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OBJECTIVES: A computer-aided detection (CAD) system was developed to support the detection of colorectal lesions by deep learning using video images of lesions and normal mucosa recorded during colonoscopy. The study's purpose was to evaluate the stand-alone performance of this device under blinded conditions. METHODS: This multicenter prospective observational study was conducted at four Japanese institutions. We used 326 videos of colonoscopies recorded with patient consent at institutions in which the Ethics Committees approved the study. The sensitivity of successful detection of the CAD system was calculated using the target lesions, which were detected by adjudicators from two facilities for each lesion appearance frame; inconsistencies were settled by consensus. Successful detection was defined as display of the detection flag on the lesion for more than 0.5 s within 3 s of appearance. RESULTS: Of the 556 target lesions from 185 cases, detection success sensitivity was 97.5% (95% confidence interval [CI] 95.8-98.5%). The "successful detection sensitivity per colonoscopy" was 93% (95% CI 88.3-95.8%). For the frame-based sensitivity, specificity, positive predictive value, and negative predictive value were 86.6% (95% CI 84.8-88.4%), 84.7% (95% CI 83.8-85.6%), 34.9% (95% CI 32.3-37.4%), and 98.2% (95% CI 97.8-98.5%), respectively. TRIAL REGISTRATION: University Hospital Medical Information Network (UMIN000044622).
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Pólipos del Colon , Neoplasias Colorrectales , Humanos , Inteligencia Artificial , Pólipos del Colon/diagnóstico , Pólipos del Colon/patología , Colonoscopía/métodos , Neoplasias Colorrectales/diagnóstico , Computadores , Estudios ProspectivosRESUMEN
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).
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Inteligencia Artificial , Neoplasias Colorrectales , Humanos , Metástasis Linfática/patología , Estudios Retrospectivos , Endoscopía , Neoplasias Colorrectales/cirugía , Neoplasias Colorrectales/patología , Ganglios Linfáticos/patologíaRESUMEN
The present study examined the therapeutic effects of preoperative neoadjuvant chemoradiation therapy (NACRT) and predictive factors for complete clinical remission, compared the prognosis and costs of abdominoperineal resection (APR) and the "watch and wait" method (WW), and evaluated the usefulness of WW. In our department, patients with stage II-III lower rectal cancer requiring APR receive NACRT. NACRT was performed as a preoperative treatment (52 Gy + S-1: 80-120 mg/day × 25 days). Eight weeks after the completion of NACRT, rectal examination, endoscopic, computed tomography, and magnetic resonance imaging findings were evaluated to assess its therapeutic effects. APR was indicated for patients in whom endoscopic findings suggested a residual tumor in which a deep ulcer or marginal swelling remained or lymph node metastasis. However, WW was selected for patients who refused APR after informed consent was obtained. In the APR and WW groups, 5- and 20-year treatment costs after CRT were calculated using the Medical Fee Points of Japan in 2020. No significant differences were observed in 3-year disease-free survival rates for either parameter between the two groups. Regarding expenses, treatment costs were lower in the WW group than in the APR group. Organ preservation using active surveillance with CRT for rectal cancer requiring APR is feasible with the achievement of endoluminal complete remission.
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OBJECTIVES: Advances in endoscopic technology, including magnifying and image-enhanced techniques, have been attracting increasing attention for the optical characterization of colorectal lesions. These techniques are being implemented into clinical practice as cost-effective and real-time approaches. Additionally, with the recent progress in endoscopic interventions, endoscopic resection is gaining acceptance as a treatment option in patients with ulcerative colitis (UC). Therefore, accurate preoperative characterization of lesions is now required. However, lesion characterization in patients with UC may be difficult because UC is often affected by inflammation, and it may be characterized by a distinct "bottom-up" growth pattern, and even expert endoscopists have relatively little experience with such cases. In this systematic review, we assessed the current status and limitations of the use of optical characterization of lesions in patients with UC. METHODS: A literature search of online databases (MEDLINE via PubMed and CENTRAL via the Cochrane Library) was performed from 1 January 2000 to 30 November 2021. RESULTS: The database search initially identified 748 unique articles. Finally, 25 studies were included in the systematic review: 23 focused on differentiation of neoplasia from non-neoplasia, one focused on differentiation of UC-associated neoplasia from sporadic neoplasia, and one focused on differentiation of low-grade dysplasia from high-grade dysplasia and cancer. CONCLUSIONS: Optical characterization of neoplasia in patients with UC, even using advanced endoscopic technology, is still challenging and several issues remain to be addressed. We believe that the information revealed in this review will encourage researchers to commit to the improvement of optical diagnostics for UC-associated lesions.
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Colitis Ulcerosa , Neoplasias Colorrectales , Neoplasias , Humanos , Colitis Ulcerosa/diagnóstico , Colitis Ulcerosa/cirugía , Colitis Ulcerosa/complicaciones , Colonoscopía/métodos , Hiperplasia/complicaciones , Tecnología , Neoplasias Colorrectales/diagnóstico , Neoplasias Colorrectales/etiología , Neoplasias Colorrectales/cirugíaRESUMEN
OBJECTIVES: Ulcerative colitis-associated neoplasias (UCAN) are often flat with an indistinct boundary from surrounding tissues, which makes differentiating UCAN from non-neoplasias difficult. Pit pattern (PIT) has been reported as one of the most effective indicators to identify UCAN. However, regenerated mucosa is also often diagnosed as a neoplastic PIT. Endocytoscopy (EC) allows visualization of cell nuclei. The aim of this retrospective study was to demonstrate the diagnostic ability of combined EC irregularly-formed nuclei with PIT (EC-IN-PIT) diagnosis to identify UCAN. METHODS: This study involved patients with ulcerative colitis whose lesions were observed by EC. Each lesion was diagnosed by two independent expert endoscopists, using two types of diagnostic strategies: PIT alone and EC-IN-PIT. We evaluated and compared the diagnostic abilities of PIT alone and EC-IN-PIT. We also examined the difference in the diagnostic abilities of an EC-IN-PIT diagnosis according to endoscopic inflammation severity. RESULTS: We analyzed 103 lesions from 62 patients; 23 lesions were UCAN and 80 were non-neoplastic. EC-IN-PIT diagnosis had a significantly higher specificity and accuracy compared with PIT alone: 84% versus 58% (P < 0.001), and 88% versus 67% (P < 0.01), respectively. The specificity and accuracy were significantly higher for Mayo endoscopic score (MES) 0-1 than MES 2-3: 93% versus 68% (P < 0.001) and 95% versus 74% (P < 0.001), respectively. CONCLUSIONS: Our novel EC-IN-PIT strategy had a better diagnostic ability than PIT alone to predict UCAN from suspected and initially detected lesions using conventional colonoscopy. UMIN clinical trial (UMIN000040698).
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Colitis Ulcerosa , Neoplasias Colorrectales , Colitis Ulcerosa/diagnóstico por imagen , Colonoscopía , Humanos , Proyectos Piloto , Estudios RetrospectivosRESUMEN
BACKGROUND AND AIMS: Recently, the use of computer-aided detection (CADe) for colonoscopy has been investigated to improve the adenoma detection rate (ADR). We aimed to assess the efficacy of a regulatory-approved CADe in a large-scale study with high numbers of patients and endoscopists. METHODS: This was a propensity score-matched prospective study that took place at a university hospital between July 2020 and December 2020. We recruited patients aged ≥20 years who were scheduled for colonoscopy. Patients with polyposis, inflammatory bowel disease, or incomplete colonoscopy were excluded. We used a regulatory-approved CADe system and conducted a propensity score matching-based comparison of the ADR between patients examined with and without CADe as the primary outcome. RESULTS: During the study period, 2261 patients underwent colonoscopy with the CADe system or routine colonoscopy, and 172 patients were excluded in accordance with the exclusion criteria. Thirty endoscopists (9 nonexperts and 21 experts) were involved in this study. Propensity score matching was conducted using 5 factors, resulting in 1836 patients included in the analysis (918 patients in each group). The ADR was significantly higher in the CADe group than in the control group (26.4% vs 19.9%, respectively; relative risk, 1.32; 95% confidence interval, 1.12-1.57); however, there was no significant increase in the advanced neoplasia detection rate (3.7% vs 2.9%, respectively). CONCLUSIONS: The use of the CADe system for colonoscopy significantly increased the ADR in a large-scale prospective study including 30 endoscopists (Clinical trial registration number: UMIN000040677.).
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Adenoma , Neoplasias Colorrectales , Adenoma/diagnóstico por imagen , Inteligencia Artificial , Colonoscopía , Neoplasias Colorrectales/diagnóstico por imagen , Humanos , Puntaje de Propensión , Estudios ProspectivosRESUMEN
With the prevalence of endoscopic submucosal dissection and endoscopic full thickness resection, which enable complete resection of T1 colorectal cancer with a negative margin, the treatment strategy following endoscopic resection has become more important. The necessity of secondary surgical resection is determined on the basis of the risk of lymph node metastasis according to the histopathological findings of resected specimens because ~10% of T1 colorectal cancer cases have lymph node metastasis. The current Japanese treatment guidelines state four risk factors for lymph node metastasis: lymphovascular invasion, histological differentiation, depth of submucosal invasion, and tumor budding. These guidelines have succeeded in stratifying the low-risk group for lymph node metastasis, in which endoscopic resection alone is acceptable for cure. On the other hand, there are some problems: there is variation in diagnosis methods and low interobserver agreement for each pathological factor and 90% of surgical resections are unnecessary, with lymph node metastasis negativity. To ensure patients with T1 colorectal cancer receive more appropriate treatment, these problems should be addressed. In this systematic review, we gave some suggestions to these practical issues of four pathological factors as predictors.
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Neoplasias Colorrectales , Resección Endoscópica de la Mucosa , Neoplasias Colorrectales/patología , Neoplasias Colorrectales/cirugía , Humanos , Ganglios Linfáticos/patología , Ganglios Linfáticos/cirugía , Metástasis Linfática , Invasividad Neoplásica/patología , Estudios Retrospectivos , Factores de RiesgoRESUMEN
OBJECTIVES: Complete endoscopic healing, defined as Mayo endoscopic score (MES) = 0, is an optimal target in the treatment of ulcerative colitis (UC). However, some patients with MES = 0 show clinical relapse within 12 months. Histologic goblet mucin depletion has emerged as a predictor of clinical relapse in patients with MES = 0. We observed goblet depletion in vivo using an endocytoscope, and analyzed the association between goblet appearance and future prognosis in UC patients. METHODS: In this retrospective cohort study, all enrolled UC patients had MES = 0 and confirmed clinical remission between October 2016 and March 2020. We classified the patients into two groups according to the goblet appearance status: preserved-goblet and depleted-goblet groups. We followed the patients until March 2021 and evaluated the difference in cumulative clinical relapse rates between the two groups. RESULTS: We identified 125 patients with MES = 0 as the study subjects. Five patients were subsequently excluded. Thus, we analyzed the data for 120 patients, of whom 39 were classified as the preserved-goblet group and 81 as the depleted-goblet group. The patients were followed-up for a median of 549 days. During follow-up, the depleted-goblet group had a significantly higher cumulative clinical relapse rate than the preserved-goblet group (19% [15/81] vs. 5% [2/39], respectively; P = 0.02). CONCLUSIONS: Observing goblet appearance in vivo allowed us to better predict the future prognosis of UC patients with MES = 0. This approach may assist clinicians with onsite decision-making regarding treatment interventions without a biopsy.
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Colitis Ulcerosa , Colitis Ulcerosa/patología , Colonoscopía , Humanos , Mucosa Intestinal/patología , Recurrencia , Estudios Retrospectivos , Índice de Severidad de la EnfermedadRESUMEN
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.
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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 (≥â20âmm) 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 83.6â% 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 91.9â% (384/418, 95â% confidence interval [CI]: 88.8â%-94.3â%). Its sensitivity and specificity for differentiating cancer was 91.8â% (212/231, 95â% CI: 87.5â%-95.0â%) and 97.3â% (182/187, 95â% CI: 93.9â%-99.1â%), respectively. Conclusions The newly developed AI system designed for endocytoscopy showed excellent specificity in identifying colorectal cancer.
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Endocytoscopy (EC) is a contact-type optical endoscope that allows in vivo cellular observation during gastrointestinal endoscopy and is now commercially available not only in Japan but also in Asian, European Union, and Middle Eastern countries. EC helps conduct a highly accurate pathological prediction without biopsy. Initially, EC was reported to be effective for esophageal diseases. Subsequently, its efficacy for stomach and colorectal diseases has been reported. In this narrative review, we searched for clinical studies that investigated the efficacy of EC. EC seems to accurately diagnose gastrointestinal diseases without biopsy. Most of the studies aimed to clarify the relationship between endocytoscopic findings of gastrointestinal neoplasia and pathological diagnosis. Some studies have investigated non-epithelial lesions or diseases, such as inflammatory bowel disease or infectious diseases. However, there are few high-level pieces of evidence, such as randomized trials; thus, further studies are needed.
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The European Society of Gastrointestinal Endoscopy does not recommend self-expanding metal stent (SEMS) placement as a bridge to surgery (BTS) for malignant colorectal obstruction (MCRO). However, no universally accepted consensus has been determined. The present study aimed to evaluate the short- and long-term outcomes of SEMS placement vs. emergency surgery (ES) for MCRO. Surgical resection of colorectal cancer was performed in 3,840 patients between April 2001 and June 2016. Of these, 93 patients had MCRO requiring emergency decompression. Only patients in whom the colorectal lesion was ultimately resected were included; thus, the present study included 62 patients treated with MCRO via SEMS placement as a BTS (n=25) or via ES (n=37). The rates of laparoscopic surgery, primary anastomosis, stoma formation, lymph node dissection, adverse events, 30-day mortality and disease-free survival were evaluated. The clinical success rate of SEMS placement was 92.0% (23/25). Compared with the ES group, the SEMS group had higher rates of laparoscopic surgery (68.0 vs. 2.7%; P<0.001) and primary anastomosis (88.0 vs. 51.4%; P=0.003), a greater number of dissected lymph nodes (30 vs. 18; P=0.001), and lower incidences of stoma formation (24.0 vs. 67.6%; P=0.002) and overall adverse events (24.0 vs. 62.2%; P=0.004). The 30-day mortality and disease-free survival of the SEMS group were not significantly different to that of the ES group (0 vs. 2.7%; P=1.000; log-rank test; P=0.10). In conclusion, as long as adverse events such as perforation are minimized, SEMS placement as a BTS could be a first treatment option for MCRO. The present study is registered in the University Hospital Medical Network Clinical Trials Registry (UMIN R000034868).
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OBJECTIVES: To compare the efficacy and safety of oral sulfate solution administered using the same-day dose and the split-dose regimens with those of polyethylene glycol plus ascorbate solution, used for bowel preparation in Japanese patients undergoing colonoscopy. METHODS: This multicenter (n = 13), randomized, active-controlled, colonoscopist- and image evaluator-blinded, noninferiority study with parallel-group comparison recruited 632 patients from December 2018 to June 2019. Of these, 602 patients were divided into the oral sulfate solution same-day dose group (n = 200); oral sulfate solution split-dose group (n = 202); and polyethylene glycol plus ascorbate same-day dose group (n = 200). Differences in the efficacy rates between the polyethylene glycol plus ascorbate group and each oral sulfate solution group were calculated using the asymptotic method. The safety of the oral sulfate solution was evaluated, based on the occurrence of adverse events and reactions. RESULTS: Both oral sulfate solution protocols were confirmed as noninferior to the polyethylene glycol plus ascorbate protocol for bowel-cleansing. The occurrence of adverse reactions was significantly lower in the oral sulfate solution same-day dose group than in the polyethylene glycol plus ascorbate group (P = 0.010). The occurrence of adverse reactions was not significantly different between the oral sulfate solution split-dose and the polyethylene glycol plus ascorbate group. CONCLUSIONS: Oral sulfate solution is not only safe and efficacious but also not inferior to polyethylene glycol plus ascorbate solution (active control). It could be used for bowel preparation in Japanese patients scheduled for colonoscopy (Clinical trial registration number: NCT03794310).
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Catárticos , Colonoscopía , Catárticos/efectos adversos , Humanos , Japón , Polietilenglicoles/efectos adversos , SulfatosRESUMEN
BACKGROUND AND AIMS: Artificial intelligence (AI)-assisted polyp detection systems for colonoscopic use are currently attracting attention because they may reduce the possibility of missed adenomas. However, few systems have the necessary regulatory approval for use in clinical practice. We aimed to develop an AI-assisted polyp detection system and to validate its performance using a large colonoscopy video database designed to be publicly accessible. METHODS: To develop the deep learning-based AI system, 56,668 independent colonoscopy images were obtained from 5 centers for use as training images. To validate the trained AI system, consecutive colonoscopy videos taken at a university hospital between October 2018 and January 2019 were searched to construct a database containing polyps with unbiased variance. All images were annotated by endoscopists according to the presence or absence of polyps and the polyps' locations with bounding boxes. RESULTS: A total of 1405 videos acquired during the study period were identified for the validation database, 797 of which contained at least 1 polyp. Of these, 100 videos containing 100 independent polyps and 13 videos negative for polyps were randomly extracted, resulting in 152,560 frames (49,799 positive frames and 102,761 negative frames) for the database. The AI showed 90.5% sensitivity and 93.7% specificity for frame-based analysis. The per-polyp sensitivities for all, diminutive, protruded, and flat polyps were 98.0%, 98.3%, 98.5%, and 97.0%, respectively. CONCLUSIONS: Our trained AI system was validated with a new large publicly accessible colonoscopy database and could identify colorectal lesions with high sensitivity and specificity. (Clinical trial registration number: UMIN 000037064.).
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Adenoma , Pólipos del Colon , Adenoma/diagnóstico por imagen , Inteligencia Artificial , Pólipos del Colon/diagnóstico por imagen , Colonoscopía , Computadores , HumanosRESUMEN
The global incidence and mortality rate of colorectal cancer remains high. Colonoscopy is regarded as the gold standard examination for detecting and eradicating neoplastic lesions. However, there are some uncertainties in colonoscopy practice that are related to limitations in human performance. First, approximately one-fourth of colorectal neoplasms are missed on a single colonoscopy. Second, it is still difficult for non-experts to perform adequately regarding optical biopsy. Third, recording of some quality indicators (e.g. cecal intubation, bowel preparation, and withdrawal speed) which are related to adenoma detection rate, is sometimes incomplete. With recent improvements in machine learning techniques and advances in computer performance, artificial intelligence-assisted computer-aided diagnosis is being increasingly utilized by endoscopists. In particular, the emergence of deep-learning, data-driven machine learning techniques have made the development of computer-aided systems easier than that of conventional machine learning techniques, the former currently being considered the standard artificial intelligence engine of computer-aided diagnosis by colonoscopy. To date, computer-aided detection systems seem to have improved the rate of detection of neoplasms. Additionally, computer-aided characterization systems may have the potential to improve diagnostic accuracy in real-time clinical practice. Furthermore, some artificial intelligence-assisted systems that aim to improve the quality of colonoscopy have been reported. The implementation of computer-aided system clinical practice may provide additional benefits such as helping in educational poorly performing endoscopists and supporting real-time clinical decision-making. In this review, we have focused on computer-aided diagnosis during colonoscopy reported by gastroenterologists and discussed its status, limitations, and future prospects.
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Adenoma , Pólipos del Colon , Neoplasias Colorrectales , Inteligencia Artificial , Ciego , Colonoscopía , Neoplasias Colorrectales/diagnóstico por imagen , HumanosRESUMEN
BACKGROUND & AIMS: In accordance with guidelines, most patients with T1 colorectal cancers (CRC) undergo surgical resection with lymph node dissection, despite the low incidence (â¼10%) of metastasis to lymph nodes. To reduce unnecessary surgical resections, we used artificial intelligence to build a model to identify T1 colorectal tumors at risk for metastasis to lymph node and validated the model in a separate set of patients. METHODS: We collected data from 3134 patients with T1 CRC treated at 6 hospitals in Japan from April 1997 through September 2017 (training cohort). We developed a machine-learning artificial neural network (ANN) using data on patients' age and sex, as well as tumor size, location, morphology, lymphatic and vascular invasion, and histologic grade. We then conducted the external validation on the ANN model using independent 939 patients at another hospital during the same period (validation cohort). We calculated areas under the receiver operator characteristics curves (AUCs) for the ability of the model and US guidelines to identify patients with lymph node metastases. RESULTS: Lymph node metastases were found in 319 (10.2%) of 3134 patients in the training cohort and 79 (8.4%) of /939 patients in the validation cohort. In the validation cohort, the ANN model identified patients with lymph node metastases with an AUC of 0.83, whereas the guidelines identified patients with lymph node metastases with an AUC of 0.73 (P < .001). When the analysis was limited to patients with initial endoscopic resection (n = 517), the ANN model identified patients with lymph node metastases with an AUC of 0.84 and the guidelines identified these patients with an AUC of 0.77 (P = .005). CONCLUSIONS: The ANN model outperformed guidelines in identifying patients with T1 CRCs who had lymph node metastases. This model might be used to determine which patients require additional surgery after endoscopic resection of T1 CRCs. UMIN Clinical Trials Registry no: UMIN000038609.
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Neoplasias Colorrectales/patología , Escisión del Ganglio Linfático/estadística & datos numéricos , Metástasis Linfática/diagnóstico , Aprendizaje Automático , Factores de Edad , Anciano , Colectomía/estadística & datos numéricos , Colon/diagnóstico por imagen , Colon/patología , Colon/cirugía , Colonoscopía/estadística & datos numéricos , Neoplasias Colorrectales/diagnóstico , Neoplasias Colorrectales/cirugía , Femenino , Estudios de Seguimiento , Humanos , Japón/epidemiología , Ganglios Linfáticos/diagnóstico por imagen , Ganglios Linfáticos/patología , Ganglios Linfáticos/cirugía , Metástasis Linfática/terapia , Masculino , Persona de Mediana Edad , Estadificación de Neoplasias , Curva ROC , Estudios Retrospectivos , Medición de Riesgo/métodos , Factores de RiesgoRESUMEN
BACKGROUND: In cases of Hirschsprung disease, complete and reproducible resection of the aganglionic bowel is ideal to achieve good postoperative bowel function. Reliable identification of the upper margin of the surgical anal canal, which is the squamous-columnar junction, is necessary during transanal pull-through. Here, we describe a novel staining technique using Lugol's iodine stain to visualize the upper margin of the surgical anal canal. METHODS: Lugol's iodine staining was performed in five patients with Hirschsprung disease treated using a single-stage laparoscopic transanal pull-through modified Swenson procedure. In two of these patients, endocytoscopic observation with ultra-high magnification was performed using methylene blue and crystal violet to mark the border of the squamous epithelium at 1 week before surgery. The alignment between the incisional line, which was revealed using Lugol's iodine staining and endocytoscopic marking, was evaluated. Complications, including postoperative bowel dysfunction, were evaluated. RESULTS: In all cases, Lugol's iodine staining produced a well-demarcated line. The endocytoscopic marking of the upper margin of the surgical anal canal was aligned with the line revealed by Lugol's iodine staining. There were no complications associated with the transanal pull-through procedure, including postoperative bowel dysfunction. CONCLUSIONS: Lugol's iodine staining could be a safe and practical method to visualize the upper margin of the surgical anal canal intraoperatively. This finding may be useful for surgeons to make a consistent removal of the aganglionic bowel during surgery for Hirschsprung disease.
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Canal Anal/cirugía , Carcinoma de Células Escamosas/diagnóstico , Enfermedad de Hirschsprung/diagnóstico , Yoduros , Carcinoma de Células Escamosas/cirugía , Enfermedad de Hirschsprung/cirugía , Humanos , Coloración y EtiquetadoRESUMEN
BACKGROUND: Endocytoscopy is a next-generation endoscopic system that facilitates real-time histopathologic endoscopic diagnosis of colorectal lesions by virtue of its 520 × maximum magnification. CASE SUMMARY: We present the case of a 63-year-old man with sigmoid colon cancer who was regularly referred for follow-up colonoscopy after endoscopic resection of T1 rectal cancer. Colonoscopy revealed a 12 mm reddish polyp, including a depression and a flat area in the sigmoid colon. Endocytoscopic observation showed unclear gland formation and agglomeration of distorted nuclei (depression), suggesting a submucosal invasive (T1) cancer. In the flat area, slit-like smooth lumens and regular pattern of fusiform nuclei were found, suggesting an adenoma. On the basis of these endocytoscopic findings, we predicted this lesion as T1 cancer (depression) with adenoma (flat area) and performed endoscopic resection corresponding to the final histopathological diagnosis. CONCLUSION: We could perform an optical diagnosis of T1 sigmoid cancer with adenoma by using endocytoscopy before treatment.
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PURPOSE: Although some studies have reported differences in clinicopathological features between left- and right-sided advanced colorectal cancer (CRC), there are few reports regarding early-stage disease. In this study, we aimed to compare the clinicopathological features of left- and right-sided T1 CRC. METHODS: Subjects were 1142 cases with T1 CRC undergoing surgical or endoscopic resection between 2001 and 2018 at Showa University Northern Yokohama Hospital. Of these, 776 cases were left-sided (descending colon to rectum) and 366 cases were right-sided (cecum to transverse colon). We compared clinical (patients age, sex, tumor size, morphology, initial treatment) and pathological features (invasion depth, histological grade, lymphatic invasion, vascular invasion, tumor budding) including lymph node metastasis (LNM). RESULTS: Left-sided T1 CRC showed significantly higher rates of LNM (left-sided 12.0% vs. right-sided 5.4%, P < 0.05) and lymphatic invasion (left-sided 32.7% vs. right-sided 23.2%, P < 0.05). Especially, the sigmoid colon and rectum showed higher rates of LNM (12.4% and 12.1%, respectively) than other locations. Patients with left-sided T1 CRC were younger than those with right-sided T1 CRC (64.9 years ±11.5 years vs. 68.7 ± 11.6 years, P < 0.05), as well as significantly lower rates of poorly differentiated carcinoma/mucinous carcinoma than right-sided T1 CRC (11.6% vs. 16.1%, P < 0.05). CONCLUSION: Left-sided T1 CRC, especially in the sigmoid colon and rectum, exhibited higher rates of LNM than right-sided T1 CRC, followed by higher rates of lymphatic invasion. These results suggest that tumor location should be considered in decisions regarding additional surgery after endoscopic resection. TRIAL REGISTRATION: This study was registered with the University Hospital Medical Network Clinical Trials Registry ( UMIN 000032733 ).