Interobserver variability in histological diagnosis of serrated colorectal polyps

What size cutoff level should be used to implement optical polyp diagnosis?

BACKGROUND : The risk of advanced pathology increases with polyp size, as does the potential for mismanagement when optical diagnosis is used. This study aimed to evaluate the proportion of patients who would be assigned inadequate surveillance intervals when different size cutoffs are adopted for use of optical diagnosis. METHODS : In a post hoc analysis of three prospective studies, the use of optical diagnosis was evaluated for three polyp size groups: 1-3, 1-5, and 1-10 mm. The primary outcome was the proportion of patients in whom advanced adenomas were found and optical diagnosis resulted in delayed surveillance. Secondary outcomes included agreements between surveillance intervals based on high confidence optical diagnosis and pathology outcomes, reduction in histopathological examinations, and proportion of patients who could receive an immediate surveillance recommendation. RESULTS : We included 3374 patients (7291 polyps ≤ 10 mm) undergoing complete colonoscopies (median age 66.0 years, 75.2 % male, 29.6 % for screening). The percentage of patients with advanced adenomas and either 2- or 7-year delayed surveillance intervals (n = 79) was 3.8 %, 15.2 %, and 25.3 % for size cutoffs of 1-3, 1-5, and 1-10 mm polyps, respectively (P < 0.001). Surveillance interval agreements between pathology and optical diagnosis for the three groups were 97.2 %, 95.5 %, and 94.2 %, respectively. Total reductions in pathology examinations for the three groups were 33.5 %, 62.3 %, and 78.2 %, respectively. CONCLUSION : A 3-mm cutoff for clinical implementation of optical diagnosis resulted in a very low risk of delayed management of advanced neoplasia while showing high surveillance interval agreement with pathology and a one-third reduction in overall requirement for pathology examinations.

Artificial intelligence-assisted colonoscopy: A review of current state of practice and research

Colonoscopy is an effective screening procedure in colorectal cancer prevention programs; however, colonoscopy practice can vary in terms of lesion detection, classification, and removal. Artificial intelligence (AI)-assisted decision support systems for endoscopy is an area of rapid research and development. The systems promise improved detection, classification, screening, and surveillance for colorectal polyps and cancer. Several recently developed applications for AI-assisted colonoscopy have shown promising results for the detection and classification of colorectal polyps and adenomas. However, their value for real-time application in clinical practice has yet to be determined owing to limitations in the design, validation, and testing of AI models under real-life clinical conditions. Despite these current limitations, ambitious attempts to expand the technology further by developing more complex systems capable of assisting and supporting the endoscopist throughout the entire colonoscopy examination, including polypectomy procedures, are at the concept stage. However, further work is required to address the barriers and challenges of AI integration into broader colonoscopy practice, to navigate the approval process from regulatory organizations and societies, and to support physicians and patients on their journey to accepting the technology by providing strong evidence of its accuracy and safety. This article takes a closer look at the current state of AI integration into the field of colonoscopy and offers suggestions for future research.

Evaluation of an Artificial Intelligence-Augmented Digital System for Histologic Classification of Colorectal Polyps

Importance

Colorectal polyps are common, and their histopathologic classification is used in the planning of follow-up surveillance. Substantial variation has been observed in pathologists' classification of colorectal polyps, and improved assessment by pathologists may be associated with reduced subsequent underuse and overuse of colonoscopy.

Objective

To compare standard microscopic assessment with an artificial intelligence (AI)-augmented digital system that annotates regions of interest within digitized polyp tissue and predicts polyp type using a deep learning model to assist pathologists in colorectal polyp classification.

Design, Setting, and Participants

In this diagnostic study conducted at a tertiary academic medical center and a community hospital in New Hampshire, 100 slides with colorectal polyp samples were read by 15 pathologists using a microscope and an AI-augmented digital system, with a washout period of at least 12 weeks between use of each modality. The study was conducted from February 10 to July 10, 2020.

Main Outcomes and Measures

Accuracy and time of evaluation were used to compare pathologists' performance when a microscope was used with their performance when the AI-augmented digital system was used. Outcomes were compared using paired t tests and mixed-effects models.

Results

In assessments of 100 slides with colorectal polyp specimens, use of the AI-augmented digital system significantly improved pathologists' classification accuracy compared with microscopic assessment from 73.9% (95% CI, 71.7%-76.2%) to 80.8% (95% CI, 78.8%-82.8%) (P < .001). The overall difference in the evaluation time per slide between the digital system (mean, 21.7 seconds; 95% CI, 20.8-22.7 seconds) and microscopic examination (mean, 13.0 seconds; 95% CI, 12.4-13.5 seconds) was -8.8 seconds (95% CI, -9.8 to -7.7 seconds), but this difference decreased as pathologists became more familiar and experienced with the digital system; the difference between the time of evaluation on the last set of 20 slides for all pathologists when using the microscope and the digital system was 4.8 seconds (95% CI, 3.0-6.5 seconds).

Conclusions and Relevance

In this diagnostic study, an AI-augmented digital system significantly improved the accuracy of pathologic interpretation of colorectal polyps compared with microscopic assessment. If applied broadly to clinical practice, this tool may be associated with decreases in subsequent overuse and underuse of colonoscopy and thus with improved patient outcomes and reduced health care costs.

Expression of Parkin, APC, APE1, and Bcl-xL in Colorectal Polyps

Colorectal cancer can develop through molecular, chromosomal, and epigenetic cumulative changes that transform the normal intestinal epithelium into the colorectal polyps, called conventional adenomas (CAs) or serrated polyps (SPs), recognized as precursors of invasive colorectal neoplasia. These benign lesions need to explore the morphology, histological diagnosis, and biomarkers profile to accurately characterize lesions with potential for evolution to cancer. This study aimed to correlate the immunohistochemical expression of Parkin and Adenomatous Polyposis Coli (APC; tumor suppressors), Human Apurinic/Apyrimidinic endonuclease 1 (APE1), and B-cell lymphoma-extra-large (Bcl-xL; oncogenic proteins) in sporadic colorectal polyps with clinical, endoscopic, and diagnostic data. Immunohistochemical analysis was performed on tissue microarray samples of 306 polyps. Based on the Allred score, the expressions were graduated in the cytoplasm and nucleus of superficial and cryptic cells. There was higher Parkin nuclear expression (p=0.006 and 0.010) and APC cytoplasmic expression in cryptic cells (p<0.001) in SPs. CAs, APE1 (p<0.001) and Bcl-xL (p<0.001) were more expressed in the nuclei and cytoplasms, respectively. These results are related to the biological role proposed for these proteins in cellular functions. They can contribute to the diagnosis criteria for polyps and improve the knowledge of biomarkers that could predict cancer development.

Serrated Lesions of the Colon-Rectum: A Focus on New Diagnostic Tools and Current Management

Prompt diagnosis and correct management of the so called "serrated lesions" (SLs) of the colon-rectum are generally considered of crucial importance in the past years, mainly due to their histological heterogeneity and peculiar clinical and molecular patterns; sometimes, they are missed at conventional endoscopy and are possibly implicated in the genesis of interval cancers. The aim of this review is to focus on the diagnostic challenges of serrated lesions, underlying the role of both conventional endoscopy and novel technologies. We will show how an accurate and precise diagnosis should immediately prompt the most appropriate therapy other than defining a proper follow-up program. It will be emphasized how novel endoscopic techniques may provide better visualization of mucosal microsurface structures other than enhancing the microvascular architecture, in order to better define and characterize specific patterns of mucosal lesions of the gastrointestinal tract. Standard therapy of SLs of the colon-rectum is still very debated, also due to the relatively lack of studies focusing on treatment issues. The high risk of incomplete resection, together with the high rate of postcolonoscopy interval cancers, suggests the need of an extra care when facing this kind of lesions. Given this background, we will outline useful technical tips and tricks in the resection of SLs, taking aspects such as the size and location of the lesions, as well as novel available techniques and technologies, other than future perspectives, including confocal laser endomicroscopy into consideration. Follow-up of SLs is another hot topic, also considering that their clinical impact has been misunderstood for a long time. The incidence of the so called interval colorectal cancer underlines how some weaknesses exist in current screening and follow-up programs. Considering the lack of wide consensus for the management of some SLs, we will try to summarize and clarify the best strategies for their optimal management.