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Review

Application of OCT in the Gastrointestinal Tract

by
Nicholas S. Samel
1 and
Hiroshi Mashimo
2,*
1
Dartmouth College, Hanover, NH 02090, USA
2
VA Boston Healthcare System, Harvard Medical School, West Roxbury, MA 02132, USA
*
Author to whom correspondence should be addressed.
Appl. Sci. 2019, 9(15), 2991; https://doi.org/10.3390/app9152991
Submission received: 12 July 2019 / Revised: 21 July 2019 / Accepted: 22 July 2019 / Published: 25 July 2019
(This article belongs to the Special Issue Optical Coherence Tomography and Its Applications II)
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Abstract

:
Optical coherence tomography (OCT) is uniquely poised for advanced imaging in the gastrointestinal (GI) tract as it allows real-time, subsurface and wide-field evaluation at near-microscopic resolution, which may improve the current limitations or even obviate the need of superficial random biopsies in the surveillance of early neoplasias in the near future. OCT’s greatest impact so far in the GI tract has been in the study of the tubular esophagus owing to its accessibility, less bends and folds and allowance of balloon employment with optimal contact to aid circumferential imaging. Moreover, given the alarming rise in the incidence of Barrett’s esophagus and its progression to adenocarcinoma in the U.S., OCT has helped identify pathological features that may guide future therapy and follow-up strategy. This review will explore the current uses of OCT in the gastrointestinal tract and future directions, particularly with non-endoscopic office-based capsule OCT and the use of artificial intelligence to aid in diagnoses.

1. Introduction

Diagnostic imaging of the gastrointestinal (GI) tract has long relied on white-light endoscopy (WLE) for the detection of mucosal abnormalities such as neoplasias, vascular deformities, and inflammatory conditions. While WLE is a clinical standard for GI imaging and cancer detection, it remains far from ideal. A standard colonoscopy can miss up to 40% of adenomas [1,2] and despite improvements to increase mucosal visualization [3], miss rates are still concerning, especially for flat lesions such as sessile serrated adenomas [4]. While part of the suboptimal detection can be attributed to patients’ inadequate preparatory colonic lavage, WLE’s limited field of view (FOV) and time-consuming mucosal inspection during endoscope withdrawal are additional limiting factors [3]. Since the survival rate from GI cancers can be improved by 5 to 10-fold if diagnosed at an early stage [5], there is an obvious need to improve detection of early GI neoplasias.
Advanced imaging in the GI tract can be broadly divided into surface and subsurface modalities. Surface imaging includes chromoendoscopy [6], virtual chromoendoscopy [7], magnification endoscopy and endocytoscopy [8], and autofluorescence imaging [9]. There have been tremendous improvements in the resolution, field of view (FOV), and methods of surface imaging, such as improving contrast in magnification endoscopy and using selected wavelengths (Narrow Band Imaging, NBI) or digital enhancements such as flexible spectral imaging color enhancement (FICE; Fujinon Inc, Saitama, Japan). However, these modalities are limited to superficial lesions and improved magnification generally comes at the cost of restricted FOV, which makes screening and surveillance for multi-focal lesions more difficult.
On the other hand, subsurface imaging, which includes endoscopic ultrasonography [10], confocal endomicroscopy [11], and OCT, allows for visualization of structures not feasible with most endoscopes. Of these technologies, OCT is a uniquely poised imaging modality, combining nearly microscopic resolution with volumetric and subsurface real-time imaging capabilities [12]. These characteristics position OCT to solve many of the weaknesses of the other GI tract imaging techniques. This review will explore some of the recent advances of OCT in GI applications and describe the future potential for OCT to incorporate purpose-build probe designs and computer-aided diagnosis techniques [12].

2. Evolving OCT Technology

Briefly, the working principle of OCT is analogous to that of an ultrasound, with analysis of reflected light rather than sound waves. An optical ranging technique called low coherence interferometry [13,14] uses a Michelson interferometer to measure the time delay and subsequent signal intensity of light reflected from a tissue sample. Since its first publication in the early 1990s [15], endoscopic OCT techniques [16] and applications have become major areas of research [17,18,19,20].
OCT can be broadly divided into two types: time-domain OCT (TD-OCT) and Fourier-domain OCT (FD-OCT). They differ in that TD-OCT considers each scan individually with a moving mirror (Figure 1a) [21,22,23], while FD-OCT applies a Fourier transform on the detected spectrum (Figure 1b) [24,25,26]. FD-OCT’s introduction in the early 2000s generated a great increase in imaging speed and sensitivity of OCT [23,24,25,26]. FD-OCT can be further divided into subcategories, spectral-domain OCT (SD-OCT) and swept-source OCT (SS-OCT) [21]. SD-OCT uses a spectrometer with a broadband light source and typically operates at shorter wavelengths [27,28]. SS-OCT measures interference spectra using a wavelength-swept light source and a photodetector, operating at longer wavelengths and with a high imaging frequency, sometimes reaching the MHz region [29,30,31]. Due to its improved tissue depth penetration at longer wavelengths, SS-OCT is the technology of choice for endoscopic applications [32,33].
Different imaging probe designs allow different perspectives for acquisition of OCT images. Side-viewing probes are the most common in endoscopic OCT applications due to their large luminal surface area coverage [12]. Different forms of side-viewing probe delivery include the small diameter flexible sheath [16], large diameter inflatable balloon [34] and rigid housing [35]. An introductory video demonstrating imaging in the gastrointestinal tract using a probe-based OCT is available [36]. Small diameter flexible sheath, also called “optical biopsy,” is excellent for obtaining high-speed visualization, but is less resolved than forward viewing probes [16]. The balloon catheter is excellent for tubular structures such as the esophagus, but is not optimized for the bends and folds of the rest of the GI tract. Rigid housing, such as in a capsule, is advantageous for a number of reasons that will be discussed in a subsequent section.
Forward viewing (en face) probes have smaller FOVs but provide a more intuitive viewing scheme akin to magnified endoscopy and endomicroscopy, and are generally integrated with other modes of microscopy and applied to tasks requiring high magnification. Forward-imaging probe designs include microelectromechanical system (MEMS) scanners, piezoelectric transducer (PZT) actuators, and the paired-angle-rotation scanner (PARS) [37,38]. While MEMS scanners have been shown to combat distortion, they often use a nonlinear scan pattern which necessitates oversampling; however, a promising study by Cogliati et al. reported the implementation of pre-shaped open-loop input signals with non-linear parts to achieve live, distortion-free imaging without post-processing with a Gabor-domain optical coherence microscope [39]. Additionally, a MEMS platform has been developed for circumferential scan by Mu et al. using an electrothermal chevron-beam actuator [40]. However, a challenge of MEMS-based scanning endoscopes has been the large probe diameter (4-5.8 mm) [38]. PZT actuators are desirable for their small size and compatibility with an endoscopic accessory channel; however, the length of the tubular PZT actuator is quite long (around 3.5 cm) [37]. Notably, Zhang et al. proposed a reverse-mount PZT design with a shorter rigid length that had comparable performance to forward-mount probes, although performed on colonic samples ex vivo [37]. PARS, which rotates a pair of angle-polished gradient index (GRIN) lenses, is advantageous for its miniaturization and variety of scan modes [41], but retaining concentricity and stable separation of the two GRIN lenses is challenging [38]. Most recently, micromotor catheters have been used to achieve high-speed, volumetric en face ultra-high resolution for the in vivo assessment of BE and dysplasia (Figure 2) [42].
The beam can also be scanned in different patterns such as raster [43], spiral [44] or Lissajou [45]. The use of these scanning patterns depends on the actuators used in the probe design [12].
OCT technology can also be combined with other imaging techniques to give it enhanced molecular sensitivity and imaging depth [38]. However, such endoscopic multi-modal imaging platforms are limited by the small size of the accessory channel of a conventional endoscope [38]. In one paper, such geometric challenges were overcome by putting the imaging and spectroscopy probes together in the same 2mm diameter silica tube [46]. Notwithstanding the challenges of miniaturizing the imaging catheters, OCT has been combined with a diffuse fluorescence spectroscopy probe to obtain simultaneous 1D laser-induced fluorescence (LIF) and 3D OCT spectra in mice. The LIF spectrum allows chemical specificity to the OCT platform [47]. However, multimodal OCT and fluorescence imaging in the GI tract is challenging, as it requires a high speed, high spatial resolution, uniform scanning system with an FDA approved contrast agent [48]. Nevertheless, one study found that layered architecture and microvasculature could be clearly identified using such a multimodal system in the rat rectum [48]. OCT can also be used simultaneously with ultrasound to result in a greater combined image depth [38]. A study in 2010 used a high-frequency ring transducer to focus the ultrasound (US) beam and OCT light beam toward a common imaging spot for simultaneously co-registered US and OCT images to access tissue beyond the traditional 1-2.5 mm OCT imaging depth [38,49]. Additionally, trimodal OCT, US and photoacoustic imaging (PAI) endoscopy have been shown to combine the high resolution subsurface imaging capabilities of OCT, deeper penetration by US and the increased optical absorption contrast of PAI for enhanced visualization of neoplasia [50]. Lastly, polarization sensitive (PS) OCT exploits the altered reflected polarization of light from different materials and tissues to quantitate and provide further contrast [51]. This can be used to detect tumors, such as in the colon, where precancerous lesions have been found to be less depolarizing than benign tissues [51,52]. OCT has been applied to both the upper and lower GI tract either through the accessory channel of an endoscope or independently. While OCT has great potential throughout the entire GI tract, its principal advancements so far have been made in the esophagus.

3. OCT Applications in the GI Tract

3.1. Esophagus

Barrett’s Esophagus (BE) is the main precursor to esophageal adenocarcinoma (EAC). EAC is the eighth most common cancer type in the world, and despite falling incidence rates of squamous cell carcinoma, the incidence of EAC continues to rise globally, especially in western countries (--including the United States) [53,54]. Alarmingly, its incidence increased 6.5-fold from 1975-2009 according to SEER data [55], making the incidence for EAC one of the fastest rising of all cancers in the US, particularly in the white male population [56]. EAC is thought to arise stepwise from specialized intestinal metaplasia (SIM) to low grade dysplasia (LGD), high grade dysplasia (HGD) and then intramucosal carcinoma (IMC) [57,58]. Guidance for surveillance of BE neoplastic progression has been provided by the Seattle Protocol, which advocates for targeted biopsies or resection of suspicious esophageal areas followed by random four-quadrant biopsies at set intervals [59]. This sampling limits itself to less than 5% of the esophageal surface area [12]. Pinch biopsies often do not acquire deeper structures and one study showed they miss the lamina propria more than 60% of the time [60,61], raising concerns regarding under-sampling for the often focal and small areas of dysplasia. Additionally, after ablation, residual BE tissues may become buried under the neosquamous epithelium as subsquamous intestinal metaplasia (SSIM) and elude detection [62].
Given these needs and the relative simplicity of a tubular structure for OCT imaging, OCT in the GI tract has been applied largely to the esophagus. OCT, with its volumetric, subsurface and near-microscopic imaging, is positioned to help the diagnostic yield of biopsies or even obviate biopsies if it can demonstrate sufficient sensitivity and specificity according the Preservation and Incorporation of Valuable Endoscopic Innovations (PIVI) standards from the American Society for Gastrointestinal Endoscopy. In order to eliminate random mucosal biopsies in BE patients, PIVI recommends that an imaging technology with targeted biopsies should have a per-patient sensitivity of at least 90% and a negative predictive value (NPV) of at least 98% for detecting high-grade dysplasia (HGD) or early esophageal adenocarcinoma (EAC) [12,63].
In the esophagus, Evans et al. showed that OCT could differentiate IMC and HGD from LGD, intermediate-grade dysplasia (IGD) and SIM without dysplasia at the squamocolumnar junction (SCJ) (Evans 2006) [64]. The endoscopic balloon-centering catheter [34] laid the foundation for the commercialization of a GI-focused OCT system (called volumetric laser endomicroscopy, or VLE; NvisionVLE® Imaging System, Ninepoint Medical) [65]. VLE provides real-time volumetric scans with ~3 mm imaging depth and 7 μum axial resolution over a 6 cm stretch of the esophageal inner wall (Figure 3). As will be discussed below, VLE can be used with diagnostic algorithms to detect dysplasia [66] and laser-marking for more precise targeting and co-registry of images with biopsies and better delineation of areas for ablation [67,68]. Similar promising OCT imaging systems are emerging for GI applications including LuminScan ™ (Micro-Tech, Nanjing, CN). On the other hand, imaging probes introduced without balloons may be helpful in real-time imaging during biopsies and may help delineate lateral margins during endoscopic resections [69].
Given the relevance of buried glands and SIM in BE recurrence and WLE’s inability to survey beneath the mucosal surface, OCT can be used as a uniquely-suited tool after radiofrequency ablation (RFA) to evaluate tissue recovery and detect buried or residual glands [12,60,70]. Recently, Tsai et al. demonstrated 3D-OCT’s ability to detect SSIM in BE patients undergoing RFA as a potential predictor for the number of RFA sessions needed for complete eradication of intestinal metaplasia [60,70,71]. They found that 3D-OCT not only provided 80×−100× larger FOV than biopsy, but that its subsurface imaging capabilities revealed that the length of SSIM had a strong correlation with the number of RFA treatments required to achieve complete eradication of intestinal metaplasia [60,71]. VLE has also been shown to differentiate between esophageal squamous cell carcinoma (ESCC) and its precursor, squamous intraepithelial neoplasia (SIN), which are highly prevalent in the non-western world [60,70,71,72]. It was also able to distinguish ESCC limited to the lamina propria and ESCC invading beyond the lamina propria, suggesting that VLE may be able to determine which patients should undergo endoscopic therapy [70].

3.2. Colon

Colorectal cancer (CRC) remains a major cause of death in the US and the second leading cause of cancer death with an estimated 145,600 new cases and an estimated 51,020 deaths for 2019 [71]. The survival rate from GI cancers can be improved by 5- to 10-fold if diagnosed at an early stage [5]. The current recommendation in the US is to screen all individuals at age 45 or earlier if deemed at higher risk for CRC based on certain conditions or family history using specific stool tests, radiological exams or direct visualization by colonoscopy [72]. Colonoscopy allows for the removal of suspect adenomatous lesions but can be time-consuming and has miss rates in the range of 17 to 28% [73]. Thus, advanced imaging modalities could help improve detection. OCT has been demonstrated to differentiate colorectal cancer from adenomatous polyps [74,75], and its ability to reveal the submucosa may allow more nuanced polyp treatments. For example, OCT showed normal submucosa underneath a rectal polyp near the dentate line and altered its management from a full thickness resection to a less invasive endoscopic mucosal resection (EMR) [76]. High-resolution en face colon images from OCT are analogous to the traditional magnified endoscopic view, but do not require contrast agents; they also yield clinically powerful multi-depth visibility [77]. Thus, OCT has the potential to improve polyp detection and management.
Besides neoplastic lesions, 3D-OCT was also able to detect changes in inflammatory conditions of the colon. For example, Crohn’s disease could be distinguished from ulcerative colitis by demonstration of changes in deeper structures not confined to the mucosa, which are hallmarks of Crohn’s Disease [78]. Moreover, OCT was able to demonstrate submucosal fibrosis, with loss of layering, loss of columnar architecture, and superficial edema, which is associated with more severe ulcerative colitis [79].

3.3. Hepatobiliary

Hepatobiliary malignancies account for around 13% of global cancer mortalities and 3% of those in the US, with cholangiocarcinoma (CCA) accounting for 15-20% of hepatobiliary malignancies [80]. The assessment of strictures in the pancreatico-biliary tract can be challenging since they can be benign or cancerous. The current protocol is an endoscopic retrograde cholangiopancreatography (ERCP) and random biopsies or brush cytology [81,82], but the practice often leads to a low diagnostic yield because of the small amount of available tissue and the tortuous anatomy of the bile duct [83,84]. Thus, a low-profile OCT probe was designed to enable passage through the pancreatic duct and demonstrated the ability to differentiate malignant from benign strictures [85,86,87]. Tyberg et al. described that strictures with cholangiocarcinoma showed a hyperreflective surface with loss of inner wall layering, while benign areas had clear delineated ductal wall layering [88]. Joshi, in a 22-patient study, found similar results and was able to quantify the thickness of each duct layer to differentiate benign, inflammatory and malignant tissue types [89]. This ability of OCT to potentially differentiate benign from cancerous lesions may obviate the need to remove tissue in the future.

3.4. Imaging of Microvasculature

In 2014, Tsai et al. demonstrated a 3D OCT angiography (OCT-A) using the biospeckle effect to reveal the subsurface vasculature of BE without exogenous contrast agents [90]. A video introduction of this promising technology in the gastrointestinal tract is available [36]. Revelation of subsurface vasculature could be clinically useful in order to highlight areas to minimize bleeding during an APC hybrid lift ablation (Erbe Elektromedizin, Tübingen, Germany) or peroral endoscopic myotomy, for example. Microvasculature irregularities also appear to be correlated with dysplasia in BE [91,92].
Additionally, OCT-A may help identify specific areas to treat in the rectal wall of chronic radiation proctopathy (CRP) which may develop consequent to pelvic irradiation for various malignancies [93,94]. OCT also may help identify other vascular abnormalities such as Dieulafoy’s lesions, often buried deeply in the submucosal architecture and a source for intermittent but brisk blood loss [95]. Additionally, en face OCT findings have been studied in patients with gastric antral vascular ectasia (GAVE), also a cause of upper GI bleeding, before and after RFA treatment. Lee et al. demonstrated OCT/OCT angiography’s (OCTA’s) ability to differentiate GAVE-associated tissue architecture and microvasculature before and after RFA, namely identifying regions of incomplete ablation hidden under coagulum [96]. Lastly, instantaneous real-time imaging may be used in the future to assess vascular changes associated with food allergies in the gut that are increasingly appreciated as potential causes of diarrhea or irritable bowel syndrome (IBS).

3.5. Small Intestine

The length, tortuous anatomy and folds in the small intestine pose particularly difficult challenges for OCT imaging in the GI tract. Nonetheless, several papers show successful utility of OCT. Masci et al. demonstrated OCT’s ability to differentiate celiac disease based on villous atrophy [97,98], while Kamboj et al. used OCT to reveal the submucosal mass of a duodenal neuroendocrine tumor (NET) [99]. Additionally, Lee et al. used ultrahigh-speed endoscopic OCT to study the structural differences of Crohn’s disease in the terminal ileum (TI), showing that TI with Crohn’s ileitis exhibited irregular mucosal patterns and enlarged villous internal structures [100].

4. New Technologies and Future Applications

4.1. Artificial Intelligence (AI)

From music suggestion algorithms to air traffic management, artificial intelligence (AI) is omnipresent in today’s cutting edge technology. However, unlike programs for checkers and chess, there may be too many predictive parameters for the detection of GI tract neoplasias for a knowledge base to be realistically programmed. Thus, machines must be able to learn. In machine learning, computational methods use experience (i.e. training) to make predictions and improve performance [101]. Deep learning addresses the major pitfall of machine learning, i.e., failure to recognize factors of variance in representation learning, by introducing and solving in terms of other simpler representations [102]. While deep learning can be viewed from a neurally-inspired perspective (often called a “neural network”), having multiple levels of composition need not be neurally inspired [102]. AI has been applied to endoscopic images to help highlight or identify areas of GI cancers [103]. The miss rates for early neoplastic lesions in the GI tract are significant; one retrospective study found a miss rate of 75.2% for gastric superficial neoplasia (GSNs) [104]. Wu et al. demonstrated the feasibility of deep learning in order to detect early cancers and even map the stomach to address the blind spots responsible for many of these misses during gastroscopies [105].
In the colon, AI may be applied to both cancerous and non-cancerous conditions. In ulcerative colitis (UC), a computer-aided diagnosis (CAD) system was able to identify histologic inflammation associated with UC with 74% sensitivity, 97% specificity and 91% accuracy; this is useful, as WLE struggles to differentiate between healing and inflammation (active disease) [106]. For detection of pre-cancerous lesions, polyps may be missed under WLE at a rate of up to 22% [107]. Thus, research has been aimed at training computers to recognize polyp shape [108], texture, and color [109]. The recently described Window Median Depth of valleys Accumulation (WM-DOVA) energy maps system defines polyps as mucosal protrusions and their boundaries in terms of intensity valleys [110,111]. On the basis of this model, which fits better for zenithal views of the polyp, a pixel inside a polyp would be surrounded by high-intensity valleys in the majority of directions, with brighter regions corresponding to pixels with a higher likelihood of a polyp being present [110]. This algorithm worked better for smaller polyps of type 0-II, and the main causes of failure were deviation from the polyp appearance model, low image quality and poor prep [110].
In the esophagus, combining OCT and AI has been aimed to improve detection of neoplasias beyond the present sensitivity of random biopsies per the Seattle Protocol [112]. OCT address this problem with its volumetric rapid imaging, but its interpretation may be time/labor intensive due to the volume of images [113] and may be highly reader-dependent. However, the voluminous library of OCT images could be used for AI training. In BE, the parameters of atypical gland counts, lack of mucosal layering, and surface-to-surface intensity can be used as metrics [66]. Although performed ex-vivo, a study by Leggett et al. used a novel VLE diagnostic algorithm (VLE-DA) for dysplastic detection, producing a sensitivity of 86%, a specificity of 88%, and a diagnostic accuracy of 87% [66], which approaches the PIVI standards. Although the authors used an earlier form of OCT technology’s diagnostic scoring index, they see an in vivo possibility for using an image viewer region of interest (ROI) over a 1 cm longitudinal distance of BE mucosa [66]. Given the importance of subsurface gland-like structures in the esophagus [62], computer-aided detection was devised to highlight these structures to potentially guide biopsies or ablative treatment in the future [114]. Another BE AI paper compared human cross-sectional VLE diagnoses and computer generated en face VLE images and scored the computer’s consistency for layering (kappa=0.62), gland count (kappa=0.62) and subsurface intensity (kappa=0.49) [99].
Intelligent real-time image segmentation (IRIS) (Nine Point Medical, Bedford, MA) is an AI-based image processing software that highlights established VLE features (surface hyper-reflectivity, increased number of glands, and lack of layering) using a color-graded scale superimposed over cross-sectional and en face perspectives (Figure 3) [115].
When VLE-IRIS observed various BE tissues with correlated histology, it demonstrated an ability to recognize increased hyper-reflectivity, number of glands and lack of layering with increasing BE severity [115]; however, the authors note that gradient was not considered for IRIS features, and glands required manual interpretation. Nonetheless, due to VLE-IRIS’s ability to review large amounts of data, further study is required and merited. Beyond structural enhancements, deep learning has yet to be implemented with OCT images in the GI tract as it has, for example, in the eyes [116]. Deep learning has been employed with images in the colon using WLE [117,118] and in the esophagus using WLE with NBI for ESCC [119,120]. Given volumetric OCT advantages over surface imaging of WLE and NBI, deep learning on an OCT platform could be a promising clinical tool. AI has the potential to utilize machine learning to improve neoplastic recognition in the GI tract, where subtleties often lead to high miss rates. Until then, AI has been relegated to a second reader role [103].

4.2. Capsule

Endoscopy requires sedation and can be time and cost demanding. Thus, an office-based delivery system for OCT beyond that of the endoscope is desirable. Early versions of OCT used catheters such as the balloon catheter [32,34,121], but these proved difficult to navigate the flexures of the colon due to their limitation to tubular structures. MEMS scanners [122] and resonant fiber scanning [29,37,123] have also been used, but rotary scanners require proximal motorized pullback, the tethers for which are susceptible to mechanical deformation which degrades scan accuracy along the longitudinal axis [124]. Wireless capsule endoscopy has been used to image the entire GI tract [125], but is not controllable by the OCT operator. However, simply tying a string to the wireless capsule [126,127,128] demonstrated SS-OCT for 3-D circumferential imaging [35,124] tolerable by patients [128]. However, a capsule serving en face OCT would be more desirable, as many markers of disease in the esophagus (mucosal patterns, pit patterns) [129,130] are detectable by such an orientation. A capsule in 2015 was able to combine en face and circumferential luminal scanning to obtain large field coverage (30 cm2) and small field inspection (1 cm2), yielding both volumetric and en face imaging [124]. A more recent capsule paper [131] also incorporated laser marking into tethered capsule endomicroscopy (TCE). Laser marking is a way of co-localizing OCT images with histology [131](120), and the laser marks had a spatial accuracy of better than 0.5 mm. However, small diameter probes sacrifice FOV for transverse resolution, which is a potential drawback of en face capsule technology [124]. In 2017, a study involving Harvard Medical School and MIT demonstrated a cycloid scanner with a tethered capsule for ultrahigh speed side-viewing OCT in vivo and also produced volumetric images of vasculature [132].

5. Conclusion/Outlook for OCT

OCT is a rapid, volumetric, nearly microscopically resolved, subsurface endoscopic imaging modality that addresses many of the pitfalls associated with WLE and NBI. OCT has been rigorously studied in the esophagus due to its tubular anatomy and is starting to gain traction throughout the rest of the GI tract including the stomach, small intestine and colon. OCT is compatible with a fleet of accessories including laser markers, autofluorescence techniques and the traditional acoustic ultrasound. Additionally, OCT has the potential to be performed using an office-based capsule, negating the need for the burdens of sedation. Given the copious amounts of data produced by OCT, it is also a promising platform for the implementation of machine learning to achieve a level of autodetection akin to or even surpassing that of the skilled endoscopist. While machine learning in OCT still has a long way to go before it reaches such a skillful level, it can nonetheless play the role of second reader. The plethora of benefits from OCT, including accessorization, ease of delivery and machine learning, uniquely position this technology to address the disease burden of gastrointestinal maladies.

Conflicts of Interest

The authors declare no conflict of interest.

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Figure 1. (a) Time-domain optical coherence tomography (TD-OCT) uses low coherence interferometry. The light source is split and the backscattered light is captured by the detector. The depth information is provided by the scanned reference path. Adapted from Tsai et al. 2014. (b). Swept-source optical coherence tomography (SS-OCT) allows 10–200-fold faster imaging compared to TD-OCT. (A) Interferometer with swept laser source and beam splitter and path difference ΔL. (B) Time delay of light from sample (dotted) and reference light (dashed). (C) Interference signal proportional to delay. (D) Fourier transform of the interference signal measures ΔL. Figure and caption adapted from Tsai et al. 2014.
Figure 1. (a) Time-domain optical coherence tomography (TD-OCT) uses low coherence interferometry. The light source is split and the backscattered light is captured by the detector. The depth information is provided by the scanned reference path. Adapted from Tsai et al. 2014. (b). Swept-source optical coherence tomography (SS-OCT) allows 10–200-fold faster imaging compared to TD-OCT. (A) Interferometer with swept laser source and beam splitter and path difference ΔL. (B) Time delay of light from sample (dotted) and reference light (dashed). (C) Interference signal proportional to delay. (D) Fourier transform of the interference signal measures ΔL. Figure and caption adapted from Tsai et al. 2014.
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Figure 2. Combined en face and volumetric OCT dataset visualization. (a) Volumetric OCT dataset with cross-sections (blue), longitudinal (red) and en face (green) views. (b) Intrinsic co-registration leads to depth-resolved en face OCT images at various depths, revealing superficial mucosal architecture near the surface and mucosal patterns in greater detail and contrast, as well as microvasculature, in deeper images. Scale bars 1 mm. Figure and caption adapted from Ahsen et al. 2019.
Figure 2. Combined en face and volumetric OCT dataset visualization. (a) Volumetric OCT dataset with cross-sections (blue), longitudinal (red) and en face (green) views. (b) Intrinsic co-registration leads to depth-resolved en face OCT images at various depths, revealing superficial mucosal architecture near the surface and mucosal patterns in greater detail and contrast, as well as microvasculature, in deeper images. Scale bars 1 mm. Figure and caption adapted from Ahsen et al. 2019.
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Figure 3. Volumetric laser endomicroscopy (VLE) of the esophagus showing a luminal en face view of an area of overlap (yellow arrow) between the 3 features of dysplasia (orange is lack of layering, blue is glandular structures and pink is a hyper-reflective surface). (A) A view looking down from the proximal esophagus. (B) A view closer to the suspected area of dysplasia. The en face view is also shown (C). Figure and caption adapted from Trindade et al. 2019.
Figure 3. Volumetric laser endomicroscopy (VLE) of the esophagus showing a luminal en face view of an area of overlap (yellow arrow) between the 3 features of dysplasia (orange is lack of layering, blue is glandular structures and pink is a hyper-reflective surface). (A) A view looking down from the proximal esophagus. (B) A view closer to the suspected area of dysplasia. The en face view is also shown (C). Figure and caption adapted from Trindade et al. 2019.
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Samel, N.S.; Mashimo, H. Application of OCT in the Gastrointestinal Tract. Appl. Sci. 2019, 9, 2991. https://doi.org/10.3390/app9152991

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Samel NS, Mashimo H. Application of OCT in the Gastrointestinal Tract. Applied Sciences. 2019; 9(15):2991. https://doi.org/10.3390/app9152991

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Samel, Nicholas S., and Hiroshi Mashimo. 2019. "Application of OCT in the Gastrointestinal Tract" Applied Sciences 9, no. 15: 2991. https://doi.org/10.3390/app9152991

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