• Artificial intelligence
• Cancer
• Clinical trial
• Deep learning
• Detection
• Machine learning
• Treatment

• Humans
• Neoplasms/diagnosis
• Neoplasms/therapy
• Neoplasms/diagnostic imaging
• Artificial Intelligence
• Machine Learning
• Medical Oncology/methods
• Neural Networks, Computer
• Deep Learning

• Humans
• Capsule Endoscopy/methods
• Capsule Endoscopy/instrumentation
• Capsule Endoscopy/adverse effects
• Gastrointestinal Hemorrhage/diagnosis
• Gastrointestinal Hemorrhage/etiology
• Intestine, Small

• Ulcerative colitis; colon capsule endoscopy; inflammatory bowel disease

• Humans
• Capsule Endoscopy/adverse effects
• Capsule Endoscopy/methods
• Colitis, Ulcerative/diagnosis
• Colitis, Ulcerative/diagnostic imaging
• Colonoscopy/methods
• Intestinal Mucosa/pathology
• Intestinal Mucosa/diagnostic imaging
• Predictive Value of Tests
• Sensitivity and Specificity

• Artificial intelligence
• Crohn's disease
• Inflammatory bowel disease
• Pan-enteric capsule
• Video capsule endoscopy

• Humans
• Capsule Endoscopy/methods
• Inflammatory Bowel Diseases/diagnosis
• Inflammatory Bowel Diseases/diagnostic imaging
• Crohn Disease/diagnosis
• Crohn Disease/diagnostic imaging
• Intestine, Small/diagnostic imaging
• Intestine, Small/pathology
• Intestinal Mucosa/pathology
• Intestinal Mucosa/diagnostic imaging

• artificial intelligence
• colon capsule endoscopy
• convolutional neural network

• Capsule endoscopy
• Crohn’s disease
• Digestive bleeding
• Inflammatory bowel disease
• Pan-enteric endoscopy

• cancer
• colon
• colon cancer
• colon cancer prevention
• colon cancer surveillance
• colon polyps
• colonoscopy
• colorectal cancer
• fit test
• fobt

• artificial intelligence in medicine
• colo-rectal carcinoma
• colon cancer prevention
• flexible sigmoidoscopy
• presence of blood in stool
• screening colonoscopy
• serum biomarkers

• Colorectal cancer
• DNA methylation
• DNA mutation
• circulating tumor cells
• colon capsule endoscopy
• cost effectiveness
• microRNA
• microbial markers
• screening
• virtual colonoscopy

• artificial intelligence
• colorectal cancer
• liquid biopsy
• patients stratification
• robotic surgery

• Unitatea Executiva pentru Finantarea Invatamantului Superior, a Cercetarii, Dezvoltarii si Inovarii

• Chromoendoscopy
• Colitis screening
• Colitis surveillance
• Colorectal cancer
• Inflammatory bowel disease
• Ulcerative colitis

• Colitis/complications
• Colonoscopy/methods
• Colorectal Neoplasms/diagnosis
• Colorectal Neoplasms/epidemiology
• Colorectal Neoplasms/etiology
• Early Detection of Cancer/methods
• Humans
• Inflammatory Bowel Diseases/complications
• Inflammatory Bowel Diseases/diagnosis
• Inflammatory Bowel Diseases/pathology

Colorectal cancer is the most common malignancy and the third leading cause of cancer-related death worldwide. This study aimed to identify potential diagnostic biomarkers for colorectal cancer by genome-wide plasma cell-free DNA (cfDNA) methylation analysis.

Peripheral blood from colorectal cancer patients and healthy controls was collected for cfDNA extraction. Genome-wide cfDNA methylation profiling, especially differential methylation profiling between colorectal cancer patients and healthy controls, was performed by methylated DNA immunoprecipitation coupled with high-throughput sequencing (MeDIP-seq). Logistic regression models were established, and the accuracy of this diagnostic model for colorectal cancer was verified using tissue-sourced data from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) due to the lack of cfDNA methylation data in public datasets.

Compared with the control group, 939 differentially methylated regions (DMRs) located in promoter regions were found in colorectal cancer patients; 16 of these DMRs were hypermethylated, and the remaining 923 were hypomethylated. In addition, these hypermethylated genes, mainly PRDM14, RALYL, ELMOD1, and TMEM132E, were validated and confirmed in colorectal cancer by using publicly available DNA methylation data.

MeDIP-seq can be used as an optimal approach for analyzing cfDNA methylomes, and 12 probes of four differentially methylated genes identified by MeDIP-seq (PRDM14, RALYL, ELMOD1, and TMEM132E) could serve as potential biomarkers for clinical application in patients with colorectal cancer.

The online version contains supplementary material available at 10.1186/s12957-022-02487-4.

• Biomarkers
• Colorectal cancer
• MeDIP-seq
• cfDNA

The COVID-19 pandemic has caused considerable disruption in healthcare services and has had a substantial impact on the care of patients with chronic diseases, such as inflammatory bowel disease. Endoscopy services were significantly restricted, resulting in long waiting lists. There has been a growing interest in the use of capsule endoscopy in the diagnostic pathway and management of these patients. This review explores the published literature on the role of colon capsule endoscopy in ulcerative colitis and Crohn’s disease as a method for mucosal assessment of extent, severity, and response to treatment. Colon capsule preparation regimens and scoring systems are reported. The studies indicate that, despite inherent limitations of minimally invasive capsule endoscopy, there is increasing evidence to support the use of the second-generation colon capsule in inflammatory bowel disease evaluation, providing an additional pathway to expedite investigation of appropriate patients especially during and after the pandemic.

Colon capsule endoscopy (CCE), which became clinically applicable in 2006, is a simple and noninvasive procedure to evaluate colonic diseases; the accuracy of second-generation CCE, introduced in 2009, has dramatically improved. Currently, CCE is used as an alternative method for colorectal cancer screening, as well as for evaluating the mucosal lesions of inflammatory bowel disease, in cases where performing colonoscopy (CS) is difficult. However, the outcomes of CCE are uncertain.

To investigate the outcomes of Japanese patients with negative findings (no polyps or colorectal cancer) on initial CCE.

This retrospective, single-center study was conducted at the Endoscopic Center at Aishinkai Nakae Hospital. This study included patients who underwent continuous CCE between November 2013 and August 2019, that exhibited no evidence of polyps or colorectal cancer at the initial CCE, and could be followed up using either the fecal immunochemical test (FIT), CS, or CCE. The observational period, follow-up method, presence or absence of polyps and colorectal cancer, pathological diagnosis, and number of colorectal cancer deaths were evaluated.

Thirty-one patients (mean age, 60.4 ± 15.6 years; range, 28–84 years; 14 men and 17 women) were enrolled in this study. The reasons for performing the first CCE were screening in 12, a positive FIT in six, lower abdominal pain in nine, diarrhea in two, and anemia in two patients. The mean total water volume at the time of examination was 3460 ± 602 mL (2250–4800 mL), and a total CS was performed in 28 patients (90%). The degree of cleanliness was excellent in 15 patients and good in 16, and no poor cases were observed. No adverse events, such as retention or capsule aspiration, were observed in any of the patients. The mean follow-up period was 3.1 ± 1.5 years (range, 0.3–5.5 years). Follow-up included FIT in nine, CS in 20, and CCE in four patients (including duplicate patients). The FIT was positive in two patients, while CS revealed five polyp lesions (three in the ascending colon, one in the transverse colon, and one in the descending colon), with sizes ranging between 2 mm and 8 mm. Histopathological findings revealed a hyperplastic polyp in one patient, and adenoma with low grade dysplasia in four patients; colorectal cancers were not recognized. In the follow-up example by CCE, polyps and colorectal cancer could not be recognized. During the follow-up period, there were no deaths due to colorectal cancer in any of the patients.

We determined the outcomes in patients with negative initial CCE findings.

• Colon capsule endoscopy
• Negative findings
• Observation
• Colorectal polyps
• Colorectal cancer
• Colorectal cancer death

Capsule endoscopy (CE) is the only non-invasive diagnostic tool that enables the direct visualization of the gastrointestinal (GI) tract. Even though CE was initially developed for small-bowel investigation, its clinical application is expanding, and technological advances continue. The final iteration of CE will be a mouth to anus (M2A) capsule that investigates the entire GI tract by the ingestion of a single capsule. This narrative review describes the current developmental status of CE and discusses the possibility of realizing an M2A capsule and what needs to be overcome in the future.

• M2A capsule
• active locomotion
• capsule endoscopy
• gastrointestinal tract
• pan-endoscopy

The development of artificial intelligence (AI) algorithms has permeated the medical field with great success. The widespread use of AI technology in diagnosing and treating several types of cancer, especially colorectal cancer (CRC), is now attracting substantial attention. CRC, which represents the third most commonly diagnosed malignancy in both men and women, is considered a leading cause of cancer-related deaths globally. Our review herein aims to provide in-depth knowledge and analysis of the AI applications in CRC screening, diagnosis, and treatment based on current literature. We also explore the role of recent advances in AI systems regarding medical diagnosis and therapy, with several promising results. CRC is a highly preventable disease, and AI-assisted techniques in routine screening represent a pivotal step in declining incidence rates of this malignancy. So far, computer-aided detection and characterization systems have been developed to increase the detection rate of adenomas. Furthermore, CRC treatment enters a new era with robotic surgery and novel computer-assisted drug delivery techniques. At the same time, healthcare is rapidly moving toward precision or personalized medicine. Machine learning models have the potential to contribute to individual-based cancer care and transform the future of medicine.

• artificial intelligence
• colonoscopy
• colorectal cancer
• computer-aided detection
• computer-aided diagnosis
• precision oncology
• robotic-assisted surgery
• screening
• therapy

• Adenoma
• Artificial Intelligence
• Colonoscopy
• Colorectal Neoplasms/diagnosis
• Colorectal Neoplasms/epidemiology
• Colorectal Neoplasms/therapy
• Early Detection of Cancer
• Female
• Humans
• Male

• artificial intelligence
• colon cancer
• colonoscopy
• colorectal cancer
• computer-aided diagnosis
• polyp
• screening

• colorectal cancer
• disposable endoscopes
• endoscopic mucosal resection
• endoscopic submucosal dissection
• robotic endoscopy