The endocytoscopic classification was particularly useful for differentiating between neoplastic and nonneoplastic lesions and between "SMm or worse" and other neoplastic lesions, which in the case of colorectal neoplasms would help to determine treatment.

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These preliminary results suggest that incorporating endocytoscopy facilities into a standard endoscope may be helpful in characterizing tissue in a variety of esophageal lesions. The potential clinical impact of this method in relation to other gastrointestinal organs requires further study.

Background and study aims Decisions concerning additional surgery after endoscopic resection of T1 colorectal cancer (CRC) are difficult because preoperative prediction of lymph node metastasis (LNM) is problematic. We investigated whether artificial intelligence can predict LNM presence, thus minimizing the need for additional surgery. Patients and methods Data on 690 consecutive patients with T1 CRCs that were surgically resected in 2001 – 2016 were retrospectively analyzed. We divided patients into two groups according to date: data from 590 patients were used for machine learning for the artificial intelligence model, and the remaining 100 patients were included for model validation. The artificial intelligence model analyzed 45 clinicopathological factors and then predicted positivity or negativity for LNM. Operative specimens were used as the gold standard for the presence of LNM. The artificial intelligence model was validated by calculating the sensitivity, specificity, and accuracy for predicting LNM, and comparing these data with those of the American, European, and Japanese guidelines. Results Sensitivity was 100 % (95 % confidence interval [CI] 72 % to 100 %) in all models. Specificity of the artificial intelligence model and the American, European, and Japanese guidelines was 66 % (95 %CI 56 % to 76 %), 44 % (95 %CI 34 % to 55 %), 0 % (95 %CI 0 % to 3 %), and 0 % (95 %CI 0 % to 3 %), respectively; and accuracy was 69 % (95 %CI 59 % to 78 %), 49 % (95 %CI 39 % to 59 %), 9 % (95 %CI 4 % to 16 %), and 9 % (95 %CI 4 % – 16 %), respectively. The rates of unnecessary additional surgery attributable to misdiagnosing LNM-negative patients as having LNM were: 77 % (95 %CI 62 % to 89 %) for the artificial intelligence model, and 85 % (95 %CI 73 % to 93 %; P < 0.001), 91 % (95 %CI 84 % to 96 %; P < 0.001), and 91 % (95 %CI 84 % to 96 %; P < 0.001) for the American, European, and Japanese guidelines, respectively. Conclusions Compared with current guidelines, artificial intelligence significantly reduced unnecessary additional surgery after endoscopic resection of T1 CRC without missing LNM positivity.

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Background and Aim: Recent advances in endoscopic technology have allowed many T1 colorectal carcinomas to be resected endoscopically with negative margins. However, the criteria for curative endoscopic resection remain unclear. We aimed to identify risk factors for nodal metastasis in T1 carcinoma patients and hence establish the indication for additional surgery with lymph node dissection. Methods: Initial or additional surgery with nodal dissection was performed in 653 T1 carcinoma cases. Clinicopathological factors were retrospectively analyzed with respect to nodal metastasis. The status of the muscularis mucosae (MM grade) was defined as grade 1 (maintenance) or grade 2 (fragmentation or disappearance). The lesions were then stratified based on the risk of nodal metastasis. Results: Muscularis mucosae grade was associated with nodal metastasis (P = 0.026), and no patients with MM grade 1 lesions had nodal metastasis. Significant risk factors for nodal metastasis in patients with MM grade 2 lesions were attribution of women (P = 0.006), lymphovascular infiltration (P < 0.001), tumor budding (P = 0.045), and poorly differentiated adenocarcinoma or mucinous carcinoma (P = 0.007). Nodal metastasis occurred in 1.06% of lesions without any of these pathological factors, but in 10.3% and 20.1% of lesions with at least one factor in male and female patients, respectively. There was good inter-observer agreement for MM grade evaluation, with a kappa value of 0.67. Conclusions: Stratification using MM grade, pathological factors, and patient sex provided more appropriate indication for additional surgery with lymph node dissection after endoscopic treatment for T1 colorectal carcinomas.

Both NBI and chromoendoscopy can be useful for distinguishing between neoplastic and non-neoplastic lesions. In the diagnosis of submucosal cancer, pit pattern diagnosis was slightly superior to vascular pattern diagnosis. It is desirable to perform chromoendoscopy in addition to NBI for distinguishing between slightly and massively invasive submucosal cancer lesions and determining the treatment.

Endocytoscopy is noninferior to standard biopsy for the discrimination of neoplastic lesions. With its advantage of providing an on-site diagnosis, endocytoscopy could provide a novel alternative to standard biopsy in routine colonoscopy.