Suboptimal endoscopic cancer recognition in colorectal lesions in a national bowel screening programme

Colon Cancer Screening, Surveillance, and Treatment: Novel Artificial Intelligence Driving Strategies in the Management of Colon Lesions

Colonoscopy, a crucial procedure for detecting and removing colorectal polyps, has seen transformative advancements through the integration of artificial intelligence, specifically in computer-aided detection (CADe) and diagnosis (CADx). These tools enhance real-time detection and characterization of lesions, potentially reducing human error, and standardizing the quality of colonoscopy across endoscopists. CADe has proven effective in increasing adenoma detection rate, potentially reducing long-term colorectal cancer incidence. However, CADe's benefits are accompanied by challenges, such as potentially longer procedure times, increased non-neoplastic polyp resections, and a higher surveillance burden. CADx, although promising in differentiating neoplastic and non-neoplastic diminutive polyps, encounters limitations in accuracy, particularly in the proximal colon. Real-world data also revealed gaps between trial efficacy and practical outcomes, emphasizing the need for further research in uncontrolled settings. Moreover, CADx limited specificity and binary output underscore the necessity for explainable artificial intelligence to gain endoscopists' trust. This review aimed to explore the benefits, harms, and limitations of artificial intelligence for colon cancer screening, surveillance, and treatment focusing on CADe and CADx systems for lesion detection and characterization, respectively, while addressing challenges in integrating these technologies into clinical practice.

Resection of Early Colorectal Neoplasms Using Endoscopic Submucosal Dissection: A Retrospective Multicenter Cohort Study

Background: Endoscopic submucosal dissection (ESD) is a reliable method that can replace surgery in the treatment of early colorectal cancer under certain conditions. Aim: The aim of the study was to analyze factors influencing the ESD procedure in early colorectal cancer, with the intention of improving its effectiveness. Patients and Methods: We conducted a multicenter, retrospective cohort study on 214 patients who underwent ESD procedures for early colorectal cancer from January 2016 to October 2023. Results:En bloc resection was achieved in 197 (92.1%) of ESD procedures, R0 resection in 149 (69.6%), and curative resection in 54 (40.9%). The submucosal invasion was classified as level 1 (SM1) in 96 cases (45.3%), level 2 (SM2) in 61 cases (28.8%), and level 3 (SM3) in 36 cases (17%). R0 resection was achieved more often in the rectum-92 (81.4%), compared to the right-24 (64.9%) and left colon-33 (61.1%), p = 0.009. In rectal tumors, R0 resection was achieved in 51 (98.1%) SM1 invasion, 27 (73%) SM2 invasion, and 13 (65%) SM3 invasion (p < 0.001). Lateral and vertical resection margins were positive in 12 (7.7%) and 52 (25.2%) cases, respectively. Vertical resection margins were statistically more often positive in lesions located in the right colon-11 cases (28.9%) and left colon-21 cases (38.9%), than in rectum-20 cases (17.5%); p = 0.010. Complications were found in 32 (15%) cases of ESD procedure-perforation in 12 cases (5.6%) and delayed bleeding in four cases (1.9%). Procedures performed in the right colon were associated with a significantly higher risk of any complications (30%) and perforations (15%) than those performed in the rectum (10.3% and 2.6%) or the left colon (13.8% and 5.2%; p = 0.016; p = 0.015), respectively. Conclusions: ESD for early colon cancer is a viable strategy due to its effectiveness and low complication rate. The ESD technique performed in the rectum yields the best results; however, in the right colon, it still requires careful attention.

Effect of optical diagnosis training on recognition and treatment of submucosal invasive colorectal cancer in community hospitals: a prospective multicenter intervention study

BACKGROUND

 Recognition of submucosal invasive colorectal cancer (T1 CRC) is difficult, with sensitivities of 35 %-60 % in Western countries. We evaluated the real-life effects of training in the OPTICAL model, a recently developed structured and validated prediction model, in Dutch community hospitals.

METHODS

 In this prospective multicenter study (OPTICAL II), 383 endoscopists from 40 hospitals were invited to follow an e-learning program on the OPTICAL model, to increase sensitivity in detecting T1 CRC in nonpedunculated polyps. Real-life recognition of T1 CRC was then evaluated in 25 hospitals. Endoscopic and pathologic reports of T1 CRCs detected during the next year were collected retrospectively, with endoscopists unaware of this evaluation. Sensitivity for T1 CRC recognition, R0 resection rate, and treatment modality were compared for trained vs. untrained endoscopists.

RESULTS

 1 year after e-learning, 528 nonpedunculated T1 CRCs were recorded for endoscopies performed by 251 endoscopists (118 [47 %] trained). Median T1 CRC size was 20 mm. Lesions were mainly located in the distal colorectum (66 %). Trained endoscopists recognized T1 CRCs more frequently than untrained endoscopists (sensitivity 74 % vs. 62 %; mixed model analysis odds ratio [OR] 2.90, 95 %CI 1.54-5.45). R0 resection rate was higher for T1 CRCs detected by trained endoscopists (69 % vs. 56 %; OR 1.73, 95 %CI 1.03-2.91).

CONCLUSION

 Training in optical recognition of T1 CRCs in community hospitals was associated with increased recognition of T1 CRCs, leading to higher en bloc and R0 resection rates. This may be an important step toward more organ-preserving strategies.

Role of the artificial intelligence in the management of T1 colorectal cancer

Approximately 10% of submucosal invasive (T1) colorectal cancers demonstrate extraintestinal lymph node metastasis, necessitating surgical intervention with lymph node dissection. The ability to identify T1b (submucosal invasion depth ≥ 1000 µm) as a risk factor for lymph node metastasis via pre-treatment endoscopy is crucial in guiding treatment strategies. Accurately distinguishing T1b from T1a (submucosal invasion depth < 1000 µm) or dysplasia remains a significant challenge for artificial intelligence (AI) systems, which require high and consistent diagnostic capabilities. Moreover, as endoscopic therapies like endoscopic full-thickness resection and endoscopic intermuscular dissection evolve, and the focus on reducing unnecessary surgeries intensifies, the initial management of T1 colorectal cancers via endoscopic treatment is anticipated to increase. Consequently, the development of highly accurate and reliable AI systems is essential, not only for pre-treatment depth assessment but also for post-treatment risk stratification of lymph node metastasis. While such AI diagnostic systems are still under development, significant advancements are expected in the near future to improve decision-making in T1 colorectal cancer management.

Substratifying the risk of covert malignancy in significant rectal polyps: Outcomes from a specialist multidisciplinary team (MDT)

AIM

A treatment strategy for patients with a significant polyp or early colon cancer (SPECC) of the rectum presents a challenge due to the significant rate of covert malignancy and lack of standardized assessment. For this reason, NICE recommends multidisciplinary meetings to improve outcomes. The primary aim of the present study was to report the performance of our specialist early rectal cancer (SERC) multidisciplinary team (MDT) in correctly substratifying the risk of cancer and to discuss the limitations of staging investigations in those patients with "poor outcomes".

METHOD

This was a retrospective review of patients referred to our SERC MDT from 2014 to 2019. Lesions were assigned by the MDT to three pre-resection categories (low, intermediate, high) according to the risk of covert malignancy. Resection method and final histology were compared to the pre-resection categories.

RESULTS

Of 350 SPECC lesions, 174 were assessed as low-risk, 108 intermediate-risk and 68 high-risk. The cancer incidence was 4.8%, 8.3% and 53%, respectively (15.5% overall). Eight lesions were categorized as low-risk but following piecemeal resection were found to be malignant. Five lesions, three of which were categorized as high-risk, were ultimately benign following conventional surgery. One pT1sm1 cancer, removed by anterior resection, may have been treated by local excision.

CONCLUSION

A total of 83% of malignant polyps were triaged to an en bloc resection technique and surgical resection avoided for nearly all benign lesions. However, 12 patients from this cohort were deemed to have a poor outcome because of miscategorization. Further comparative research is needed to establish the optimum strategy for rectal SPECC lesion assessment.

ORIGINALITY STATEMENT

There is currently no consensus for staging significant polyps of the rectum. This paper reports the effectiveness of a specialist early rectal cancer MDT to correctly risk-stratify significant rectal polyps. It underscores the importance of accurate categorization for treatment decision-making, while acknowledging the limitations of current staging modalities.

Whole slide image-based prediction of lymph node metastasis in T1 colorectal cancer using unsupervised artificial intelligence

OBJECTIVES

Lymph node metastasis (LNM) prediction for T1 colorectal cancer (CRC) is critical for determining the need for surgery after endoscopic resection because LNM occurs in 10%. We aimed to develop a novel artificial intelligence (AI) system using whole slide images (WSIs) to predict LNM.

METHODS

We conducted a retrospective single center study. To train and test the AI model, we included LNM status-confirmed T1 and T2 CRC between April 2001 and October 2021. These lesions were divided into two cohorts: training (T1 and T2) and testing (T1). WSIs were cropped into small patches and clustered by unsupervised K-means. The percentage of patches belonging to each cluster was calculated from each WSI. Each cluster's percentage, sex, and tumor location were extracted and learned using the random forest algorithm. We calculated the areas under the receiver operating characteristic curves (AUCs) to identify the LNM and the rate of over-surgery of the AI model and the guidelines.

RESULTS

The training cohort contained 217 T1 and 268 T2 CRCs, while 100 T1 cases (LNM-positivity 15%) were the test cohort. The AUC of the AI system for the test cohort was 0.74 (95% confidence interval [CI] 0.58-0.86), and 0.52 (95% CI 0.50-0.55) using the guidelines criteria (P = 0.0028). This AI model could reduce the 21% of over-surgery compared to the guidelines.

CONCLUSION

We developed a pathologist-independent predictive model for LNM in T1 CRC using WSI for determination of the need for surgery after endoscopic resection.

TRIAL REGISTRATION

UMIN Clinical Trials Registry (UMIN000046992, https://center6.umin.ac.jp/cgi-open-bin/ctr/ctr_view.cgi?recptno=R000053590).

CT morphological features for predicting the risk of lymph node metastasis in T1 colorectal cancer

OBJECTIVES

The aim of this study is to evaluate the feasibility of clinicopathological characteristics and computed tomography (CT) morphological features in predicting lymph node metastasis (LNM) for patients with T1 colorectal cancer (CRC).

METHODS

A total of 144 patients with T1 CRC who underwent CT scans and surgical resection were retrospectively included in our study. The clinicopathological characteristics and CT morphological features were assessed by two observers. Univariate and multiple logistic regression analyses were used to identify significant LNM predictive variables. Then a model was developed using the independent predictive factors. The predictive model was subjected to bootstrapping validation (1000 bootstrap resamples) to calculate the calibration curve and relative C-index.

RESULTS

LNM were found in 30/144 patients (20.83%). Four independent risk factors were determined in the multiple logistic regression analysis, including presence of necrosis (adjusted odds ratio [OR] = 10.32, 95% confidence interval [CI] 1.96-54.3, p = 0.004), irregular outer border (adjusted OR = 5.94, 95% CI 1.39-25.45, p = 0.035), and heterogeneity enhancement (adjusted OR = 7.35, 95% CI 3.11-17.38, p = 0.007), as well as tumor location (adjusted ORright-sided colon = 0.05 [0.01-0.60], p = 0.018; adjusted ORrectum = 0.22 [0.06-0.83], p = 0.026). In the internal validation cohort, the model showed good calibration and good discrimination with a C-index of 0.89.

CONCLUSIONS

There are significant associations between lymphatic metastasis status and tumor location as well as CT morphologic features in T1 CRC, which could help the doctor make decisions for additional surgery after endoscopic resection.

KEY POINTS

• LNM more frequently occurs in left-sided T1 colon cancer than in right-sided T1 colon and rectal cancer. • CT morphologic features are risk factors for LNM of T1 CRC, which may be related to fundamental biological behaviors. • The combination of tumor location and CT morphologic features can more effectively assist in predicting LNM in patients with T1 CRC, and decrease the rate of unnecessary extra surgeries after endoscopic resection.

pT1 colorectal cancer: A treatment dilemma

The implementation of population screening programs for colorectal cancer (CRC) has led to a considerable increase in the prevalence pT1-CRC originating on polyps amenable by local treatments. However, a high proportion of patients are referred for unnecessary oncological surgeries without a clear benefit in terms of survival. Selecting the appropriate endoscopic resection technique in the moment of diagnosis becomes crucial to provide the best treatment alternative to each individual polyp and patient. For this, it is imperative to increase the optical diagnostic skill for differentiating pT1-CRCs and decide the appropriate initial therapy. En bloc resection is crucial to obtain an adequate histological specimen that might allow organ preserving therapeutic management. In this review, we address key challenges in T1 CRC management, explore the efficacy and safety of the available diagnostic and therapeutic approaches, and shed light on upcoming advances in the field.

Diagnostic Value of Adding Magnifying Chromoendoscopy to Magnifying Narrow-Band Imaging Endoscopy for Colorectal Polyps

BACKGROUND & AIMS

This study examined the additional value of magnifying chromoendoscopy (MCE) on magnifying narrow-band imaging endoscopy (M-NBI) in the optical diagnosis of colorectal polyps.

METHODS

A multicenter prospective study was conducted at 9 facilities in Japan and Germany. Patients with colorectal polyps scheduled for resection were included. Optical diagnosis was performed by M-NBI first, followed by MCE. Both diagnoses were made in real time. MCE was performed on all type 2B lesions classified according to the Japan NBI Expert Team classification and other lesions at the discretion of endoscopists. The diagnostic accuracy and confidence of M-NBI and MCE for colorectal cancer (CRC) with deep invasion (≥T1b) were compared on the basis of histologic findings after resection.

RESULTS

In total, 1173 lesions were included between February 2018 and December 2020, with 654 (5 hyperplastic polyp/sessile serrated lesion, 162 low-grade dysplasia, 403 high-grade dysplasia, 97 T1 CRCs, and 32 ≥T2 CRCs) examined using MCE after M-NBI. In the diagnostic accuracy for predicting CRC with deep invasion, sensitivity, specificity, positive predictive value, negative predictive value, and accuracy for M-NBI were 63.1%, 94.2%, 61.6%, 94.5%, and 90.2%, respectively, and for MCE they were 77.4%, 93.2%, 62.5%, 96.5%, and 91.1%, respectively. The sensitivity was significantly higher in MCE (P < .001). However, these additional values were limited to lesions with low confidence in M-NBI or the ones diagnosed as ≥T1b CRC by M-NBI.

CONCLUSIONS

In this multicenter prospective study, we demonstrated the additional value of MCE on M-NBI. We suggest that additional MCE be recommended for lesions with low confidence or the ones diagnosed as ≥T1b CRC. Trials registry number: UMIN000031129.

Comprehensive review of publicly available colonoscopic imaging databases for artificial intelligence research: availability, accessibility, and usability

BACKGROUND AND AIMS

Publicly available databases containing colonoscopic imaging data are valuable resources for artificial intelligence (AI) research. Currently, little is known regarding the available number and content of these databases. This review aimed to describe the availability, accessibility, and usability of publicly available colonoscopic imaging databases, focusing on polyp detection, polyp characterization, and quality of colonoscopy.

METHODS

A systematic literature search was performed in MEDLINE and Embase to identify AI studies describing publicly available colonoscopic imaging databases published after 2010. Second, a targeted search using Google's Dataset Search, Google Search, GitHub, and Figshare was done to identify databases directly. Databases were included if they contained data about polyp detection, polyp characterization, or quality of colonoscopy. To assess accessibility of databases, the following categories were defined: open access, open access with barriers, and regulated access. To assess the potential usability of the included databases, essential details of each database were extracted using a checklist derived from the Checklist for Artificial Intelligence in Medical Imaging.

RESULTS

We identified 22 databases with open access, 3 databases with open access with barriers, and 15 databases with regulated access. The 22 open access databases contained 19,463 images and 952 videos. Nineteen of these databases focused on polyp detection, localization, and/or segmentation; 6 on polyp characterization, and 3 on quality of colonoscopy. Only half of these databases have been used by other researcher to develop, train, or benchmark their AI system. Although technical details were in general well reported, important details such as polyp and patient demographics and the annotation process were under-reported in almost all databases.

CONCLUSIONS

This review provides greater insight on public availability of colonoscopic imaging databases for AI research. Incomplete reporting of important details limits the ability of researchers to assess the usability of current databases.

Long-term oncological outcomes of endoscopic full-thickness resection after previous incomplete resection of low-risk T1 CRC (LOCAL-study): study protocol of a national prospective cohort study

BACKGROUND

T1 colorectal cancer (CRC) without histological high-risk factors for lymph node metastasis (LNM) can potentially be cured by endoscopic resection, which is associated with significantly lower morbidity, mortality and costs compared to radical surgery. An important prerequisite for endoscopic resection as definite treatment is the histological confirmation of tumour-free resection margins. Incomplete resection with involved (R1) or indeterminate (Rx) margins is considered a strong risk factor for residual disease and local recurrence. Therefore, international guidelines recommend additional surgery in case of R1/Rx resection, even in absence of high-risk factors for LNM. Endoscopic full-thickness resection (eFTR) is a relatively new technique that allows transmural resection of colorectal lesions. Local scar excision after prior R1/Rx resection of low-risk T1 CRC could offer an attractive minimal invasive strategy to achieve confirmation about radicality of the previous resection or a second attempt for radical resection of residual luminal cancer. However, oncologic safety has not been established and long-term data are lacking. Besides, surveillance varies widely and requires standardization.

METHODS/DESIGN

In this nationwide, multicenter, prospective cohort study we aim to assess feasibility and oncological safety of completion eFTR following incomplete resection of low-risk T1 CRC. The primary endpoint is to assess the 2 and 5 year luminal local tumor recurrence rate. Secondary study endpoints are to assess feasibility, percentage of curative eFTR-resections, presence of scar tissue and/or complete scar excision at histopathology, safety of eFTR compared to surgery, 2 and 5 year nodal and/or distant tumor recurrence rate and 5-year disease-specific and overall-survival rate.

DISCUSSION

Since the implementation of CRC screening programs, the diagnostic rate of T1 CRC is steadily increasing. A significant proportion is not recognized as cancer before endoscopic resection and is therefore resected through conventional techniques primarily reserved for benign polyps. As such, precise histological assessment is often hampered due to cauterization and fragmentation and frequently leads to treatment dilemmas. This first prospective trial will potentially demonstrate the effectiveness and oncological safety of completion eFTR for patients who have undergone a previous incomplete T1 CRC resection. Hereby, substantial surgical overtreatment may be avoided, leading to treatment optimization and organ preservation. Trial registration Nederlands Trial Register, NL 7879, 16 July 2019 ( https://trialregister.nl/trial/7879 ).

Multidisciplinary Treatment Strategy for Early Colon Cancer: A Review-An English Version

Treatment for early colon cancer has progressed rapidly, with endoscopic resection and minimally invasive surgery. It is important to select patients without risk of lymph node metastasis before deciding on endoscopic resection for early colon cancer treatment. Pathological risk factors include histologic grade of cancer cell differentiation, lymphovascular invasion, perineural invasion, tumor budding, and deep submucosal invasion. These risk factors for predicting lymph node metastasis are crucial for determining the treatment strategy of endoscopic excision and radical resection for early colon cancer. A multidisciplinary approach is emphasized to establish a treatment strategy for early colon cancer to minimize the risk of complications and obtain excellent oncologic outcomes by selecting an appropriate treatment optimized for the patient's stage and condition. Therefore, we aimed to review the optimal multidisciplinary treatment strategies, including endoscopy and surgery, for early colon cancer.

Multidisciplinary treatment strategy for early colon cancer

Background: Treatment for early colon cancer has progressed rapidly with endoscopic resection and minimally invasive surgery. Selection of patients without risk of lymph node metastasis is necessary before deciding on endoscopic resection for early colon cancer treatment. We aimed to review the optimal multidisciplinary treatment strategies for early colon cancer, including endoscopy and surgery.Current Concepts: Pathological risk factors include histologic grade of cancer cell differentiation, lymphovascular invasion, perineural invasion, tumor budding, and deep submucosal invasion. These risk factors for predicting lymph node metastasis are crucial for determining the treatment strategy of endoscopic excision and radical resection for early colon cancer. Prediction of the depth of invasion in early colon cancer using endoscopic optical assessments is vital to determine the appropriate treatment method for endoscopic or surgical resection. Furthermore, optical assessment of pit and vascular patterns is useful for estimating the depth of submucosal invasion using magnifying chromoendoscopy and narrow-band imaging endoscopy. Performing an endoscopic and pathologic evaluation of the risk factors for lymph node metastasis is imperative when selecting endoscopic or surgical resection. Endoscopic treatments include cold snare polypectomy, endoscopic mucosal resection, and endoscopic submucosal dissection. In addition, appropriate surgical treatment should be recommended for patients with early colon cancer with a high risk of lymph node metastasis.Discussion and Conclusion: A multidisciplinary approach should be recommended to establish an optimized treatment strategy, minimize the risk of complications, and obtain excellent oncologic outcomes via patienttailored treatment in patients with early colon cancer.

New method for real-time visualization and quantitative characterization of early colorectal cancer in endoscopy: a pilot study

Background and study aims  Endoscopic optical diagnosis is crucial to the therapeutic strategy for early gastrointestinal cancer. It accurately (> 85 %) predicts pT category based on microsurface (SP) and vascular patterns (VP). However, interobserver variability is a major problem. We have visualized and digitalized the graded irregularities based on bioinformatically enhanced quantitative endoscopic image analysis (BEE) of high-definition white-light images. Methods  In a pilot study of 26 large colorectal lesions (LCLs, mean diameter 39 mm), we retrospectively compared BEE variables with corresponding histopathology of the resected LCLs. Results  We included 10 adenomas with low-grade intraepithelial neoplasia (LGIN), nine with high-grade intraepithelial neoplasia (HGIN) and early adenocarcinoma (EAC), and seven deeply submucosal invasive carcinomas. Quantified density (d) and nonuniformity (C _U ) of vascular and surface structures correlated with histology (r _s d VP: -0.77, r _s C _U VP: 0.13, r _s d SP: -0.76, and r _s C _U SP: 0.45, respectively). A computed BEE score showed a sensitivity and specificity of 90 % and 100 % in the group with LGINs, 89 % and 41 % in the group with HGINs and EACs, and 100 % and 95 % in the group with deeply invasive carcinoma, respectively. Conclusions  In this pilot study, BEE showed promise as a tool for endoscopic characterization of LCLs during routine endoscopy. Prospective clinical studies are needed.

Setting up a regional expert panel for complex colorectal polyps

BACKGROUND AND AIMS

Advanced endoscopic resection techniques for complex colorectal polyps have evolved significantly over the past decade, leading to a management shift from surgical to endoscopic resection as the preferred treatment. However, in practice, interhospital consultation and appropriate referral management remain challenging, leading to unnecessary surgical resections. To support regional care for patients with complex colorectal polyps, facilitate peer consultations, and lower thresholds for referrals, an expert panel consultation platform was initiated in the northwestern region of the Netherlands.

METHODS

We initiated a regional expert panel in the northwestern region of the Netherlands for patients with complex colorectal polyps and studied the implementation, adaption, and clinical impact. All panel consultations between June 2019 and May 2021 were retrospectively analyzed, and user satisfaction among panel members was evaluated.

RESULTS

Eighty-eight patients with complex colorectal polyps from 11 of 15 participating centers (73.3%) were discussed in our panel. The most common reason for panel consultation was suspicion of invasive cancer in 36.4% (n = 32). After panel consultation, 43.2% of the consulting endoscopists (n = 38) changed their initial treatment strategy, and in 63.6% (n = 56) patients were referred to another endoscopy center. Of 26 cases submitted with a primary proposal for surgical treatment, surgery was avoided in 7 (26.9%). User satisfaction was rated high in most participating centers (91.7%).

CONCLUSIONS

Our study shows that implementation of and consultation with a regional expert panel can be a valuable tool for endoscopists to guide and optimize treatment of complex colorectal polyps and facilitate interhospital referrals in a regional network.

Endoscopic full-thickness resection of T1 colorectal cancers: a retrospective analysis from a multicenter Dutch eFTR registry

BACKGROUND

Complete endoscopic resection and accurate histological evaluation for T1 colorectal cancer (CRC) are critical in determining subsequent treatment. Endoscopic full-thickness resection (eFTR) is a new treatment option for T1 CRC < 2 cm. We aimed to report clinical outcomes and short-term results.

METHODS

Consecutive eFTR procedures for T1 CRC, prospectively recorded in our national registry between November 2015 and April 2020, were retrospectively analyzed. Primary outcomes were technical success and R0 resection. Secondary outcomes were histological risk assessment, curative resection, adverse events, and short-term outcomes.

RESULTS

We included 330 procedures: 132 primary resections and 198 secondary scar resections after incomplete T1 CRC resection. Overall technical success, R0 resection, and curative resection rates were 87.0 % (95 % confidence interval [CI] 82.7 %-90.3 %), 85.6 % (95 %CI 81.2 %-89.2 %), and 60.3 % (95 %CI 54.7 %-65.7 %). Curative resection rate was 23.7 % (95 %CI 15.9 %-33.6 %) for primary resection of T1 CRC and 60.8 % (95 %CI 50.4 %-70.4 %) after excluding deep submucosal invasion as a risk factor. Risk stratification was possible in 99.3 %. The severe adverse event rate was 2.2 %. Additional oncological surgery was performed in 49/320 (15.3 %), with residual cancer in 11/49 (22.4 %). Endoscopic follow-up was available in 200/242 (82.6 %), with a median of 4 months and residual cancer in 1 (0.5 %) following an incomplete resection.

CONCLUSIONS

eFTR is relatively safe and effective for resection of small T1 CRC, both as primary and secondary treatment. eFTR can expand endoscopic treatment options for T1 CRC and could help to reduce surgical overtreatment. Future studies should focus on long-term outcomes.

Practical Perfusion Quantification in Multispectral Endoscopic Video: Using the Minutes after ICG Administration to Assess Tissue Pathology

The wide availability of near infrared light sources in interventional medical imaging stacks enables non-invasive quantification of perfusion by using fluorescent dyes, typically Indocyanine Green (ICG). Due to their often leaky and chaotic vasculatures, intravenously administered ICG perfuses through cancerous tissues differently. We investigate here how a few characteristic values derived from the time series of fluorescence can be used in simple machine learning algorithms to distinguish benign lesions from cancers. These features capture the initial uptake of ICG in the colon, its peak fluorescence, and its early wash-out. By using simple, explainable algorithms we demonstrate, in clinical cases, that sensitivity (specificity) rates of over 95% (95%) for cancer classification can be achieved.

Clinicopathological features of small T1 colorectal cancers

BACKGROUND

Although small colorectal neoplasms (< 10 mm) are often easily resected endoscopically and are considered to have less malignant potential compared with large neoplasms (≥ 10 mm), some are invasive to the submucosa.

AIM

To clarify the clinicopathological features of small T1 colorectal cancers.

METHODS

Of 32025 colorectal lesions between April 2001 and March 2018, a total of 1152 T1 colorectal cancers resected endoscopically or surgically were included in this study and were divided into two groups by tumor size: a small group (< 10 mm) and a large group (≥ 10 mm). We compared clinicopathological factors including lymph node metastasis (LNM) between the two groups.

RESULTS

The incidence of small T1 cancers was 10.1% (116/1152). The percentage of initial endoscopic treatment in small group was significantly higher than in large group (< 10 mm 74.1% vs ≥ 10 mm 60.2%, P < 0.01). In the surgical resection cohort (n = 798), the rate of LNM did not significantly differ between the two groups (small 12.3% vs large 10.9%, P = 0.70). In addition, there were also no significant differences between the two groups in pathological factors such as histological grade, vascular invasion, or lymphatic invasion.

CONCLUSION

Because there was no significant difference in the rate of LNM between small and large T1 colorectal cancers, the requirement for additional surgical resection should be determined according to pathological findings, regardless of tumor size.

Management of large polyps in a colorectal cancer screening program with fecal immunochemical test: a community- and population-based observational study

Background and study aims  The aim of this study was to analyze presentation, management, and outcomes of large polyps (LPs; ≥ 20 mm) detected in a colorectal cancer (CRC) screening program using a quantitative fecal immunochemical test (FIT). Patients and methods  This was a retrospective community- and population-based observational study of all LPs detected in patients aged 50 to 74 years between 2015 and 2019 during FIT-positive colonoscopies within the screening program organized in Alsace (France). Results  Among 13,633 FIT-positive colonoscopies, 1256 LPs (8.5 % malignant and 51.8 % nonpedunculated) were detected by 102 community gastroenterologists in 1164 patients (one in 12 colonoscopies). The sensitivity of optical diagnosis of malignancy was 54 % for nonpedunculated and 27 % for pedunculated T1 CRCs. The endoscopic resection rate was 82.7 % (95 % confidence interval [CI] 80.3-84.9) for benign LPs (70.2 % [95 % CI 66.4-74.1]) nonpedunculated, 95.2 % [95 % CI 93.4-97.1] pedunculated), varying from 0 to 100 % depending on the endoscopist. It was correlated with cecal intubation (Pearson r  = 0.49, P  < 0.01) and adenoma detection rates ( r  = 0.25, P  = 0.01). Most endoscopists did not refer patients to more experienced endoscopists, and as a result, 60 % to 90 % of 183 surgeries for benign LPs were unwarranted. Endoscopic resection was curative for 4.3 % (95 % CI 0.9-12.0) of nonpedunculated and 37.8 % (95 % CI 22.5-55.2) of pedunculated T1 CRCs. Overall, 22 endoscopic submucosal dissections had to be performed to avoid one surgery. Conclusions  Compared with current recommendations, there is tremendous room for improvement in community endoscopy practices in the diagnosis and management of LPs. Detection and polypectomy competencies are correlated and highly variable among endoscopists. Endoscopic resection is curative for 83 % of benign LPs and 16 % of T1 CRCs.

Compound Endoscopic Morphological Features for Identifying Non-Pedunculated Lesions ≥20 mm with Intramucosal Neoplasia

BACKGROUND

The major limitation of piecemeal endoscopic mucosal resection (EMR) is the inaccurate histological assessment of the resected specimen, especially in cases of submucosal invasion.

OBJECTIVE

To classify non-pedunculated lesions ≥20 mm based on endoscopic morphological features, in order to identify those that present intramucosal neoplasia (includes low-grade neoplasia and high-grade neoplasia) and are suitable for piecemeal EMR.

DESIGN

A post-hoc analysis from an observational prospective multicentre study conducted by 58 endoscopists at 17 academic and community hospitals was performed. Unbiased conditional inference trees (CTREE) were fitted to analyse the association between intramucosal neoplasia and the lesions' endoscopic characteristics.

RESULT

542 lesions from 517 patients were included in the analysis. Intramucosal neoplasia was present in 484 of 542 (89.3%) lesions. A conditional inference tree including all lesions' characteristics assessed with white light imaging and narrow-band imaging (NBI) found that ulceration, pseudodepressed type and sessile morphology changed the accuracy for predicting intramucosal neoplasia. In ulcerated lesions, the probability of intramucosal neoplasia was 25% (95%CI: 8.3-52.6%; p < 0.001). In non-ulcerated lesions, its probability in lateral spreading lesions (LST) non-granular (NG) pseudodepressed-type lesions rose to 64.0% (95%CI: 42.6-81.3%; p < 0.001). Sessile morphology also raised the probability of intramucosal neoplasia to 86.3% (95%CI: 80.2-90.7%; p < 0.001). In the remaining 319 (58.9%) non-ulcerated lesions that were of the LST-granular (G) homogeneous type, LST-G nodular-mixed type, and LST-NG flat elevated morphology, the probability of intramucosal neoplasia was 96.2% (95%CI: 93.5-97.8%; p < 0.001).

CONCLUSION

Non-ulcerated LST-G type and LST-NG flat elevated lesions are the most common non-pedunculated lesions ≥20 mm and are associated with a high probability of intramucosal neoplasia. This means that they are good candidates for piecemeal EMR. In the remaining lesions, further diagnostic techniques like magnification or diagnostic +/- therapeutic endoscopic submucosal dissection should be considered.

A Liquid Biopsy Assay for Noninvasive Identification of Lymph Node Metastases in T1 Colorectal Cancer

BACKGROUND & AIMS

We recently reported use of tissue-based transcriptomic biomarkers (microRNA [miRNA] or messenger RNA [mRNA]) for identification of lymph node metastasis (LNM) in patients with invasive submucosal colorectal cancers (T1 CRC). In this study, we translated our tissue-based biomarkers into a blood-based liquid biopsy assay for noninvasive detection of LNM in patients with high-risk T1 CRC.

METHODS

We analyzed 330 specimens from patients with high-risk T1 CRC, which included 188 serum samples from 2 clinical cohorts-a training cohort (N = 46) and a validation cohort (N = 142)-and matched formalin-fixed paraffin-embedded samples (N = 142). We performed quantitative reverse-transcription polymerase chain reaction, followed by logistic regression analysis, to develop an integrated transcriptomic panel and establish a risk-stratification model combined with clinical risk factors.

RESULTS

We used comprehensive expression profiling of a training cohort of LNM-positive and LMN-negative serum specimens to identify an optimized transcriptomic panel of 4 miRNAs (miR-181b, miR-193b, miR-195, and miR-411) and 5 mRNAs (AMT, forkhead box A1 [FOXA1], polymeric immunoglobulin receptor [PIGR], matrix metalloproteinase 1 [MMP1], and matrix metalloproteinase 9 [MMP9]), which robustly identified patients with LNM (area under the curve [AUC], 0.86; 95% confidence interval [CI], 0.72-0.94). We validated panel performance in an independent validation cohort (AUC, 0.82; 95% CI, 0.74-0.88). Our risk-stratification model was more accurate than the panel and an independent predictor for identification of LNM (AUC, 0.90; univariate: odds ratio [OR], 37.17; 95% CI, 4.48-308.35; P < .001; multivariate: OR, 17.28; 95% CI, 1.82-164.07; P = .013). The model limited potential overtreatment to only 18% of all patients, which is dramatically superior to pathologic features that are currently used (92%).

CONCLUSIONS

A novel risk-stratification model for noninvasive identification of T1 CRC has the potential to avoid unnecessary operations for patients classified as high-risk by conventional risk-classification criteria.

Artificial intelligence-assisted colonic endocytoscopy for cancer recognition: a multicenter study

Background and study aims  Large adenomas are sometimes misidentified as cancers during colonoscopy and are surgically removed. To address this overtreatment, we developed an artificial intelligence (AI) tool that identified cancerous pathology in vivo with high specificity. We evaluated our AI tool under the supervision of a government agency to obtain regulatory approval. Patients and methods  The AI tool outputted three pathological class predictions (cancer, adenoma, or non-neoplastic) for endocytoscopic images obtained at 520-fold magnification and previously trained on 68,082 images from six academic centers. A validation test was developed, employing 500 endocytoscopic images taken from various parts of randomly selected 50 large (≥ 20 mm) colorectal lesions (10 images per lesion). An expert board labelled each of the 500 images with a histopathological diagnosis, which was made using endoscopic and histopathological images. The validation test was performed using the AI tool under a controlled environment. The primary outcome measure was the specificity in identifying cancer. Results  The validation test consisted of 30 cancers, 15 adenomas, and five non-neoplastic lesions. The AI tool could analyze 83.6 % of the images (418/500): 231 cancers, 152 adenomas, and 35 non-neoplastic lesions. Among the analyzable images, the AI tool identified the three pathological classes with an overall accuracy of 91.9 % (384/418, 95 % confidence interval [CI]: 88.8 %-94.3 %). Its sensitivity and specificity for differentiating cancer was 91.8 % (212/231, 95 % CI: 87.5 %-95.0 %) and 97.3 % (182/187, 95 % CI: 93.9 %-99.1 %), respectively. Conclusions  The newly developed AI system designed for endocytoscopy showed excellent specificity in identifying colorectal cancer.

Systematic Review on Optical Diagnosis of Early Gastrointestinal Neoplasia

BACKGROUND

Meticulous endoscopic characterization of gastrointestinal neoplasias (GN) is crucial to the clinical outcome. Hereby the indication and type of resection (endoscopically, en-bloc or piece-meal, or surgical resection) are determined. By means of established image-enhanced (IEE) and magnification endoscopy (ME) GN can be characterized in terms of malignancy and invasion depth. In this context, the statistical evidence and accuracy of these diagnostic procedures should be elucidated. Here, we present a systematic review of the literature.

RESULTS

21 Studies could be found which met the inclusion criteria. In clinical prospective trials and meta-analyses, the diagnostic accuracy of >90% for characterization of malignant neoplasms could be documented, if ME with IEE was used in squamous cell esophageal cancer, stomach, or colonic GN.

CONCLUSIONS

Currently, by means of optical diagnosis, today's gastrointestinal endoscopy is capable of determining the histological subtype, exact lateral spread, and depth of invasion of a lesion. The prerequisites for this are an exact knowledge of the anatomical structures, the endoscopic classifications based on them, and a systematic learning process, which can be supported by training courses. More prospective clinical studies are required, especially in the field of Barrett's esophagus and duodenal neoplasia.

Curriculum for optical diagnosis training in Europe: European Society of Gastrointestinal Endoscopy (ESGE) Position Statement

This manuscript represents an official Position Statement of the European Society of Gastrointestinal Endoscopy (ESGE) aiming to guide general gastroenterologists to develop and maintain skills in optical diagnosis during endoscopy. In general, this requires additional training beyond the core curriculum currently provided in each country. In this context, ESGE have developed a European core curriculum for optical diagnosis practice across Europe for high quality optical diagnosis training. 1:  ESGE suggests that every endoscopist should have achieved general competence in upper and/or lower gastrointestinal (UGI/LGI) endoscopy before commencing training in optical diagnosis of the UGI/LGI tract, meaning personal experience of at least 300 UGI and/or 300 LGI endoscopies and meeting the ESGE quality measures for UGI/LGI endoscopy. ESGE suggests that every endoscopist should be able and competent to perform UGI/LGI endoscopy with high definition white light combined with virtual and/or dye-based chromoendoscopy before commencing training in optical diagnosis. 2:  ESGE suggests competency in optical diagnosis can be learned by attending a validated optical diagnosis training course based on a validated classification, and self-learning with a minimum number of lesions. If no validated training course is available, optical diagnosis can only be learned by attending a non-validated onsite training course and self-learning with a minimum number of lesions. 3:  ESGE suggests endoscopists are competent in optical diagnosis after meeting the pre-adoption and learning criteria, and meeting competence thresholds by assessing a minimum number of lesions prospectively during real-time endoscopy. ESGE suggests ongoing in vivo practice by endoscopists to maintain competence in optical diagnosis. If a competent endoscopist does not perform in vivo optical diagnosis on a regular basis, ESGE suggests repeating the learning and competence phases to maintain competence.Key areas of interest were optical diagnosis training in Barrett's esophagus, esophageal squamous cell carcinoma, early gastric cancer, diminutive colorectal lesions, early colorectal cancer, and neoplasia in inflammatory bowel disease. Condition-specific recommendations are provided in the main document.