Cited by 13Colorectal Cancer Surgical TreatmentsPelvic floor disorders treatmentsEnhanced Recovery After Surgery

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

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Zhang, Lijuan, Wang, Feng·2022·Contrast Media & Molecular Imaging

Abstract

Based on magnetic resonance imaging (MRI) technology under artificial intelligence algorithm, the postoperative nursing effects of pelvic floor muscle rehabilitation exercise on gastrointestinal tract rectal cancer (RC) patients were investigated. A total of 88 patients receiving RC anus‐preserving surgery in hospital were selected. The included patients were divided randomly into the experimental group (44 cases) and the control group (44 cases). Patients in the control group engaged in Kegel motion, while patients in the experimental group underwent self‐designed comprehensive pelvic floor training. Anorectum function rating scale and quality of life questionnaire for colorectal cancer (EORTC QLQ‐CR29) were utilized to compare and analyze anus functions and living quality of patients in the two groups. Besides, all patients in two groups received MRI examinations, and images were processed by a convolutional neural network (CNN) algorithm. The results showed that in MRI images, there were significant signal differences between lesion tissues and normal tissues. After being processed by an artificial intelligence algorithm, the definition of MRI images was remarkably enhanced with clearer lesion edges. The quality of images was also significantly improved. Besides, the comparison of anus functions of patients in two groups showed that the differences demonstrated statistical meaning after the intervention ( P < 0.05). In conclusion, artificial intelligence algorithm‐based MRI and comprehensive pelvic floor muscle exercise showed significant application prospects and values in the recovery of patients’ intestinal functions after RC anus‐preserving surgery.

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Authors
Zhang, L., & Wang, F.
Affiliations
  • Shanxi Medical University (CN)
  • Shanxi Provincial Children's Hospital (CN)
Corresponding author
Wang, Feng
Venue
Contrast Media & Molecular Imaging
Publisher
Wiley
Published
2022-01
Volume
2022
Issue
1
Pages
1613632-1613632
ISSN
  • 1555-4309 (ISSN-L)
  • 1555-4317
OpenAlex
W4280611290
Cited by
13
References
26
Citations by year
2026: 3 · 2025: 5 · 2024: 2 · 2023: 3
FWCI
1.05
Type
journal article
Language
en
Open access
Locations
  • Contrast Media & Molecular Imaging (publishedVersion, cc-by)
  • PubMed Central (publishedVersion, cc-by)
  • PubMed (publishedVersion)
Topics
  • Health Sciences › Medicine › Oncology › Colorectal Cancer Surgical Treatments
  • Health Sciences › Medicine › Rheumatology › Pelvic floor disorders treatments
  • Health Sciences › Medicine › Surgery › Enhanced Recovery After Surgery
Keywords
rectal cancer, anus-preserving surgery, pelvic floor muscle rehabilitation, pelvic floor muscle training, postoperative nursing care, convolutional neural networks, image enhancement, anorectal function, quality of life, gastrointestinal function recovery
MeSH terms
Algorithms, Anal Canal, Artificial Intelligence, Exercise Therapy, Gastrointestinal Neoplasms, Humans, Magnetic Resonance Imaging, Quality of Life, Rectal Neoplasms, Pelvic Floor

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