title: Optical frequency domain imaging of ex vivo pulmonary resection specimens: obtaining one to one image to histopathology correlation.
abstract: Lung cancer is the leading cause of cancer-related deaths. Squamous cell and small cell cancers typically arise in association with the conducting airways, whereas adenocarcinomas are typically more peripheral in location. Lung malignancy detection early in the disease process may be difficult due to several limitations: radiological resolution, bronchoscopic limitations in evaluating tissue underlying the airway mucosa and identifying early pathologic changes, and small sample size and/or incomplete sampling in histology biopsies. High resolution imaging modalities, such as optical frequency domain imaging (OFDI), provide non-destructive, large area 3-dimensional views of tissue microstructure to depths approaching 2 mm in real time (Figure 1). OFDI has been utilized in a variety of applications, including evaluation of coronary artery atherosclerosis and esophageal intestinal metaplasia and dysplasia. Bronchoscopic OCT/OFDI has been demonstrated as a safe in vivo imaging tool for evaluating the pulmonary airways (Animation). OCT has been assessed in pulmonary airways and parenchyma of animal models and in vivo human airway. OCT imaging of normal airway has demonstrated visualization of airway layering and alveolar attachments, and evaluation of dysplastic lesions has been found useful in distinguishing grades of dysplasia in the bronchial mucosa. OFDI imaging of bronchial mucosa has been demonstrated in a short bronchial segment (0.8 cm). Additionally, volumetric OFDI spanning multiple airway generations in swine and human pulmonary airways in vivo has been described. Endobronchial OCT/OFDI is typically performed using thin, flexible catheters, which are compatible with standard bronchoscopic access ports. Additionally, OCT and OFDI needle-based probes have recently been developed, which may be used to image regions of the lung beyond the airway wall or pleural surface. While OCT/OFDI has been utilized and demonstrated as feasible for in vivo pulmonary imaging, no studies with precisely matched one-to-one OFDI:histology have been performed. Therefore, specific imaging criteria for various pulmonary pathologies have yet to be developed. Histopathological counterparts obtained in vivo consist of only small biopsy fragments, which are difficult to correlate with large OFDI datasets. Additionally, they do not provide the comprehensive histology needed for registration with large volume OFDI. As a result, specific imaging features of pulmonary pathology cannot be developed in the in vivo setting. Precisely matched, one-to-one OFDI and histology correlation is vital to accurately evaluate features seen in OFDI against histology as a gold standard in order to derive specific image interpretation criteria for pulmonary neoplasms and other pulmonary pathologies. Once specific imaging criteria have been developed and validated ex vivo with matched one-to-one histology, the criteria may then be applied to in vivo imaging studies. Here, we present a method for precise, one to one correlation between high resolution optical imaging and histology in ex vivo lung resection specimens. Throughout this manuscript, we describe the techniques used to match OFDI images to histology. However, this method is not specific to OFDI and can be used to obtain histology-registered images for any optical imaging technique. We performed airway centered OFDI with a specialized custom built bronchoscopic 2.4 French (0.8 mm diameter) catheter. Tissue samples were marked with tissue dye, visible in both OFDI and histology. Careful orientation procedures were used to precisely correlate imaging and histological sampling locations. The techniques outlined in this manuscript were used to conduct the first demonstration of volumetric OFDI with precise correlation to tissue-based diagnosis for evaluating pulmonary pathology. This straightforward, effective technique may be extended to other tissue types to provide precise imaging to histology correlation needed to determine fine imaging features of both normal and diseased tissues.
authors: Department of Pathology, Harvard Medical School, USA.
authors: Lida P
authors: LP
authors: Hariri
authors: Matthew B
authors: MB
authors: Applegate
authors: Mari
authors: M
authors: Mino-Kenudson
authors: Eugene J
authors: EJ
authors: Mark
authors: Brett E
authors: BE
authors: Bouma
authors: Guillermo J
authors: GJ
authors: Tearney
authors: Melissa J
authors: MJ
authors: Suter
mesh_terms: D000818:Animals; D006801:Humans; D007090:Image Interpretation, Computer-Assisted; D008168:Lung / Q000033:anatomy & histology* / Q000473:pathology* / Q000648:ultrastructure; D008171:Lung Diseases / Q000473:pathology; D013552:Swine; D041623:Tomography, Optical Coherence / Q000379:methods*
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