Risk factors for lymph node metastasis in T2 colorectal cancer: a systematic review and meta-analysis.

BACKGROUND: Lymph node metastasis (LNM) occurs in 20-25% of patients with T2 colorectal cancer (CRC). Identification of risk factors for LNM in T2 CRC may help identify patients who are at low risk and thereby potential candidates for endoscopic full-thickness resection. We examined risk factors for LNM in T2 CRC with the goal of establishing further criteria of the indications for endoscopic resection. METHODS: MEDLINE, CENTRAL, and EMBASE were systematically searched from inception to November 2023. Studies that investigated the association between the presence of LNM and the clinical and pathological factors of T2 CRC were included. Odds ratios (ORs) and 95% confidence intervals (CIs) were calculated. Certainty of evidence (CoE) was assessed using the GRADE approach. RESULTS: Fourteen studies (8349 patients) were included. Overall, the proportion of LNM was 22%. The meta-analysis revealed that the presence of lymphovascular invasion (OR, 5.5; 95% CI 3.7-8.3; high CoE), high-grade tumor budding (OR, 2.4; 95% CI 1.5-3.7; moderate CoE), poor differentiation (OR, 2.2; 95% CI 1.8-2.7; moderate CoE), and female sex (OR, 1.3; 95% CI 1.1-1.7; high CoE) were associated with LNM in T2 CRC. Lymphatic invasion (OR, 5.0; 95% CI 3.3-7.6) was a stronger predictor of LNM than vascular invasion (OR, 2.4; 95% CI 2.1-2.8). CONCLUSIONS: Lymphovascular invasion, high-grade tumor budding, poor differentiation, and female sex were risk factors for LNM in T2 CRC. Endoscopic resection of T2 CRC in patients with very low risk for LNM may become an alternative to conventional surgical resection. TRIAL REGISTRATION: PROSPERO, CRD42022316545.

Computer-Aided Diagnosis for Leaving Colorectal Polyps In Situ : A Systematic Review and Meta-analysis.

BACKGROUND: Computer-aided diagnosis (CADx) allows prediction of polyp histology during colonoscopy, which may reduce unnecessary removal of nonneoplastic polyps. However, the potential benefits and harms of CADx are still unclear. PURPOSE: To quantify the benefit and harm of using CADx in colonoscopy for the optical diagnosis of small (≤5-mm) rectosigmoid polyps. DATA SOURCES: Medline, Embase, and Scopus were searched for articles published before 22 December 2023. STUDY SELECTION: Histologically verified diagnostic accuracy studies that evaluated the real-time performance of physicians in predicting neoplastic change of small rectosigmoid polyps without or with CADx assistance during colonoscopy. DATA EXTRACTION: The clinical benefit and harm were estimated on the basis of accuracy values of the endoscopist before and after CADx assistance. The certainty of evidence was assessed using the GRADE (Grading of Recommendations Assessment, Development and Evaluation) framework. The outcome measure for benefit was the proportion of polyps predicted to be nonneoplastic that would avoid removal with the use of CADx. The outcome measure for harm was the proportion of neoplastic polyps that would be not resected and left in situ due to an incorrect diagnosis with the use of CADx. Histology served as the reference standard for both outcomes. DATA SYNTHESIS: Ten studies, including 3620 patients with 4103 small rectosigmoid polyps, were analyzed. The studies that assessed the performance of CADx alone (9 studies; 3237 polyps) showed a sensitivity of 87.3% (95% CI, 79.2% to 92.5%) and specificity of 88.9% (CI, 81.7% to 93.5%) in predicting neoplastic change. In the studies that compared histology prediction performance before versus after CADx assistance (4 studies; 2503 polyps), there was no difference in the proportion of polyps predicted to be nonneoplastic that would avoid removal (55.4% vs. 58.4%; risk ratio [RR], 1.06 [CI, 0.96 to 1.17]; moderate-certainty evidence) or in the proportion of neoplastic polyps that would be erroneously left in situ (8.2% vs. 7.5%; RR, 0.95 [CI, 0.69 to 1.33]; moderate-certainty evidence). LIMITATION: The application of optical diagnosis was only simulated, potentially altering the decision-making process of the operator. CONCLUSION: Computer-aided diagnosis provided no incremental benefit or harm in the management of small rectosigmoid polyps during colonoscopy. PRIMARY FUNDING SOURCE: European Commission. (PROSPERO: CRD42023402197).

Artificial intelligence-assisted colonoscopy to identify histologic remission and predict the outcomes of patients with ulcerative colitis: A systematic review.

This systematic review evaluated the current status of AI-assisted colonoscopy to identify histologic remission and predict the clinical outcomes of patients with ulcerative colitis. The use of artificial intelligence (AI) has increased substantially across several medical fields, including gastrointestinal endoscopy. Evidence suggests that it may be helpful to predict histologic remission and relapse, which would be beneficial because current histological diagnosis is limited by the inconvenience of obtaining biopsies and the high cost and time-intensiveness of pathological diagnosis. MEDLINE and the Cochrane Central Register of Controlled Trials were searched for studies published between January 1, 2000, and October 31, 2023. Nine studies fulfilled the selection criteria and were included; five evaluated the prediction of histologic remission, two assessed the prediction of clinical outcomes, and two evaluated both. Seven were prospective observational or cohort studies, while two were retrospective observational studies. No randomized controlled trials were identified. AI-assisted colonoscopy demonstrated sensitivity between 65 %-98 % and specificity values of 80 %-97 % for identifying histologic remission. Furthermore, it was able to predict future relapse in patients with ulcerative colitis. However, several challenges and barriers still exist to its routine clinical application, which should be overcome before the true potential of AI-assisted colonoscopy can be fully realized.

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.

Outcomes of Metastatic and Unresectable Small Bowel Adenocarcinoma in Japan According to the Treatment Strategy: A Nationwide Observational Study.

PURPOSE: Limited information is available regarding the characteristics and outcomes of stage IV small bowel adenocarcinoma (SBA) in Japan. This study examined the clinical and pathological characteristics and outcomes according to the treatment strategies in patients with stage IV SBA. METHODS: This retrospective observational study used the data of patients with jejunal or ileal adenocarcinoma collected by the Small Bowel Malignant Tumor Project of the Japanese Society for Cancer of the Colon and Rectum. Descriptive statistics were expressed as the mean (standard deviation) or median (range). Survival analysis was performed using Kaplan-Meier curves and pairwise log-rank tests. RESULTS: Data from 128 patients were analyzed. The treatment strategies were chemotherapy alone (26 of 128, 20.3%), surgery alone (including palliative surgery; 21 of 128, 16.4%), surgery + chemotherapy (74 of 128, 57.8%), and best supportive care (7 of 128, 5.5%). The median (range) overall survival was 16 (0-125) months overall, and 11 (1-38) months, 8 (0-80) months, 18 (0-125) months, and 0 (0-1) months for the chemotherapy, surgery, surgery + chemotherapy, and best supportive care groups, respectively. Three main categories of chemotherapeutic regimen were used: a combination of fluoropyrimidine and oxaliplatin (F + Ox), fluoropyrimidine and irinotecan (F + Iri), and single-agent fluoropyrimidine. Among patients treated with chemotherapy, the median (range) OS was 16 (1-106) months overall, and 17 (1-87) months, 29 (7-39) months, and 16 (1-106) months in patients treated with fluoropyrimidine, F + Iri, and F + Ox, respectively. CONCLUSION: Patients treated with surgery, chemotherapy, or both had a better prognosis than those who received best supportive care. Among patients who received chemotherapy, survival did not differ according to the chemotherapeutic regimen.

Clinicopathological features and prognosis of primary small bowel adenocarcinoma: a large multicenter analysis of the JSCCR database in Japan.

BACKGROUND: The clinicopathological features and prognosis of primary small bowel adenocarcinoma (PSBA), excluding duodenal cancer, remain undetermined due to its rarity in Japan. METHODS: We analyzed 354 patients with 358 PSBAs, between January 2008 and December 2017, at 44 institutions affiliated with the Japanese Society for Cancer of the Colon and Rectum. RESULTS: The median age was 67 years (218 males, 61.6%). The average tumor size was 49.9 (7-100) mm. PSBA sites consisted of jejunum (66.2%) and ileum (30.4%). A total of 219 patients (61.9%) underwent diagnostic small bowel endoscopy, including single-balloon endoscopy, double-balloon endoscopy, and capsule endoscopy before treatment. Nineteen patients (5.4%) had Lynch syndrome, and 272 patients (76.8%) had symptoms at the initial diagnosis. The rates for stages 0, I, II, III, and IV were 5.4%, 2.5%, 27.1%, 26.0%, and 35.6%, respectively. The 5-year overall survival rates at each stage were 92.3%, 60.0%, 75.9%, 61.4%, and 25.5%, respectively, and the 5-year disease-specific survival (DSS) rates were 100%, 75.0%, 84.1%, 59.3%, and 25.6%, respectively. Patients with the PSBA located in the jejunum, with symptoms at the initial diagnosis or advanced clinical stage had a worse prognosis. However, multivariate analysis using Cox-hazard model revealed that clinical stage was the only significant predictor of DSS for patients with PSBA. CONCLUSIONS: Of the patients with PSBA, 76.8% had symptoms at the initial diagnosis, which were often detected at an advanced stage. Detection during the early stages of PSBA is important to ensure a good prognosis.

Evaluating false-positive detection in a computer-aided detection system for colonoscopy.

BACKGROUND AND AIM: Computer-aided detection (CADe) systems can efficiently detect polyps during colonoscopy. However, false-positive (FP) activation is a major limitation of CADe. We aimed to compare the rate and causes of FP using CADe before and after an update designed to reduce FP. METHODS: We analyzed CADe-assisted colonoscopy videos recorded between July 2022 and October 2022. The number and causes of FPs and excessive time spent by the endoscopist on FP (ET) were compared pre- and post-update using 1:1 propensity score matching. RESULTS: During the study period, 191 colonoscopy videos (94 and 97 in the pre- and post-update groups, respectively) were recorded. Propensity score matching resulted in 146 videos (73 in each group). The mean number of FPs and median ET per colonoscopy were significantly lower in the post-update group than those in the pre-update group (4.2 ± 3.7 vs 18.1 ± 11.1; P < 0.001 and 0 vs 16 s; P < 0.001, respectively). Mucosal tags, bubbles, and folds had the strongest association with decreased FP post-update (pre-update vs post-update: 4.3 ± 3.6 vs 0.4 ± 0.8, 0.32 ± 0.70 vs 0.04 ± 0.20, and 8.6 ± 6.7 vs 1.6 ± 1.7, respectively). There was no significant decrease in the true positive rate (post-update vs pre-update: 95.0% vs 99.2%; P = 0.09) or the adenoma detection rate (post-update vs pre-update: 52.1% vs 49.3%; P = 0.87). CONCLUSIONS: The updated CADe can reduce FP without impairing polyp detection. A reduction in FP may help relieve the burden on endoscopists.

A novel artificial intelligence-assisted "vascular healing" diagnosis for prediction of future clinical relapse in patients with ulcerative colitis: a prospective cohort study.

BACKGROUND AND AIMS: Image-enhanced endoscopy has attracted attention as a method for detecting inflammation and predicting outcomes in patients with ulcerative colitis (UC); however, the procedure requires specialist endoscopists. Artificial intelligence (AI)-assisted image-enhanced endoscopy may help nonexperts provide objective accurate predictions with the use of optical imaging. We aimed to develop a novel AI-based system using 8853 images from 167 patients with UC to diagnose "vascular-healing" and establish the role of AI-based vascular-healing for predicting the outcomes of patients with UC. METHODS: This open-label prospective cohort study analyzed data for 104 patients with UC in clinical remission. Endoscopists performed colonoscopy using the AI system, which identified the target mucosa as AI-based vascular-active or vascular-healing. Mayo endoscopic subscore (MES), AI outputs, and histologic assessment were recorded for 6 colorectal segments from each patient. Patients were followed up for 12 months. Clinical relapse was defined as a partial Mayo score >2 RESULTS: The clinical relapse rate was significantly higher in the AI-based vascular-active group (23.9% [16/67]) compared with the AI-based vascular-healing group (3.0% [1/33)]; P = .01). In a subanalysis predicting clinical relapse in patients with MES ≤1, the area under the receiver operating characteristic curve for the combination of complete endoscopic remission and vascular healing (0.70) was increased compared with that for complete endoscopic remission alone (0.65). CONCLUSIONS: AI-based vascular-healing diagnosis system may potentially be used to provide more confidence to physicians to accurately identify patients in remission of UC who would likely relapse rather than remain stable.

Endoscopic Removal of Premalignant Lesions Reduces Long-Term Colorectal Cancer Risk: Results From the Japan Polyp Study.

BACKGROUND & AIMS: To date, no regional evidence of long-term colorectal cancer (CRC) risk reduction after endoscopic premalignant lesion removal has been established. We aimed to analyze this over a long-term follow-up evaluation. METHODS: This was a prospective cohort study of participants from the Japan Polyp Study conducted at 11 Japanese institutions. Participants underwent scheduled follow-up colonoscopies after a 2-round baseline colonoscopy process. The primary outcome was CRC incidence after randomization. The observed/expected ratio of CRC was calculated using data from the population-based Osaka Cancer Registry. Secondary outcomes were the incidence and characteristics of advanced neoplasia (AN). RESULTS: A total of 1895 participants were analyzed. The mean number of follow-up colonoscopies and the median follow-up period were 2.8 years (range, 1-15 y) and 6.1 years (range, 0.8-11.9 y; 11,559.5 person-years), respectively. Overall, 4 patients (all males) developed CRCs during the study period. The observed/expected ratios for CRC in all participants, males, and females, were as follows: 0.14 (86% reduction), 0.18, and 0, respectively, and 77 ANs were detected in 71 patients (6.1 per 1000 person-years). Of the 77 ANs detected, 31 lesions (40.3%) were laterally spreading tumors, nongranular type. Nonpolypoid colorectal neoplasms (NP-CRNs), including flat (<10 mm), depressed, and laterally spreading, accounted for 59.7% of all detected ANs. Furthermore, 2 of the 4 CRCs corresponded to T1 NP-CRNs. CONCLUSIONS: Endoscopic removal of premalignant lesions, including NP-CRNs, effectively reduced CRC risk. More than half of metachronous ANs removed by surveillance colonoscopy were NP-CRNs. The Japan Polyp Study: University Hospital Medical Information Network Clinical Trial Registry: University Hospital Medical Information Network Clinical Trial Registry, C000000058; cohort study: UMIN000040731.

Challenges in Implementing Endoscopic Resection for T2 Colorectal Cancer.

The current standard treatment for muscularis propria-invasive (T2) colorectal cancer is surgical colectomy with lymph node dissection. With the advent of new endoscopic resection techniques, such as endoscopic full-thickness resection or endoscopic intermuscular dissection, T2 colorectal cancer, with metastasis to 20%-25% of the dissected lymph nodes, may be the next candidate for endoscopic resection following submucosal-invasive (T1) colorectal cancer. We present a novel endoscopic treatment strategy for T2 colorectal cancer and suggest further study to establish evidence on oncologic and endoscopic technical safety for its clinical implementation.

Impact of computer-aided characterization for diagnosis of colorectal lesions, including sessile serrated lesions: Multireader, multicase study.

OBJECTIVES: Computer-aided characterization (CADx) may be used to implement optical biopsy strategies into colonoscopy practice; however, its impact on endoscopic diagnosis remains unknown. We aimed to evaluate the additional diagnostic value of CADx when used by endoscopists for assessing colorectal polyps. METHODS: This was a single-center, multicase, multireader, image-reading study using randomly extracted images of pathologically confirmed polyps resected between July 2021 and January 2022. Approved CADx that could predict two-tier classification (neoplastic or nonneoplastic) by analyzing narrow-band images of the polyps was used to obtain a CADx diagnosis. Participating endoscopists determined if the polyps were neoplastic or not and noted their confidence level using a computer-based, image-reading test. The test was conducted twice with a 4-week interval: the first test was conducted without CADx prediction and the second test with CADx prediction. Diagnostic performances for neoplasms were calculated using the pathological diagnosis as reference and performances with and without CADx prediction were compared. RESULTS: Five hundred polyps were randomly extracted from 385 patients and diagnosed by 14 endoscopists (including seven experts). The sensitivity for neoplasia was significantly improved by referring to CADx (89.4% vs. 95.6%). CADx also had incremental effects on the negative predictive value (69.3% vs. 84.3%), overall accuracy (87.2% vs. 91.8%), and high-confidence diagnosis rate (77.4% vs. 85.8%). However, there was no significant difference in specificity (80.1% vs. 78.9%). CONCLUSIONS: Computer-aided characterization has added diagnostic value for differentiating colorectal neoplasms and may improve the high-confidence diagnosis rate.

Differentiation grade as a risk factor for lymph node metastasis in T1 colorectal cancer.

Objectives: Japanese guidelines include high-grade (poorly differentiated) tumors as a risk factor for lymph node metastasis (LNM) in T1 colorectal cancer (CRC). However, whether the grading is based on the least or most predominant component when the lesion consists of two or more levels of differentiation varies among institutions. This study aimed to investigate which method is optimal for assessing the risk of LNM in T1 CRC. Methods: We retrospectively evaluated 971 consecutive patients with T1 CRC who underwent initial or additional surgical resection from 2001 to 2021 at our institution. Tumor grading was divided into low-grade (well- to moderately differentiated) and high-grade based on the least or predominant differentiation analyses. We investigated the correlations between LNM and these two grading analyses. Results: LNM was present in 9.8% of patients. High-grade tumors, as determined by least differentiation analysis, accounted for 17.0%, compared to 0.8% identified by predominant differentiation analysis. A significant association with LNM was noted for the least differentiation method (p < 0.05), while no such association was found for predominant differentiation (p = 0.18). In multivariate logistic regression, grading based on least differentiation was an independent predictor of LNM (p = 0.04, odds ratio 1.68, 95% confidence interval 1.00-2.83). Sensitivity and specificity for detecting LNM were 27.4% and 84.1% for least differentiation, and 2.1% and 99.3% for predominant differentiation, respectively. Conclusions: Tumor grading via least differentiation analysis proved to be a more reliable measure for assessing LNM risk in T1 CRC compared to grading by predominant differentiation.

Precision endoscopy in colorectal polyps' characterization and planning of endoscopic therapy.

Precision endoscopy in the management of colorectal polyps and early colorectal cancer has emerged as the standard of care. It includes optical characterization of polyps and estimation of submucosal invasion depth of large nonpedunculated colorectal polyps to select the appropriate endoscopic resection modality. Over time, several imaging modalities have been implemented in endoscopic practice to improve optical performance. Among these, image-enhanced endoscopy systems and magnification endoscopy represent now well-established tools. New advanced technologies, such as endocytoscopy and confocal laser endomicroscopy, have recently shown promising results in predicting the histology of colorectal polyps. In recent years, artificial intelligence has continued to enhance endoscopic performance in the characterization of colorectal polyps, overcoming the limitations of other imaging modes. In this review we retrace the path of precision endoscopy, analyzing the yield of various endoscopic imaging techniques in personalizing management of colorectal polyps and early colorectal cancer.

Optimal Timing of Laparoscopic Cholecystectomy After Conservative Therapy for Acute Cholecystitis.

Background/Aim: According to the Tokyo Guidelines 2018, the operation for acute cholecystitis is recommended to be performed as early as possible. However, there are cases in which early surgeries cannot be performed due to complications of patients or facility conditions, resulting in elective surgery. Hence, we retrospectively analyzed elective surgery cases in this study. Patients and Methods: There were 345 patients who were underwent laparoscopic cholecystectomy (LC) at our hospital from January 2019 to December 2020 in this retrospective study. A total of 83 patients underwent LC more than 3 days after conservative treatment. The elective LC patients were divided into the Early group (4-90 days after onset, n=36) and the Delayed group [91 days or more (13 weeks or more) after onset, n=31], excluding 16 patients who underwent percutaneous transhepatic gallbladder drainage. Results: As for operative time, there was a significant difference between the Delayed and Early groups (91.2 vs. 117 minutes, p=0.0108). And also, there was a significant difference in the postoperative hospital stay, which was significantly shorter in the Delayed group than in the Early group (3.4 vs. 5.9 days, p=0.0436). Although there were no significant differences in either conversion rates or complication rates, both of these were decreasing in the Delayed group. In particular, there were no complications in the Delayed group. Conclusion: When the conservative treatment for acute cholecystitis precedes and precludes urgent/early LC within 3 days, delaying LC for at least 91 days (13 weeks or more) after onset could reduce operative time and postoperative hospital stay. Moreover, there would be no complications after LC, and the rates of conversion during LC may be kept low.

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).

Gaussian affinity and GIoU-based loss for perforation detection and localization from colonoscopy videos.

PURPOSE: Endoscopic submucosal dissection (ESD) is a minimally invasive treatment for early gastric cancer. However, perforations may happen and cause peritonitis during ESD. Thus, there is a potential demand for a computer-aided diagnosis system to support physicians in ESD. This paper presents a method to detect and localize perforations from colonoscopy videos to avoid perforation ignoring or enlarging by ESD physicians. METHOD: We proposed a training method for YOLOv3 by using GIoU and Gaussian affinity losses for perforation detection and localization in colonoscopic images. In this method, the object functional contains the generalized intersection over Union loss and Gaussian affinity loss. We propose a training method for the architecture of YOLOv3 with the presented loss functional to detect and localize perforations precisely. RESULTS: To qualitatively and quantitatively evaluate the presented method, we created a dataset from 49 ESD videos. The results of the presented method on our dataset revealed a state-of-the-art performance of perforation detection and localization, which achieved 0.881 accuracy, 0.869 AUC, and 0.879 mean average precision. Furthermore, the presented method is able to detect a newly appeared perforation in 0.1 s. CONCLUSIONS: The experimental results demonstrated that YOLOv3 trained by the presented loss functional were very effective in perforation detection and localization. The presented method can quickly and precisely remind physicians of perforation happening in ESD. We believe a future CAD system can be constructed for clinical applications with the proposed method.