Design and evaluation of a colon cancer mobile application.

BACKGROUND: Colorectal cancer (CRC) is the third leading cause of cancer and the second cause of cancer-related deaths in the world. Despite the infrastructure and the availability of organized screening programs, participation in their screening programs is less than the set goals. Considering the importance of informing the society about the prevention and early detection of colorectal cancer symptoms and the positive impact of mobile health technologies, the present research was conducted with the aim of designing and evaluating a colon cancer mobile application. METHODS: The present research was conducted in two phases: software design and evaluation. In the first phase, the software was prepared using the cascade method. First, all the educational content related to colorectal cancer was collected through an expert panel with the participation of 10 specialists. Then the software was evaluated with alpha and beta testing, and the initial version was approved by users in terms of simplicity and usability. In the second phase, a parallel clinical randomized trial study was conducted with the aim of investigating the effect of a colon cancer mobile application on the early detection of colorectal cancer. In this stage, 204 volunteers participated; inclusion criteria were age 18-85 years, owning a smartphone and the ability to read and write. Participants were randomized into control and intervention groups. The intervention group was educated with the colon cancer application for education about colorectal cancer, and the control group was educated with a pamphlet. After education, both groups were screened for colorectal cancer symptoms, and the results were compared. RESULTS: In the software evaluation phase, the application was used by 204 users. In this stage, 84 (41.2%) women and 120 (58.8%) men, with an average (Standard Deviation) age of 47.53 (13.68) participated. Participants were randomized in two groups, 103 people with an average (Standard Deviation) age of 47.62 (14.65) in intervention group and 101 people with an average (Standard Deviation) age of 47.44 (12.70) in control group. There were no significant differences between the demographic characteristics of age, gender, marriage, occupation, instruction level, digestive disease history, cancer history, cancer risk factors, and family history of cancer between the two groups (P > 0.05). The Mann-Whitney U test indicated that there is a significant difference between the two groups of participants in self-assessment, willingness to do the screening, and the results of the assessment of colorectal cancer (P < 0.05). CONCLUSION: The results of the research indicated the positive impact of the Colon Cancer Application on the abilities of the users of self-assessment of colon cancer. Therefore, based on the findings, it can be concluded that the use of the colon cancer mobile application is effective for colon cancer prevention and self-care. TRIAL REGISTRATION: This study was registered in the Iranian Registry of Clinical Trials ( https://irct.behdasht.gov.ir ) on 13/2/2024, with the IRCT ID: IRCT20210131050189N9.

Application of artificial intelligence in pancreas endoscopic ultrasound imaging- A systematic review.

The pancreas is a vital organ in digestive system which has significant health implications. It is imperative to evaluate and identify malignant pancreatic lesions promptly in light of the high mortality rate linked to such malignancies. Endoscopic Ultrasound (EUS) is a non-invasive precise technique to detect pancreas disorders, but it is highly operator dependent. Artificial intelligence (AI), including traditional machine learning (ML) and deep learning (DL) techniques can play a pivotal role to enhancing the performance of EUS regardless of operator. AI performs a critical function in the detection, classification, and segmentation of medical images. The utilization of AI-assisted systems has improved the accuracy and productivity of pancreatic analysis, including the detection of diverse pancreatic disorders (e.g., pancreatitis, masses, and cysts) as well as landmarks and parenchyma. This systematic review examines the rapidly developing domain of AI-assisted system in EUS of the pancreas. Its objective is to present a thorough study of the present research status and developments in this area. This paper explores the significant challenges of AI-assisted system in pancreas EUS imaging, highlights the potential of AI techniques in addressing these challenges, and suggests the scope for future research in domain of AI-assisted EUS systems.

Rectal gastrointestinal stromal tumor (GIST) in a patient with Crohn's disease: a rare coincidence case report and brief literature review.

Gastrointestinal stromal tumors (GISTs) are the most common type of gastrointestinal mesenchymal tumors. The most common site for developing these neoplasms is the stomach and small intestine. In contrast, anorectal GISTs are very rare. Population-based studies have shown an increased risk of colorectal cancers (CRC) in patients with Crohn's disease (CD). As in sporadic CRC, adenocarcinomas are the most commonly observed tumor. Accordingly, it is expected that rectal mass in CD patients to be an adenocarcinoma. Some reports have presented CD cases with GISTs along the gastrointestinal tract; however, to the best of our knowledge, a rectal GIST has not been reported in CD. Herein, we report a 41-year-old woman with CD who presented with 8 weeks of constipation and was diagnosed with rectal GIST and briefly review existing reports regarding GIST in IBD.

Whole exome sequencing identifies MAP3K1, MSH2, and MLH1 as potential cancer-predisposing genes in familial early-onset colorectal cancer.

The incidence of early-onset colorectal cancer (CRC), which affects people under 50, is increasing for unknown reasons. Additionally, no underlying genetic cause is found in 20%-30% of patients suspected of having familial CRC syndrome. Whole exome sequencing (WES) has generated evidence for new genes associated with CRC susceptibility, but many patients remain undiagnosed. This study applied WES in five early-onset CRC patients from three unrelated families to identify novel genetic variants that could be linked to rapid disease development. Furthermore, the candidate variants were validated using Sanger sequencing. Two heterozygote variations, c.1077-2A>G and c.199G>A, were found in the MSH2 and the MLH1 genes, respectively. Sanger sequencing analysis confirmed that these (likely) pathogenic mutations segregated in all the affected families' members. In addition, we identified a rare heterozygote variant (c.175C>T) with suspected pathogenic potential in the MAP3K1 gene; formally the variant is of uncertain significance (VUS). Our findings support the hypothesis that CRC onset may be oligogenic and molecularly heterogeneous. Larger and more robust studies are needed to understand the genetic basis of early-onset CRC development, combined with novel functional analyses and omics approaches.