Showa University Northern Yokohama Hospital

BACKGROUND: Peroral endoscopic myotomy (POEM) was developed by our group to provide a less invasive permanent treatment for esophageal achalasia. PATIENTS AND METHODS: POEM was performed in 17 consecutive patients with achalasia (10 men, 7 women; mean age 41.4 years). A long submucosal tunnel was created (mean length 12.4 cm), followed by endoscopic myotomy of circular muscle bundles of a mean total length of 8.1 cm (6.1 cm in distal esophagus and 2.0 cm in cardia). Smooth passage of an endoscope through the gastroesophageal junction was confirmed at the end of the procedure. RESULTS: In all cases POEM significantly reduced the dysphagia symptom score (from mean 10 to 1.3; P = 0.0003) and the resting lower esophageal sphincter (LES) pressure (from mean 52.4 mmHg to 19.9 mmHg; P = 0.0001). No serious complications related to POEM were encountered. During follow-up (mean 5 months), additional treatment or medication was necessary in only one patient (case 17) who developed reflux esophagitis (Los Angeles classification B); this was well controlled with regular intake of protein pump inhibitors (PPIs). CONCLUSIONS: The short-term outcome of POEM for achalasia was excellent; further studies on long-term efficacy and on comparison of POEM with other interventional therapies are awaited.

Many clinical studies on narrow-band imaging (NBI) magnifying endoscopy classifications advocated so far in Japan (Sano, Hiroshima, Showa, and Jikei classifications) have reported the usefulness of NBI magnifying endoscopy for qualitative and quantitative diagnosis of colorectal lesions. However, discussions at professional meetings have raised issues such as: (i) the presence of multiple terms for the same or similar findings; (ii) the necessity of including surface patterns in magnifying endoscopic classifications; and (iii) differences in the NBI findings in elevated and superficial lesions. To resolve these problems, the Japan NBI Expert Team (JNET) was constituted with the aim of establishing a universal NBI magnifying endoscopic classification for colorectal tumors (JNET classification) in 2011. Consensus was reached on this classification using the modified Delphi method, and this classification was proposed in June 2014. The JNET classification consists of four categories of vessel and surface pattern (i.e. Types 1, 2A, 2B, and 3). Types 1, 2A, 2B, and 3 are correlated with the histopathological findings of hyperplastic polyp/sessile serrated polyp (SSP), low-grade intramucosal neoplasia, high-grade intramucosal neoplasia/shallow submucosal invasive cancer, and deep submucosal invasive cancer, respectively.

Background: Computer-aided diagnosis (CAD) for colonoscopy may help endoscopists distinguish neoplastic polyps (adenomas) requiring resection from nonneoplastic polyps not requiring resection, potentially reducing cost. Objective: To evaluate the performance of real-time CAD with endocytoscopes (×520 ultramagnifying colonoscopes providing microvascular and cellular visualization of colorectal polyps after application of the narrow-band imaging [NBI] and methylene blue staining modes, respectively). Design: Single-group, open-label, prospective study. (UMIN [University hospital Medical Information Network] Clinical Trial Registry: UMIN000027360). Setting: University hospital. Participants: 791 consecutive patients undergoing colonoscopy and 23 endoscopists. Intervention: Real-time use of CAD during colonoscopy. Measurements: CAD-predicted pathology (neoplastic or nonneoplastic) of detected diminutive polyps (≤5 mm) on the basis of real-time outputs compared with pathologic diagnosis of the resected specimen (gold standard). The primary end point was whether CAD with the stained mode produced a negative predictive value (NPV) of 90% or greater for identifying diminutive rectosigmoid adenomas, the threshold required to "diagnose-and-leave" nonneoplastic polyps. Best- and worst-case scenarios assumed that polyps lacking either CAD diagnosis or pathology were true- or false-positive or true- or false-negative, respectively. Results: Overall, 466 diminutive (including 250 rectosigmoid) polyps from 325 patients were assessed by CAD, with a pathologic prediction rate of 98.1% (457 of 466). The NPVs of CAD for diminutive rectosigmoid adenomas were 96.4% (95% CI, 91.8% to 98.8%) (best-case scenario) and 93.7% (CI, 88.3% to 97.1%) (worst-case scenario) with stained mode and 96.5% (CI, 92.1% to 98.9%) (best-case scenario) and 95.2% (CI, 90.3% to 98.0%) (worst-case scenario) with NBI. Limitation: Two thirds of the colonoscopies were conducted by experts who had each experienced more than 200 endocytoscopies; 186 polyps not assessed by CAD were excluded. Conclusion: Real-time CAD can achieve the performance level required for a diagnose-and-leave strategy for diminutive, nonneoplastic rectosigmoid polyps. Primary Funding Source: Japan Society for the Promotion of Science.

BACKGROUND: After the first case of per-oral endoscopic myotomy (POEM) at our institution in 2008, the procedure was quickly accepted as an alternative to surgical myotomy and is now established as an excellent treatment option for achalasia. This study aimed to examine the safety and outcomes of POEM at our institution. STUDY DESIGN: Per-oral endoscopic myotomy was performed on 500 consecutive achalasia patients at our institution between September 2008 and November 2013. A review of prospectively collected data was conducted, including procedure time, myotomy location and length, adverse events, and patient data with short- (2 months) and long-term (1 and 3 years) follow-up. RESULTS: Per-oral endoscopic myotomy was successfully completed in all patients, with adverse events observed in 3.2%. Two months post-POEM, significant reductions in symptom scores (Eckardt score 6.0 ± 3.0 vs 1.0 ± 2.0, p < 0.0001) and lower esophageal sphincter (LES) pressures (25.4 ± 17.1 vs 13.4 ± 5.9 mmHg, p < 0.0001) were achieved, and this persisted at 3 years post-POEM. Gastroesophageal reflux was seen in 16.8% of patients at 2 months and 21.3% at 3-year follow-up. CONCLUSIONS: Per-oral endoscopic myotomy was successfully completed in all cases, even when extended indications (extremes of age, previous interventions, or sigmoid esophagus) were used. Adverse events were rare (3.2%), and there were no mortalities. Significant improvements in Eckardt scores and LES pressures were seen at 2 months, 1 year, and 3 years post-POEM. Based on our large series, POEM is a safe and effective treatment for achalasia; there are relatively few contraindications, and the procedure may be used as either first- or second-line therapy.

The adenoma detection rate is an established quality indicator for colonoscopy. For instance, a 1% increase in the adenoma detection rate was associated with a 3% decrease in interval colorectal cancer incidence.1Corley D.A. Jensen C.D. Marks A.R. et al.Adenoma detection rate and risk of colorectal cancer and death.N Engl J Med. 2014; 370: 1298-1306Crossref PubMed Scopus (1166) Google Scholar However, a previous meta-analysis showed that approximately 26% of neoplastic diminutive polyps were missed in single colonoscopy.2van Rijn J.C. Reitsma J.B. Stoker J. et al.Polyp miss rate determined by tandem colonoscopy: a systematic review.Am J Gastroenterol. 2006; 101: 343-350Crossref PubMed Scopus (1031) Google Scholar Two factors are considered to affect this rate; one is blind spots and the other is human error. The first factor could be solved using a wide-angle scope or distal attachments, but human error is not easily overcome. As a solution to address human error, artificial intelligence has been attracting attention.3Byrne M.F. Shahidi N. Rex D.K. Will Computer-Aided Detection and Diagnosis Revolutionize Colonoscopy?.Gastroenterology. 2017; 153: 1460-1464.e1Abstract Full Text Full Text PDF PubMed Scopus (45) Google Scholar, 4Misawa M. Kudo S.E. Mori Y. et al.Characterization of colorectal lesions using a computer-aided diagnostic system for narrow-band imaging endocytoscopy.Gastroenterology. 2016; 150: 1531-1532.e3Abstract Full Text Full Text PDF PubMed Scopus (113) Google Scholar, 5Chen P.J. Lin M.C. Lai M.J. et al.Accurate classification of diminutive colorectal polyps using computer-aided analysis.Gastroenterology. 2018; 154: 568-575Abstract Full Text Full Text PDF PubMed Scopus (227) Google Scholar Karkanis et al6Karkanis S.A. Iakovidis D.K. Maroulis D.E. et al.Computer-aided tumor detection in endoscopic video using color wavelet features.IEEE Trans Inf Technol Biomed. 2003; 7: 141-152Crossref PubMed Scopus (371) Google Scholar first reported using computer-aided detection (CADe) systems for colorectal polyps and achieved a >90% detection rate.6Karkanis S.A. Iakovidis D.K. Maroulis D.E. et al.Computer-aided tumor detection in endoscopic video using color wavelet features.IEEE Trans Inf Technol Biomed. 2003; 7: 141-152Crossref PubMed Scopus (371) Google Scholar However, the study results could not be applied clinically because the system was based on static images. Recently, Fernández-Esparrach et al7Fernández-Esparrach G. Bernal J. López-Cerón M. et al.Exploring the clinical potential of an automatic colonic polyp detection method based on the creation of energy maps.Endoscopy. 2016; 48: 837-842Crossref PubMed Scopus (83) Google Scholar reported using a CADe system based on routine colonoscopy videos. Although their system could localize the polyps, sensitivity was only approximately 70% because of the limited number of study samples. To tackle these issues, we used an algorithm designed to analyze videos, and we secured a large number of routine colonoscopy videos. Subsequently, we conducted a pilot study to evaluate the performance of the developed CADe system. In this study, we developed an original artificial intelligence-assisted CADe system. Figure 1 shows an output sample from the system; the full algorithm appears in the Supplementary Document. To develop the CADe, we retrospectively collected colonoscopy videos from study participants who underwent colonoscopy from April 2015 to October 2015 in our institution. Recording for each colonoscopy video ran from cecal intubation to withdrawal of the scope across the anus. The inclusion criterion was patients with colorectal polyp(s) and the exclusion criteria were (1) advanced colorectal cancer, (2) inflammatory bowel disease, and (3) non-epithelial lesions. We collected 73 colonoscopy videos (total duration, 997 minutes; 1.8 million frames) from 73 patients, which included 155 colorectal polyps. Two expert endoscopists retrospectively annotated the presence of polyps in each frame of each video, and this annotation was treated as the gold standard for the presence of polyps. To use these videos for machine leaning and its evaluation, we divided these full-length videos into short videos based on the method described in the Supplementary Document, which produced 155 polyp-positive short videos and 391 polyp-negative videos. These 546 short videos were randomly divided into 2 groups: learning samples (105 positive and 306 negative) and test samples (50 positive and 85 negative). Learning samples were used for machine learning, and test samples were used to evaluate our system’s performance. Thus, test samples were a completely separate dataset that was never used during machine learning. The CADe system presented the probability of the presence of polyps as a percentage (0%–100%) in each frame. This probability value simulated the confidence level of human endoscopists on a given image frame and was not related to adenoma detection rate. To decide the cutoff value for this probability and to develop the CADe with a sensitivity of ≥90%, we performed receiver-operating characteristic analysis. To evaluate the CADe performance, we then calculated the system’s sensitivity, specificity, and accuracy on an image-frame basis. When the probability exceeded the cutoff value, the system considered this a positive detection. Sensitivity was calculated by dividing the number of frames correctly detected by the system by the total number of polyp frames in the test sample. Specificity was calculated by dividing the number of negative frames correctly diagnosed by the system by the total number of negative frames in the test samples. We also performed a polyp-based analysis where we defined polyp detection by the CADe as the system output over the cutoff value for >75% of the duration of each short video. We also calculated the sensitivity and false positive ratio for the polyp-based analysis. Ethics statements are included in the Supplementary Document. Video 1 is a sample with the CADe providing the probability in the upper left of the endoscopy image. When the probability exceeded the cutoff, the CADe warned of the possibility of the presence of polyps by changing the color in the 4 corners of the endoscopic image to red. When a lesion appeared on the screen, a warning was issued, and the warning stopped as the lesion disappeared from the screen. The clinicopathologic features of the study participants and the polyps are shown in Supplementary Table 1. In this study, flat lesions, which are considered difficult for CADe to find, were included at a rate of 64.5% (100 of 155). Figure 2 shows the CADe receiver-operating characteristic curve. Based on the receiver-operating characteristic analysis, we set the cutoff value for the probability of detecting a polyp at 15%. The sensitivity, specificity, and accuracy for the frame-based analysis, were 90.0%, 63.3%, and 76.5%, respectively. Regarding the polyp-based analysis, the CADe detected 94% of the test polyps (47 of 50), and the false-positive detection was 60% (51 of 85). This sensitivity and false-positive rate were similar to results of a recent deep learning-based CADe system for gastric cancer.8Hirasawa T. Aoyama K. Tanimoto T. et al.Application of artificial intelligence using a convolutional neural network for detecting gastric cancer in endoscopic images.Gastric Cancer. 2018 Jan 15; ([Epub ahead of print])Crossref Scopus (390) Google Scholar Supplementary Table 2 shows the result of each test lesions. Our proposed CADe system showed that artificial intelligence has the potential to provide automated detection of colorectal polyps. Further machine learning and prospective evaluation are mandatory; however, such CADe systems are expected to fill the gap between endoscopists with different levels of experience. The authors express their gratitude to Mr Takashi Wakisaka and Mr Hideo Kahara (Cybernet Systems). In this study, we developed an original algorithm based on a convolutional 3-dimensional neural network, which is a type of deep learning. Deep learning is a recent machine learning method using a deep neural network that automatically extracts specific features from data without human power if very high numbers of learning samples are available. Convolutional 3-dimensional network is designed for spatiotemporal data; therefore, it is more suitable for video datasets compared with previous deep learning methods.1Tran D, Bourdev L, Fergus R, et al. Learning spatiotemporal features with 3d convolutional networks. Proceedings of the IEEE International Conference on Computer Vision, 2015.Google Scholar First, because this study included 155 polyps, we extracted all polyp-positive frame sequences with white-light imaging among the 73 colonoscopy videos. We then divided the polyp-positive frames into 155 short videos (total duration of polyp positive frames: 35 minutes; 63,135 frames) based on the individual polyps. We excluded frames with narrow-band imaging and chromoendoscopy because these methods were usually used after detecting the polyps. Next, we randomly extracted polyp-negative frame sequences of random lengths. By learning all negative frames, the specificity of the system increases, but the sensitivity decreases; therefore, because CADe systems require high sensitivity, we decided not to use all of the negative frames. Regarding this random extraction, we set the number of negative frames so that the ratio of the number of positive frames to negative frames was approximately 1:2. Thus, the total number of extracted negative frames was 133,496 frames (80 minutes), which also created 391 negative short videos. We chose a 1:2 ratio because it provided high sensitivity with sufficient specificity for this initial experiment. The 155 positive short videos and 391 negative short videos were used for the final analysis. After discussion with our institutional ethics committee, it was decided that informed consent would be obtained on an “opt-out” basis in the present trial because the intervention was considered to be minimally serious (No. 1411-02), and no patients refused to participate in the study. All procedures performed in this study were in accordance with the Declaration of Helsinki. Information about the current trial and the method of informing staff on presenting the option for refusal to participate appears on Showa University's home page (www.showa-u.ac.jp/pick_up/chiken/frdi8b000000mopb-att/17H056.pdf; posted until March 2020).Supplementary Table 1Clinicopathologic Features of the Study Participants and the PolypsLearning SamplesTest SamplesPPatients, n5914-Male/Female34/2510/4.38aFisher’s exact test was used.Mean age ± SD (y)61.3 ± 11.160.8 ± 14.8.88bStudent t test was used.Lesions, n10550-Morphology (protruded/flat and depressed)38/6716/34.72aFisher’s exact test was used.Mean size ± SD (mm)4.8 ± 3.04.9 ± 5.0.45cMann-Whitney U testPathologic diagnosis.50aFisher’s exact test was used. High-grade adenoma21 Low-grade adenoma7139 Hyperplastic polyp288 Sessile serrated adenoma/polyp20 Other non-neoplasmsdOther non-neoplasms included inflammatory polyps and juvenile polyps.32Location.45aFisher’s exact test was used. Right/left/rectum47/45/1326/16/8SD, standard deviation.a Fisher’s exact test was used.b Student t test was used.c Mann-Whitney U testd Other non-neoplasms included inflammatory polyps and juvenile polyps. Open table in a new tab Supplementary Table 2Results of the Test LesionsCase No.MorphologySize (mm)LocationPathologic diagnosisDetected ratio (%)aPercentage of the length of each short video which the system output over the cutoff value.1Ip6SJuvenile polyp1002IIa2ALow-grade adenoma1003IIa3ALow-grade adenoma1004IIa3SLow-grade adenoma975IIa3THyperplastic polyp896IIa2DLow-grade adenoma1007Ip10RLow-grade adenoma918IIa4SLow-grade adenoma979Isp8ALow-grade adenoma9410Isp6ALow-grade adenoma10011Is5RLow-grade adenoma10012Is10RSLow-grade adenoma10013IIa2RLow-grade adenoma10014IIa4THyperplastic polyp8815IIa3ALow-grade adenoma10016IIa2ALow-grade adenoma10017IIa2ALow-grade adenoma9718Is4ALow-grade adenoma8819IIa4ALow-grade adenoma10020IIa3SLow-grade adenoma10021IIa3TLow-grade adenoma10022IIa4SHyperplastic polyp10023Is6SLow-grade adenoma10024IIa3ALow-grade adenoma10025IIa2ALow-grade adenoma10026IIa2ALow-grade adenoma9827IIa3ALow-grade adenoma10028IIa3SLow-grade adenoma10029IIa4ALow-grade adenoma10030IIa2SHyperplastic polyp9531IIa3TLow-grade adenoma9532Is12RSLow-grade adenoma10033IIa35RLow-grade adenoma9834IIa2SHyperplastic polyp10035Is12RHigh-grade adenoma10036Is4ALow-grade adenoma9537Is3RInflammatory polyp10038Isp5SLow-grade adenoma9839IIa3ALow-grade adenoma8240IIa2SHyperplastic polyp6041IIa3SHyperplastic polyp10042IIa4CHyperplastic polyp10043Isp8ALow-grade adenoma9744Is5SLow-grade adenoma10045IIa8SLow-grade adenoma9546IIa7CLow-grade adenoma5047IIa3ALow-grade adenoma10048IIa3TLow-grade adenoma6749IIa5DLow-grade adenoma10050Is2TLow-grade adenoma80A, ascending colon; C, cecum; D, descending colon; Ip, pedunculated; IIa, flat elevated; Isp, subpedunculated; Is, sessile; R, rectum; RS, rectosigmoid colon; S, sigmoid colon; T, transverse colon.a Percentage of the length of each short video which the system output over the cutoff value. Open table in a new tab SD, standard deviation. A, ascending colon; C, cecum; D, descending colon; Ip, pedunculated; IIa, flat elevated; Isp, subpedunculated; Is, sessile; R, rectum; RS, rectosigmoid colon; S, sigmoid colon; T, transverse colon. eyJraWQiOiI4ZjUxYWNhY2IzYjhiNjNlNzFlYmIzYWFmYTU5NmZmYyIsImFsZyI6IlJTMjU2In0.eyJzdWIiOiJhODhjNWE4NDIyMjdiMGFmMDE4ZGExNmI4YjBjNDc0MiIsImtpZCI6IjhmNTFhY2FjYjNiOGI2M2U3MWViYjNhYWZhNTk2ZmZjIiwiZXhwIjoxNjc4MTkyMzkwfQ.EaXgtHBU1HK5yYllhG_wbwK1zClIbgO5-MYxehkFFvvbAOX7xGXMl4YYjHTa66Yr3yhLxsHRmn7a3RVROFw_IhlK9kDq6CpmW11SHs1S5aEHp58Cm21R7F6YiT1lKiJcvbAUANlnqUYr8oz4HH9mK3ggOV3-wV1wVrdYwNrwL-I348usKbha0GCp1EWS3gNfkOJKZDRRYBMcS4G_EYSK7qNBu1DnF8l-Bs7ICh7eJIg9sm9gX2NeXW0qrAbjjd6G1bVcRFSWou09wd8bdFga3eKiaPVO85HnR6EI8J2df8c6bH5PwjBY8PeRpkPKp97NHZY0lqlfJOkXNht1BmJ8Fw Download .mp4 (81 MB) Help with .mp4 files Video 1

OBJECTIVES: Endoscopic balloon dilatation and laparoscopic myotomy are established treatments for achalasia. Recently, a new endoscopic technique for complete myotomy was described. Herein, we report the results of the first prospective trial of peroral endoscopic myotomy (POEM) in Europe. METHODS: POEM was performed under general anesthesia in 16 patients (male:female (12:4), mean age 45 years, range 26-76). The primary outcome was symptom relief at 3 months, defined as an Eckhard score ≤3. Secondary outcomes were procedure-related adverse events, lower esophageal sphincter (LES) pressure on manometry, reflux symptoms, and medication use before and after POEM. RESULTS: A 3-month follow-up was completed for all patients. Treatment success (Eckhard score ≤3) was achieved in 94% of cases (mean score pre- vs. post-treatment (8.8 vs. 1.4); P<0.001). Mean LES pressure was 27.2 mm Hg pre-treatment and 11.8 mm Hg post-treatment (P<0.001). No patient developed symptoms of gastro-esophageal reflux after treatment, but one patient was found to have an erosive lesion (LA grade A) on follow-up esophagogastroduodenoscopy. No patient required medication with proton pump inhibitors or antacids after POEM. CONCLUSIONS: POEM is a promising new treatment for achalasia resulting in short-term symptom relief in >90% of cases. Studies evaluating long-term efficacy and comparing POEM with established treatments have been initiated.

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.

Coronavirus-19 (COVID-19) caused by SARS-CoV-2 has become a global pandemic. Risk of transmission may occur during endoscopy and the goal is to prevent infection among healthcare professionals while providing essential services to patients. Asia was the first continent to have a COVID-19 outbreak, and this position statement of the Asian Pacific Society for Digestive Endoscopy shares our successful experience in maintaining safe and high-quality endoscopy practice at a time when resources are limited. Sixteen experts from key societies of digestive endoscopy in Asia were invited to develop position statements, including patient triage and risk assessment before endoscopy, resource prioritisation and allocation, regular monitoring of personal protective equipment, infection control measures, protective device training and implementation of a strategy for stepwise resumption of endoscopy services after control of the COVID-19 outbreak.

BACKGROUND AND STUDY AIMS: Type III achalasia is characterized by rapidly propagating pressurization attributable to spastic contractions. Although laparoscopic Heller myotomy (LHM) is the current gold standard management for type III achalasia, peroral endoscopic myotomy (POEM) is conceivably superior because it allows for a longer myotomy. Our aims were to compare the efficacy and safety of POEM with LHM for type III achalasia patients. PATIENTS AND METHODS: A retrospective study of 49 patients who underwent POEM for type III achalasia across eight centers were compared to 26 patients who underwent LHM at a single institution. Procedural data were abstracted and pre- and post-procedural symptoms were recorded. Clinical response was defined by improvement of symptoms and decrease in Eckardt stage to ≤ 1. Secondary outcomes included length of myotomy, procedure duration, length of hospital stay, and rate of adverse events. RESULTS: Clinical response was significantly more frequent in the POEM cohort (98.0 % vs 80.8 %; P = 0.01). POEM patients had significantly shorter mean procedure time than LHM patients (102 min vs 264 min; P < 0.01) despite longer length of myotomy (16 cm vs 8 cm; P < 0.01). There was no significant difference between POEM and LHM in the length of hospital stay (3.3 days vs 3.2 days; P = 0.68), respectively. Rate of adverse events was significantly less in the POEM group (6 % vs 27 %; P < 0.01). CONCLUSIONS: POEM allows for a longer myotomy than LHM, which may result in improved clinical outcomes. POEM appears to be an effective and safe alternative to LHM in patients with type III achalasia.

OBJECTIVE: The aim of this study was to elucidate the clinicopathological features and prognosis of mucinous cystic neoplasms (MCNs). MATERIALS AND METHODS: We performed a multi-institutional, retrospective study on a collected series of patients with MCN pathologically defined by ovarian-type stroma. Clinicopathological features and prognosis were investigated. RESULT: Mucinous cystic neoplasm was confirmed in 156 cases, including 129 adenomas (82.7%) and 21 noninvasive (13.4%) and 6 invasive carcinomas (3.9%). Patients with MCN were exclusively women (98.1%) with the mean age of 48.1 years. All but 1 MCN were in the pancreatic body/tail region with a mean size of 65.3 mm. Communication between the cyst and the pancreatic duct was found in 18.1%. The 3-, 5-, and 10-year survival rates were 97.6%, 96.6%, and 96.6%, respectively. A significant difference in the survival rates was observed between adenomas and carcinomas and between minimally invasive carcinomas and invasive carcinomas. Cyst diameter and presence of mural nodule were predictive of malignant MCN. CONCLUSIONS: Mucinous cystic neoplasm is a rare but distinctive pancreatic cystic neoplasm with a favorable overall prognosis. All MCNs should be resected to prevent malignant changes but can be observed for an appropriate time when the lesion is small without the presence of mural nodules.

OBJECTIVES: Conventional endoscopic resection (CER) is a widely accepted treatment for early colorectal neoplasia; however, large colorectal neoplasias remain problematic, as they necessitate piecemeal resection, increasing the risk of local recurrence. Endoscopic submucosal dissection (ESD) can improve the en bloc resection rate. This study aimed to evaluate local recurrence and its associated risk factors after endoscopic resection (ER) for colorectal neoplasias ≥20 mm. METHODS: A multicenter prospective study at 18 medium- and high-volume specialized institutions was conducted in Japan. Follow-up colonoscopy was performed after 12 months in cases of complete resection and after 3-6 months in cases of incomplete resection. Local recurrence was confirmed by endoscopic findings and/or pathological analysis. RESULTS: Follow-up colonoscopy was performed in 1,524 of 1,845 enrolled colorectal neoplasias (mean age, 65 years; 885 men; median tumor size, 32.8 mm). The local recurrence rates were 4.3% (65/1,524), 6.8% (55/808), and 1.4% (10/716) for the entire cohort, for CER, and for ESD, respectively. The relative risks of local recurrence were 0.21 (95% confidence interval, 0.11-0.39) with ESD compared with CER, 0.32 (95% confidence interval, 0.11-0.92) with en bloc ESD compared with en bloc CER, and 0.90 (95% confidence interval, 0.39-2.12) with piecemeal ESD compared with piecemeal CER. Significant factors associated with local recurrence were piecemeal resection, laterally spreading tumors of granular type, tumor size ≥40 mm, no pre-treatment magnification, and ≤10 years of experience in CER, and piecemeal resection only in ESD. CONCLUSIONS: En bloc ESD reduces the local recurrence rate for large colorectal neoplasias. Piecemeal resection is the most important risk factor for local recurrence regardless of the ER method used.

BACKGROUND AND STUDY AIMS: Resection of submucosal tumors by means of endoscopy has been reported using a variety of techniques, but cannot be performed safely in tumors originating from the muscularis propria. Using the submucosal tunnel created by the technique of peroral endoscopic myotomy (POEM), we report the first series describing the new technique of submucosal endoscopic tumor resection (SET) for tumors of the esophagus and cardia. PATIENTS AND METHODS: SET was attempted in nine consecutive patients with tumors (size >2cm) of either the esophagus or cardia with clinical indications for lesion removal. Following creation of a submucosal tunnel from 5 cm above the tumor, as described previously, the tumor was dissected from the overlying mucosa/submucosa and then carefully removed from the muscular layer using triangle-tip and insulated-tip knives. Following specimen retrieval through the tunnel, the orifice was closed by clips. RESULTS: Of the nine patients, two had tumors that were too large (60 mm and 75 mm, respectively) to allow safe removal due to loss of endoscopic overview. All remaining tumors (maximal tumor extension 12-30 mm) could be resected safely using this method. No complications occurred and follow-up was unremarkable. On histology, all tumors were resected completely (one gastrointestinal stromal tumor, five leiomyomas). The technique had to be modified in one patient with an aberrant pancreas. CONCLUSIONS: SET is a promising new technique for selected submucosal tumors in the esophagus and cardia up to a size of 4 cm and should be studied further.

BACKGROUND: Artificial intelligence (AI)-based polyp detection systems are used during colonoscopy with the aim of increasing lesion detection and improving colonoscopy quality. PATIENTS AND METHODS: We performed a systematic review and meta-analysis of prospective trials to determine the value of AI-based polyp detection systems for detection of polyps and colorectal cancer. We performed systematic searches in MEDLINE, EMBASE, and Cochrane CENTRAL. Independent reviewers screened studies and assessed eligibility, certainty of evidence, and risk of bias. We compared colonoscopy with and without AI by calculating relative and absolute risks and mean differences for detection of polyps, adenomas, and colorectal cancer. RESULTS: Five randomized trials were eligible for analysis. Colonoscopy with AI increased adenoma detection rates (ADRs) and polyp detection rates (PDRs) compared to colonoscopy without AI (values given with 95 %CI). ADR with AI was 29.6 % (22.2 % - 37.0 %) versus 19.3 % (12.7 % - 25.9 %) without AI; relative risk (RR] 1.52 (1.31 - 1.77), with high certainty. PDR was 45.4 % (41.1 % - 49.8 %) with AI versus 30.6 % (26.5 % - 34.6 %) without AI; RR 1.48 (1.37 - 1.60), with high certainty. There was no difference in detection of advanced adenomas (mean advanced adenomas per colonoscopy 0.03 for each group, high certainty). Mean adenomas detected per colonoscopy was higher for small adenomas (≤ 5 mm) for AI versus non-AI (mean difference 0.15 [0.12 - 0.18]), but not for larger adenomas (> 5 - ≤ 10 mm, mean difference 0.03 [0.01 - 0.05]; > 10 mm, mean difference 0.01 [0.00 - 0.02]; high certainty). Data on cancer are unavailable. CONCLUSIONS: AI-based polyp detection systems during colonoscopy increase detection of small nonadvanced adenomas and polyps, but not of advanced adenomas.

Background and AimsIn the treatment of ulcerative colitis (UC), an incremental benefit of achieving histologic healing beyond that of endoscopic mucosal healing has been suggested; persistent histologic inflammation increases the risk of exacerbation and dysplasia. However, identification of persistent histologic inflammation is extremely difficult using conventional endoscopy. Furthermore, the reproducibility of endoscopic disease activity is poor. We developed and evaluated a computer-aided diagnosis (CAD) system to predict persistent histologic inflammation using endocytoscopy (EC; 520-fold ultra-magnifying endoscope).MethodsWe evaluated the accuracy of the CAD system using test image sets. First, we retrospectively reviewed the data of 187 patients with UC from whom biopsy samples were obtained after endocytoscopic observation. EC images and biopsy samples of each patient were collected from 6 colorectal segments: cecum, ascending colon, transverse colon, descending colon, sigmoid colon, and rectum. All EC images were tagged with reference to the biopsy sample’s histologic activity. For validation samples, 525 validation sets of 525 independent segments were collected from 100 patients, and 12,900 EC images from the remaining 87 patients were used for machine learning to construct CAD. The primary outcome measure was the diagnostic ability of CAD to predict persistent histologic inflammation. Its reproducibility for all test images was also assessed.ResultsCAD provided diagnostic sensitivity, specificity, and accuracy as follows: 74% (95% confidence interval, 65%-81%), 97% (95% confidence interval, 95%-99%), and 91% (95% confidence interval, 83%-95%), respectively. Its reproducibility was perfect (κ = 1).ConclusionsOur CAD system potentially allows fully automated identification of persistent histologic inflammation associated with UC. In the treatment of ulcerative colitis (UC), an incremental benefit of achieving histologic healing beyond that of endoscopic mucosal healing has been suggested; persistent histologic inflammation increases the risk of exacerbation and dysplasia. However, identification of persistent histologic inflammation is extremely difficult using conventional endoscopy. Furthermore, the reproducibility of endoscopic disease activity is poor. We developed and evaluated a computer-aided diagnosis (CAD) system to predict persistent histologic inflammation using endocytoscopy (EC; 520-fold ultra-magnifying endoscope). We evaluated the accuracy of the CAD system using test image sets. First, we retrospectively reviewed the data of 187 patients with UC from whom biopsy samples were obtained after endocytoscopic observation. EC images and biopsy samples of each patient were collected from 6 colorectal segments: cecum, ascending colon, transverse colon, descending colon, sigmoid colon, and rectum. All EC images were tagged with reference to the biopsy sample’s histologic activity. For validation samples, 525 validation sets of 525 independent segments were collected from 100 patients, and 12,900 EC images from the remaining 87 patients were used for machine learning to construct CAD. The primary outcome measure was the diagnostic ability of CAD to predict persistent histologic inflammation. Its reproducibility for all test images was also assessed. CAD provided diagnostic sensitivity, specificity, and accuracy as follows: 74% (95% confidence interval, 65%-81%), 97% (95% confidence interval, 95%-99%), and 91% (95% confidence interval, 83%-95%), respectively. Its reproducibility was perfect (κ = 1). Our CAD system potentially allows fully automated identification of persistent histologic inflammation associated with UC.

Alport syndrome (AS) is a progressive hereditary renal disease that is characterized by sensorineural hearing loss and ocular abnormalities. It is divided into three modes of inheritance, namely, X-linked Alport syndrome (XLAS), autosomal recessive AS (ARAS), and autosomal dominant AS (ADAS). XLAS is caused by pathogenic variants in COL4A5, while ADAS and ARAS are caused by those in COL4A3/COL4A4. Diagnosis is conventionally made pathologically, but recent advances in comprehensive genetic analysis have enabled genetic testing to be performed for the diagnosis of AS as first-line diagnosis. Because of these advances, substantial information about the genetics of AS has been obtained and the genetic background of this disease has been revealed, including genotype-phenotype correlations and mechanisms of onset in some male XLAS cases that lead to milder phenotypes of late-onset end-stage renal disease (ESRD). There is currently no radical therapy for AS and treatment is only performed to delay progression to ESRD using nephron-protective drugs. Angiotensin-converting enzyme inhibitors can remarkably delay the development of ESRD. Recently, some new drugs for this disease have entered clinical trials or been developed in laboratories. In this article, we review the diagnostic strategy, genotype-phenotype correlation, mechanisms of onset of milder phenotypes, and treatment of AS, among others.

BACKGROUND: Artificial intelligence (AI) tools increase detection of precancerous polyps during colonoscopy and might contribute to long-term colorectal cancer prevention. The aim of the study was to investigate the incremental effect of the implementation of AI detection tools in screening colonoscopy on colorectal cancer incidence and mortality, and the cost-effectiveness of such tools. METHODS: We conducted Markov model microsimulation of using colonoscopy with and without AI for colorectal cancer screening for individuals at average risk (no personal or family history of colorectal cancer, adenomas, inflammatory bowel disease, or hereditary colorectal cancer syndrome). We ran the microsimulation in a hypothetical cohort of 100 000 individuals in the USA aged 50-100 years. The primary analysis investigated screening colonoscopy with versus without AI every 10 years starting at age 50 years and finishing at age 80 years, with follow-up until age 100 years, assuming 60% screening population uptake. In secondary analyses, we modelled once-in-life screening colonoscopy at age 65 years in adults aged 50-79 years at average risk for colorectal cancer. Post-polypectomy surveillance followed the simplified current guideline. Costs of AI tools and cost for downstream treatment of screening detected disease were estimated with 3% annual discount rates. The main outcome measures included the incremental effect of AI-assisted colonoscopy versus standard (no-AI) colonoscopy on colorectal cancer incidence and mortality, and cost-effectiveness of screening projected for the average risk screening US population. FINDINGS: In the primary analyses, compared with no screening, the relative reduction of colorectal cancer incidence with screening colonoscopy without AI tools was 44·2% and with screening colonoscopy with AI tools was 48·9% (4·8% incremental gain). Compared with no screening, the relative reduction in colorectal cancer mortality with screening colonoscopy with no AI was 48·7% and with screening colonoscopy with AI was 52·3% (3·6% incremental gain). AI detection tools decreased the discounted costs per screened individual from $3400 to $3343 (a saving of $57 per individual). Results were similar in the secondary analyses modelling once-in-life colonoscopy. At the US population level, the implementation of AI detection during screening colonoscopy resulted in yearly additional prevention of 7194 colorectal cancer cases and 2089 related deaths, and a yearly saving of US$290 million. INTERPRETATION: Our findings suggest that implementation of AI detection tools in screening colonoscopy is a cost-saving strategy to further prevent colorectal cancer incidence and mortality. FUNDING: European Commission and Japan Society of Promotion of Science.

BACKGROUND: Angiographic classifications of the location and severity of disease in the main vessel and side branch of coronary artery bifurcations have been proposed and applied to distal left main coronary artery (LMCA) bifurcation. METHODS AND RESULTS: We reviewed 140 angiograms of distal LMCA and ostial left anterior descending (LAD) and left circumflex (LCX) artery lesions with preintervention intravascular ultrasound (IVUS) of both the LAD and LCX arteries as well as the LMCA. Of 140 patients, 92.9% had at least 1 cross section with > or =40% IVUS plaque burden versus 57.2% of patients with an angiographic diameter stenosis > or =50%. Contrary to angiographic classifications, IVUS showed that bifurcation disease was rarely focal and that both sides of the flow divider were always disease-free. Continuous plaque from the LMCA into the proximal LAD artery was seen in 90%, from the LMCA into the LCX artery in 66.4%, and from the LMCA into both the LAD and LCX arteries in 62%. Plaque localized to either the LAD or LCX ostium and not involving the distal LMCA was seen in only 9.3% of LAD arteries and 17.1% of LCX arteries. Plaque distribution was not influenced by the LAD/LCX angiographic angle, lesion severity, LMCA length, or remodeling. We proposed an IVUS classification for bifurcation lesions illustrating longitudinal and circumferential spatial plaque distribution. CONCLUSIONS: Angiographic classification of LMCA bifurcation lesions is rarely accurate. IVUS shows that the carina is always spared and that the disease is diffuse rather than focal.

BACKGROUND: Artificial intelligence computer-aided detection (CADe) of colorectal neoplasia during colonoscopy may increase adenoma detection rates (ADRs) and reduce adenoma miss rates, but it may increase overdiagnosis and overtreatment of nonneoplastic polyps. PURPOSE: To quantify the benefits and harms of CADe in randomized trials. DESIGN: Systematic review and meta-analysis. (PROSPERO: CRD42022293181). DATA SOURCES: Medline, Embase, and Scopus databases through February 2023. STUDY SELECTION: Randomized trials comparing CADe-assisted with standard colonoscopy for polyp and cancer detection. DATA EXTRACTION: Adenoma detection rate (proportion of patients with ≥1 adenoma), number of adenomas detected per colonoscopy, advanced adenoma (≥10 mm with high-grade dysplasia and villous histology), number of serrated lesions per colonoscopy, and adenoma miss rate were extracted as benefit outcomes. Number of polypectomies for nonneoplastic lesions and withdrawal time were extracted as harm outcomes. For each outcome, studies were pooled using a random-effects model. Certainty of evidence was assessed using the GRADE (Grading of Recommendations Assessment, Development and Evaluation) framework. DATA SYNTHESIS: Twenty-one randomized trials on 18 232 patients were included. The ADR was higher in the CADe group than in the standard colonoscopy group (44.0% vs. 35.9%; relative risk, 1.24 [95% CI, 1.16 to 1.33]; low-certainty evidence), corresponding to a 55% (risk ratio, 0.45 [CI, 0.35 to 0.58]) relative reduction in miss rate (moderate-certainty evidence). More nonneoplastic polyps were removed in the CADe than the standard group (0.52 vs. 0.34 per colonoscopy; mean difference [MD], 0.18 polypectomy [CI, 0.11 to 0.26 polypectomy]; low-certainty evidence). Mean inspection time increased only marginally with CADe (MD, 0.47 minute [CI, 0.23 to 0.72 minute]; moderate-certainty evidence). LIMITATIONS: This review focused on surrogates of patient-important outcomes. Most patients, however, may consider cancer incidence and cancer-related mortality important outcomes. The effect of CADe on such patient-important outcomes remains unclear. CONCLUSION: The use of CADe for polyp detection during colonoscopy results in increased detection of adenomas but not advanced adenomas and in higher rates of unnecessary removal of nonneoplastic polyps. PRIMARY FUNDING SOURCE: European Commission Horizon 2020 Marie Skłodowska-Curie Individual Fellowship.

BACKGROUND & AIMS: Deep submucosal invasion (DSI) is considered a key risk factor for lymph node metastasis (LNM) and important criterion to recommend surgery in T1 colorectal cancer. However, metastatic risk for DSI is shown to be low in the absence of other histologic risk factors. This meta-analysis determines the independent risk of DSI for LNM. METHODS: Suitable studies were included to establish LNM risk for DSI in univariable analysis. To assess DSI as independent risk factor, studies were eligible if risk factors (eg, DSI, poor differentiation, lymphovascular invasion, and high-grade tumor budding) were simultaneously included in multivariable analysis or LNM rate of DSI was described in absence of poor differentiation, lymphovascular invasion, and high-grade tumor budding. Odds ratios (OR) and 95% CIs were calculated. RESULTS: Sixty-seven studies (21,238 patients) were included. Overall LNM rate was 11.2% and significantly higher for DSI-positive cancers (OR, 2.58; 95% CI, 2.10-3.18). Eight studies (3621 patients) were included in multivariable meta-analysis and did not weigh DSI as a significant predictor for LNM (OR, 1.73; 95% CI, 0.96-3.12). As opposed to a significant association between LNM and poor differentiation (OR, 2.14; 95% CI, 1.39-3.28), high-grade tumor budding (OR, 2.83; 95% CI, 2.06-3.88), and lymphovascular invasion (OR, 3.16; 95% CI, 1.88-5.33). Eight studies (1146 patients) analyzed DSI as solitary risk factor; absolute risk of LNM was 2.6% and pooled incidence rate was 2.83 (95% CI, 1.66-4.78). CONCLUSIONS: DSI is not a strong independent predictor for LNM and should be reconsidered as a sole indicator for oncologic surgery. The expanding armamentarium for local excision as first-line treatment prompts serious consideration in amenable cases to tailor T1 colorectal cancer management.

BACKGROUND AND STUDY AIMS: Video capsule endoscopy has been established in diagnosis of small-bowel disease and has been evaluated for esophageal pathology and recently for colorectal diagnostics. Gastric capsule endoscopy has not hitherto been feasible due to the stomach's large surface area and volume. We present the first application of a magnetically navigated capsule in the human stomach. PATIENTS AND METHODS: 29 volunteers and 24 patients (men 42, women 11; mean age 47.5 years) were included in a feasibility study. Low-level magnetic fields were used to maneuver the double-sensor video capsule within the human stomach with an air-water interface provided by ingestion of 1300 ml water within 1 hour before examination. Visualization of all parts of the stomach was attempted; time for visualization was recorded, and a subjective assessment of completeness of visualization was documented. RESULTS: There was technical failure in one individual; thus technical success rate was 98 %. In the 52 remaining cases, examiners assessed that the antrum, body, fundus, and cardia were fully visualized in 98 %, 96 %, 73 % and 75 %, respectively. Mean duration of examinations was 30 minutes (range 8 - 50), with a longer time (mean 37 minutes) for volunteers for study reasons. In total, 30 findings were identified: 14 were detected by both gastroscopy and capsule, 10 lesions were identified by guided capsule examination only, 6 by gastroscopy only. No significant capsule-related adverse events occurred. CONCLUSION: Magnetically navigated video capsule endoscopy appears to be feasible and sufficiently accurate for gastric examination. It may permit endoscopic examinations that are more patient-friendly and without sedation. Comparative studies are under way.