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Background: Use of artificial intelligence may increase detection of colorectal neoplasia at colonoscopy by improving lesion recognition (CADe) and reduce pathology costs by improving optical diagnosis (CADx).Methods: A multicenter library of ≥ 200 000 images from 1572 polyps was used to train a combined CADe/CADx system. System testing was performed on two independent image sets (CADe: 446 with polyps, 234 without; CADx: 267) from 234 polyps, which were also evaluated by six endoscopists (three experts, three non-experts).Results: CADe showed sensitivity, specificity, and accuracy of 92.9 %, 90.6 %, and 91.7 %, respectively. Experts showed significantly higher accuracy and specificity, and similar sensitivity, while non-experts + CADe showed comparable sensitivity but lower specificity and accuracy than CADe and experts. CADx showed sensitivity, specificity, and accuracy of 85.0 %, 79.4 %, and 83.6 %, respectively. Experts showed comparable performance, whereas non-experts + CADx showed comparable accuracy but lower specificity than CADx and experts.Conclusions: The high accuracy shown by CADe and CADx was similar to that of experts, supporting further evaluation in a clinical setting. When using CAD, non-experts achieved a similar performance to experts, with suboptimal specificity. [ABSTRACT FROM AUTHOR]

BACKGROUND : The European Society of Gastrointestinal Endoscopy (ESGE) has developed a core curriculum for high quality optical diagnosis training for practice across Europe. The development of easy-to-measure competence standards for optical diagnosis can optimize clinical decision-making in endoscopy. This manuscript represents an official Position Statement of the ESGE aiming to define simple, safe, and easy-to-measure competence standards for endoscopists and artificial intelligence systems performing optical diagnosis of diminutive colorectal polyps (1 - 5 mm). METHODS : A panel of European experts in optical diagnosis participated in a modified Delphi process to reach consensus on Simple Optical Diagnosis Accuracy (SODA) competence standards for implementation of the optical diagnosis strategy for diminutive colorectal polyps. In order to assess the clinical benefits and harms of implementing optical diagnosis with different competence standards, a systematic literature search was performed. This was complemented with the results from a recently performed simulation study that provides guidance for setting alternative competence standards for optical diagnosis. Proposed competence standards were based on literature search and simulation study results. Competence standards were accepted if at least 80 % agreement was reached after a maximum of three voting rounds. RECOMMENDATION 1:  In order to implement the leave-in-situ strategy for diminutive colorectal lesions (1-5 mm), it is clinically acceptable if, during real-time colonoscopy, at least 90 % sensitivity and 80 % specificity is achieved for high confidence endoscopic characterization of colorectal neoplasia of 1-5 mm in the rectosigmoid. Histopathology is used as the gold standard.Level of agreement 95 %. RECOMMENDATION 2:  In order to implement the resect-and-discard strategy for diminutive colorectal lesions (1-5 mm), it is clinically acceptable if, during real-time colonoscopy, at least 80 % sensitivity and 80 % specificity is achieved for high confidence endoscopic characterization of colorectal neoplasia of 1-5 mm. Histopathology is used as the gold standard.Level of agreement 100 %. CONCLUSION : The developed SODA competence standards define diagnostic performance thresholds in relation to clinical consequences, for training and for use when auditing the optical diagnosis of diminutive colorectal polyps. [ABSTRACT FROM AUTHOR]

Background: Linked color imaging (LCI) has been shown to be effective in multiple randomized controlled trials for enhanced colorectal polyp detection. Recently, artificial intelligence (AI) with deep learning through convolutional neural networks has dramatically improved and is increasingly recognized as a promising new technique for enhancing colorectal polyp detection. Aim: This study aims to evaluate a newly developed computer-aided detection (CAD) system in combination with LCI for colorectal polyp detection. Methods: First, a convolutional neural network was trained for colorectal polyp detection in combination with the LCI technique using a dataset of anonymized endoscopy videos. For validation, 240 polyps within fully recorded endoscopy videos in LCI mode, covering the entire spectrum of adenomatous histology, were used. Sensitivity (true-positive rate per lesion) and false-positive frames in a full procedure were assessed. Results: The new CAD system used in LCI mode could process at least 60 frames per second, allowing for real-time video analysis. Sensitivity (true-positive rate per lesion) was 100%, with no lesion being missed. The calculated false-positive frame rate was 0.001%. Among the 240 polyps, 34 were sessile serrated lesions. The detection rate for sessile serrated lesions with the CAD system used in LCI mode was 100%. Conclusions: The new CAD system used in LCI mode achieved a 100% sensitivity per lesion and a negligible false-positive frame rate. Note that the new CAD system used in LCI mode also specifically allowed for detection of serrated lesions in all cases. Accordingly, the AI algorithm introduced here for the first time has the potential to dramatically improve the quality of colonoscopy. [ABSTRACT FROM AUTHOR]

Background: The BASIC classification for predicting in vivo colorectal polyp histology incorporates both surface and pit/vessel descriptor domains. This study aimed to define new BASIC classes for adenomatous and hyperplastic polyps.Methods: A video library (102 still images/videos of < 10-mm polyps using white-light [WLI] and blue-light imaging [BLI]) was reviewed by seven expert endoscopists. Polyps were rated according to the individual descriptors of the three BASIC domains (surface/pit/vessel). A model to predict polyp histology (adenomatous or hyperplastic) was developed using multivariable logistic regression and subsequent "leave-one-out" cross-validation. New BASIC rules were then defined by Delphi agreement. The overall accuracy of these rules when used by experts was evaluated according to the level of confidence and light type.Results: The strength of prediction for adenomatous histology from 2175 observations assessed by area under the curve (AUC; 95 % confidence interval) was poor-to-fair for the surface descriptors (0.50 [0.33 - 0.69] for mucus; 0.68 [0.57 - 0.79] for irregular surface), but stronger for pits (0.87 [0.80 - 0.96] for featureless/round/not round) and vessels (0.80 [0.65 - 0.87] for not present/lacy/pericryptal). By combining the domains, a good-to-excellent prediction was shown (AUC 0.89 [0.81 - 0.96]). After the definition of new BASIC rules for adenomatous and hyperplastic polyps, accuracy for high confidence BLI predictions was 90.3 % (86.3 % - 93.2 %), which was superior to high confidence WLI (83.7 % [77.3 % - 87.7 %]) and low confidence BLI predictions (77.7 % [61.1 % - 88.6 %]).Conclusions: Based on the strength of prediction, the new BASIC classes for adenomatous and hyperplastic histology show favorable results for accuracy and confidence levels. [ABSTRACT FROM AUTHOR]

1:  ESGE suggests that high definition endoscopy, and dye or virtual chromoendoscopy, as well as add-on devices, can be used in average risk patients to increase the endoscopist's adenoma detection rate. However, their routine use must be balanced against costs and practical considerations.Weak recommendation, high quality evidence. 2:  ESGE recommends the routine use of high definition systems in individuals with Lynch syndrome.Strong recommendation, high quality evidence. 3:  ESGE recommends the routine use, with targeted biopsies, of dye-based pancolonic chromoendoscopy or virtual chromoendoscopy for neoplasia surveillance in patients with long-standing colitis.Strong recommendation, moderate quality evidence. 4:  ESGE suggests that virtual chromoendoscopy and dye-based chromoendoscopy can be used, under strictly controlled conditions, for real-time optical diagnosis of diminutive (≤ 5 mm) colorectal polyps and can replace histopathological diagnosis. The optical diagnosis has to be reported using validated scales, must be adequately photodocumented, and can be performed only by experienced endoscopists who are adequately trained, as defined in the ESGE curriculum, and audited.Weak recommendation, high quality evidence. 5:  ESGE recommends the use of high definition white-light endoscopy in combination with (virtual) chromoendoscopy to predict the presence and depth of any submucosal invasion in nonpedunculated colorectal polyps prior to any treatment. Strong recommendation, moderate quality evidence. 6:  ESGE recommends the use of virtual or dye-based chromoendoscopy in addition to white-light endoscopy for the detection of residual neoplasia at a piecemeal polypectomy scar site. Strong recommendation, moderate quality evidence. 7:  ESGE suggests the possible incorporation of computer-aided diagnosis (detection and characterization of lesions) to colonoscopy, if acceptable and reproducible accuracy for colorectal neoplasia is demonstrated in high quality multicenter in vivo clinical studies. Possible significant risks with implementation, specifically endoscopist deskilling and over-reliance on artificial intelligence, unrepresentative training datasets, and hacking, need to be considered. Weak recommendation, low quality evidence. [ABSTRACT FROM AUTHOR]

Background and study aims: In order to reduce time, costs, and risks associated with resection of diminutive colorectal polyps, the American Society for Gastrointestinal Endoscopy (ASGE) recently proposed performance thresholds that new technologies should meet for the accurate real-time assessment of histology of colorectal polyps. In this study, we prospectively assessed whether laser-induced fluorescence spectroscopy (LIFS), using the new WavSTAT4 optical biopsy system, can meet the ASGE criteria. Patients and methods: 27 patients undergoing screening or surveillance colonoscopy were included. The histology of 137 diminutive colorectal polyps was predicted in real time using LIFS and findings were compared with the results of conventional histopathological examination. The accuracy of predicting polyp histology with WavSTAT4 was assessed according to the ASGE criteria. Results: The overall accuracy of LIFS using WavSTAT4 for predicting polyp histology was 84.7 % with sensitivity, specificity, and negative predictive value (NPV) of 81.8 %, 85.2 %, and 96.1 %. When only distal colorectal diminutive polyps were considered, the NPV for excluding adenomatous histology increased to 100 % (accuracy 82.4 %, sensitivity 100 %, specificity 80.6 %). On-site, LIFS correctly predicted the recommended surveillance intervals with an accuracy of 88.9 % (24/27 patients) when compared with histology-based United States guideline recommendations; in the 3 patients for whom LIFS- and histopathology-based recommended surveillance intervals differed, LIFS predicted shorter surveillance intervals. Conclusions: From the data of this pilot study, LIFS using the WavSTAT4 system appears accurate enough to allow distal colorectal polyps to be left in place and nearly reaches the threshold to “resect and discard” them without pathologic assessment. WavSTAT4 therefore has the potential to reduce costs and risks associated with the removal of diminutive colorectal polyps. [ABSTRACT FROM AUTHOR]

Background: Distal diminutive colorectal polyps are common and accurate endoscopic prediction of hyperplastic or adenomatous polyp histology could reduce procedural time, costs and potential risks associated with the resection. Within this study we assessed whether digital chromoendoscopy can accurately predict the histology of distal diminutive colorectal polyps according to the ASGE PIVI statement.Methods: In this prospective cohort study, 224 consecutive patients undergoing screening or surveillance colonoscopy were included. Real time histology of 121 diminutive distal colorectal polyps was evaluated using high-definition endoscopy with digital chromoendoscopy and the accuracy of predicting histology with digital chromoendoscopy was assessed.Results: The overall accuracy of digital chromoendoscopy for prediction of adenomatous polyp histology was 90.1 %. Sensitivity, specificity, positive and negative predictive values were 93.3, 88.7, 88.7, and 93.2 %, respectively. In high-confidence predictions, the accuracy increased to 96.3 % while sensitivity, specificity, positive and negative predictive values were calculated as 98.1, 94.4, 94.5, and 98.1 %, respectively. Surveillance intervals with digital chromoendoscopy were correctly predicted with >90 % accuracy.Conclusions: High-definition endoscopy in combination with digital chromoendoscopy allowed real-time in vivo prediction of distal colorectal polyp histology and is accurate enough to leave distal colorectal polyps in place without resection or to resect and discard them without pathologic assessment. This approach has the potential to reduce costs and risks associated with the redundant removal of diminutive colorectal polyps.Trial Registration: ClinicalTrials NCT02217449. [ABSTRACT FROM AUTHOR]

Abstract: This mini review deals with autofluorescence and cellular imaging using endomicroscopy or endocytoscopy during colonoscopy. Autofluorescence can be used to detect and characterize colorectal lesions whereas endomicroscopy and endocytoscopy are techniques to characterize colonic polyps based on cellular and subcellular patterns. [Copyright &y& Elsevier]

The article presents the author views of efficacy related to image- enhanced endoscopy for Colorectal Polyps diagnosis. Topics discussed include assistance of colorectal polyps detection for prevention of colorectal cancer; collaboration of colonoscopy and sigmoidoscopy leads to reduction in distal colorectum cancer incidence; and introduction of the Preservation and Incorporation of valuable endoscopic innovations (PIVI) statement by the American Society for Gastrointestinal Endoscopy (ASGE).

A correction is presented for the article "Development and Validation of the SIMPLE Endoscopic Classification of Diminutive and Small Colorectal Polyps" by M. Iacucci, C. Trovato, M. Daperno, et al. which appears in the same issue of the journal.