Hot Keywords
Non-small cell lung cancer Artificial intelligence Gastroesophageal reflux Esophagectomy Thoracic surgery Atherosclerosis Robotic surgery Gastric cancer Lung cancer Lobectomy Complications Quality of life Rectal cancer

Mini-invasive Surg 2022;6:55. 10.20517/2574-1225.2022.35 © The Author(s) 2022.
Open Access Review

Advanced mucosal imaging in colonoscopy: technical details and clinical applications

1Department of Gastroenterology, Lyell McEwin Hospital, Elizabeth Vale 5112, Australia.

2University of Adelaide, Faculty of Health and Medical Sciences, Adelaide 5005, Australia.

Correspondence to: Prof. Rajvinder Singh, Department of Gastroenterology, Lyell McEwin Hospital, Haydown Road, Elizabeth Vale 5112, Australia. E-mail: Rajvinder.Singh@sa.gov.au

    Views:785 | Downloads:130 | Cited:0 | Comments:0 | :30
    Academic Editor: Giulio Belli | Copy Editor: Jia-Xin Zhang | Production Editor: Jia-Xin Zhang

    © The Author(s) 2022. Open Access This article is licensed under a Creative Commons Attribution 4.0 International License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, sharing, adaptation, distribution and reproduction in any medium or format, for any purpose, even commercially, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.


    Over the past decades, the significant development in endoscopic imaging has revolutionized digestive endoscopy. Real-time optical diagnosis has become possible using different tools and techniques (dye-based and virtual chromoendoscopy) such as narrow band imaging, flexible spectral imaging color enhancement, i-Scan, blue-laser imaging and linked-color imaging. Polyp detection and characterization, and prediction of depth of invasion of colorectal cancers have improved remarkably. Confocal laser endomicroscopy and endocytoscopy have allowed the evaluation of lesions on a cellular level. Not far from the horizon are newer technological innovations such as artificial intelligence and texture and color enhancement imaging that are now being studied for their potential to further improve mucosal visualization, optical diagnosis and virtual histology. This review gives an overview of image-enhanced endoscopy (IEE) and discusses its clinical applications and future directions in the lower gastrointestinal (GI) tract.


    Image-enhanced endoscopy (IEE) continues to evolve and has assisted endoscopists in diagnosing gastrointestinal (GI) diseases. IEE has significantly helped improve the quality of screening colonoscopies, aiding in polyp detection and characterization and predicting the depth of invasion of colorectal cancers. Additionally, it has allowed endoscopists to provide real-time optical diagnosis. Consequently, IEE has reduced unnecessary resections of benign lesions and has played a significant role in deciding whether to perform an endoscopic or surgical resection for the malignant lesions. This review summarizes the different existing IEE techniques and discusses their clinical applications and future directions in the lower GI tract.


    IEE is an endoscopic imaging method used to improve the visualization of mucosal surface patterns and microvasculature features of GI lesions that are even in an early stage[1]. It provides high-contrast endoscopic images of lesions through different dyes and optical and electronic technologies[2]. It has assisted in the endoscopic assessment of neoplastic lesions with greater depth and has enabled subsequent therapeutic decisions to be made with greater precision[3].

    IEE can be classified into conventional dye-based chromoendoscopy (CE) and equipment-based methods or virtual CE [Table 1]. In dye-based CE, a dye such as indigo carmine, methylene blue, or crystal violet is applied onto the mucosa as the endoscope is slowly withdrawn while directed to suspicious lesions or the whole colon, such as in surveillance for patients with inflammatory bowel disease (IBD)[6]. The application of dye enhances features of mucosal surface architecture and aids in facilitating the resection of lesions or targeted biopsies of suspicious areas. However, a disadvantage of this technique is that it is often operator-dependent and requires technical expertise in the use of dyes and additional time[7].

    Table 1

    Overview of different IEE techniques and their clinical applicability[3-5]

    TechniqueMechanism of IEEClinical applications
    High-definition white light endoscopySignal images with high pixel density (up to millions), allowing visualization of a surface at a 30- to 35-fold magnificationDetection of colorectal neoplasm
    MagnifIcation endoscopy150-fold optical magnification while maintaining image display resolutionDetection or characterization of colorectal neoplasm
    Dye-based CE
    - Absorptive dye: crystal violet, methylene blueProvide sharp detail of cellular surface as the dye is absorbed by specific cellsCharacterization and diagnosis of suspicious cancerous lesions
    - Contrast dye: indigo carmineProvide overall detail of the mucosal surface topography when the dye seeps into the crevices and grooves between cells. They do not stain cellular surfaces.Detection and diagnosis of colorectal neoplasm
    Equipment-based CE
    Optical digital IEE
    - Narrow-band imaging (NBI)Use of two narrow-banded wavelengths of 415 nm (blue light) and 540 nm (green light), which are selectively absorbed by mucosal hemoglobin in the blood to enhance both surface and capillary patternsDetection, characterization, and diagnosis of colorectal neoplasm
    - Flexible spectral imaging color enhancement (FICE)Computed spectral estimation technology that reconstructs dedicated wavelengths resulting in enhanced visualization of mucosal structures and microvasculatureDetection, characterization, and diagnosis of colorectal neoplasm
    - Blue-laser imaging (BLI)Use of semiconductor laser beams to generate brighter images which enhances the visibility of the superficial mucosal and capillary patternsDetection, characterization, and diagnosis of colorectal neoplasm
    - Linked-color imaging (LCI)Addition of red-wavelength information in signal processing to produce brighter images comparable to white light imagingDetection, characterization, and diagnosis of colorectal neoplasm
    Equipment-based CE
    Digital IEE
    - I-ScanDigital post-processing filter technology, which generates high-definition images using three functions: contrast enhancement, surface enhancement, and tone enhancementDetection, characterization, and diagnosis of colorectal neoplasm
    Autofluorescence endoscopyHighlights endogenous fluorescence generated from tissue by excitation light (370-470 nm) and green light (540-560 nm) radiated sequentiallyDetection of colorectal neoplasm
    Confocal laser endomicroscopy (CLE)Image confined to reflected laser light that is refocused via a pinholeDetection of colorectal neoplasm in IBD
    EndocytoscopyUltra-high magnified white light images (520×) through a high-power fixed-focus objective lensDetection and characterization of colorectal neoplasm

    Equipment-based methods or virtual CE refers to advanced endoscopic imaging technologies that provide detailed contrast image enhancement of the mucosal epithelium and vasculature through optical filtering of white light or software-driven post-image processing[8]. Narrow Band Imaging (NBI) (Olympus Medical Systems Tokyo, Japan), flexible spectral imaging color enhancement (FICE) (Fujinon, Fujifilm Medical Co, Saitama, Japan), linked color imaging (LCI) (Fujinon, Fujifilm Medical Co, Saitama, Japan), blue light imaging (BLI) (Fujinon, Fujifilm Medical Co, Saitama, Japan), and i-Scan (Pentax Endoscopy, Tokyo, Japan) are examples of this technology. High-definition white light endoscopy (WLE) and magnification endoscopy (ME) also aid in providing high-resolution images and can be considered as part of virtual CE. Compared to using dyes, equipment-based methods have the advantage of ease of use, shorter procedure time, short learning curve, and no need for special assembly or dye[9].


    The use of IEE by endoscopists worldwide has rapidly grown, given its numerous advantages over conventional endoscopy. In fact, different societies and groups have advocated its use and its role in assessing GI lesions due to its ability to provide precise visual tissue characterization and accurate prediction of histology. To adapt IEE efficiently in practice, it is suggested that training is necessary to improve performance in the use of the advanced imaging technique[10].

    The European Society of Gastrointestinal Endoscopy (ESGE) suggests that advanced endoscopic imaging technologies be used as they can improve mucosal visualization and enhance fine structural and microvascular details[10]. The Asian Novel Bio-Imaging and Intervention Group (ANBI2G), an Asian professional group, also recommends using IEE to enhance the quality of endoscopic diagnosis and improve the detection of early-stage colorectal neoplasia and polyp detection in average-risk patients[1]. Additionally, validated classification systems should be utilized in the advanced endoscopic imaging and optical diagnosis of lesions in the lower GI tract[10].

    In patients with IBD, IEE is recommended as it improves the detection of dysplasia[1]. To characterize colorectal lesions in this subset of patients, ANBI2G recommends macroscopic classification using indigo carmine spray. The application of dye unmasks flat lesions and the borders and surface contours become better visible[11]. The ESGE and the British Society of Gastroenterology (BSG) recommend CE with targeted biopsies as the surveillance method in patients with IBD[12]. On the other hand, the American Gastroenterological Association (AGA) and the American Society for Gastrointestinal Endoscopy (ASGE) endorse the use of IEE with HD colonoscopy as surveillance for persons with long-term colonic IBD[13,14]. This was part of the SCENIC (Surveillance for Colorectal Endoscopic Neoplasia Detection and Management in Inflammatory Bowel Disease Patients: International Consensus Recommendations) international consensus statements published in 2015[15].


    Dye-based chromoendoscopy

    Dye-based CE aids the endoscopist in the detection and characterization of lesions in the GI tract with the application of dyes or stains. It can enhance lesion discrimination by highlighting the mucosal surface and light-absorptive patterns[16]. The topical staining agents used are considered generally safe except for those with known prior allergic reactions[17]. It is often applied with spraying catheters producing a fine mist onto the GI tract surface. While the endoscope is slowly withdrawn, dye is sprayed through the endoscope tip as the scope is directed onto the mucosa in a spiral motion[6]. As the effect of dye is only transient, short segments of approximately 20 cm should be stained each time, followed by a careful inspection. The staining solution can be applied through nontargeted pancolonic CE or targeted CE directed toward suspicious visible abnormalities[17]. It is important to note that good bowel preparation is critical when using dye-based CE in the lower GI tract. Anti-spasmodic agents can also be used to minimize bowel peristalsis that could lead to uneven dye distribution.

    Dyes used in the evaluation of colonic lesions can be classified into two major categories: absorptive dyes and contrast dyes. Absorptive dyes allow sharp detail of cellular surface as it is absorbed by specific cells[6]. An example is crystal violet which stains epithelial cells in the colonic mucosal glands, making the pit look white after dyeing. Staining usually takes 2 to 3 minutes after the dye is sprayed onto the colonic mucosa. Methylene blue is another example of an absorptive dye. It stains the epithelial cells of the small or large intestine blue, as opposed to dysplastic lesions, which remain unstained[17]. A more practical and less time-consuming approach has been studied using Methylene blue in tablet form. If given orally (MB-MMX 200 mg) with bowel preparation agents, it has shown the potential to increase the adenoma detection rate[18].

    Contrast or non-absorptive dyes provide detail of the mucosal surface contour when the dye seeps into the crevices and grooves between cells. Contrast dyes do not stain cellular surfaces. An example of this is indigo carmine, a dark blue stain, which can enhance the contrast of raised and deepened areas and highlight the topography of the mucosal surface, leading to improved detection of neoplastic lesions. It is useful to differentiate between benign and malignant lesions, delineate borders of early-stage neoplastic lesions, and estimate the depth of invasion of cancers[2]. It is generally used at a concentration of 0.1%-0.5%[5].

    When applying dyes, staining pit patterns can be categorized according to different classification systems, such as the Kudo pit pattern classification. Endoscopic polyp appearance can be characterized by the colonic mucosal pit pattern following the application of a dye[19]. Neoplastic tissue demonstrates irregular, tubular, or villous pits, whereas non-neoplastic tissue with rounded or stellar pits.

    Equipment-based chromoendoscopy

    High-definition white light endoscopy and magnification endoscopy

    High-definition white light endoscopy (HD WLE) and magnification endoscopy (ME) are categorized as IEE as they can produce high-resolution images that aid in the evaluation of the mucosal surfaces and subtle changes in lesions. In HD WLE, the endoscope produces signal images with higher pixel densities up to millions, allowing visualization of a surface at a 30- to 35-fold magnification[3]. It also has faster line scanning on the monitor, resulting in sharper images with fewer artifacts. In HD WLE, optical zooming can be done by positioning the optical lens at the tip of the endoscope very close to the mucosal surface to control focal distance. With a closer distance, subtle changes in lesions can be examined.

    In contrast to HD WLE, ME can examine changes in the mucosal microstructure and microvasculature by providing 150-fold magnification while maintaining image display resolution. As a result, more surface details, including pit patterns and vascular details, can be assessed. At times, ME also allows histological diagnosis of a lesion by endoscopic visualization. The use of a distal transparent cap attachment can facilitate magnification as it helps control and stabilize the short distance from the optical lens to the mucosa[20].

    Narrow band imaging

    Narrow band imaging (NBI) is an endoscopic optical image enhancement technology developed by Olympus Medical Systems, which works through optical filters and the principle of light penetration. With a special optical filter, it uses two narrow-banded wavelengths of 415 ± 15 nm (blue light) and 540 ± 15 nm (green light), which are selectively absorbed by mucosal hemoglobin in the blood[21]. This results in the marked enhancement of capillaries and micropatterns in the mucosal surface layer[22]. Capillaries in the superficial mucosa appear brown when highlighted by the 415 nm wavelength, while deeper veins appear blue-green (cyan) when the 540 nm wavelength penetrates. This contrasts with the nonvascular structures in the mucosa[10].

    NBI markedly improves the visualization of cancerous tissues characterized by abnormal surface and vascular patterns [Figure 1]. This is important in GI screening for early colorectal cancers[23]. If combined with ME, visualization of lesions is further improved, making the assessment of mucosal microstructure and microvasculature clearer and more accurate[2].

    Figure 1. White light, narrow band imaging, and magnification endoscopy of colorectal polyps. Hyperplastic polyp NICE 1, JNET Type 1, MS I on (A) WLE, (B) NBI, and (C) Magnification NBI. Adenomatous polyp NICE 2, JNET Type 2A, MS II on (D) WLE, (E) NBI, and (F) Magnification NBI. Malignant polyp (invasive adenocarcinoma) NICE 3, JNET Type 3, MS IIIb on (G) WLE, (H) NBI, and (I) Magnification NBI. NICE: Narrow-band imaging international colorectal endoscopic classification; JNET: Japan NBI expert team; MS: modified Sano; WLE: white light endoscopy; NBI: narrow-band imaging.

    Several magnifying NBI observation classification systems for colorectal tumors have been developed. These classification systems aid lesion characterization and therapeutic decision-making if endoscopic resection is possible. The most used ones are the NBI International Colorectal Endoscopic (NICE) classification proposed in 2009 [Table 2] and the Japan NBI Expert Team (JNET) classification developed in 2014 [Table 3]. The NICE classification is based on the visualized color, vessels, and surface pattern of the colorectal tumor. Given these characteristics, the lesion is classified into three types, which also predict the most likely histology of the lesion - hyperplastic, adenoma, or deep submucosal invasive cancer. Different international studies have validated its usefulness in diagnosing colorectal polyp histology and predicting the depth of carcinoma invasion[24-26].

    Table 2

    Narrow-band imaging international colorectal endoscopic classification (NICE)[24]

    CharacteristicNICE 1NICE 2NICE 3
    ColorSame or lighter than backgroundBrown relative to backgroundBrown to dark brown relative to background; occasional white patches
    VesselsNone or lacy vessels along surfaceThick brown vessels surrounding white structures or dotsAreas of markedly distorted vessels (varying thickness and irregular pattern) or absence of vessel pattern
    Surface patternDark spots surrounded by whiteOval, tubular, or branched white structures bordered by brown vesselsDistortion or absence of pattern
    Most likely pathologyHyperplastic or sessile serrated lesionAdenomaSubmucosal invasive cancer
    Table 3

    Japan NBI expert team (JNET) classification[25]

    Type 1Type 2AType 2BType 3
    Vessel patternInvisible*1Regular caliber
    Regular distribution (meshed/spiral pattern)*2
    Variable caliber
    Irregular distribution
    Loose vessel areas
    Interruption of thick vessels
    Surface patternRegular dark or white spots
    Similar to surrounding normal mucosa
    Regular (tubular/branched/papillary)Irregular or obscureAmorphous areas
    Most likely histologyHyperplastic polyp/Sessile serrated polypLow grade intramucosal neoplasiaHigh grade intramucosal neoplasia/Shallow submucosal invasive cancer*3Deep submucosal invasive cancer

    The JNET classification is based on the visualized vessel and surface pattern of colorectal lesions on NBI. It was proposed based on the consensus of selected NBI specialists, establishing a universal NBI magnifying endoscopic classification[25]. Like NICE, it is also predictive of the most likely histology of the lesion; however, it has further classified adenomatous lesions as possible low-grade intramucosal neoplasia (Type 2A) and lesions that may be of high grade or with shallow submucosal invasive cancer (Type 2B).

    Another NBI-based classification system is the modified Sano’s (MS) classification [Table 4], which defines colorectal tumors in accordance with the color, capillary network surrounding the pit pattern and surface pattern evaluated under magnification. In the MS classification, a separate sub-classification for sessile serrated adenoma/polyp (SSA/P) is included[27-29].

    Table 4

    Modified Sano’s classification[27]

    MS classificationPredicted histologyDescription
    Category IHyperplastic (HP)Pale color ± round pits with central brown star-like dots or bland appearance ± minute capillaries that may meander across polyp
    Category IIoSessile serrated adenoma/polyp (SSA/P)Pale or light dark color ± open pits ± 3 out of 5: cloud-like surface, inconspicuous margins, mucous cap, irregular shape and varicose microvascular vessels1
    Category IITubular adenoma with low-grade dysplasiaLight dark or dark color ± white linear or oval pits ± linear or oval regular capillary network surrounding pits
    Category IIIaHigh-grade dysplasia2/villous or tubulovillous adenoma/superficial cancerLight dark or dark color ± white villous/cerebriform pits ± tortuous/branched mildly regular capillary network surrounding pits3
    Category IIIbInvasive cancerDark surroundings with pale central area ± loss of pits and vascular pattern


    i-Scan is a software-based digital post-processing filter technology developed by Pentax Endoscopy (Tokyo, Japan). It produces high-definition images using image enhancement functions, namely contrast enhancement (C/E), surface enhancement (S/E), and tone enhancement (T/E)[30]. The C/E mode sharpens the views of surface vessels and increases the visibility of depressed lesions with the enhancement of blue light and suppression of the red and green light components. The S/E mode increases the light and dark color contrast, enhancing the visualization of mucosal surface texture and inspection of subtle mucosal changes. The T/E mode increases the contrast between the mucosa and blood vessels by dividing images obtained using normal white light into red, green and blue (RGB) components. This is then converted and resynthesized into a new image in which vascular patterns or subtle mucosal irregularities are highlighted, thereby improving visibility[2,30].

    Flexible spectral imaging color enhancement

    Flexible spectral imaging color enhancement (FICE), also known as Fujinon intelligent chromoendoscopy, is a computed spectral estimation technology developed by Fujifilm (Tokyo, Japan). It is a software-driven digital imaging post-processing system that reconstructs dedicated wavelengths resulting in enhanced visualization of mucosal structures and microvasculature[31]. Using an image processing algorithm, it can produce a composite computerized virtual chromoendoscopy enhanced color image using 60 types of spectral images between 400 and 695 nm wavelengths at 5 nm intervals[32].

    Blue laser/light imaging

    Blue laser imaging (BLI) system is an endoscopy system developed by Fujifilm (Kanagawa, Japan) to address FICE’s limitation in producing bright and high-contrast images[9]. BLI is made of the LASEREO endoscope system, which utilizes semiconductor laser beams (4-light-emitting diode multi-light system) as the light source compared to the conventional xenon light. This technology produces brighter images, improving the visibility of both the superficial mucosal and microvascular patterns. The 410 nm narrow-band laser light source (410 ± 10 nm) produces a narrow spectrum that enhances the microvasculature to visualize subtle changes in the mucosal surface, whereas the 450 nm laser light source provides white light illumination[2,8]. In 2016, Fujifilm released blue light imaging (also called BLI) to cater to some areas where LASER endoscopes have not been approved for use. This variation uses a four-light emitting diode (LED) as a light source instead of LASER[33].

    BLI provides high-contrast images using three modes: (I) BLI mode for detailed magnified observation; (II) BLI bright mode to visualize both surface and vascular patterns even from a distant view; and (III) white light mode which uses a 450-nm laser to better enhance the microvasculature[8]. The Hiroshima classification system to delineate lesions was developed using BLI [Table 5]. It characterizes colorectal polyps using both surface and vascular patterns. In this classification, type A describes non-adenomatous polyps, type B describes adenomatous polyps, type C1 describes intramucosal carcinoma, and type C3 describes deep submucosal invasion[8,25].

    Table 5

    Hiroshima classification of colorectal polyps[25]

    AMicrovessel intensity is vague or invisible
    None or isolated lacy vessels may be present coursing across the lesion. Brown or black dots, start or round shaped surrounded by white
    BRegular surface pattern is observed by the increased microvessel intensity around the pits and enhanced image.
    Or regular meshed microvessel network pattern is observed
    C1Irregular surface pattern is observed by the increased microvessel intensity around the pits and enhanced image.
    Thickness and distribution of vessels are homogeneous
    2A more irregular surface pattern is observed by the increased microvessel intensity around the pits and enhanced image
    Thickness and distribution of vessels are heterogeneous
    3Surface pattern is completely unclear
    Thickness and distribution of vessels are heterogeneous
    Avascular areas (AVA) and scattered microvascular fragments are observed

    Linked color imaging

    In 2014, Fujifilm developed linked color imaging (LCI) to further enhance the brightness and image contrast of the BLI system. In LCI, red-wavelength information was added to the green and blue wavelengths for signal processing to produce brighter images comparable to white light imaging[34]. In addition, LCI differentiates the red color spectrum by a unique image processing to produce increased color contrast making red regions more vivid[8]. This results in increased detection and accurate delineation of colorectal lesions.

    Autofluorescence imaging

    Autofluorescence imaging (AFI) is an endoscopic system developed by Olympus that highlights endogenous fluorescence generated from tissues by excitation light[35,36]. In AFI, excitation light (370-470 nm) and green light (540-560 nm) are radiated sequentially in autofluorescence mode[3]. This wide-field red-flag technology can potentially aid in the detection of dysplasia or early cancer displayed on the pseudo-color image as magenta. Nevertheless, due to inconsistent efficacy results in several studies, the overall benefit of AFI currently appears limited to the research setting[31].

    Confocal laser endomicroscopy and endocytoscopy

    Confocal laser endomicroscopy (CLE) and endocytoscopy are advanced endoscopic imaging technologies that provide higher-resolution, cellular-level views of gastrointestinal epithelia in real-time[3]. Using these technologies, the histological structure of the colonic epithelium can be recognized and evaluated.

    In CLE, an image resolution is markedly increased through the confinement of an image to reflected laser light that is refocused using a source pinhole[37]. To allow tissue excitation and further achieve a higher resolution, topical or intravenous fluorescence dyes can be used to enhance the cellular, subcellular and vessel architecture. There are two different CLE systems in clinical endoscopy, namely probe-based CLE (pCLE) and endoscope-based CLE (eCLE). In pCLE, a probe is delivered in vivo through the endoscope channel, whereas in eCLE, the probe is fitted at the distal end of a conventional endoscope. In the lower GI tract, CLE can assist in targeted optical biopsies[38]. Several studies have shown that it has moderate to high diagnostic accuracy in the evaluation of colonic polyps and the characterization of colorectal lesions in IBD[39,40].

    Endocytoscopy generates ultra-high magnified white light images (520x) through a high-power fixed-focus objective lens in real-time[41]. In this technique, cellular structures are visualized in vivo with the application of crystal violet and methylene blue, which stains the cell stroma and nucleus[42,43]. As endocytoscopy can provide real-time cellular imaging, its utility includes the characterization and depth assessment of dysplastic or early cancerous lesions of the GI tract and their histological differentiation.


    Adenoma detection rate and polyp detection

    High-definition imaging has resulted in an overall improvement in adenoma detection[16]. Studies have shown that newer IEE technology can potentially better enhance polyp detection by highlighting lesion characteristics. This is particularly significant as early detection can effectively avert colorectal cancer (CRC) and its related mortality. However, to date, different IEE techniques have heterogeneous evidence for adenoma detection.

    Since the development of the first-generation NBI in 2005, consistent results have shown that the overall adenoma detection rate (ADR) was just the same when comparing first-generation NBI and WLE[44,45]. However, with the second-generation NBI introduced in 2012, where brighter images can be achieved, its benefits for adenoma detection were noted to be more evident. A recent meta-analysis of 4,491 individual patients in 11 randomized controlled trials (RCT) showed that second-generation NBI has a better ADR than WLE (OR: 1.28; 95%CI: 1.05-1.56; P = 0.02)[46]. Overall, including the trials using the first-generation NBI, the ADR was 45.2% for NBI vs. 42.3% for HD-WLE (OR for adenoma detection of 1.14 NBI vs. HD-WLE; 95%CI: 1.01-1.29; P = 0.02).

    The utility of i-Scan in improving ADR had contradictory results. A meta-analysis of five RCTs showed no significant difference in the ADR of i-Scan T/E mode and WLE (RR: 1.09; 95%CI: 0.97-1.23)[47]. In contrast, an RCT comparing the ADR between HD i-Scan S/E mode and SD-WLE revealed that the use of i-Scan had a significantly higher ADR (38% vs. 13%; P < 0.0001)[48]. A more recent RCT by Kidambi et al. has also shown that i-Scan (S/E + C/E mode) has a higher ADR compared to HD-WLE (47.6% vs. 37.2%; P = 0.005)[49].

    Given its dark image, Fujifilm’s FICE has shown no benefit in the improvement of overall ADR[50,51]. However, with the development of the newer IEE mode BLI that produces a brighter image, its benefit in enhancing polyp detection was more definite, although the study results had been inconsistent. A small RCT in Singapore has shown that BLI-bright could enhance ADR compared to HD-WLE (46.2% vs. 27.8%; P = 0.010)[52]. In addition, a tandem endoscopy study by Shimoda et al. has shown that BLI had a lower colon adenoma miss rate compared to HD-WLE (1.6% vs. 10%; P = 0.001)[53]. In contrast, an earlier study showed that BLI-bright mode could make polyps more visible but with no improvement in ADR compared to WLE (54.8% vs. 52.7%; P = 0.52)[54].

    With the enhanced brightness and image contrast, Fujifilm’s LCI has shown more favorable evidence for the improvement of ADR. Study results were more consistent when comparing the ADR of LCI over HD-WLE. A multicenter, randomized, crossover trial has shown that LCI was associated with higher ADR compared to HD-WLE (37% vs. 29%; P = 0.001)[55]. Another study by Paggi et al. demonstrated that LCI improves the ADR and decreases the polyp miss rate in the right colon (OR: 0.25; 95%CI: 0.11-0.56)[56]. Their group also published an RCT in which LCI is associated with a higher ADR compared to HD-WLE amongst the FIT-positive population in a CRC-screening program[57]. Finally, a recently published meta-analysis of seven RCTs has concluded that LCI could significantly improve ADR compared to WLE (RR: 1.26; 95%CI: 1.14-1.39;P < 0.001)[58].

    Polyp characterization and histology prediction

    Both dye-based and equipment-based IEE have been shown to be promising tools for the characterization of colorectal polyps and real-time prediction of their histology[16]. Dye-based CE can highlight the surface pattern of polyps, and its histology can be reliably predicted using the Kudo pit pattern classification for colonic lesions[19,59]. Non-neoplastic lesions can be classified as Type 1 (round pits) and Type II (stellate pits), whereas neoplastic lesions can be classified as Type III (tubular pits), Type IV (gyros-like pits), and Type V (irregular pits). A meta-analysis has shown that the Kudo pit pattern classification can predict neoplastic vs. non-neoplastic lesions with a sensitivity of 92% and specificity of 94%[60].

    The use of equipment-based IEE has also been shown to aid in the characterization of polyps and the prediction of histology of benign and neoplastic lesions. In a meta-analysis of 28 studies, NBI has been shown to accurately differentiate neoplastic from non-neoplastic lesions with a high sensitivity and negative predictive value (NPV) greater than 90%[61]. I-Scan can also predict histology with a sensitivity of 98% and specificity of 93%[48]. Similarly, FICE was shown to have a high sensitivity of 93% and NPV of 85% in distinguishing neoplastic from non-neoplastic colorectal lesions[62].

    The utility of equipment-based IEE may permit a predict-resect-and-discard approach[63]. However, this strategy has several drawbacks. For instance, this approach may not be appropriate for larger polyps as evidence only recommends its use for diminutive polyps where the risk of advanced neoplasia is very low[64,65]. Likewise, identification of serrated lesions despite being classified as JNET type 1 or NICE type 1 on IEE should not preclude the use of a resect-and-discard strategy as these lesions are associated with a higher risk of advanced neoplasia. Given these criticisms, while IEE can aid in the prediction of underlying histology, it is important to consider other polyp factors such as size, site, and morphology before considering a resect-and-discard approach.

    Endocytoscopy is another modality with the potential to predict polyp histology. According to an RCT by Mori et al., endocytoscopy is noninferior to standard biopsy for the discrimination of neoplastic lesions, which supports using endocytoscopy as a novel alternative to standard biopsy in routine colonoscopy[66]. However, the technology is not widely available and has struggled to make inroads in routine clinical practice.

    Prediction of the depth of invasion

    The depth of invasion of a colorectal neoplasm can be predicted by endoscopic visualization of the lesion through WLE. In Japan’s national colorectal cancer screening program, submucosal invasion is significantly higher for non-polypoid lesions compared to polypoid types (42.4% vs. 21.0%)[67]. However, given the nature of these non-polypoid lesions, which are often subtle and flat, their detection remains a challenge.

    Few studies have shown the potential of IEE in predicting the depth of invasion of a colorectal neoplasm. Dye-based CE with magnification can identify neoplastic invasive patterns and can aid in differentiating superficial or intramucosal submucosal cancers from deep submucosal cancers[68,69]. Virtual CE can also predict the risk of invasive cancer in suspected lesions[70]. The utility of NBI in predicting the depth of invasion was first described by Hirata et al., who noted that vessel thickness and microvascular density (meshed capillary vessels, vascular pattern intensity, or brown hue) are predictive of tumor invasion[71]. This knowledge has led to the development of the NICE classification system, which is based on visualized vessels, color, and surface patterns of colonic polyps [Table 2][24]. It had a high accuracy of 89%, sensitivity of 98%, and NPV of 95% in diagnosing small colorectal polyps[26]. A more recent classification system developed by Japanese endoscopists is the JNET classification[25]. This subdivides NICE type 2 (adenomatous lesions) into JNET type 2A (low-grade adenomas) and JNET type 2B (high-grade adenomas and shallow submucosally invasive cancer). However, its performance is limited in the differentiation of superficial and invasive cancer types (e.g., JNET type 2B and 3).

    Endocytoscopy also proves to have a high diagnostic accuracy in predicting deep submucosal invasion compared to pit pattern diagnosis (OR: 1.31; 95%CI: 1.00-1.71; I2 = 0%; P = 0.05) based on a meta-analysis[72]. However, selection bias could be possible because the four studies included in the analysis were all retrospective.

    Evaluating sessile serrated lesions

    Sessile serrated lesions (SSL) are recognized as antecedent lesions of colorectal cancer [Figure 2][73]. With the aid of IEE, four SSL-like features can be described, namely, clouded surface, indistinctive border, irregular shape, and dark spots inside the crypts. These constitute the ‘Workgroup serrated polypS and Polyposis’ (WASP) classification, in which the presence of at least two features is considered sufficient to diagnose an SSL [Figure 3]. This classification system was validated with a high pooled accuracy of 84% and a pooled NPV of 91% for diminutive neoplastic lesions[74].

    Figure 2. Sessile serrated lesion in the descending colon, NICE 1, JNET Type 1, MS IIo, on (A) WLE, (B) NBI, and (C) Magnification NBI. NICE: Narrow-band imaging international colorectal endoscopic classification; JNET: Japan NBI expert team; MS: modified Sano; WLE: white light endoscopy; NBI: narrow-band imaging.

    Figure 3. WASP criteria: features of sessile serrated lesions (SSL), hyperplastic polyps, and adenomatous polyps. NICE: NBI international colorectal endoscopic classification; NBI: narrow band imaging. From IJspeert JE et al.[74] (Permission for publication obtained).

    Utility in inflammatory bowel disease

    Dysplastic lesions in IBD can be difficult to detect because they often have subtle and flat characteristics[75]. As these lesions could be precursors to colorectal cancer, it is important to identify them on screening or surveillance colonoscopies, especially for high-risk patients with long-term IBD. To increase the yield of colorectal dysplasia detection, there are pieces of evidence supporting the use of dye-based pancolonic CE with targeted biopsy vs. standard definition WLE with random biopsies[16,76,77]. A study by Kiesslich et al. showed that pancolonic CE results in a significant 3.2-fold increase in dysplasia detection[40]. CE is now the recommended standard of care in international guidelines[15,78,79].

    Equipment-based CE techniques have been shown to have evolving benefits in IBD. Compared to NBI, there was initially an insignificant trend in favor of dye-based CE for dysplasia detection in patients with long-standing IBD[80]. However, a large randomized prospective study by Bisschops et al. showed that CE and NBI do not differ significantly in the detection of colitis-associated neoplasia[81]. Given the easier technique, NBI may possibly replace dye-based CE in these settings. The newer IEE technologies, such as i-Scan, FICE, and BLI, have no available data in the context of colitis surveillance[1].


    For optimal utilization of IEE, an excellent field of view should be ensured. The entire colonic mucosa should be well visualized with no residual staining, stool fragments, liquid, gas bubbles or blood. Washing the field until clear may take more time than performing the advanced mucosal imaging technique itself. Hence, adequate bowel preparation should be advised prior to the colonoscopy. Simethicone may be flushed on areas with gas bubbles to lower their surface tension. Loop formation during scope insertion or any mucosal trauma should be avoided as far as possible. The use of a transparent cap during colonoscopy has been shown to improve polyp detection rates and might also contribute to colonoscope tip stability and may also help when combined with the underwater magnification technique[82].

    Based on the current level of evidence and the applicability of the different IEE technologies, we suggest that the entire colonic lesion and the surrounding mucosa should be initially inspected with WLE, followed by careful inspection with IEE. Optical magnification is easy and only takes a short time when assessing colonic lesions. Any areas within the lesion that appears to harbor worrisome features (e.g., depression, suspected pit, or vascularity distortion) should be further inspected with magnification. High-quality images should be taken for documentation. Moreover, assessment of the margins of the lesion is paramount, especially in sessile serrated lesions where the inconspicuous margins might be assessed more clearly with IEE. IEE with magnification should also be performed before and after polyp resection to delineate lesion borders and to ensure complete resection. As for surveillance of patients with IBD, WLE could be used during the progression of the scope to the cecum and IEE during scope withdrawal.

    Given the relative availability of the different advanced technologies, it is recommended that endoscopists should make every effort to improve their performances whenever possible. The ESGE has suggested that training on advanced endoscopic imaging be a prerequisite for its use in clinical practice for improved performance[10].


    Optivista is a new IEE mode introduced by Pentax in 2016. It is based on the use of a mechanical optical filter that generates bandwidth-limiting light to improve mucosal surface and vascular characterization of colorectal polyps[5]. A recent study demonstrated that Optivista has a similar ADR with the older Pentax IEE technology i-Scan (39.4% vs. 38.3%; P = 0.82)[83]. Other data including a direct comparison to WLE remains lacking.

    In 2020, Olympus introduced Texture and Color Enhancement Imaging (TXI). In TXI, three image factors in WLE, namely texture, brightness, and color, are enhanced to clearly define subtle tissue differences [Figure 4][84]. The images obtained under normal white light are divided into a texture image and a base image. These two images are then recombined to enhance the structure, color tone, and brightness of the mucosal surface[5]. A recent study of 27 patients in Japan showed that TXI provided higher visibility than WLE for colorectal polyps, including SSLs[85]. Another study of 22 Japanese patients with 68 lesions also showed TXI enables improved visualization of colorectal lesions than WLE and NBI (TXI mode1 80.5, TXI mode2 75.6, WLE 70.0, NBI 69.0)[86]. Several studies are currently in progress to determine TXI’s efficacy in improving detection rates in colonoscopy.

    Figure 4. Rectal polyp measuring 3.5 cm, Paris IIa + 1s, NICE 3, JNET Type 2B, MS IIIa, on (A) WLE, (B) TXI, (C) NBI, and (D) Magnification NBI.

    Red dichromatic imaging (RDI) is a new IEE technology developed by Olympus, which can enhance the visibility of deep blood vessels using green (540 nm), amber (600 nm), and red (630 nm) wavelengths[87]. Hemoglobin can absorb different wavelengths, leading to the identification of possible bleeding points. RDI has three modes, with mode 1 helpful in visualizing bleeding points, whereas modes 2 and 3 in visualizing deep and superficial vessels. To date, limited published data on RDI exists. A study by Hirai et al. has shown that RDI improves the detection of bleeding points in acute GI bleeding compared to WLE (3.12 ± 0.51 vs. 2.72 ± 0.50; P < 0.001)[88]. Recent case reports have also shown its efficacy in reducing the risk of bleeding in endoscopic submucosal dissection (ESD) and per-oral endoscopic myotomy (POEM)[89,90].

    Computer-aided detection (CADe) using artificial intelligence (AI) for colonoscopy is a newer technology being developed and studied to improve ADR and allow pathological prediction of detected colorectal lesions[91]. A prospective, RCT by Repici et al. has shown that computer-aided detection (CADe) (GI Genius, Medtronic) during colonoscopy increases ADR when compared with the control group (53.3% vs. 44.5%; RR: 1.22, 95%CI: 1.04-1.40; P < 0.01 for non-inferiority and P = 0.02 for superiority)[92]. A recent network meta-analysis of 50 RCTs, comprising 34,445 participants, has also shown that ADR was higher with CADe by 7.4% (OR: 1.78; 95%CI: 1.44-2.18) and higher with chromoendoscopy by 4.4% (OR: 1.22; 95%CI: 1.08-1.39) compared with WLE[93].

    Aside from polyp identification, AI has also been studied to provide real-time in vivo computer-aided diagnoses (CADx) of neoplastic vs. non-neoplastic lesions[94]. In a recent study of 60 colorectal polyps assessed with CADx vs. intuitive optical diagnosis, CADx had a diagnostic accuracy of 88.3% using high-definition WL images and 86.7% using BLI images[95]. In a multicenter library of > 200,000 images from 1572 polyps, CADx had a sensitivity, specificity, and accuracy of 85%, 79%, and 84%, respectively[96].


    The advancements in IEE technology have allowed better detection and management of colorectal cancers and other pre-malignant conditions. It has played distinctive roles in polyp and histologic characterization and prediction of depth of invasion of colorectal cancers, thereby improving clinical outcomes. With the advent of tools such as AI and newer IEE modes, detection rates can potentially be further improved and promising future directions such as the resect-and-discard strategy of diminutive polyps, prediction of histology of difficult polyps such as sessile serrated lesions, and AI-driven prediction of depth of invasion of colorectal cancers can come to fruition. Growing research in this area could significantly impact the diagnostic and therapeutic process in GI endoscopy.


    Author’s contributions

    Made substantial contributions to conception and design of the review article: Aguila ET, Beany A, Singh R

    Availability of data and materials

    Not applicable.

    Financial support and sponsorship


    Conflicts of interest

    All authors declared that there are no conflicts of interest.

    Ethical approval and consent to participate

    Not applicable.

    Consent for publication

    Not applicable.


    © The Author(s) 2022.


    • 1. Sano Y, Chiu HM, Li XB, et al. Standards of diagnostic colonoscopy for early-stage neoplasia: recommendations by an Asian private group. Dig Endosc 2019;31:227-44.

      DOIPubMed PMC
    • 2. Jang JY. The past, present, and future of image-enhanced endoscopy. Clin Endosc 2015;48:466-75.

      DOIPubMed PMC
    • 3. Subramanian V, Ragunath K. Advanced endoscopic imaging: a review of commercially available technologies. Clin Gastroenterol Hepatol 2014;12:368-76.e1.

    • 4. Kaltenbach T, Sano Y, Friedland S, Soetikno R. American Gastroenterological Association. American gastroenterological association (AGA) institute technology assessment on image-enhanced endoscopy. Gastroenterology 2008;134:327-40.

    • 5. Chang WY, Chiu HM. Can image-enhanced endoscopy improve adenoma detection rate? Dig Endosc 2022;34:284-96.

    • 6. Singh R, Chiam KH, Leiria F, Pu LZCT, Choi KC, Militz M. Chromoendoscopy: role in modern endoscopic imaging. Transl Gastroenterol Hepatol 2020;5:39.

      DOIPubMed PMC
    • 7. Trivedi PJ, Braden B. Indications, stains and techniques in chromoendoscopy. QJM 2013;106:117-31.

      DOIPubMed PMC
    • 8. Pal P, Singh AP, Kanuri ND, Banerjee R. Electronic chromo-endoscopy: technical details and a clinical perspective. Transl Gastroenterol Hepatol 2022;7:6.

      DOIPubMed PMC
    • 9. Osawa H, Yamamoto H. Present and future status of flexible spectral imaging color enhancement and blue laser imaging technology. Dig Endosc 2014;26 Suppl 1:105-15.

    • 10. East JE, Vleugels JL, Roelandt P, et al. Advanced endoscopic imaging: european society of gastrointestinal endoscopy (ESGE) technology review. Endoscopy 2016;48:1029-45.

    • 11. Kiesslich R. SCENIC update 2021: is chromoendoscopy still standard of care for inflammatory bowel disease surveillance? Gastrointest Endosc 2022;95:38-41.

    • 12. Cairns SR, Scholefield JH, Steele RJ, et al. British Society of Gastroenterology. Guidelines for colorectal cancer screening and surveillance in moderate and high risk groups (update from 2002). Gut 2010;59:666-89.

    • 13. Murthy SK, Feuerstein JD, Nguyen GC, Velayos FS. AGA Clinical practice update on endoscopic surveillance and management of colorectal dysplasia in inflammatory bowel diseases: expert review. Gastroenterology 2021;161:1043-1051.e4.

    • 14. Shergill AK, Lightdale JR, Bruining DH, et al. American Society for Gastrointestinal Endoscopy Standards of Practice Committee. The role of endoscopy in inflammatory bowel disease. Gastrointest Endosc 2015;81:1101-21.e1.

    • 15. Laine L, Kaltenbach T, Barkun A, McQuaid KR, Subramanian V, Soetikno R. SCENIC Guideline Development Panel. SCENIC international consensus statement on surveillance and management of dysplasia in inflammatory bowel disease. Gastrointest Endosc 2015;81:489-501.e26.

    • 16. Buchner AM. The role of chromoendoscopy in evaluating colorectal dysplasia. Gastroenterol Hepatol 2017;13:336-47.

      PubMed PMC
    • 17. Repici A, Ciscato C, Wallace M, et al. Evaluation of genotoxicity related to oral methylene blue chromoendoscopy. Endoscopy 2018;50:1027-32.

    • 18. Repici A, Wallace MB, East JE, et al. Efficacy of per-oral methylene blue formulation for screening colonoscopy. Gastroenterology 2019;156:2198-2207.e1.

    • 19. Kudo S, Tamura S, Nakajima T, Yamano H, Kusaka H, Watanabe H. Diagnosis of colorectal tumorous lesions by magnifying endoscopy. Gastrointest Endosc 1996;44:8-14.

    • 20. Cohen J. Top tips for using image-enhanced endoscopy during colonoscopy (with videos). Gastrointest Endosc 2022;95:780-6.

    • 21. Muto M, Horimatsu T, Ezoe Y, Morita S, Miyamoto S. Improving visualization techniques by narrow band imaging and magnification endoscopy. J Gastroenterol Hepatol 2009;24:1333-46.

    • 22. Gono K, Obi T, Yamaguchi M, et al. Appearance of enhanced tissue features in narrow-band endoscopic imaging. J Biomed Opt 2004;9:568-77.

    • 23. Muto M, Katada C, Sano Y, Yoshida S. Narrow band imaging: a new diagnostic approach to visualize angiogenesis in superficial Neoplasia. Clin Gastroenterol Hepatol 2005;3:S16-20.

    • 24. Hayashi N, Tanaka S, Hewett DG, et al. Endoscopic prediction of deep submucosal invasive carcinoma: validation of the narrow-band imaging international colorectal endoscopic (NICE) classification. Gastrointest Endosc 2013;78:625-32.

    • 25. Sano Y, Tanaka S, Kudo SE, et al. Narrow-band imaging (NBI) magnifying endoscopic classification of colorectal tumors proposed by the Japan NBI expert team. Dig Endosc 2016;28:526-33.

    • 26. Hewett DG, Kaltenbach T, Sano Y, et al. Validation of a simple classification system for endoscopic diagnosis of small colorectal polyps using narrow-band imaging. Gastroenterology 2012;143:599-607.e1.

    • 27. Zorron Cheng Tao Pu L, Yamamura T, Nakamura M, et al. Comparison of different virtual chromoendoscopy classification systems for the characterization of colorectal lesions. JGH Open 2020;4:818-26.

      DOIPubMed PMC
    • 28. Singh R, Jayanna M, Navadgi S, Ruszkiewicz A, Saito Y, Uedo N. Narrow-band imaging with dual focus magnification in differentiating colorectal neoplasia. Dig Endosc 2013;25 Suppl 2:16-20.

    • 29. Pu LZCT, Cheong KL, Koay DSC, et al. Randomised controlled trial comparing modified Sano’s and narrow band imaging international colorectal endoscopic classifications for colorectal lesions. World J Gastrointest Endosc 2018;10:210-8.

      DOIPubMed PMC
    • 30. Kodashima S, Fujishiro M. Novel image-enhanced endoscopy with i-scan technology. World J Gastroenterol 2010;16:1043-9.

      DOIPubMed PMC
    • 31. Lee HH, Lee BI. Image-enhanced endoscopy in lower gastrointestinal diseases: present and future. Clin Endosc 2018;51:534-40.

      DOIPubMed PMC
    • 32. Miyake Y, Nakaguchi T, Tsumura N, et al. .

    • 33. Yoshida N, Dohi O, Inoue K, et al. Blue laser imaging, blue light imaging, and linked color imaging for the detection and characterization of colorectal tumors. Gut Liver 2019;13:140-8.

      DOIPubMed PMC
    • 34. Sun X, Dong T, Bi Y, et al. Linked color imaging application for improving the endoscopic diagnosis accuracy: a pilot study. Sci Rep 2016;6:33473.

      DOIPubMed PMC
    • 35. Zhao ZY, Guan YG, Li BR, et al. Detection and miss rates of autofluorescence imaging of adenomatous and polypoid lesions during colonoscopy: a systematic review and meta-analysis. Endosc Int Open 2015;3:E226-35.

      DOIPubMed PMC
    • 36. Takeuchi Y, Sawaya M, Oka S, et al. Efficacy of autofluorescence imaging for flat neoplasm detection: a multicenter randomized controlled trial (A-FLAT trial). Gastrointest Endosc 2019;89:460-9.

    • 37. Kantsevoy SV, Adler DG, Conway JD, et al. ASGE Technology Committee. Confocal laser endomicroscopy. Gastrointest Endosc 2009;70:197-200.

    • 38. Pilonis ND, Januszewicz W, di Pietro M. Confocal laser endomicroscopy in gastro-intestinal endoscopy: technical aspects and clinical applications. Transl Gastroenterol Hepatol 2022;7:7.

      DOIPubMed PMC
    • 39. Kiesslich R, Burg J, Vieth M, et al. Confocal laser endosopy for diagnosing intraepithelial neoplasia and colorectal cancer in vivo. Gastroenterology 2004;127:706-13.

    • 40. Kiesslich R, Goetz M, Lammersdorf K, et al. Chromoscopy-guided endomicroscopy increases the diagnostic yield of intraepithelial neoplasia in ulcerative colitis. Gastroenterology 2007;132:874-82.

    • 41. Singh R, Sathananthan D, Tam W, Ruszkiewicz A. Endocytoscopy for diagnosis of gastrointestinal neoplasia: the expert’s approach. Video J Encycl GI Endosc 2013;1:18-9.

    • 42. Ichimasa K, Kudo SE, Mori Y, et al. Double staining with crystal violet and methylene blue is appropriate for colonic endocytoscopy: an in vivo prospective pilot study. Dig Endosc 2014;26:403-8.

      DOIPubMed PMC
    • 43. Kodashima S, Fujishiro M, Takubo K, et al. Ex-vivo study of high-magnification chromoendoscopy in the gastrointestinal tract to determine the optimal staining conditions for endocytoscopy. Endoscopy 2006;38:1115-21.

    • 44. Dinesen L, Chua TJ, Kaffes AJ. Meta-analysis of narrow-band imaging versus conventional colonoscopy for adenoma detection. Gastrointest Endosc 2012;75:604-11.

    • 45. Pasha SF, Leighton JA, Das A, et al. Comparison of the yield and miss rate of narrow band imaging and white light endoscopy in patients undergoing screening or surveillance colonoscopy: a meta-analysis. Am J Gastroenterol 2012;107:363-70; quiz 371.

    • 46. Atkinson NSS, Ket S, Bassett P, et al. Narrow-band imaging for detection of neoplasia at colonoscopy: a meta-analysis of data from individual patients in randomized controlled trials. Gastroenterology 2019;157:462-71.

    • 47. Omata F, Ohde S, Deshpande GA, Kobayashi D, Masuda K, Fukui T. Image-enhanced, chromo, and cap-assisted colonoscopy for improving adenoma/neoplasia detection rate: a systematic review and meta-analysis. Scand J Gastroenterol 2014;49:222-37.

    • 48. Hoffman A, Sar F, Goetz M, et al. High definition colonoscopy combined with i-Scan is superior in the detection of colorectal neoplasias compared with standard video colonoscopy: a prospective randomized controlled trial. Endoscopy 2010;42:827-33.

    • 49. Kidambi TD, Terdiman JP, El-Nachef N, Singh A, Kattah MG, Lee JK. Effect of I-scan electronic chromoendoscopy on detection of adenomas during colonoscopy. Clin Gastroenterol Hepatol 2019;17:701-708.e1.

    • 50. Pohl J, Lotterer E, Balzer C, et al. Computed virtual chromoendoscopy versus standard colonoscopy with targeted indigocarmine chromoscopy: a randomised multicentre trial. Gut 2009;58:73-8.

    • 51. Aminalai A, Rösch T, Aschenbeck J, et al. Live image processing does not increase adenoma detection rate during colonoscopy: a randomized comparison between FICE and conventional imaging (Berlin Colonoscopy Project 5, BECOP-5). Am J Gastroenterol 2010;105:2383-8.

    • 52. Ang TL, Li JW, Wong YJ, et al. A prospective randomized study of colonoscopy using blue laser imaging and white light imaging in detection and differentiation of colonic polyps. Endosc Int Open 2019;7:E1207-13.

      DOIPubMed PMC
    • 53. Shimoda R, Sakata Y, Fujise T, et al. The adenoma miss rate of blue-laser imaging vs. white-light imaging during colonoscopy: a randomized tandem trial. Endoscopy 2017;49:186-90.

    • 54. Ikematsu H, Sakamoto T, Togashi K, et al. Detectability of colorectal neoplastic lesions using a novel endoscopic system with blue laser imaging: a multicenter randomized controlled trial. Gastrointest Endosc 2017;86:386-94.

    • 55. Min M, Deng P, Zhang W, Sun X, Liu Y, Nong B. Comparison of linked color imaging and white-light colonoscopy for detection of colorectal polyps: a multicenter, randomized, crossover trial. Gastrointest Endosc 2017;86:724-30.

    • 56. Paggi S, Mogavero G, Amato A, et al. Linked color imaging reduces the miss rate of neoplastic lesions in the right colon: a randomized tandem colonoscopy study. Endoscopy 2018;50:396-402.

    • 57. Paggi S, Radaelli F, Senore C, et al. Linked-color imaging versus white-light colonoscopy in an organized colorectal cancer screening program. Gastrointest Endosc 2020;92:723-30.

    • 58. Shinozaki S, Kobayashi Y, Hayashi Y, et al. Colon polyp detection using linked color imaging compared to white light imaging: systematic review and meta-analysis. Dig Endosc 2020;32:874-81.

    • 59. Kudo S, Rubio CA, Teixeira CR, Kashida H, Kogure E. Pit pattern in colorectal neoplasia: endoscopic magnifying view. Endoscopy 2001;33:367-73.

    • 60. Brown SR, Baraza W, Hurlstone P, Brown SR. Chromoscopy versus conventional endoscopy for the detection of polyps in the colon and rectum. Cochrane Database Syst Rev ;2007:CD006439.

    • 61. McGill SK, Evangelou E, Ioannidis JP, Soetikno RM, Kaltenbach T. Narrow band imaging to differentiate neoplastic and non-neoplastic colorectal polyps in real time: a meta-analysis of diagnostic operating characteristics. Gut 2013;62:1704-13.

      DOIPubMed PMC
    • 62. Longcroft-Wheaton G, Brown J, Cowlishaw D, Higgins B, Bhandari P. High-definition vs. standard-definition colonoscopy in the characterization of small colonic polyps: results from a randomized trial. Endoscopy 2012;44:905-10.

    • 63. Dayyeh BK, Thosani N, Konda V, et al; ASGE Technology Committee. ASGE Technology Committee systematic review and meta-analysis assessing the ASGE PIVI thresholds for adopting real-time endoscopic assessment of the histology of diminutive colorectal polyps. Gastrointest Endosc 2015;81:502.e1-502.e16.

    • 64. Radaelli F. The resect-and-discard strategy for management of small and diminutive colonic polyps. Gastroenterol Hepatol 2013;9:305-8.

      PubMed PMC
    • 65. Rex DK, Kahi C, O’Brien M, et al. The American Society for Gastrointestinal Endoscopy PIVI (Preservation and Incorporation of Valuable Endoscopic Innovations) on real-time endoscopic assessment of the histology of diminutive colorectal polyps. Gastrointest Endosc 2011;73:419-22.

    • 66. Mori Y, Kudo S, Ikehara N, et al. Comprehensive diagnostic ability of endocytoscopy compared with biopsy for colorectal neoplasms: a prospective randomized noninferiority trial. Endoscopy 2013;45:98-105.

    • 67. Kudo Se, Lambert R, Allen JI, et al. Nonpolypoid neoplastic lesions of the colorectal mucosa. Gastrointest Endosc 2008;68:S3-47.

    • 68. Lee A, Tutticci N. Enhancing polyp detection: technological advances in colonoscopy imaging. Transl Gastroenterol Hepatol 2021;6:61.

      DOIPubMed PMC
    • 69. Matsuda T, Fujii T, Saito Y, et al. Efficacy of the invasive/non-invasive pattern by magnifying chromoendoscopy to estimate the depth of invasion of early colorectal neoplasms. Am J Gastroenterol 2008;103:2700-6.

    • 70. Barbeiro S, Libânio D, Castro R, Dinis-Ribeiro M, Pimentel-Nunes P. Narrow-band imaging: clinical application in gastrointestinal endoscopy. GE Port J Gastroenterol 2018;26:40-53.

      DOIPubMed PMC
    • 71. Hirata M, Tanaka S, Oka S, et al. Evaluation of microvessels in colorectal tumors by narrow band imaging magnification. Gastrointest Endosc 2007;66:945-52.

    • 72. Takamaru H, Wu SYS, Saito Y. Endocytoscopy: technology and clinical application in the lower GI tract. Transl Gastroenterol Hepatol 2020;5:40.

      DOIPubMed PMC
    • 73. East JE, Vieth M, Rex DK. Serrated lesions in colorectal cancer screening: detection, resection, pathology and surveillance. Gut 2015;64:991-1000.

    • 74. IJspeert JE, Bastiaansen BA, van Leerdam ME, et al. Dutch Workgroup serrAted polypS & Polyposis (WASP). Development and validation of the WASP classification system for optical diagnosis of adenomas, hyperplastic polyps and sessile serrated adenomas/polyps. Gut 2016;65:963-70.

    • 75. Rubin DT, Rothe JA, Hetzel JT, Cohen RD, Hanauer SB. Are dysplasia and colorectal cancer endoscopically visible in patients with ulcerative colitis? Gastrointest Endosc 2007;65:998-1004.

    • 76. Soetikno R, Subramanian V, Kaltenbach T, et al. The detection of nonpolypoid (flat and depressed) colorectal neoplasms in patients with inflammatory bowel disease. Gastroenterology 2013;144:1349-52, 1352.e1.

    • 77. Subramanian V, Mannath J, Ragunath K, Hawkey CJ. Meta-analysis: the diagnostic yield of chromoendoscopy for detecting dysplasia in patients with colonic inflammatory bowel disease. Aliment Pharmacol Ther 2011;33:304-12.

    • 78. Kamiński MF, Hassan C, Bisschops R, et al. Advanced imaging for detection and differentiation of colorectal neoplasia: European society of gastrointestinal endoscopy (ESGE) guideline. Endoscopy 2014;46:435-49.

    • 79. Annese V, Daperno M, Rutter MD, et al. European Crohn’s and Colitis Organisation. European evidence based consensus for endoscopy in inflammatory bowel disease. J Crohns Colitis 2013;7:982-1018.

    • 80. Efthymiou M, Allen PB, Taylor AC, et al. Chromoendoscopy versus narrow band imaging for colonic surveillance in inflammatory bowel disease. Inflamm Bowel Dis 2013;19:2132-8.

    • 81. Bisschops R, Bessissow T, Joseph JA, et al. Chromoendoscopy versus narrow band imaging in UC: a prospective randomised controlled trial. Gut 2018;67:1087-94.

    • 82. Mir FA, Boumitri C, Ashraf I, et al. Cap-assisted colonoscopy versus standard colonoscopy: is the cap beneficial? Ann Gastroenterol 2017;30:640-8.

      DOIPubMed PMC
    • 83. Djinbachian R, Pohl H, Marques P, et al. Sa2010 optical diagnosis of small colorectal polyps using optivista and iscan image enhanced endoscopy: a randomized controlled trial. Gastro Endosc 2020;91:AB240.

    • 84. Sato T. TXI: texture and color enhancement imaging for endoscopic image enhancement. J Healthc Eng 2021;2021:5518948.

      DOIPubMed PMC
    • 85. Nishizawa T, Toyoshima O, Yoshida S, et al. TXI (texture and color enhancement imaging) for serrated colorectal lesions. J Clin Med 2021;11:119.

      DOIPubMed PMC
    • 86. Tamai N, Horiuchi H, Matsui H, et al. Visibility evaluation of colorectal lesion using texture and color enhancement imaging with video. DEN open 2022;2:e90.

      DOIPubMed PMC
    • 87. Al-Sabban AHM, Al-Kawas FH. Red dichromatic imaging in acute GI bleeding: does it make a difference? Gastrointest Endosc 2022;95:701-2.

    • 88. Hirai Y, Fujimoto A, Matsutani N, et al. Evaluation of the visibility of bleeding points using red dichromatic imaging in endoscopic hemostasis for acute GI bleeding (with video). Gastrointest Endosc 2022;95:692-700.e3.

    • 89. Maehata T, Fujimoto A, Uraoka T, et al. Efficacy of a new image-enhancement technique for achieving hemostasis in endoscopic submucosal dissection. Gastrointest Endosc 2020;92:667-74.

    • 90. KV A, Ramchandani M, Inavolu P, et al. Red dichromatic imaging in peroral endoscopic myotomy: a novel image-enhancing technique. VideoGIE 2021;6:203-6.

      DOIPubMed PMC
    • 91. Kudo SE, Mori Y, Abdel-Aal UM, et al. Artificial intelligence and computer-aided diagnosis for colonoscopy: where do we stand now? Transl Gastroenterol Hepatol 2021;6:64.

      DOIPubMed PMC
    • 92. Repici A, Spadaccini M, Antonelli G, et al. Artificial intelligence and colonoscopy experience: lessons from two randomised trials. Gut 2022;71:757-65.

    • 93. Spadaccini M, Iannone A, Maselli R, et al. Computer-aided detection versus advanced imaging for detection of colorectal neoplasia: a systematic review and network meta-analysis. Lancet Gastroenterol Hepatol 2021;6:793-802.

    • 94. Joseph J, LePage EM, Cheney CP, Pawa R. Artificial intelligence in colonoscopy. World J Gastroenterol 2021;27:4802-17.

      DOIPubMed PMC
    • 95. van der Zander QEW, Schreuder RM, Fonollà R, et al. Optical diagnosis of colorectal polyp images using a newly developed computer-aided diagnosis system (CADx) compared with intuitive optical diagnosis. Endoscopy 2021;53:1219-26.

    • 96. Weigt J, Repici A, Antonelli G, et al. Performance of a new integrated computer-assisted system (CADe/CADx) for detection and characterization of colorectal neoplasia. Endoscopy 2022;54:180-4.


    Cite This Article

    OAE Style

    Aguila EJ, Beany A, Singh R. Advanced mucosal imaging in colonoscopy: technical details and clinical applications. Mini-invasive Surg 2022;6:55. http://dx.doi.org/10.20517/2574-1225.2022.35

    AMA Style

    Aguila EJ, Beany A, Singh R. Advanced mucosal imaging in colonoscopy: technical details and clinical applications. Mini-invasive Surgery. 2022; 6:55. http://dx.doi.org/10.20517/2574-1225.2022.35

    Chicago/Turabian Style

    Aguila, Enrik John, Andrawus Beany, Rajvinder Singh. 2022. "Advanced mucosal imaging in colonoscopy: technical details and clinical applications" Mini-invasive Surgery. 6: 55. http://dx.doi.org/10.20517/2574-1225.2022.35

    ACS Style

    Aguila, EJ.; Beany A.; Singh R. Advanced mucosal imaging in colonoscopy: technical details and clinical applications. Mini-invasive. Surg. 20226, 55. http://dx.doi.org/10.20517/2574-1225.2022.35




    Comments must be written in English. Spam, offensive content, impersonation, and private information will not be permitted. If any comment is reported and identified as inappropriate content by OAE staff, the comment will be removed without notice. If you have any queries or need any help, please contact us at support@oaepublish.com.

    © 2016-2023 OAE Publishing Inc., except certain content provided by third parties