-invasive imaging technique to identify and quantify airway remodeling in obstructive lung diseases. |
| Audience | Academic |
| Author | Goorsenberg, Annika W. M. de Bruin, Daniel M. d’Hooghe, Julia N. S. Roelofs, Joris J. T. H. Bonta, Peter I. Annema, Jouke T. |
| AuthorAffiliation | 2 Department of Biomedical Engineering & Physics, Academic Medical Center, University of Amsterdam, Amsterdam, the Netherlands 3 Department of Pathology, Academic Medical Center, University of Amsterdam, Amsterdam, the Netherlands 1 Department of Pulmonology, Academic Medical Center, University of Amsterdam, Amsterdam, the Netherlands Simon Fraser University, CANADA |
| AuthorAffiliation_xml | – name: 1 Department of Pulmonology, Academic Medical Center, University of Amsterdam, Amsterdam, the Netherlands – name: Simon Fraser University, CANADA – name: 3 Department of Pathology, Academic Medical Center, University of Amsterdam, Amsterdam, the Netherlands – name: 2 Department of Biomedical Engineering & Physics, Academic Medical Center, University of Amsterdam, Amsterdam, the Netherlands |
| Author_xml | – sequence: 1 givenname: Julia N. S. surname: d’Hooghe fullname: d’Hooghe, Julia N. S. – sequence: 2 givenname: Annika W. M. surname: Goorsenberg fullname: Goorsenberg, Annika W. M. – sequence: 3 givenname: Daniel M. surname: de Bruin fullname: de Bruin, Daniel M. – sequence: 4 givenname: Joris J. T. H. surname: Roelofs fullname: Roelofs, Joris J. T. H. – sequence: 5 givenname: Jouke T. surname: Annema fullname: Annema, Jouke T. – sequence: 6 givenname: Peter I. surname: Bonta fullname: Bonta, Peter I. |
| BackLink | https://www.ncbi.nlm.nih.gov/pubmed/28981500$$D View this record in MEDLINE/PubMed |
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| SubjectTerms | Aged Airway Remodeling Asthma Biology and Life Sciences Biopsy Bronchoscopy Bronchoscopy - methods Care and treatment CAT scans Catheters Chronic obstructive pulmonary disease Computed tomography Correlation Correlation coefficient Correlation coefficients Critical care Engineering and Technology Feasibility studies Female Histology Histopathology Humans Imaging Invasiveness Lung cancer Lung diseases Lung Diseases, Obstructive - diagnostic imaging Lung Neoplasms - diagnostic imaging Male Medical imaging Medicine and Health Sciences Middle Aged Mucosa Obstructive lung disease Optical Coherence Tomography Pathology Patients Physical Sciences Prospective Studies Remodeling Reproducibility Reproducibility of Results Research and Analysis Methods Respiratory System - diagnostic imaging Respiratory tract Smooth muscle Tomography Tomography, Optical Coherence - methods |
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| Title | Optical coherence tomography for identification and quantification of human airway wall layers |
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