Optical diagnosis of colorectal polyps using novel blue light imaging classification among trainee endoscopists

Koehn, Christopher; Rex, Douglas K.; Allen, Jimmy; Bhatti, Umer; Bhavsar-Burke, Indira; Chandrasekar, Viveksandeep Thoguluva; Challa, Abhiram; Duvvuri, Abhiram; Dakhoul, Lara; Ha, John; Hamade, Nour; Hicks, Stephen B.; Jansson-Knodell, Claire; Krajicek, Edward; Kundumadam, Shanker; Nutalapati, Venkat; Phatharacharukul, Parkpoom; Razmdjou, Shadi; Saito, Akira; Sarkis, Fayez; Sutton, Richard; Wehbeh, Antonios; Desai, Madhav

doi:10.1111/den.14050

Cited by 5 publications

(5 citation statements)

References 9 publications

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“…LCI has shown to improve the ADR compared to white light (58.7% vs. 46.7%; P<0.01) ( 90 ). LCI also improves detection of SSL and diminutive polyps ( 86 , 95 , 96 ). LCI keeps the color of residual as yellow, similar to white light, and therefore enhances the visibility and detection of the polyps ( 93 ).…”

Section: Discussionmentioning

confidence: 99%

“…Koehn et al reported that BLI can be taught to trainee endoscopists with online module and the improvement in accuracy of polyp characterization seemed to correlate with the years in training. Overall diagnostic accuracy improved from 74.7% (before the training) to 85.4% (after the training), P<0.01 ( 86 ).…”

Section: Electronic Enhancing Techniques (Virtual Chromoendoscopy)mentioning

confidence: 95%

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Image enhanced colonoscopy: updates and prospects—a review

Shahsavari¹,

Waqar²,

Chandrasekar³

2023

Transl Gastroenterol Hepatol

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Colonoscopy has been proven to be a successful approach in both identifying and preventing colorectal cancer. The incorporation of advanced imaging technologies, such as image-enhanced endoscopy (IEE), plays a vital role in real-time diagnosis. The advancements in endoscopic imaging technology have been continuous, from replacing fiber optics with charge-coupled devices to the introduction of chromoendoscopy in the 1970s. Recent technological advancements include “push-button” technologies like autofluorescence imaging (AFI), narrowed-spectrum endoscopy, and confocal laser endomicroscopy (CLE). Dye-based chromoendoscopy (DCE) is falling out of favor due to the longer time required for application and removal of the dye and the difficulty of identifying lesions in certain situations. Narrow band imaging (NBI) is a technology that filters the light used for illumination leading to improved contrast and better visibility of structures on the mucosal surface and has shown a consistently higher adenoma detection rate (ADR) compared to white light endoscopy. CLE has high sensitivity and specificity for polyp detection and characterization, and several classifications have been developed for accurate identification of normal, regenerative, and dysplastic epithelium. Other IEE technologies, such as blue laser imaging (BLI), linked-color imaging (LCI), i-SCAN, and AFI, have also shown promise in improving ADR and characterizing polyps. New technologies, such as Optivista, red dichromatic imaging (RDI), texture and color enhancement imaging (TXI), and computer-aided detection (CAD) using artificial intelligence (AI), are being developed to improve polyp detection and pathology prediction prior to widespread use in clinical practice.

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Section: Discussionmentioning

confidence: 99%

Section: Electronic Enhancing Techniques (Virtual Chromoendoscopy)mentioning

confidence: 95%

Image enhanced colonoscopy: updates and prospects—a review

Shahsavari¹,

Waqar²,

Chandrasekar³

2023

Transl Gastroenterol Hepatol

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“…In recent years, image-enhanced endoscopy techniques, such as blue light imaging (BLI), narrow-band imaging (NBI), and i-Scan have been developed, enabling clear visualization of microvascular architectures and surface structures of colorectal polyps [8][9][10]. Systematic classifications based on NBI findings have been established, such as the NBI International Colorectal Endoscopic Classification and BLI Adenoma Serrated International Classification (BASIC) [11,12]. Despite these advances, optical diagnosis poses challenges to the implementation of "resect and discard" strategies and artificial intelligence (AI) holds promise in revitalizing optical diagnosis savings [13].…”

Section: Introductionmentioning

confidence: 99%

Artificial intelligence for characterization of colorectal polyps: Prospective multicenter study

De Lange,

Prouvost,

Rahmi

et al. 2024

Endosc Int Open

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Background and study aims: Optical diagnosis poses challenges to the implementation of "resect and discard" strategies. This study aimed to assess the feasibility and performance of a new commercially available system for colorectal polyps. Patients and Methods: Nine expert endoscopists in three centres performed colonoscopies using AI-equipped colonoscopes (CAD EYE, Fujifilm). Histology and predictions were compared, with hyperplastic polyps and sessile serrated lesions grouped for analysis. Results: Overall, 253 polyps in 119 patients were documented (n=152 adenomas, n=78 hyperplastic polyps, n=23 sessile serrated lesions). CAD EYE detected polyps before endoscopists in 81/253 (32%) of cases. The mean polyp size was 5.5 mm (SD 0.6 mm). Polyp morphology was Paris Ip (4 %), Is (28 %), IIa (60 %), and IIb (8 %). CAD EYE achieved a sensitivity of 80%, specificity of 83%, PPV of 96%, and NPV of 72%. Expert endoscopists had a sensitivity of 88%, specificity of 83%, PPV of 96%, and NPV of 72%. Diagnostic accuracy was similar between CAD EYE (81%) and endoscopists (86%). However, sensitivity was greater with endoscopists as compared to CAD EYE (p<0.05). CAD EYE classified sessile serrated lesions as hyperplasia in 22/23 cases, and endoscopists correctly classified 16/23 cases. Conclusions: The CAD EYE system shows promise for detecting and characterising colorectal polyps. Larger studies are however needed to confirm these findings.

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“…This Web‐based learning system was composed of “pre‐test,” “didactic videos explaining BASIC,” “interactive examples,” and “post‐test assessment.” This system was provided by European BASIC investigators. Although the interobserver agreement in adenoma diagnosis was moderate ( k = 0.52), the efficiency of this Web‐based learning program seemed promising for facilitating comprehension of BASIC classification in gastroenterology fellows 6 …”

mentioning

confidence: 99%

“…Although the interobserver agreement in adenoma diagnosis was moderate (k = 0.52), the efficiency of this Web-based learning program seemed promising for facilitating comprehension of BASIC classification in gastroenterology fellows. 6 Allen et al conducted a randomized control study to clarify the optimal method for teaching NICE classification. Twenty medical trainees were randomized into an inclassroom (a single live-teaching session with an NBI expert) group and a self-directed training (educational tool with recorded audio) group.…”

mentioning

confidence: 99%

Can we efficiently learn a variety of classifications for the differentiation of colorectal polyps?

Tamai

Sumiyama

2022

Digestive Endoscopy

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Optical diagnosis of colorectal polyps using novel blue light imaging classification among trainee endoscopists

Abstract: Background: Blue light imaging (BLI) has been shown to improve the characterization of colorectal polyps among the endoscopy experts. We aimed to determine if this technology could be taught to endoscopy trainees while maintaining high accuracy and interobserver agreement.

Cited by 5 publications

References 9 publications

Image enhanced colonoscopy: updates and prospects—a review

Image enhanced colonoscopy: updates and prospects—a review

Artificial intelligence for characterization of colorectal polyps: Prospective multicenter study

Can we efficiently learn a variety of classifications for the differentiation of colorectal polyps?

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