Evaluation of Nursing Effects of Pelvic Floor Muscle Rehabilitation Exercise on Gastrointestinal Tract Rectal Cancer Patients Receiving Anus-preserving Operation by Intelligent Algorithm-based Magnetic Resonance Imaging

Current Status and Role of Artificial Intelligence in Anorectal Diseases and Pelvic Floor Disorders

Background

Anorectal diseases and pelvic floor disorders are prevalent among the general population. Patients may present with overlapping symptoms, delaying diagnosis, and lowering quality of life. Treating physicians encounter numerous challenges attributed to the complex nature of pelvic anatomy, limitations of diagnostic techniques, and lack of available resources. This article is an overview of the current state of artificial intelligence (AI) in tackling the difficulties of managing benign anorectal disorders and pelvic floor disorders.

Methods

A systematic literature review was performed according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines. We searched the PubMed database to identify all potentially relevant studies published from January 2000 to August 2023. Search queries were built using the following terms: AI, machine learning, deep learning, benign anorectal disease, pelvic floor disorder, fecal incontinence, obstructive defecation, anal fistula, rectal prolapse, and anorectal manometry. Malignant anorectal articles and abstracts were excluded. Data from selected articles were analyzed.

Results

139 articles were found, 15 of which met our inclusion and exclusion criteria. The most common AI module was convolutional neural network. researchers were able to develop AI modules to optimize imaging studies for pelvis, fistula, and abscess anatomy, facilitated anorectal manometry interpretation, and improved high-definition anoscope use. None of the modules were validated in an external cohort.

Conclusion

There is potential for AI to enhance the management of pelvic floor and benign anorectal diseases. Ongoing research necessitates the use of multidisciplinary approaches and collaboration between physicians and AI programmers to tackle pressing challenges.

Efficacy of Pelvic Floor Muscle Training for Postoperative Patients With Rectal Cancer: A Systematic Review and Meta-Analysis

This study aimed to assess the effectiveness of pelvic floor muscle training (PFMT) for fecal incontinence (FI) and health-related quality of life (HR-QOL) after colorectal cancer surgery. This systematic review (SR) and meta-analysis included randomized controlled trials (RCTs) that examined the effects of PFMT after colorectal cancer surgery, which were extracted from several databases in January 2023. The primary outcomes were FI (Wexner scores), HR-QOL, and adverse events. We used the Grading of Recommendations, Assessment, Development, and Evaluation (GRADE) approach to assess the certainty of evidence (CoE). A total of seven RCTs were included. Our SR results suggested that PFMT showed little to no difference in FI (mean difference 0.62 higher; 95% CI: -1.26 to 2.5, low CoE) and adverse events (risk ratio 5.78; 95% CI: 0.28-117.22, low CoE). Two adverse events occurred in the PFMT group (anastomotic stenosis, suboptimal use of laxatives) and were not observed in controls. HR-QOL was measured in two RCTs using 12-item Short Form Survey (SF-12) and fecal incontinence quality of life (FIQL). Two RCTs found no trend toward a positive impact on HR-QOL. Higher quality RCTs on colorectal cancer after surgery are required. Furthermore, extending the duration of the PFMT intervention may be necessary to ensure its success.

Effect of 3D Animation Combined with Teach-Back Health Education on Pelvic Floor Muscle Training in LARS Patients: A Randomized Controlled Trial

Aim. The present study aimed to evaluate the effect of 3D animation combined with teach-back health education on the recovery of low anterior resection syndrome (LARS) patients. Background. LARS is the most common problem after anus-preserving surgery in rectal cancer. Pelvic floor muscle training can promote the recovery of recto-anal function. Methods. Ninety-nine patients with LARS were randomly divided into control group, experiment group I, and experiment group II. The control group was guided by one-to-one verbal pelvic floor muscle training. The experiment group I was given self-made 3D animation along with one-to-one pelvic floor muscle guidance. The 3D animation and teach-back methods were used for training and guidance in the experiment group II. The outcome measures were scores of low anterior resection syndrome scale items, as well as the completion of training content. Results. The degree of completion of training content in the experiment group II was higher than that of the control group and experiment group I. The total score of LARSS in the experiment group II was significantly lower than in the control group and experiment group I. In particular, scores of loose stool incontinence, defecation frequency level, tenesmus, and defecation urgency in experiment group II were better than those in the control group. Conclusion. 3D animation combined with teach-back health education improved the mastery of pelvic floor muscle training theory and practice in LARS patients, and effectively reduced the symptoms. Implications for Nursing Management. This intervention promoted the recovery of pelvic floor muscle function in LARS patients and can be regarded as an effective measure to improve quality of life and provide better clinical care for patients.