Linked color imaging improves visibility of colorectal serrated lesion by high color contrast to surrounding mucosa

Efficacy of texture and color enhancement imaging for the visibility and diagnostic accuracy of non-polypoid colorectal lesions

Objective

A newly launched endoscopy system (EVIS X1, CV-1500; Olympus) is equipped with texture and color enhancement imaging (TXI). We aimed to investigate the efficacy of TXI for the visibility and diagnostic accuracy of non-polypoid colorectal lesions.

Methods

We examined 100 non-polypoid lesions in 42 patients from the same position, angle, and distance of the view in three modes: white light imaging (WLI), narrow-band imaging (NBI), and TXI. The primary outcome was to compare polyp visibility in the three modes using subjective polyp visibility score and objective color difference values. The secondary outcome was to compare the diagnostic accuracy without magnification.

Results

Overall, the visibility score of TXI was significantly higher than that of WLI (3.7 ± 1.1 vs. 3.6 ± 1.1; p = 0.008) and lower than that of NBI (3.7 ± 1.1 vs. 3.8 ± 1.1; p = 0.013). Color difference values of TXI were higher than those of WLI (11.5 ± 6.9 vs. 9.1 ± 5.4; p < 0.001) and lower than those of NBI (11.5 ± 6.9 vs. 13.1 ± 7.7; p = 0.002). No significant differences in TXI and NBI (visibility score: 3.7 ± 1.0 vs. 3.8 ± 1.1; p = 0.833, color difference values: 11.6 ± 7.1 vs. 12.9 ± 8.3; p = 0.099) were observed for neoplastic lesions. Moreover, the diagnostic accuracy of TXI was significantly higher than that of NBI (65.5% vs. 57.6%, p = 0.012) for neoplastic lesions.

Conclusions

TXI demonstrated higher visibility than that of WLI and lower than that of NBI. Further investigations are warranted to validate the performance of the TXI mode comprehensively.

Practical utility of linked color imaging in colonoscopy: Updated literature review

The remarkable recent developments in image-enhanced endoscopy (IEE) have significantly contributed to the advancement of diagnostic techniques. Linked color imaging (LCI) is an IEE technique in which color differences are expanded by processing image data to enhance short-wavelength narrow-band light. This feature of LCI causes reddish areas to appear redder and whitish areas to appear whiter. Because most colorectal lesions, such as neoplastic and inflammatory lesions, have a reddish tone, LCI is an effective tool for identifying colorectal lesions by clarifying the redder areas and distinguishing them from the surrounding normal mucosa. To date, eight randomized controlled trials have been conducted to evaluate the effectiveness of LCI in identifying colorectal adenomatous lesions. The results of a meta-analysis integrating these studies demonstrated that LCI was superior to white-light endoscopy for detecting colorectal adenomatous lesions. LCI also improves the detection of serrated lesions by enhancing their whiteness. Furthermore, accumulating evidence suggests that LCI is superior to white-light endoscopy for the diagnosis of the colonic mucosa in patients with ulcerative colitis. In this review, based on a comprehensive search of the current literature since the implementation of LCI, the utility of LCI in the detection and diagnosis of colorectal lesions is discussed. Additionally, the latest data, including attempts to combine artificial intelligence and LCI, are presented.

Computer-aided diagnosis system for optical diagnosis of colorectal polyps under white light imaging

OBJECTIVES

This study presents a novel computer-aided diagnosis (CADx) designed for optically diagnosing colorectal polyps using white light imaging (WLI).We aimed to evaluate the effectiveness of the CADx and its auxiliary role among endoscopists with different levels of expertise.

METHODS

We collected 2,324 neoplastic and 3,735 nonneoplastic polyp WLI images for model training, and 838 colorectal polyp images from 740 patients for model validation. We compared the diagnostic accuracy of the CADx with that of 15 endoscopists under WLI and narrow band imaging (NBI). The auxiliary benefits of CADx for endoscopists of different experience levels and for identifying different types of colorectal polyps was also evaluated.

RESULTS

The CADx demonstrated an optical diagnostic accuracy of 84.49%, showing considerable superiority over all endoscopists, irrespective of whether WLI or NBI was used (P < 0.001). Assistance from the CADx significantly improved the diagnostic accuracy of the endoscopists from 68.84% to 77.49% (P = 0.001), with the most significant impact observed among novice endoscopists. Notably, novices using CADx-assisted WLI outperform junior and expert endoscopists without such assistance.

CONCLUSIONS

The CADx demonstrated a crucial role in substantially enhancing the precision of optical diagnosis for colorectal polyps under WLI and showed the greatest auxiliary benefits for novice endoscopists.

Comparison of diagnostic accuracy between linked color imaging and autofluorescence imaging in patients with ulcerative colitis: A prospective observational study

BACKGROUND AND AIM

Image enhancement endoscopy techniques, such as linked color imaging (LCI) and autofluorescence imaging (AFI), have shown promise in diagnosing mucosal inflammation in ulcerative colitis (UC). However, no studies have directly compared the diagnostic efficacy of LCI and AFI. This prospective observational study aimed to compare their diagnostic accuracy for histological healing in UC.

METHODS

This study included 81 UC patients, resulting in a total of 204 endoscopic images captured using LCI and AFI, respectively. Spearman's rank correlation coefficients assessed the correlation between LCI and AFI coloration and Geboes histopathology score (GHS). Six endoscopists, who were blinded to clinicopathological features, evaluated these images, and subsequently, the diagnostic accuracy was evaluated.

RESULTS

Spearman's rank correlation coefficients between LCI index, AFI index (reverse gamma value), and GHS were 0.324 and -0.428, respectively (P < 0.001), indicating a significant correlation between LCI and AFI coloration and histological healing. In LCI and AFI classifications, mean values for diagnostic accuracy, sensitivity, specificity, positive predictive value, and negative predictive value were 76.3 ± 2.2 versus 77.8 ± 2.7, 91.8 ± 4.0 versus 83.2 ± 7.6, 53.4 ± 10.0 versus 70.0 ± 5.3, 74.0 ± 3.5 versus 80.0 ± 1.6, and 82.9 ± 5.2 versus 75.5 ± 7.5, respectively. No significant difference in diagnostic accuracy existed between LCI and AFI classifications. However, LCI displayed higher sensitivity than AFI while AFI showed higher specificity compared with LCI (P < 0.05).

CONCLUSIONS

LCI and AFI offer comparable diagnostic accuracy for histological healing. Clinically, it is necessary to recognize diagnostic features characterized by higher sensitivity in LCI and greater specificity in AFI.

Linked-color imaging with or without artificial intelligence for adenoma detection: a randomized trial

BACKGROUND

Adenoma detection rate (ADR) is an important indicator of colonoscopy quality and colorectal cancer incidence. Both linked-color imaging (LCI) with artificial intelligence (LCA) and LCI alone increase adenoma detection during colonoscopy, although it remains unclear whether one modality is superior. This study compared ADR between LCA and LCI alone, including according to endoscopists' experience (experts and trainees) and polyp size.

METHODS

Patients undergoing colonoscopy for positive fecal immunochemical tests, follow-up of colon polyps, and abdominal symptoms at a single institution were randomly assigned to the LCA or LCI group. ADR, adenoma per colonoscopy (APC), cecal intubation time, withdrawal time, number of adenomas per location, and adenoma size were compared.

RESULTS

The LCA (n=400) and LCI (n=400) groups showed comparable cecal intubation and withdrawal times. The LCA group showed a significantly higher ADR (58.8% vs. 43.5%; P<0.001) and mean (95%CI) APC (1.31 [1.15 to 1.47] vs. 0.94 [0.80 to 1.07]; P<0.001), particularly in the ascending colon (0.30 [0.24 to 0.36] vs. 0.20 [0.15 to 0.25]; P=0.02). Total number of nonpolypoid-type adenomas was also significantly higher in the LCA group (0.15 [0.09 to 0.20] vs. 0.08 [0.05 to 0.10]; P=0.02). Small polyps (≤5, 6-9mm) were detected significantly more frequently in the LCA group (0.75 [0.64 to 0.86] vs. 0.48 [0.40 to 0.57], P<0.001 and 0.34 [0.26 to 0.41] vs. 0.24 [0.18 to 0.29], P=0.04, respectively). In both groups, ADR was not significantly different between experts and trainees.

CONCLUSIONS

LCA was significantly superior to LCI alone in terms of ADR.

Detecting colorectal lesions with image-enhanced endoscopy: an updated review from clinical trials

Colonoscopy plays an important role in reducing the incidence and mortality of colorectal cancer by detecting adenomas and other precancerous lesions. Image-enhanced endoscopy (IEE) increases lesion visibility by enhancing the microstructure, blood vessels, and mucosal surface color, resulting in the detection of colorectal lesions. In recent years, various IEE techniques have been used in clinical practice, each with its unique characteristics. Numerous studies have reported the effectiveness of IEE in the detection of colorectal lesions. IEEs can be divided into two broad categories according to the nature of the image: images constructed using narrowband wavelength light, such as narrowband imaging and blue laser imaging/blue light imaging, or color images based on white light, such as linked color imaging, texture and color enhancement imaging, and i-scan. Conversely, artificial intelligence (AI) systems, such as computer-aided diagnosis systems, have recently been developed to assist endoscopists in detecting colorectal lesions during colonoscopy. To better understand the features of each IEE, this review presents the effectiveness of each type of IEE and their combination with AI for colorectal lesion detection by referencing the latest research data.