Published online May 27, 2023. doi: 10.4240/wjgs.v15.i5.882
Peer-review started: December 12, 2022
First decision: January 2, 2023
Revised: January 16, 2023
Accepted: March 30, 2023
Article in press: March 30, 2023
Published online: May 27, 2023
Perianal fistulising Crohn's disease (PFCD) and glandular anal fistula have many similarities on conventional magnetic resonance imaging (MRI); therefore, it is difficult to differentiate these conditions in the early stages with conventional MRI. Texture analysis based on conventional MRI images can quantitatively analyze image pixel information and reflect the internal heterogeneity and pathological characteristics of the lesion.
This study aimed to analyze the texture of the rectum and anal canal wall in the PFCD group and glandular anal fistula group to explore whether the texture feature parameters are valuable in identifying and differentiating these two lesions, which provides a non-invasive method for preoperatively differentiating these two entities.
Therefore, the purpose of this study is to differentiate PFCD from glandular anal fistula using MRI texture analysis.
Patients with rectal water sac implantation were screened from the first part of this study (48 patients with PFCD and 22 patients with glandular anal fistula). Open-source software ITK-SNAP (Version 3.6.0, http://www.itksnap.org/) was used to delineate the region of interest (ROI) of the entire rectum and anal canal wall on every axial section, and then the ROIs were input in the Analysis Kit software (version V3.0.0.R, GE Healthcare) to calculate the textural feature parameters. Textural feature parameter differences were compared between the two groups and selected for further analysis.
In all, 385 textural parameters were obtained, including 37 parameters with statistically significant differences between the PFCD and glandular anal fistula groups. Then, 16 texture feature parameters remained after bivariate Spearman correlation analysis, including one histogram parameter; four grey level co-occurrence matrix (GLCM) parameters; four texture parameters; five grey level run-length matrix (RLM) parameters; and two form factor parameters. The AUC, sensitivity, and specificity of the model of textural feature parameters were 0.917, 85.42%, and 86.36%, respectively.
The model of textural feature parameters showed good diagnostic performance for PFCD. The texture feature parameters of the rectum and anal canal in fat suppression T2-weighted imaging are helpful to distinguish PFCD from glandular anal fistula.
This study provides a non-invasive method (MRI texture analysis) to preoperatively differentiate PFCD from glandular anal fistula, which has a profound clinical significance in guiding treatment strategy and predicting prognosis for patients with PFCD and anal fistula.