Conventional White-light Imaging Research Articles

An ingestible near-infrared fluorescence capsule endoscopy for specific gastrointestinal diagnoses

Early diagnosis of gastrointestinal (GI) diseases is important to effectively prevent carcinogenesis. Capsule endoscopy (CE) can address the pain caused by wired endoscopy in GI diagnosis. However, existing CE approaches have difficulty effectively diagnosing lesions that do not exhibit obvious morphological changes. In addition, the current CE cannot achieve wireless energy supply and attitude control at the same time. Here, we successfully developed a novel near-infrared fluorescence capsule endoscopy (NIFCE) that can stimulate and capture near-infrared (NIR) fluorescence images to specifically identify subtle mucosal microlesions and submucosal lesions while capturing conventional white light (WL) images to detect lesions with significant morphological changes. Furthermore, we constructed the first synergetic system that simultaneously enables multi-attitude control in NIFCE and supplies long-term power, thus addressing the issue of excessive power consumption caused by the NIFCE emitting near-infrared light (NIRL). We performed in vivo experiments to verify that the NIFCE can specifically "light up" tumors while sparing normal tissues by synergizing with probes actively aggregated in tumors, thus realizing specific detection and penetration. The prototype NIFCE system represents a significant step forward in the field of CE and shows great potential in efficiently achieving early targeted diagnosis of various GI diseases.

Simultaneous detection of Helicobacter pylori infection comparing between white light and image-enhanced endoscopy

BackgroundHelicobacter pylori (H. pylori) is associated with gastric cancer. Early and accurate diagnosis of H. pylori infection can reduce risk of gastric cancer. Conventional white light imaging (WLI) and image-enhanced endoscopic (IEE) techniques such as narrow-band imaging (NBI), linked color imaging (LCI) and blue laser imaging (BLI) plays pivotal role in H. pylori diagnosis. This study aimed to determine diagnostic performance of real-time endoscopy between WLI and other IEE techniques for diagnosis of H. pylori infection.MethodsThis prospective study compared endoscopic images by gastroscopy using WLI and IEE techniques (LCI, Magnifying-BLI, and Magnifying-NBI) at Thammasat University Hospital, Thailand between January 2020, and July 2021. All participants underwent gastroscopy. Three biopsies at gastric antrum and two biopsies at body were obtained for H.pylori diagnosis. H. pylori infection was defined as a positive test of either one of the following tests: rapid urease test, histopathology, H. pylori culture.ResultsOf 167 dyspeptic patients undergoing gastroscopy, 100 were enrolled in this study. Overall H. pylori infection was 40%. Patients had the mean age of 59.1 years and 53% were males. Enlarged gastric folds and antral nodularity can predict H. pylori infection with 100% PPV, while fundic gland polyps and red streak provided 100% PPV for exclusion of H. pylori infection on WLI. Sensitivity, specificity, PPV, NPV and accuracy for diagnosis of H. pylori infection for WLI were 80%, 71.7%, 65.3%, 84.3% and 75% respectively, while those for LCI were 90%, 70%, 66.7%, 91.3% and 78% respectively. M-NBI and M-BLI endoscopy demonstrated elongated pits in H. pylori-positive patients. Sensitivity, specificity, PPV, NPV and accuracy for M-BLI were 95%, 80%, 76%, 96% and 86% respectively, whereas those for M-NBI were 92.5%, 86.7%, 82.2%, 94.6% and 89% respectively. Sensitivity of M-BLI was better than WLI, while sensitivities of LCI and M-NBI were also numerically higher than WLI without statistical difference (M-BLI 95%vs.WLI 80%, p = 0.03; M-NBI 92.5%vs.WLI 80%, p = 0.13; LCI 90%vs.WLI 80%, p = 0.22). Sensitivities of all IEE modes were not different from one another (LCI 90%vs.M-BLI 95%, p = 0.50; LCI 90%vs.M-NBI 92.5%, p = 1.00, M-BLI 95%vs.M-NBI 92.5%, p = 1.00).ConclusionsM-BLI significantly improved sensitivity of real-time endoscopic diagnosis of H. pylori infection compared with WLI. Enlarged gastric folds and antral nodularity could be reliable predictors for H. pylori infection, while fundic gland polyps and red streak could be important endoscopic findings for H. pylori-negative mucosa.

Comprehensive advancement in endoscopy: optical design, algorithm enhancement, and clinical validation for merged WLI and CBI imaging.

As endoscopic imaging technology advances, there is a growing clinical demand for enhanced imaging capabilities. Although conventional white light imaging (WLI) endoscopy offers realistic images, it often cannot reveal detailed characteristics of the mucosa. On the other hand, optical staining endoscopy, such as Compound Band Imaging (CBI), can discern subtle structures, serving to some extent as an optical biopsy. However, its image brightness is low, and the colors can be abrupt. These two techniques, commonly used in clinical settings, have complementary advantages. Nonetheless, they require different lighting conditions, which makes it challenging to combine their imaging strengths on living tissues. In this study, we introduce a novel endoscopic imaging technique that effectively combines the advantages of both WLI and CBI. Doctors don't need to manually switch between these two observation modes, as they can obtain the image information of both modes in one image. We calibrated an appropriate proportion for simultaneous illumination with the light required for WLI and CBI. We designed a new illumination spectrum tailored for gastrointestinal examination, achieving their fusion at the optical level. Using a new algorithm that focuses on enhancing specific hemoglobin tissue features, we restored narrow-band image characteristics lost due to the introduction of white light. Our hardware and software innovations not only boost the illumination brightness of the endoscope but also ensure the narrow-band feature details of the image. To evaluate the reliability and safety of the new endoscopic system, we conducted a series of tests in line with relevant international standards and validated the design parameters. For clinical trials, we collected a total of 256 sets of images, each set comprising images of the same lesion location captured using WLI, CBI, and our proposed method. We recruited four experienced clinicians to conduct subjective evaluations of the collected images. The results affirmed the significant advantages of our method. We believe that the novel endoscopic system we introduced has vast potential for clinical application in the future.

Clinical usefulness of linked color imaging in identifying Helicobacter pylori infection: A systematic review and meta-analysis.

Accurate diagnosis of Helicobacter pylori (H. pylori) infection status is a crucial premise for eradication therapy, as well as evaluation of risk for gastric cancer. Recent progress on imaging enhancement endoscopy (IEE) made it possible to not only detect precancerous lesions and early gastrointestinal cancers but also to predict H. pylori infection in real time. As a novel IEE modality, linked color imaging (LCI) has exhibited its value on diagnosis of lesions of gastric mucosa through emphasizing minor differences of color tone. To compare the efficacy of LCI for H. pylori active infection vs conventional white light imaging (WLI). PubMed, Embase, Embase and Cochrane Library were searched up to the end of April 11, 2022. The random-effects model was adopted to calculate the diagnostic efficacy of LCI and WLI. The calculation of sensitivity, specificity, and likelihood ratios were performed; symmetric receiver operator characteristic (SROC) curves and the areas under the SROC curves were computed. Quality of the included studies was chosen to assess using the quality assessment of diagnostic accuracy studies-2 tool. Seven original studies were included in this study. The pooled sensitivity, specificity, positive likelihood rate, and negative likelihood rate of LCI for the diagnosis of H. pylori infection of gastric mucosa were 0.85 [95% confidence interval (CI): 0.76-0.92], 0.82 (95%CI: 0.78-0.85), 4.71 (95%CI: 3.7-5.9), and 0.18 (95%CI: 0.10-0.31) respectively, with diagnostic odds ratio = 26 (95%CI: 13-52), SROC = 0.87 (95%CI: 0.84-0.90), which showed superiority of diagnostic efficacy compared to WLI. Our results showed LCI can improve efficacy of diagnosis on H. pylori infection, which represents a useful endoscopic evaluation modality for clinical practice.

Assessment of hyperspectral imaging and CycleGAN-simulated narrowband techniques to detect early esophageal cancer

The clinical signs and symptoms of esophageal cancer (EC) are often not discernible until the intermediate or advanced phases. The detection of EC in advanced stages significantly decreases the survival rate to below 20%. This study conducts a comparative analysis of the efficacy of several imaging techniques, including white light image (WLI), narrowband imaging (NBI), cycle-consistent adversarial network simulated narrowband image (CNBI), and hyperspectral imaging simulated narrowband image (HNBI), in the early detection of esophageal cancer (EC). In conjunction with Kaohsiung Armed Forces General Hospital, a dataset consisting of 1000 EC pictures was used, including 500 images captured using WLI and 500 images captured using NBI. The CycleGAN model was used to generate the CNBI dataset. Additionally, a novel method for HSI imaging was created with the objective of generating HNBI pictures. The evaluation of the efficacy of these four picture types in early detection of EC was conducted using three indicators: CIEDE2000, entropy, and the structural similarity index measure (SSIM). Results of the CIEDE2000, entropy, and SSIM analyses suggest that using CycleGAN to generate CNBI images and HSI model for creating HNBI images is superior in detecting early esophageal cancer compared to the use of conventional WLI and NBI techniques.

Usefulness of AI-Equipped Endoscopy for Detecting Colorectal Adenoma during Colonoscopy Screening: Confirm That Colon Neoplasm Finely Can Be Identified by AI without Overlooking Study (Confidential Study).

In the present prospective case series study, we investigated the lesion-detection ability of an AI-equipped colonoscopy as an addition to colonoscopy (CS) screening. Participants were 100 patients aged ≥20 years who had not undergone CS at the study site in the last 3 years and passed the exclusion criteria. CS procedures were conducted using conventional white light imaging and computer-aided detection (CADe). Adenoma detection rate (ADR; number of individuals with at least one adenoma detected) was compared between the conventional group and the CADe group. Of the 170 lesions identified, the ADR of the CADe group was significantly higher than the ADR of the conventional group (69% vs. 61%, p = 0.008). For the expert endoscopists, although ADR did not differ significantly, the mean number of detected adenomas per procedure (MAP) was significantly higher in the CADe group than in the conventional group (1.7 vs. 1.45, p = 0.034). For non-expert endoscopists, ADR and MAP were significantly higher in the CADe group than in the conventional group (ADR 69.5% vs. 56.6%, p = 0.016; MAP 1.66 vs. 1.11, p < 0.001). These results indicate that the CADe function in CS screening has a positive effect on adenoma detection, especially for non-experts.

First-in-human Evaluation of a Prostate-specific Membrane Antigen–targeted Near-infrared Fluorescent Small Molecule for Fluorescence-based Identification of Prostate Cancer in Patients with High-risk Prostate Cancer Undergoing Robotic-assisted Prostatectomy

BackgroundMen with high-risk prostate cancer undergoing surgery likely recur due to failure to completely excise regional and/or local disease. ObjectiveThe first-in-human evaluation of safety, pharmacokinetics, and exploratory efficacy of IS-002, a novel near-infrared prostate-specific membrane antigen (PSMA)-targeted fluorescence imaging agent, designed for intraoperative prostate cancer visualization. Design, setting, and participantsA phase 1, single-center, dose-escalation study was conducted in 24 men with high-risk prostate cancer scheduled for robotic-assisted radical prostatectomy with (extended) pelvic lymph node dissection using the da Vinci surgical system. Outcome measurements and statistical analysisAdverse events (AEs), vital signs, complete blood count, complete metabolic panel, urinalysis, and electrocardiogram were assessed over a 14-d period and compared with baseline. The pharmacokinetic profile of IS-002 was determined. Diagnostic accuracy was assessed for exploratory efficacy. Results and limitationsAEs predominantly included discoloration of urine (n = 22/24; expected, related, grade 1). There were no grade ≥2 AEs. IS-002 Cmax and area under the curve increased with increasing dose. Plasma concentrations declined rapidly in a biphasic manner, with the median terminal half-lives ranging from 5.0 to 7.6 h, independent of dose and renal function. At 25 μg/kg, the exploratory efficacy readouts for the negative and positive predictive values were, 97% and 45% for lymph nodes, and 100% and 80% for residual/locoregional disease detection, respectively. ConclusionsIS-002 is safe and well tolerated, and has the potential to enable intraoperative tumor detection that could not be identified using standard imaging. Patient summaryIS-002 is a new imaging agent that specifically targets the prostate-specific membrane antigen receptor. In this study, we tested IS-002 for the first time in men with high-risk prostate cancer undergoing surgery and found that IS-002 is safe, is cleared from the body quickly, and potentially allows identification of prostate cancer in areas that would not be identified by conventional white light imaging.

The effect of short-term training about depth predicting score on the diagnostic ability of invasion depth for differentiated early gastric Cancer among non-expert endoscopists

BackgroundThe depth-predicting score (DPS) was proposed based on conventional white-light imaging (C-WLI) endoscopic features of early gastric cancer (EGC) to determine the invasion depth of the neoplasm. However, the effect of DPS on training endoscopists remains unclear. Therefore, we aimed to investigate the effect of short-term DPS training on improving the diagnostic ability of EGC invasion depth and compare the training effect among non-expert endoscopists at different levels.MethodsIn the training session, the definitions and scoring rules of DPS were instructed, and classic C-WLI endoscopic example graphics were exhibited to the participants. Another C-WLI endoscopic images of 88 cases of histologically proven differentiated EGC were selected as an independent test dataset for evaluating the training effect. Each participant was tested, and the diagnostic accuracy rate of invasion depth was calculated differently one week before the training and after the completion of training.ResultsA total of 16 participants were enrolled and completed the training. Participants were divided into a trainee group and a junior endoscopist group according to the total number of C-WLI endoscopies performed. The total number of C-WLI endoscopies performed showed a significant difference between the trainee group and junior endoscopist group (350 vs. 2500, P = 0.001). No significant difference between the trainee group and junior endoscopist group was observed for pre-training accuracy. The overall diagnostic accuracy of invasion depth was improved significantly after completing DPS training compared with before (68.75 ± 5.71% vs. 61.58 ± 9.61%, P = 0.009). In the subgroup analysis, the post-training accuracy was higher than the pre-training accuracy, but significant improvement was observed only in the trainee group (61.65 ± 7.33% vs. 68.32 ± 5.71%, P = 0.034). In addition, no significant difference in post-training accuracy between the two groups was observed.ConclusionShort-term DPS training can improve the diagnostic ability of the invasion depth of EGC and homogenize the diagnostic ability of non-expert endoscopists at different levels. The depth-predicting score was convenient and effective for endoscopist training.

Blue light imaging and linked color imaging as a screening mode for esophageal squamous cell carcinoma in high-risk patients: Multicenter randomized trial.

Blue light imaging (BLI) and linked color imaging (LCI) are superior to conventional white light imaging for detecting esophageal squamous cell carcinoma (ESCC). Hence, we compared their diagnostic performances in ESCC screening. This open-labeled, randomized controlled trial was performed at seven hospitals. Patients with a high risk of ESCC were randomly assigned to the BLI group (BLI followed by LCI) and LCI group (LCI followed by BLI). The primary end-point was the detection rate of ESCC in the primary mode. The main secondary end-point was its miss rate in the primary mode. In total, 699 patients were enrolled. The detection rate of ESCC did not significantly differ between the BLI and LCI groups (4.0% [14/351] vs. 4.9% [17/348]; P=0.565); however, the number of patients with ESCC tended to be smaller in the BLI group (19 vs. 30). Notably, the miss rate of ESCC was lower in the BLI group (26.3% [5/19] vs. 63.3% [19/30]; P=0.012) and LCI detected no ESCCs missed by BLI. The sensitivity was higher in BLI (75.0% vs. 47.6%; P=0.042); on the other hand, the positive predictive value in BLI tended to be lower (28.8% vs. 45.5%; P=0.092). The detection rates of ESCC did not significantly differ between BLI and LCI. Although BLI may have the potential to be advantageous over LCI for the diagnosis of ESCC, it is still unclear whether BLI is superior to LCI, and a further large-scale study is needed. Japan Registry of Clinical Trials (jRCT1022190018-1).

Development of artificial intelligence for the detection and staging of esophageal cancer

: Computer-assisted diagnosis (CAD) using deep learning, based on convolutional neural networks (CNNs), is rapidly developing in modern society and clinical practice. In the medical field of endoscopy, a CAD system can be used in the detection and staging of superficial esophageal cancer. In the detection of superficial esophageal squamous cell carcinoma (ESCC), several studies were reported as using still images of conventional white-light endoscopy and narrow-band imaging (NBI). The sensitivity of CAD systems is over 90%, and in some reports, higher than that of expert endoscopists. In addition, there is a report using video for a validation set that showed good performance. In diagnosing invasion depth, there are reports using conventional white-light imaging, NBI, and magnifying endoscopy with NBI using still images; there are also reports of intrapapillary capillary loop pattern identification using still images. Using white-light endoscopy and NBI, CAD systems showed sensitivity of 84.1–95.4%, specificity of 73.3–79.2%, and accuracy of 80.9–92.9% for differentiating SM1 cancers from SM2 or SM3 cancers in pathology. Additional systems could accurately classify intrapapillary capillary loop patterns as normal or abnormal, with comparable performance to experienced endoscopists. As for esophageal adenocarcinoma (EAC) that arises in Barrett’s esophagus (BE), there are detection reports that show favorable performance. Furthermore, the CAD system from one report identified the location suitable for biopsy; this is helpful for endoscopists because of the difficulty in determining the location of early EAC in BE. Although these studies are still only at research level, excellent performance has been achieved for detecting and staging of superficial esophageal carcinoma by CAD systems. In the near future, CAD systems will support us in detecting and staging esophageal cancers in daily clinical practice, leading to a better prognosis.

High-definition camera systems versus Conventional White Light Imaging assisted resection for treatment of Non-muscle invasive bladder cancer

High-definition camera systems versus Conventional White Light Imaging assisted resection for treatment of Non-muscle invasive bladder cancer

Assessing the development status of intraoperative fluorescence imaging for anatomy visualisation, using the IDEAL framework

ObjectivesIntraoperative fluorescence imaging is currently used in a variety of surgical fields for four main purposes: visualising anatomy, assessing tissue perfusion, identifying/localising cancer and mapping lymphatic systems. To establish evidence-based...

Novel endoscopic approaches using the endocytoscopy for the target biopsy in esophageal eosinophilia.

Multiple biopsies are recommended for the diagnosis of eosinophilic esophagitis (EoE) because inflammatory changes are frequently patchy. Reports on EoE using endocytoscopy (ECS) are limited. This present study aimed to assess if diagnostic yield improves by adding ECS on conventional white light imaging (WLI) in patients with esophageal eosinophilia (EE). A total of 284 biopsy specimens from 71 patients with a known diagnosis of EE were enrolled and divided into the WLI group (156 specimens) or the ECS group (128 specimens). Four biopsies from 5 and 10cm proximal to the esophagogastric junction were taken from each patient. In the ECS group, the biopsy was performed where bilobed nuclei were observed. The biopsy sensitivity for EE, eosinophil count of a single specimen and the biopsy sensitivity of each endoscopic finding were evaluated between both groups. The sensitivity of a single biopsy specimen was higher in the ECS group than that of the WLI group (62.5 vs. 41.7%, P < 0.001). In addition, the median eosinophil count in the ECS group was significantly higher [19 vs. 6.5/high-power field (HPF), P < 0.001]. For each endoscopic finding, ECS-based biopsy had higher sensitivity than that of WLI in the diagnosis of edema (33.1 vs. 11.3%, P = 0.007) and linear furrows (75.8 vs. 52%, P = 0.005). This study showed that adding ECS to WLI improved the biopsy sensitivity and eosinophil detection in patients with EE.

The classification of gastric antral vascular ectasia in cirrhotic patients by Versatile Intelligent Staining Technology

BackgroundPortal hypertensive gastropathy (PHG) and gastric antral vascular ectasia (GAVE) are two different pathologies that cause bleeding in cirrhotic patients. These two pathologies are still difficult to be distinguished by white light endoscopy (conventional), as they both appear as red spots in the gastric antral mucosa in the case of severe PHG. The aim of our study was to assess the efficacy of Versatile Intelligent Staining Technology (VIST) in comparison to histopathology in the diagnosis and classification of GAVE.MethodsA cross-sectional study included 50 patients with liver cirrhosis recruited from Alexandria Main University Hospital. Patients with connective tissue diseases and chronic kidney disease were excluded. All patients were examined by both conventional white light endoscopy (WLE) and image enhancement technology (VIST) using Sonoscape HD500 endoscope. GAVE was diagnosed as tortuous columns of ectatic vessels in the gastric antrum. Histopathological examination was used as the standard tool for the diagnosis of GAVE.ResultsA total of 50 patients were included, 28 patients (56 %) were diagnosed as GAVE by pathology vs 22 (44 %) as non-GAVE. Twenty-three of 28 (78.6 %) cases of GAVE were detected by VIST. VIST had superior sensitivity than WLE in the detection of GAVE, 82.1 % vs 7.1 %, while WLE had higher specificity 95.5 % vs 59.1 % by VIST. There was statistical significance between VIST and pathology in the diagnosis of GAVE, p<0.035, but no statistical significance between WLE and pathology. VIST has identified two types of GAVE: focal in 12/28 cases and diffuse in 11/28, and five were not diagnosed by VIST.ConclusionsVersatile Intelligent Staining Technology could be used as an alternative tool to histopathological diagnosis of GAVE. GAVE can present as a focal group of ectatic vessels which adds a new class to GAVE classification that was previously misdiagnosed.

Magnifying endoscopy with narrow-band imaging is useful in differentiating gastric cancer from matched adenoma in white light imaging

This study assessed the effect of magnifying endoscopy with narrow-band imaging (M-NBI) on the endoscopic differential diagnosis between intramucosal gastric carcinomas and adenomas with matched characteristics. Associations between magnified endoscopic findings and pathological high-grade cellular and architectural atypia were also investigated. In total, the records of 50 adenomas and 50 intramucosal well-differentiated adenocarcinomas matched by tumor size (≥ 20 mm or < 20 mm), shape (depression or non-depression), and color (red or non-red) were extracted. Fourteen endoscopists diagnosed adenoma or cancer in the 100 cases with conventional white light imaging (C-WLI), then did the same with C-WLI + M-NBI.The cancer diagnostic sensitivity, specificity, and accuracy were assessed. The sensitivity of C-WLI + M-NBI for cancer diagnosis was 79.9% compared to 71.6% with C-WLI (p < 0.001). There were no significant differences in specificity (40.1% vs. 36.3%, p = 0.296) and accuracy (55.9% vs. 58.1%, p = 0.163). High-grade cytological or architectural atypia was diagnosed more often with irregular microvascular pattern (IMVP) or microsurface pattern (IMSP), respectively, than the low-grade forms. In conclusion, IMVP and IMSP correlate with high-grade cytological and architectural atypia. M-NBI is useful in differentiating intramucosal carcinoma from adenoma and can reduce underdiagnosis of cancer.

Artificial Intelligence for Segmentation of Bladder Tumor Cystoscopic Images Performed by U-Net with Dilated Convolution.

Background: Early intravesical recurrence after transurethral resection of bladder tumors (TURBT) is often caused by overlooking of tumors during TURBT. Although narrow-band imaging and photodynamic diagnosis were developed to detect more tumors than conventional white-light imaging, the accuracy of these systems has been subjective, along with poor reproducibility due to their dependence on the physician's experience and skills. To create an objective and reproducible diagnosing system, we aimed at assessing the utility of artificial intelligence (AI) with Dilated U-Net to reduce the risk of overlooked bladder tumors when compared with the conventional AI system, termed U-Net. Materials and Methods: We retrospectively obtained cystoscopic images by converting videos obtained from 120 patients who underwent TURBT into 1790 cystoscopic images. The Dilated U-Net, which is an extension of the conventional U-Net, analyzed these image datasets. The diagnostic accuracy of the Dilated U-Net and conventional U-Net were compared by using the following four measurements: pixel-wise sensitivity (PWSe); pixel-wise specificity (PWSp); pixel-wise positive predictive value (PWPPV), representing the AI diagnostic accuracy per pixel; and dice similarity coefficient (DSC), representing the overlap area between the bladder tumors in the ground truth images and segmentation maps. Results: The cystoscopic images were divided as follows, according to the pathological T-stage: 944, Ta; 412, T1; 329, T2; and 116, carcinoma in situ. The PWSe, PWSp, PWPPV, and DSC of the Dilated U-Net were 84.9%, 88.5%, 86.7%, and 83.0%, respectively, which had improved when compared to that with the conventional U-Net by 1.7%, 1.3%, 2.1%, and 2.3%, respectively. The DSC values were high for elevated lesions and low for flat lesions for both Dilated and conventional U-Net. Conclusions: Dilated U-Net, with higher DSC values than conventional U-Net, might reduce the risk of overlooking bladder tumors during cystoscopy and TURBT.

Efficacy of narrow-band imaging during peroral cholangioscopy for predicting malignancy of indeterminate biliary strictures (with videos)

Direct peroral cholangioscopy (POC) can be useful when combined with narrow-band imaging (NBI) to explore the etiologies of indeterminate biliary strictures. We evaluated the efficacy of NBI compared with that of conventional white-light imaging (WLI) during POC diagnosis of indeterminate biliary strictures. Consecutive patients with indeterminate biliary strictures were enrolled from 2016 to 2019. The primary outcome was diagnostic accuracy, and secondary outcomes were technical success, adverse events, and visualization quality when predicting malignancy. Seventy-one patients underwent direct POC under NBI during targeted biopsy sampling. The strictures were successfully explored and adequate biopsy samples obtained in 67 of 71 patients (94.4%). In terms of visual impression, WLI and NBI afforded 75.0% and 87.5% sensitivity, 82.9 and 91.4% specificity, and 82.8 and 91.3% accuracy, respectively. The areas under the WLI and NBI receiver-operating characteristic curves were .80 and .96 (P= .01). Under NBI, the visualization quality of surface structures, microvessels, and lesional margins was higher than that under conventional WLI (P< .05). Direct POC under NBI effectively and accurately predicts malignancies of indeterminate biliary strictures. NBI effectively illuminated surface structures, microvessels, and lesional margins.

Usefulness of linked color imaging for the detection of obscure early gastric cancer: Multivariate analysis of 508 lesions.

Early gastric cancers (EGCs) of the elevated type or with submucosal invasion are easily found by routine endoscopy. However, most early cancers are challenging to detect because of subtle morphological or color differences from surrounding atrophic mucosa and intestinal metaplasia. Linked color imaging (LCI) enhances mucosal color difference, making it easier to detect EGCs. The aim of this study is to clarify the advantages and possible disadvantages of LCI for screening for obscure EGC. A total of 665 malignant gastric lesions resected using endoscopic submucosal dissection between January 2015 and April 2018 were retrospectively reviewed. Obviously detectable lesions were not included in the main analysis when determining the target lesion. White light imaging (WLI)/LCI images of 508 endoscopically obscure malignant lesions were included in the final analysis and evaluated by three non-expert and three expert endoscopists using visibility scores for detection and extent. The detection visibility scores using LCI were significantly higher than those using WLI regardless of lesion characteristics including location, size, histological type, depth of invasion, and Helicobacter pylori status. The detection score improved in 46.4% cases and deteriorated in 4.9% when the modality changed from WLI to LCI. A mixed-effects multivariate logistic regression analysis showed that use of LCI (odds ratio [OR] 2.57), elevated type (OR 1.92), invasion to submucosa (OR 2.18) were significantly associated with improved visibility of EGC. Linked color imaging significantly improves visibility of EGC regardless of differences in lesion morphology, histology, location, depth of invasion, and H. pylori status compared to conventional WLI.

Artificial Intelligence for Detecting and Delineating Margins of Early ESCC Under WLI Endoscopy.

INTRODUCTION:Conventional white light imaging (WLI) endoscopy is the most common screening technique used for detecting early esophageal squamous cell carcinoma (ESCC). Nevertheless, it is difficult to detect and delineate margins of early ESCC using WLI endoscopy. This study aimed to develop an artificial intelligence (AI) model to detect and delineate margins of early ESCC under WLI endoscopy.METHODS:A total of 13,083 WLI images from 1,239 patients were used to train and test the AI model. To evaluate the detection performance of the model, 1,479 images and 563 images were used as internal and external validation data sets, respectively. For assessing the delineation performance of the model, 1,114 images and 211 images were used as internal and external validation data sets, respectively. In addition, 216 images were used to compare the delineation performance between the model and endoscopists.RESULTS:The model showed an accuracy of 85.7% and 84.5% in detecting lesions in internal and external validation, respectively. For delineating margins, the model achieved an accuracy of 93.4% and 95.7% in the internal and external validation, respectively, under an overlap ratio of 0.60. The accuracy of the model, senior endoscopists, and expert endoscopists in delineating margins were 98.1%, 78.6%, and 95.3%, respectively. The proposed model achieved similar delineating performance compared with that of expert endoscopists but superior to senior endoscopists.DISCUSSION:We successfully developed an AI model, which can be used to accurately detect early ESCC and delineate the margins of the lesions under WLI endoscopy.

Endoscopic Diagnosis for H. pylori Infection: White Light Imaging (WLI) vs. Image-Enhanced Endoscopy (IEE).

Helicobacter pylori infection is a class I carcinogen that can lead to gastric cancer. Early diagnosis and eradication of H. pylori infection are important to eliminate the risk of gastric cancer. Several invasive diagnostic techniques require biopsy samples, resulting in avoidable injury and medical expense. Furthermore, due to the localized distribution of H. pylori, random biopsies are not always reliable in diagnosing H. pylori infection. This article aimed to review endoscopic findings and new endoscopic options for the diagnosis of H. pylori infection. Using conventional white light imaging (WLI) and image-enhanced endoscopy (IEE), the endoscopic features associated with histological changes have increasingly become apparent. Real-time endoscopy is essential to make a diagnosis of H. pylori infection and allow targeted biopsy. Image-enhanced endoscopy (IEE), such as narrow-band imaging (NBI), linked color imaging (LCI), and blue laser imaging (BLI), enhances visualization of the surface vascular pattern and provides accurate diagnostic performance in H. pylori infection, as well as gastric neoplastic lesions, compared to conventional white light endoscopy. In conclusion, the new endoscopic technologies could be used in current practice with conventional white light endoscopy for accurate and real-time diagnosis of H. pylori infection and pre-cancerous lesions.