In Vivo Optical Coherence Tomography

In Vivo Optical Coherence Tomography The Role of the Pathologist Lida P. Hariri, MD, PhD; Mari Mino-Kenudson, MD; Eugene J. Mark, MD; Melissa J. Suter...
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In Vivo Optical Coherence Tomography The Role of the Pathologist Lida P. Hariri, MD, PhD; Mari Mino-Kenudson, MD; Eugene J. Mark, MD; Melissa J. Suter, PhD

 Optical coherence tomography (OCT) is a nondestructive, high-resolution imaging modality, providing crosssectional, architectural images at near histologic resolutions, with penetration depths up to a few millimeters. Optical frequency domain imaging is a second-generation OCT technology that has equally high resolution with significantly increased image acquisition speeds and allows for large area, high-resolution tissue assessments. These features make OCT and optical frequency domain imaging ideal imaging techniques for surface and endoscopic imaging, specifically when tissue is unsafe to obtain and/ or suffers from biopsy sampling error. This review focuses on the clinical impact of OCT in coronary, esophageal, and pulmonary imaging and the role of the pathologist in interpreting high-resolution OCT images as a complement to standard tissue pathology. (Arch Pathol Lab Med. 2012;136:1492–1501; doi: 10.5858/arpa.2012-0252-SA)

OPTICAL COHERENCE TOMOGRAPHY AND OPTICAL FREQUENCY DOMAIN IMAGING ptical coherence tomography (OCT) is a nondestructive, high-resolution imaging modality that generates cross-sectional images with endogenous contrast based on mismatches in index of refraction (Figure 1, A).1–3 Optical coherence tomography is similar in principle to ultrasound, but, rather than measuring the sound echoes reflected back from the tissue, OCT measures the amount of backscattered near-infrared light. This results in significantly higher

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Accepted for publication June 7, 2012. From the Departments of Pathology (Drs Hariri, Mino-Kenudson, and Mark), the Pulmonary and Critical Care Unit (Dr Suter), and the Wellman Center for Photomedicine, Massachusetts General Hospital, Boston (Drs Hariri and Suter); and the Harvard Medical School, Cambridge, Massachusetts (Drs Hariri, Mino-Kenudson, Mark, and Suter). Dr Suter receives research support from NinePoint Medical, Cambridge, Massachusetts. Dr Suter reserves the right to receive royalty payments from NinePoint Medical. The other authors have no relevant financial interest in the products or companies described in this article. Presented at the Houston Lung Symposium; April 28–29, 2012; Houston, Texas. Reprints: Lida P. Hariri, MD, PhD, Department of Pathology, Massachusetts General Hospital, 55 Fruit St, Warren Building 219, Boston, MA 02114, (e-mail: [email protected]). 1492 Arch Pathol Lab Med—Vol 136, December 2012

resolutions (,10 lm axial, 20–40 lm lateral) than can be achieved with ultrasound. However, the rapid attenuation of the OCT signal in tissue, because of the scattering and absorption of light, results in shallower depth penetration which is typically limited to 1 to 3 mm.4 Because of the rapid speed of light propagation in tissue, the delay of the optical echoes is measured with lowcoherence interferometry. Light from a broadband nearinfrared source is split into 2 paths: one path travels to a sample arm, where light is focused onto the tissue sample, and the other travels to a reference arm, which typically consists of a mechanically scanning reference mirror.1–3 When the optical path length of light backscattered from the sample and light reflected from the reference mirror are within the coherence length of the light source, constructive interference occurs, and a signal is generated. When the light returning from the sample and reference arms are not within the coherence length of the light source, destructive interference occurs, and no signal is generated. This allows for precise detection of backscattered signal associated with a specific tissue depth. To generate an axial depth profile, or A-line, the reference mirror is mechanically scanned to alter the optical path length of the reference arm and, therefore, the location within the tissue. Two-dimensional and 3dimensional images can be generated by systematically scanning the OCT light source across the tissue. Optical coherence tomography is limited in its imaging speed to only a few frames per second. Optical frequency domain imaging (OFDI), also termed frequency domain optical coherence tomography or swept source optical coherence tomography, is a second-generation OCT imaging technology capable of significantly more rapid image acquisition rates (100 times faster, up to 200 frames/s) without compromising image quality (Figure 1, A).5–12 This increased image acquisition speed allows for high-resolution imaging over larger tissue volumes, providing a method of in vivo comprehensive microscopy. Both OCT and OFDI systems are compatible with benchtop imaging and a variety of catheter-based imaging systems (Figure 1, A through C). Throughout the rest of this article, the term OCT refers to both traditional time-domain OCT and OFDI. The nondestructive nature and high-resolution inherent to OCT imaging is ideal for imaging tissue during standard endoscopic procedures. Optical coherence tomography is particularly useful when tissue cannot be removed for pathologic assessment, such as in assessment of coronary artery disease. In clinical scenarios where tissue biopsy samples are collected to assess pathology but suffer from In Vivo OCT: The Role of the Pathologist—Hariri et al

Figure 1. Principles of optical coherence tomography and optical frequency domain imaging. A, Minimally invasive catheters or endoscopes provide for access of the optical fiber to the organ or system of interest. An optical beam is focused into the tissue, and the backreflected signal is detected to form a single depth profile along the axial line (or A-line). A-lines are continuously acquired as the probe is actuated to provide spatial scanning of the beam in 2 directions that are orthogonal to the axial line (rotational and pull-back motion by a rotary junction). The resulting 3dimensional data sets can be rendered and viewed in arbitrary orientations for gross screening, and individual, high-resolution cross-sections can be displayed at specific locations of interest. Reprinted from Yun et al,12 Nature Medicine, 2006;12(12):1429–1433, with permission from the Nature Publishing Group. B, Balloon catheter for esophageal imaging with proximal stabilization device and distal, rapid guidewire-exchange provision. The balloon acts to dilate the esophageal lumen and center the inner optical core. The inflation diameter of the balloon is 25 mm, and the imaging window is 6.5 cm. The inner optical core (1 mm in diameter) is contained inside a sheath that allows the core to move (rotate and translate) independently of the balloon catheter. Optical rotary junction is mounted on the pullback tray and connected to the proximal portion of the imaging catheter. Reprinted from Suter et al,53 Gastrointestinal Endoscopy, 2008;68(4):745–753, with permission from Elsevier. C, Side-facing, optical coherence tomography needle probe encased in a 23-gauge needle. Reprinted from Quirk et al,59 Journal of Biomedical Optics, 2011;16(3):036009 with permission from the Journal of Biomedical Optics.

sampling errors, such as the assessment of intestinal metaplasia and dysplasia of the esophagus, OCT can aid in guiding biopsy-site selection to reduce the likelihood of missed diagnoses. In pulmonary pathology, tissue biopsy may suffer from small sample size as well as sampling error. Optical coherence tomography can aid in guiding biopsysite selection to ensure accurate targeting of lesional tissue and to increase diagnostic yield of tissue biopsy. The large volumes of tissue assessed by second-generation OCT also provide a form of additional virtual in vivo tissue, which could be used for pathologic assessment, in addition to the physical tissue collected. As the imaging features of various tissue pathologies are developed and validated, OCT may be able to provide an in vivo optical biopsy. The pathologist is Arch Pathol Lab Med—Vol 136, December 2012

well suited to play a role in the development and implementation of OCT in clinical practice, interpreting high-resolution OCT images as a complement to standard tissue pathology. Although OCT has been conducted in many clinical applications, we will briefly touch on intracoronary, esophageal, and pulmonary OCT imaging. OCT in Intravascular Coronary Imaging The vulnerable plaque, termed the thin-cap fibroatheroma, has been identified as the culprit lesion in approximately 80% of sudden cardiac deaths.13–19 The thin-cap fibroatheroma typically consists of a minimally occlusive, atheromatous lesion with the following histologic features: (1) thin, fibrous cap (,65 lm); (2) large lipid pool; and (3) activated In Vivo OCT: The Role of the Pathologist—Hariri et al 1493

Table 1.

Summary of Optical Coherence Tomography (OCT) Findings for the Identification and Quantification of Intravascular Microstructure

Arterial Microstructure

OCT Appearance

Source, y

Macrophages Cholesterol crystals White thrombus Red thrombus Calcium deposits Lipid-rich plaques

Signal-rich, heterogeneously distributed, discrete structures Signal-rich, heterogeneously distributed, linear structures Homogeneous signal, spatially disparate from the arterial wall High signal attenuation, spatially disparate from the arterial wall Echolucent regions with sharply demarcated borders Echolucent regions with poorly demarcated borders

MacNeill et al,31 2004; Tearney et al,32 2004 Tearney et al,23 2006; Tearney et al,33 2003 Jang et al,34 2002; Kume et al,35 2006 Jang et al,34 2002; Kume et al,35 2006 Yabushita et al,24 2002; Rieber et al,36 2006 Yabushita et al,24 2002; Rieber et al,36 2006; Kume et al,82 2007 Yabushita et al,24 2002; Rieber et al,36 2006

Fibrous plaques

Strong, homogeneous signal regions 37

Reprinted from Suter et al,

IEEE Journal of Selected Topics in Quantum Electronics, 2010;16(4):706–714, with permission from IEEE.

macrophages near or within the fibrous cap.13–19 Clearly, biopsy of coronary arteries in patients to evaluate these features is not feasible. The ability to assess vulnerable plaques nondestructively with near-histologic resolution during in vivo, intracoronary imaging may significantly enhance the evaluation and management of patients with coronary artery disease. Intravascular optical coherence tomography has been studies by many groups.12,20–38 Thin, flexible intracoronary OCT catheters have been developed that are compatible with standard percutaneous coronary intervention techniques (Figure 1, A). These catheters facilitate imaging of the coronary arteries during proximal balloon occlusion or flushing of the vessel to temporarily displace the highly light-scattering blood from the imaging field of view. Large scale, ex vivo studies have been performed to develop and validate OCT diagnostic criteria for atheromatous lesions, including the identification of features of thin-cap fibroatheromas (Table 1).20–30,37 Fibrous plaques were characterized by homogeneous, signal-rich regions; fibrocalcific plaques by signal-poor regions with sharp borders; and lipid-rich plaques by signal-poor regions with diffuse borders (Figure 2, A through F). These OCT imaging criteria demonstrated high sensitivities and specificities for various plaque morphologies (71%–79% and 97%–98% for fibrous plaques, 95%– 96% and 97% for fibrocalcific plaques, and 90%–94% and 90%–92% for lipid-rich plaques, respectively) in blinded assessments.24 Calcific nodules appear as signal-poor regions with a sharp delineation between the calcific nodule and the surrounding tissue. Optical coherence tomography imaging of cholesterol crystals demonstrated linearly oriented, highly reflecting structures within atheromatous plaques.24 The high refractive index contrast results in strong optical signals from macrophages. Studies evaluating the ability to quantify macrophage density in fibrous caps yielded greater than 90% sensitivity and specificity for identifying caps containing more than 10% CD68 staining.32 Optical coherence tomography identification of all 3 components of thin-cap fibroatheromas with high sensitivity and specificity provides nondestructive, in vivo assessments of vulnerable plaques during standard percutaneous coronary intervention procedures. Intracoronary OCT is becoming a widely used tool in interventional cardiology with the potential to affect clinical management of coronary artery disease. OCT in Esophageal Imaging Barrett’s esophagus, or specialized intestinal metaplasia (SIM), is a major risk factor for the development of 1494 Arch Pathol Lab Med—Vol 136, December 2012

esophageal adenocarcinoma. For patients with known SIM, periodic endoscopic surveillance is recommended to screen for high-grade dysplasia and intramucosal carcinoma.39–44 Current guidelines for surveillance recommend 4quadrant biopsies at 1- to 2-cm increments along the axial length of the glandular mucosa of the distal esophagus; however, the efficacy of surveillance endoscopy is limited by sampling error.40–44 The ability to provide a more targeted approach to surveillance endoscopic biopsy via in vivo OCT may decrease sampling error and increase diagnostic yield. The use of OCT for differentiating esophageal pathology relevant to screening and surveillance of Barrett’s esophagus has been conducted by many groups.45–53 A novel ballooncentering OCT catheter was developed to conduct volumetric imaging of the entire distal esophagus (6 cm) (Figure 1, B).53 Squamous mucosa is characterized by the presence of layering without epithelial glands. Gastric cardia is characterized by the identification of at least 2 of the following features: vertical pit structure; well-defined, epithelial surface reflectivity; relatively poor image penetration; and/or broad, regular foveolar regions or rugae. Specialized intestinal metaplasia is characterized by the presence of glands in a layered epithelium, or at least 2 of the following features: lack of layered or vertical pit architecture; heterogeneous scattering; or an irregular surface (Figure 3, A through F). The OCT diagnostic criteria are summarized in Table 2.53 The potential of OCT to diagnose SIM has been demonstrated in prospective studies, with sensitivities of 81% to 97% and specificities of 57% to 92%.45–53 Additionally, studies have demonstrated successful grading of dysplasia with OCT. Reported sensitivities and specificities for detecting high-grade dysplasia/intramucosal carcinoma range from 54% to 83% and 72% to 75%, respectively.45–53 Currently, studies are being conducted to evaluate real-time endoscopic OCT-guided biopsy with laser marking in patients.53–55 OCT in Pulmonary Imaging Pathology diagnosis of lung biopsies and fine-needle aspirations can be limited by small tissue volumes and/or sampling errors. Larger quantities of tissue can improve diagnostic yield but are often difficult to obtain. The ability to assess larger tissue volumes by high-resolution OCT during bronchoscopy could potentially enhance biopsy site selection of targeted lesions and provide considerably more architectural information via ‘‘virtual tissue,’’ which may be used to aid diagnosis. Helical-scanning OCT catheters can be used to generate cross-sectional or volumetric images of the airways and are ideal for endobronchial imaging (Figure 1). Second-generIn Vivo OCT: The Role of the Pathologist—Hariri et al

Figure 2. Optical coherence tomography (OCT) imaging of in vivo coronary artery. The OCT images and corresponding histology for fibrous (A and B), calcific (C and D), and lipid-rich (E and F) plaque types (obtained ex vivo). In fibrous plaques, the OCT signal (Fib) is observed to be strong and homogeneous. In comparison, both calcific (arrows) and lipid-rich regions (L) appear as signal-poor regions within the vessel wall. Lipid-rich plaques have diffuse or poorly demarcated borders, whereas the borders of calcific nodules are sharply delineated (hematoxylin-eosin, original magnifications 340 [B and D] and Masson trichome, original magnification 340 [F]; scale bars, tick marks, 500 l). Reprinted from Tearney et al,23 Journal of Biomedical Optics, 2006;11(2):021002, with permission from the Journal of Biomedical Optics.

ation OCT (OFDI) is capable of imaging entire bronchial segments, spanning multiple airway generations, and obtaining comprehensive microstructural evaluations in 3 dimensions. Optical coherence tomography has been used to assess the pulmonary airways and parenchyma in animal models56–61 and in vivo human airway.62–68 Optical coherence tomography imaging of the normal bronchial wall (Figure 4, A through E) reveals the fine, layered features of the airway, including the epithelium, basement membrane, lamina propria, salivary-type glands and ducts, vessels, and cartilage with surrounding perichondrium. In more distal airways, airway layering and attached lattice-like, signalvoid alveoli can be appreciated. In vivo OCT imaging of airway-based carcinomas reveals architectural disorganization of the bronchial layering, segments of mucosa where normal surface maturation is lost, and increased surfaceimage intensity when compared with the underlying tissue.64,66,67 The ability of OCT to discern preinvasive cancers of the bronchial mucosa has been assessed.67,68 Lam et al68 used OCT to evaluate bronchial mucosal lesions identified by autofluorescence bronchoscopy in a group of high-risk smokers. A total of 281 OCT images were evaluated from 148 patients (145 normal/hyperplasia, 61 metaplasia, 39 mild dysplasia, 10 moderate dysplasia, 6 severe dysplasia, 7 Arch Pathol Lab Med—Vol 136, December 2012

carcinoma in situ, and 13 invasive carcinomas). Normal respiratory epithelium or hyperplasia was characterized by 1 or 2 cell layers above a highly scattering basement membrane and upper lamina propria. Thickening of the epithelial cell layer was observed in metaplasia, various grades of dysplasia, and carcinoma in situ. Quantitative evaluation of epithelial thickness revealed that invasive carcinoma appears to have a significantly thicker epithelium than does carcinoma in situ (P ¼ .004). Dysplasia was found to have significantly thicker epithelium than was seen in metaplasia or hyperplasia (P ¼ .002). The basement membrane was still intact in carcinoma in situ, but was discontinuous or no longer visible in invasive cancer.68 Solitary pulmonary nodules frequently require biopsy to determine malignant potential. Peripheral lesions may be assessed via transthoracic fine-needle aspiration, which has reasonable diagnostic yields but has an increased rate of pneumothorax (pneumothorax rate of approximately 25%, of which, at least 15% require chest tube insertion).69 Transbronchial needle aspiration has a much lower risk of pneumothorax, but the diagnostic yield can be as low as 14%, even with the acquisition of 4 to 8 serial tissue specimens.69–71 The diagnostic yield of transbronchial needle aspiration does increase when performed in conjunction with biopsy-guidance techniques, such as endobronchial In Vivo OCT: The Role of the Pathologist—Hariri et al 1495

Figure 3. Optical coherence tomography (OCT) of specialized intestinal metaplasia (SIM) of the esophagus. A, OCT image of SIM without dysplasia demonstrates glandular architecture with a relatively low reflectivity. B, Histology corresponding to A, with an inset that demonstrates a low nuclear to cytoplasm ratio in the superficial epithelium. C, OCT image of intramucosal carcinoma/high-grade dysplasia enables visualization of large and irregular glands (arrows). D, Irregular, dilated glands are also seen in the histology corresponding to C (arrows). E, OCT image of intramucosal carcinoma/high-grade dysplasia shows a disorganized architecture and increased surface reflectivity (arrows). F, Histology corresponding to E demonstrates abnormal glandular architecture and an increased superficial nuclear to cytoplasm ration (inset) (hematoxylin-eosin; original magnifications, 340 [B, D, and F]; scale bars, 500 l). Reprinted from Evans et al,47 Clinical Gastroenterology and Hepatology, 2006;4(1):38–43, with permission from Elsevier.

Table 2. Optical Coherence Tomography (OCT) Diagnostic Criteria Developed and Prospectively Tested to Diagnose SIM and to Grade Dysplasia Diagnosis

OCT Finding

Normal 1. Layered architecture squamous mucosa 1. Vertical pit and crypt architecture Normal cardiaa 2. Highly reflective surface 3. Broad, regular-glandular architecture 4. Poor image penetration SIMb

1. Lack of layered or vertical pit and crypt architecture 2. Heterogeneous scattering 3. Irregular surface 4. Glands in epithelium with layered architecture

HGD/IMCc

1. Increased surface/subsurface reflectivity (score, 0–2) 2. Irregular gland/duct architecture (score, 0–2)

Abbreviations: HGD, high-grade dysplasia; IMC, intramucosal carcinoma; SIM, specialized intestinal metaplasia. a See algorithm in Evans et al,46 2007. b Two of the first 3 criteria or the fourth criterion indicate SIM. c Total score 2 indicates HGD/IMC. Reprinted from Suter et al, 5 3 Gastrointestinal Endoscopy, 2008;68(4):745–753, with permission from Elsevier. 1496 Arch Pathol Lab Med—Vol 136, December 2012

ultrasound72; however, the yield is still unacceptably low, particularly for lesions smaller than 2 cm in diameter (,33%).69–71,73,74 Recently developed, needle-based OCT catheters provide a method to image peripheral lung (Figure 1, C).59,60 In particular, a novel, needle-based OCT catheter, developed to be compatible with standard bronchoscopic transbronchial biopsy/needle aspiration, has the potential to access solitary, peripheral nodules, assess needle location just before tissue acquisition, and potentially increase diagnostic yield.60 Preliminary studies have demonstrated the potential of OCT for identifying pulmonary pathology in vivo. However, before OCT can make a significant impact, in vivo OCTimage interpretation criteria for pulmonary pathology need to be developed and validated, similar to the validated OCT criteria for intracoronary and esophageal imaging. To appropriately characterize OCT imaging features of normal airway, parenchyma, and pulmonary pathology, images need to be correlated one-to-one with histopathology, which can only be performed in the ex vivo setting. In a recent ex vivo study, initial OCT-image feature interpretations of common, benign, and malignant lung lesions and interstitial fibrosis were described by precisely correlating OCT images with histopathology (Table 3)57:   

Carcinomas displayed architectural disarray with loss of normal airway/alveolar structure and rapid light attenuation. Squamous cell carcinomas showed nested architecture. Atypical glandular formation was seen in adenocarcinomas. In Vivo OCT: The Role of the Pathologist—Hariri et al

Figure 4. In vivo bronchoscopic optical frequency domain imaging (OFDI) of normal airway. A, An OFDI cross section of airway. B, Highermagnification view of the airway cross section, visualizing typical layering of the airway, including respiratory epithelium (e), transition between epithelium and underlying basement membrane/lamina propria (b), lamina propria (lp), perichondrium (p), and cartilage (c). C, Representative histology from a normal airway, demonstrating similar layering to the in vivo OFDI airway image shown in B. D, Higher-magnification view of the airway cross section demonstrates alveolar attachments (arrows) with overlying respiratory epithelium (e), transition between epithelium and underlying basement membrane/lamina propria (b), and lamina propria (lp). E, Representative histology from a normal airway demonstrating similar layering and alveolar attachments as seen in the in vivo OFDI airway image shown in D. Legend: asterisks, OFDI imaging artifacts; scale bars on histology images, 0.5 mm; tick marks in OFDI images, 0.5 mm. Reprinted from Hariri et al57 [published online ahead of print March 29, 2012], CHEST, doi:10.1378/chest.11–2797, with permission from American College of Chest Physicians.

Figure 5. Ex vivo optical frequency domain imaging (OFDI) of mucinous adenocarcinoma. A, An OFDI catheter-based longitudinal section (scale bar, 5.0 mm). B, An OFDI, catheter-based cross section at the site of the red line shown in A (scale bar, 1.0 mm). C and D An OFDI benchtop longitudinal section and the corresponding histology (scale bars, 1.0 mm). E, Higher-magnification of the OFDI benchtop longitudinal section shown in C and the corresponding histology at location of the box shown in D (scale bars, 1.0 mm). Legend: asterisks, ink marks; V, blood vessel; fat arrows, tumor-associated scar; thin arrows, thickened, signal-intense alveolar walls. Reprinted from Hariri et al57 [published online ahead of print March 29, 2012], CHEST, doi:10.1378/chest.11–2797, with permission from American College of Chest Physicians. Arch Pathol Lab Med—Vol 136, December 2012

In Vivo OCT: The Role of the Pathologist—Hariri et al 1497

Figure 6. Ex vivo optical frequency domain imaging (OFDI) of usual interstitial pneumonitis. A, En face OFDI at the location of the side tick marks shown in B. B and C, An OFDI longitudinal section and the corresponding histopathology. D, An OFDI cross section. E, Histopathology from the longitudinal section corresponding to subpleural cyst shown in D. Legend: asterisks, ink marks; boxed regions, subpleural cystic spaces; F, subpleural fibrosis; P, pleural surface (scale bars, 1.0 mm). Reprinted from Hariri et al57 [published online ahead of print March 29, 2012], CHEST, doi:10.1378/ chest.11–2797, with permission from American College of Chest Physicians.  





Uniform trabecular gland formation was seen in salivary gland carcinomas. Mucinous adenocarcinomas (previously know as mucinous bronchioloalveolar carcinomas) showed alveolar wall thickening with intra-alveolar mucin (Figure 5, A through F). Cartilaginous hamartomas showed well-circumscribed, lobulated architecture with evenly dispersed, fine-scale regions of high signal intensity. Interstitial fibrosis was visualized as signal-dense tissue, with an interstitial distribution in mild interstitial fibrotic disease and a diffuse, subpleural pattern of signal-dense tissue with cystic space formation in usual interstitial pneumonitis (Figure 6, A through E).57

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The acquisition of large, volumetric OCT data sets, both endobronchially and transbronchially, may provide additional architectural information (comparable to low power bright field microscopy) to accompany standard biopsies. For instance, OCT could be particularly useful in instances where small tissue biopsies are needed for multiple pathology assessments, such as in biopsies of carcinoma, where tissue must be used for both histologic tumor subclassification and molecular analyses.75–81 Optical coherence tomography could both increase tumor yield by intraprocedural guidance of biopsy-site selection and provide a form of additional, ‘‘virtual’’ tissue for the pathologist to assess as a complement to the tissue biopsy. In Vivo OCT: The Role of the Pathologist—Hariri et al

Table 3.

Initial Optical Frequency Domain Imaging Features of Pulmonary Pathology

Pathology Normal Airway

Parenchyma Neoplastic Adenocarcinoma Mucinous adenocarcinoma

Squamous cell carcinoma, basaloid type

Salivary gland adenocarcinoma, adenoid cystic carcinoma

Benign Cartilaginous hamartoma

Fibrosis Usual interstitial fibrosis Focal, mild, subpleural fibrosis, idiopathic

Imaging Features Layered architecture, including Respiratory epithelium and underlying basement membrane Lamina propria Cartilaginous rings Thin, lattice-like, alveolar architecture, with signal void spaces Loss of layered architecture Mass with signal heterogeneity with rapid attenuation Atypical gland formation Signal-intense alveolar wall thickening Preserved, lattice-like architecture Signal-poor, intra-alveolar mucin Homogeneous, signal-intense tumor-associated scar may be seen Loss of layered architecture Mass with signal heterogeneity and rapid attenuation Irregular tumor nests with Signal-intense periphery corresponding to malignant cells Signal-poor center corresponding to central necrosis Luminal mass protrusion Uniform distribution of signal-intense trabeculae Small, pseudocystic spaces, filled with mucin Intact, overlying respiratory epithelium may be present Lobulated mass, with well-delineated borders and Evenly dispersed, fine-scale regions of high signal intensity Background of uniform, moderate signal intensity Diffuse, signal-dense, subpleural fibrosis Irregularly shaped, signal-poor, subpleural cysts Focal, signal-dense, pleural fibrosis Interspersed latticelike alveoli, with mildly thickened alveolar walls

Reprinted from Hariri et al,57 [published online ahead of print March 29, 2012], CHEST, doi:10.1378/chest.11–2797, with permission from the American College of Chest Physicians.

In cases of interstitial pneumonitis, patients often must undergo thoracoscopic wedge resections of multiple lung lobes to obtain diagnostic tissue for histopathology. This form of surgical assessment can be problematic because these patients often have severely compromised respiratory systems, and both the surgical procedure and the loss of lung tissue may pose a significant risk for respiratory failure. The ability to visualize the small, subpleural cystic spaces in a background of subpleural fibrosis with OCT is very promising (Figure 6). These features could possibly be used to identify areas of diagnostic tissue for biopsy (to avoid areas consisting predominantly of cystic spaces [honey combing]) and to decrease the amount of tissue needed to make the histologic diagnosis. However, for OCT to be used in these types of settings, the imaging features of a variety of pulmonary diseases would have to be established and validated in large-scale studies. THE ROLE OF THE PATHOLOGIST Optical coherence tomography provides high-resolution, cross-sectional, architectural information that is homologous to low power (34) microscopy. In clinical scenarios in which there are few diagnostic possibilities with somewhatstraightforward imaging features, such as in coronary and esophageal imaging, image interpretation will likely be performed by the interventionalist at the time of procedure. In coronary imaging, OCT provides a means of tissue assessment where a biopsy is not obtainable for pathology Arch Pathol Lab Med—Vol 136, December 2012

evaluation. When performed and assessed in real time, intracoronary OCT could aid in plaque assessment and patient management. The nondestructive nature of OCT also allows for serial imaging, which could aid in increasing our understanding of the pathophysiology and natural history of the vulnerable plaque. Regular Barrett’s esophagus surveillance protocols for the detection of dysplasia and adenocarcinoma suffer from sampling errors. Volumetric OCT of the entire distal esophagus performed during endoscopy could be used to identify regions most suspicious for high-grade dysplasia and/or carcinoma to guide biopsy-site selection and to improve the performance of endoscopic biopsies. Similar to intracoronary OCT, this form of OCT image assessment would likely be performed by the endoscopist during the procedure. Optical coherence tomography has numerous, potential clinical applications in pulmonary medicine and may be used during bronchoscopy to guide biopsy-site selection in both the conducting airways and the parenchyma. Similar to coronary and esophageal imaging, both pulmonary nodules and adjacent normal lung have distinct imaging features and could be evaluated by the pulmonologist in real-time during bronchoscopy to guide biopsy-site selection. Additionally, OCT could also be used to identify regions of fibrosis and/or necrosis within nodules, which could then be avoided by the pulmonologist during biopsy acquisition. This would likely result in increased diagnostic yield of both endobronchial and transbronchial biopsies. In Vivo OCT: The Role of the Pathologist—Hariri et al 1499

However, in contrast to coronary and esophageal pathology, the differential diagnosis of pulmonary nodules can be quite broad, often including reactive, infectious, benign, and/or malignant etiologies. The ability to distinguish these entities requires knowledge of the histomorphologic features characteristic of each entity, which is a skill set inherent to pathologists. Thus, volumetric data sets as a form of ‘‘virtual’’ tissue would be best evaluated by the pathologist interpreting the accompanying physical tissue biopsy. Features seen in OCT imaging are likely related to the histopathologic architecture characteristics of each entity. For example, squamous cell carcinomas frequently display signal-intense nests, which correspond to nests of malignant squamous cell cells, whereas atypical gland formation is seen in many adenocarcinomas. Given the strong parallels between histopathology and OCT imaging, trained pathologists should be ideal interpreters of OCT images. Pulmonary pathologists have been involved in the development of the initial imaging features described in Table 3. However, for OCT to be used as a diagnostic modality complementary to tissue biopsy, OCT imaging criteria of a variety of pulmonary pathologies will have to be established and validated in large-scale studies and will require continued involvement of pathologists. References 1. Brezinski ME, Tearney GJ, Bouma BE, et al. Optical coherence tomography for optical biopsy: properties and demonstration of vascular pathology. Circulation. 1996;93(6):1206–1213. 2. Tearney GJ, Brezinski ME, Bouma BE, et al. In vivo endoscopic optical biopsy with optical coherence tomography. Science. 1997;276(5321):2037– 2039. 3. Huang D, Swanson EA, Lin CP, et al. Optical coherence tomography. Science. 1991;254(5035):1178–1181. 4. Sainter AW, King TA, Dickinson MR. Effect of target biological tissue and choice of light source on penetration depth and resolution in optical coherence tomography. J Biomed Opt. 2004;9(1):193–199. 5. Braaf B, Vermeer KA, Sicam VA, van Zeeburg E, van Meurs JC, de Boer JF. Phase-stabilized optical frequency domain imaging at 1-microm for the measurement of blood flow in the human choroid. Opt Express. 2011;19(21): 20886–20903. 6. Choma M, Sarunic M, Yang C, Izatt J. Sensitivity advantage of swept source and Fourier domain optical coherence tomography. Opt Express. 2003;11(18): 2183–2189. 7. Gora M, Karnowski K, Szkulmowski M, et al. Ultra high-speed swept source OCT imaging of the anterior segment of human eye at 200 kHz with adjustable imaging range. Opt Express. 2009;17(17):14880–14894. 8. Oh WY, Vakoc BJ, Shishkov M, Tearney GJ, Bouma BE. .400 kHz repetition rate wavelength-swept laser and application to high-speed optical frequency domain imaging. Opt Lett. 2010;35(17):2919–2921. 9. Yun S, Tearney G, Bouma B, Park B, de Boer J. High-speed spectral-domain optical coherence tomography at 1.3 mum wavelength. Opt Express. 2003; 11(26):3598–3604. 10. Yun S, Tearney G, de Boer J, Bouma B. Removing the depth-degeneracy in optical frequency domain imaging with frequency shifting. Opt Express. 2004; 12(20):4822–4828. 11. Yun S, Tearney G, de Boer J, Iftimia N, Bouma B. High-speed optical frequency-domain imaging. Opt Express. 2003;11(22):2953–2963. 12. Yun SH, Tearney GJ, Vakoc BJ, et al. Comprehensive volumetric optical microscopy in vivo. Nat Med. 2006;12(12):1429–1433. 13. Davies MJ. Stability and instability: two faces of coronary atherosclerosis— the Paul Dudley White Lecture 1995. Circulation. 1996;94(8):2013–2020. 14. Davies MJ. Detecting vulnerable coronary plaques. Lancet. 1996; 347(9013):1422–1423. 15. Falk E. Why do plaques rupture? Circulation. 1992;86(6)(suppl III):30–42. 16. Kolodgie FD, Burke AP, Farb A, et al. The thin-cap fibroatheroma: a type of vulnerable plaque: the major precursor lesion to acute coronary syndromes. Curr Opin Cardiol. 2001;16(5):285–292. 17. Virmani R, Burke AP, Farb A, Kolodgie FD. Pathology of the unstable plaque. Prog Cardiovasc Dis. 2002;44(5):349–356. 18. Virmani R, Burke AP, Kolodgie FD, Farb A. Vulnerable plaque: the pathology of unstable coronary lesions. J Interv Cardiol. 2002;15(6):439–446. 19. Virmani R, Kolodgie FD, Burke AP, Farb A, Schwartz SM. Lessons from sudden coronary death: a comprehensive morphological classification scheme for atherosclerotic lesions. Arterioscler Thromb Vasc Biol. 2000;20(5):1262– 1275.

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20. Patel NA, Stamper DL, Brezinski ME. Review of the ability of optical coherence tomography to characterize plaque, including a comparison with intravascular ultrasound. Cardiovasc Intervent Radiol. 2005;28(1):1–9. 21. Regar E, Schaar JA, Mont E, Virmani R, Serruys PW. Optical coherence tomography. Cardiovasc Radiat Med. 2003;4(4):198–204. 22. van der Meer FJ, Faber DJ, Baraznji Sassoon DM, Aalders MC, Pasterkamp G, van Leeuwen TG. Localized measurement of optical attenuation coefficients of atherosclerotic plaque constituents by quantitative optical coherence tomography. IEEE Trans Med Imaging. 2005;24(10):1369–1376. 23. Tearney GJ, Jang IK, Bouma BE. Optical coherence tomography for imaging the vulnerable plaque. J Biomed Opt. 2006;11(2):021002. http://dx.doi. org/10.1117/1.2192697. 24. Yabushita H, Bouma BE, Houser SL, et al. Characterization of human atherosclerosis by optical coherence tomography. Circulation. 2002;106(13): 1640–1645. 25. Barlis P, Schmitt JM. Current and future developments in intracoronary optical coherence tomography imaging. EuroIntervention. 2009;4(4):529–533. 26. Bezerra HG, Costa MA, Guagliumi G, Rollins AM, Simon DI. Intracoronary optical coherence tomography: a comprehensive review clinical and research applications. JACC Cardiovasc Interv. 2009;2(11):1035–1046. 27. Kubo T, Akasaka T. Recent advances in intracoronary imaging techniques: focus on optical coherence tomography. Expert Rev Med Devices. 2008;5(6): 691–697. 28. Okamura T, Onuma Y, Garcia-Garcia HM, et al. First-in-man evaluation of intravascular optical frequency domain imaging (OFDI) of Terumo: a comparison with intravascular ultrasound and quantitative coronary angiography. EuroIntervention. 2011;6(9):1037–1045. 29. Tanaka A, Tearney GJ, Bouma BE. Challenges on the frontier of intracoronary imaging: atherosclerotic plaque macrophage measurement by optical coherence tomography. J Biomed Opt. 2010;15(1):011104. http://dx.doi. org/10.1117/1.3290810. 30. Tearney GJ, Waxman S, Shishkov M, et al. Three-dimensional coronary artery microscopy by intracoronary optical frequency domain imaging. JACC Cardiovasc Imaging. 2008;1(6):752–761. 31. MacNeill BD, Jang IK, Bouma BE, et al. Focal and multi-focal plaque macrophage distributions in patients with acute and stable presentations of coronary artery disease. J Am Coll Cardiol. 2004;44(5):972–979. 32. Tearney GJ, Yabushita H, Houser SL, et al. Quantification of macrophage content in atherosclerotic plaques by optical coherence tomography. Circulation. 2003;107(1):113–119. 33. Tearney GJ, Jang IK, Bouma BE. Evidence of cholesterol crystals in atherosclerotic plaque by optical coherence tomographic (OCT) imaging. Eur Heart J. 2003;24(15): Cover. 34. Jang IK, Bouma BE, Kang DH, et al. Visualization of coronary atherosclerotic plaques in patients using optical coherence tomography: comparison with intravascular ultrasound. J Am Coll Cardiol. 2002;39(4):604– 609. 35. Kume T, Akasaka T, Kawamoto T, et al. Assessment of coronary arterial thrombus by optical coherence tomography. Am J Cardiol. 2006;97(12):1713– 1717. 36. Rieber J, Meissner O, Babaryka G, et al. Diagnostic accuracy of optical coherence tomography and intravascular ultrasound for the detection and characterization of atherosclerotic plaque composition in ex-vivo coronary specimens: a comparison with histology. Coron Artery Dis. 2006;17(5):425–430. 37. Suter MJ, Tearney GJ, Oh WY, Bouma BE. Progress in intracoronary optical coherence tomography. IEEE J Sel Topics Quantum Electronics. 2010;16(4):706– 714. 38. Kume T, Okura H, Kawamoto T, et al. Relationship between coronary remodeling and plaque characterization in patients without clinical evidence of coronary artery disease. Atherosclerosis. 2008;197(2):799–805. 39. Lagergren J, Bergstrom R, Lindgren A, Nyren O. Symptomatic gastroesophageal reflux as a risk factor for esophageal adenocarcinoma. N Engl J Med. 1999;340(11):825–831. 40. Sharma P, McQuaid K, Dent J, et al. A critical review of the diagnosis and management of Barrett’s esophagus: the AGA Chicago Workshop. Gastroenterology. 2004;127(1):310–330. 41. Dulai GS. Surveying the case for surveillance. Gastroenterology. 2002; 122(3):820–823. 42. Levine DS, Haggitt RC, Blount PL, Rabinovitch PS, Rusch VW, Reid BJ. An endoscopic biopsy protocol can differentiate high-grade dysplasia from early adenocarcinoma in Barrett’s esophagus. Gastroenterology. 1993;105(1):40–50. 43. Streitz JM Jr, Andrews CW Jr, Ellis FH Jr. Endoscopic surveillance of Barrett’s esophagus: does it help? J Thorac Cardiovasc Surg. 1993;105(3):383– 387; discussion 387–388. 44. van Sandick JW, van Lanschot JJ, Kuiken BW, Tytgat GN, Offerhaus GJ, Obertop H. Impact of endoscopic biopsy surveillance of Barrett’s oesophagus on pathological stage and clinical outcome of Barrett’s carcinoma. Gut. 1998;43(2): 216–222. 45. Chen Y, Aguirre AD, Hsiung PL, et al. Ultrahigh resolution optical coherence tomography of Barrett’s esophagus: preliminary descriptive clinical study correlating images with histology. Endoscopy. 2007;39(7):599–605. 46. Evans JA, Bouma BE, Bressner J, et al. Identifying intestinal metaplasia at the squamocolumnar junction by using optical coherence tomography. Gastrointest Endosc. 2007;65(1):50–56.

In Vivo OCT: The Role of the Pathologist—Hariri et al

47. Evans JA, Poneros JM, Bouma BE, et al. Optical coherence tomography to identify intramucosal carcinoma and high-grade dysplasia in Barrett’s esophagus. Clin Gastroenterol Hepatol. 2006;4(1):38–43. 48. Poneros JM, Brand S, Bouma BE, Tearney GJ, Compton CC, Nishioka NS. Diagnosis of specialized intestinal metaplasia by optical coherence tomography. Gastroenterology. 2001;120(1):7–12. 49. Qi X, Pan Y, Sivak MV, Willis JE, Isenberg G, Rollins AM. Image analysis for classification of dysplasia in Barrett’s esophagus using endoscopic optical coherence tomography. Biomed Opt Express. 2010;1(3):825–847. 50. Testoni PA, Mangiavillano B. Optical coherence tomography in detection of dysplasia and cancer of the gastrointestinal tract and bilio-pancreatic ductal system. World J Gastroenterol. 2008;14(42):6444–6452. 51. Suter MJ, Jillella PA, Vakoc BJ, et al. Image-guided biopsy in the esophagus through comprehensive optical frequency domain imaging and laser marking: a study in living swine. Gastrointest Endosc. 2010;71(2):346–353. 52. Vakoc BJ, Shishko M, Yun SH, et al. Comprehensive esophageal microscopy by using optical frequency-domain imaging (with video). Gastrointest Endosc. 2007;65(6):898–905. 53. Suter MJ, Vakoc BJ, Yachimski PS, et al. Comprehensive microscopy of the esophagus in human patients with optical frequency domain imaging. Gastrointest Endosc. 2008;68(4):745–753. 54. Suter MJ, Jillella PA, Vakoc BJ, et al. Image-guided biopsy in the esophagus through comprehensive optical frequency domain imaging and laser marking: a study in living swine. Gastrointest Endosc. 2010;71(2):346–353. 55. Suter MJ, Yoo H, Gallagher KA, et al. An interactive volumetric microscopy and guided biopsy platform for the management of Barrett’s patients. Paper presented at: the SPIE Photonics West; 22 January 2011; San Francisco, CA. Abstract 7889-24. 56. Yang Y, Whiteman S, Gey van Pittius D, He Y, Wang RK, Spiteri MA. Use of optical coherence tomography in delineating airways microstructure: comparison of OCT images to histopathological sections. Phys Med Biol. 2004;49(7):1247– 1255. 57. Hariri LP, Applegate MB, Mino-Kenudson M, et al. Volumetric optical frequency domain imaging of pulmonary pathology with precise correlation to histopathology [published online ahead of print March 29, 2012]. Chest. doi:10. 1378/chest.11–2797. 58. Xie T, Liu G, Kreuter K, et al. In vivo three-dimensional imaging of normal tissue and tumors in the rabbit pleural cavity using endoscopic swept source optical coherence tomography with thoracoscopic guidance. J Biomed Opt. 2009;14(6):064045. http://dx.doi.org/10.1117/1.3275478. 59. Quirk BC, McLaughlin RA, Curatolo A, Kirk RW, Noble PB, Sampson DD. In situ imaging of lung alveoli with an optical coherence tomography needle probe. J Biomed Opt. 2011;16(3):036009. http://dx.doi.org/10.1117/1.3556719. 60. Chee AC, Hariri LP, Applegate MB, et al. Optical detection and diagnosis of peripheral pulmonary lesions. Paper presented at the Optical Techniques in Pulmonary Medicine a: the SPIE Photonics West; 22 January 2011; San Francisco, CA. Abstract 8207D-64. 61. Hanna N, Saltzman D, Mukai D, et al. Two-dimensional and 3dimensional optical coherence tomographic imaging of the airway, lung, and pleura. J Thorac Cardiovasc Surg. 2005;129(3):615–622. 62. Coxson HO, Lam S. Quantitative assessment of the airway wall using computed tomography and optical coherence tomography. Proc Am Thorac Soc. 2009;6(5):439–443. 63. Coxson HO, Quiney B, Sin DD, et al. Airway wall thickness assessed using computed tomography and optical coherence tomography. Am J Respir Crit Care Med. 2008;177(11):1201–1206. 64. Michel RG, Kinasewitz GT, Fung KM, Keddissi JI. Optical coherence tomography as an adjunct to flexible bronchoscopy in the diagnosis of lung cancer: a pilot study. Chest. 2010;138(4):984–988.

Arch Pathol Lab Med—Vol 136, December 2012

65. Su J, Zhang J, Yu L, Colt HG, Brenner M, Chen Z. Real-time swept source optical coherence tomography imaging of the human airway using a microelectromechanical system endoscope and digital signal processor. J Biomed Opt. 2008;13(3):030506. http://dx.doi.org/10.1117/1.2938700. 66. Suter MJ, Riker DR, Gallagher KA, et al. Real-time comprehensive microscopy of the pulmonary airways: a pilot clinical study. Am J Respir Crit Care Med. 2010;181(1)(suppl meeting abstracts):A5159. 67. Tsuboi M, Hayashi A, Ikeda N, et al. Optical coherence tomography in the diagnosis of bronchial lesions. Lung Cancer. 2005;49(3):387–394. 68. Lam S, Standish B, Baldwin C, et al. In vivo optical coherence tomography imaging of preinvasive bronchial lesions. Clin Cancer Res. 2008;14(7):2006– 2011. 69. Gould MK, Fletcher J, Iannettoni MD, et al. Evaluation of patients with pulmonary nodules: when is it lung cancer?: ACCP evidence-based clinical practice guidelines (2nd edition). Chest. 2007;132(3)(suppl):108S–130S. 70. Baaklini WA, Reinoso MA, Gorin AB, Sharafkaneh A, Manian P. Diagnostic yield of fiberoptic bronchoscopy in evaluating solitary pulmonary nodules. Chest. 2000;117(4):1049–1054. 71. Rivera MP, Mehta AC. Initial diagnosis of lung cancer: ACCP evidencebased clinical practice guidelines (2nd edition). Chest. 2007;132(3)(suppl):131S– 148S. 72. Dooms C, Seijo L, Gasparini S, Trisolini R, Ninane V, Tournoy KG. Diagnostic bronchoscopy: state of the art. Eur Respir Rev. 2010;19(117):229–236. 73. Mazzone P, Jain P, Arroliga AC, Matthay RA. Bronchoscopy and needle biopsy techniques for diagnosis and staging of lung cancer. Clin Chest Med. 2002;23(1):137–158. ix. 74. Shure D, Fedullo PF. Transbronchial needle aspiration of peripheral masses. Am Rev Respir Dis. 1983;128(6):1090–1092. 75. Cooper WA, O’Toole S, Boyer M, Horvath L, Mahar A. What’s new in nonsmall cell lung cancer for pathologists: the importance of accurate subtyping, EGFR mutations and ALK rearrangements. Pathology. 2011;43(2):103–115. 76. Loo PS, Thomas SC, Nicolson MC, Fyfe MN, Kerr KM. Subtyping of undifferentiated non-small cell carcinomas in bronchial biopsy specimens. J Thorac Oncol. 2010;5(4):442–447. 77. Mukhopadhyay S, Katzenstein AL. Subclassification of non-small cell lung carcinomas lacking morphologic differentiation on biopsy specimens: utility of an immunohistochemical panel containing TTF-1, napsin A, p63, and CK5/6. Am J Surg Pathol. 2011;35(1):15–25. 78. Nicholson AG, Gonzalez D, Shah P, et al. Refining the diagnosis and EGFR status of non-small cell lung carcinoma in biopsy and cytologic material, using a panel of mucin staining, TTF-1, cytokeratin 5/6, and P63, and EGFR mutation analysis. J Thorac Oncol. 2010;5(4):436–441. 79. Pelosi G, Rossi G, Bianchi F, et al. Immunohistochemistry by means of widely agreed-upon markers (cytokeratins 5/6 and 7, p63, thyroid transcription factor-1, and vimentin) on small biopsies of non-small cell lung cancer effectively parallels the corresponding profiling and eventual diagnoses on surgical specimens. J Thorac Oncol. 2011;6(6):1039–1049. 80. Rekhtman N, Ang DC, Sima CS, Travis WD, Moreira AL. Immunohistochemical algorithm for differentiation of lung adenocarcinoma and squamous cell carcinoma based on large series of whole-tissue sections with validation in small specimens. Mod Pathol. 2011;24(10):1348–59. 81. Righi L, Graziano P, Fornari A, et al. Immunohistochemical subtyping of nonsmall cell lung cancer not otherwise specified in fine-needle aspiration cytology: a retrospective study of 103 cases with surgical correlation. Cancer. 2011;117(15):3416–3423. 82. Kume T, Okura H, Kawamoto T, et al. Relationship between coronary remodeling and plaque characterization in patients without clinical evidence of coronary artery disease. Atherosclerosis. 2008;197(2):799–805.

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