Role of colonoscopy in colorectal cancer screening: Available evidence

Fundamentals and research progression on electrochemical sensing of colorectal cancer

Colorectal cancer (CRC) is a type of malignant disease that affects the large intestine (colon) and rectum. The CRC is among the causes of the highest mortality rates worldwide, so its rapid and sensitive early diagnosis is substantial. In the last few decades, CRC detection by electrochemical biosensors has progressed significantly due to their amenability and cost-effectiveness. Various electrochemical sensing strategies have been implemented, involving CRC biomarkers, such as protein, gene, or even CRC cells, that play a crucial role in screening tests, treatment, and prognosis. Electrochemical sensors are favored in this regard, owing to their ability to provide real-time, on-site detection with a straightforward preparation of samples. The present work provides an overview from the basic concepts to the recent research advances in electrochemical CRC biosensors for the management of patients. The review covers the importance of CRC detection, an introduction to electrochemical sensors, and cutting-edge electrochemical CRC biosensors. Further, challenges, limitations, and future research directions in developing and applying electrochemical sensing tools for CRC biomarkers are also comprehensively discussed. By consolidating the current research status, the present work aims to inspire further innovation in the development of electrochemical CRC biosensors. The insights presented here are expected to contribute to advancing more efficient, accessible diagnostic devices for CRC in the future.

Clinical value of multi-slice spiral CT in evaluating preoperative TNN staging and postoperative recurrence and metastasis of colon carcinoma

OBJECTIVE

To evaluate the clinical value of multi-slice spiral CT in preoperative TNN staging and postoperative recurrence and metastasis of colon carcinoma, and to provide evidence for the reliability of CT in the diagnosis of colon carcinoma METHODS: 89 patients with colon carcinoma diagnosed pathologically in our hospital from July 2020 to April 2023 were selected retrospectively. The preoperative TNN staging and postoperative recurrence and metastasis were monitored by 64 row 128 layer spiral CT. The diagnostic coincidence rate, TNM staging coincidence rate and postoperative recurrent TNM staging accuracy were evaluated according to the pathological diagnosis RESULTS: The diagnostic coincidence rate of multi-slice spiral CT was 97.8 % (87/89), and the detection rate of lymph nodes was 86.1 % (31/36). The coincidence rate of T staging was 93.3 % (83/89), N staging was 91.0 % (81/89), M staging was 100 % (Kappa=0.897,0.879, 1.000). The diagnosis of recurrent TNM stage was consistent (Kappa=0.893, 0.801, 1.000) CONCLUSION: Multi-slice spiral CT is of high diagnostic coincidence rate, high accuracy of TNM staging and rapid noninvasive examination. It can obtain reliable results in preoperative staging and postoperative recurrence and metastasis diagnosis, which is worth popularizing in clinic.

Fecal miRNAs as potential biomarkers for early detection of colorectal cancer: An updated review

•The first comprehensive summarization of miRNA profiles from stool samples. •Fecal miRNAs show promise as reliable biomarkers for early detection of CRC. •Fecal miRNAs have particular advantages for integration into FIT-guided CRC screening.

Colorectal cancer detection with enhanced precision using a hybrid supervised and unsupervised learning approach

The current work introduces the hybrid ensemble framework for the detection and segmentation of colorectal cancer. This framework will incorporate both supervised classification and unsupervised clustering methods to present more understandable and accurate diagnostic results. The method entails several steps with CNN models: ADa-22 and AD-22, transformer networks, and an SVM classifier, all inbuilt. The CVC ClinicDB dataset supports this process, containing 1650 colonoscopy images classified as polyps or non-polyps. The best performance in the ensembles was done by the AD-22 + Transformer + SVM model, with an AUC of 0.99, a training accuracy of 99.50%, and a testing accuracy of 99.00%. This group also saw a high accuracy of 97.50% for Polyps and 99.30% for Non-Polyps, together with a recall of 97.80% for Polyps and 98.90% for Non-Polyps, hence performing very well in identifying both cancerous and healthy regions. The framework proposed here uses K-means clustering in combination with the visualisation of bounding boxes, thereby improving segmentation and yielding a silhouette score of 0.73 with the best cluster configuration. It discusses how to combine feature interpretation challenges into medical imaging for accurate localization and precise segmentation of malignant regions. A good balance between performance and generalization shall be done by hyperparameter optimization-heavy learning rates; dropout rates and overfitting shall be suppressed effectively. The hybrid schema of this work treats the deficiencies of the previous approaches, such as incorporating CNN-based effective feature extraction, Transformer networks for developing attention mechanisms, and finally the fine decision boundary of the support vector machine. Further, we refine this process via unsupervised clustering for the purpose of enhancing the visualisation of such a procedure. Such a holistic framework, hence, further boosts classification and segmentation results by generating understandable outcomes for more rigorous benchmarking of detecting colorectal cancer and with higher reality towards clinical application feasibility.

The diagnostic value of serum Ephrin-A1 in patients with colorectal cancer

Colorectal cancer (CRC) is one of the most common malignant tumors worldwide, with a high incidence rate and mortality. The analysis of serum biomarkers for colorectal cancer diagnosis has attracted more and more attention because of its low cost, repeatability, and quantification. This study was aimed to evaluate the diagnostic performance of serum Ephrin-A1 in patients with CRC. We retrospectively analyzed CRC cases in a test cohort (121 patients and 108 controls) and validated them in a validation cohort (119 patients and 118 controls). The concentration of Ephrin-A1 in serum was detected by Enzyme-linked immunosorbent assay (ELISA) and the diagnostic performance of serum Ephrin-A1 was evaluated by receiver operating characteristic (ROC) analysis. In the test cohort, serum Ephrin-A1 levels in patients with all-stage CRC and early-stage CRC were significantly higher than those in healthy controls. The area under the ROC curve (AUC), sensitivity and specificity of all-stage CRC and early-stage CRC were 0.709 (95% CI 0.644-0.775) and 0.660 (95% CI 0.530-0.790), 48.76% and 45.00%, 81.48% and 81.48%, respectively. Similar results were observed in the validation cohort. Serum Ephrin-A1 might be served as a potential biomarker in the diagnosis of CRC.

Colorectal Cancer: Epidemiology, Risk Factors, and Prevention

Colorectal cancer (CRC) is the third most common cancer and the second most common cause of cancer mortality worldwide. There are disparities in the epidemiology of CRC across different populations, most probably due to differences in exposure to lifestyle and environmental factors related to CRC. Prevention is the most effective method for controlling CRC. Primary prevention includes determining and avoiding modifiable risk factors (e.g., alcohol consumption, smoking, and dietary factors) as well as increasing protective factors (e.g., physical activity, aspirin). Further studies, especially randomized, controlled trials, are needed to clarify the association between CRC incidence and exposure to different risk factors or protective factors. Detection and removal of precancerous colorectal lesions is also an effective strategy for controlling CRC. Multiple factors, both at the individual and community levels (e.g., patient preferences, availability of screening modalities, costs, benefits, and adverse events), should be taken into account in designing and implementing CRC screening programs. Health policymakers should consider the best decision in identifying the starting age and selection of the most effective screening strategies for the target population. This review aims to present updated evidence on the epidemiology, risk factors, and prevention of CRC.