Intestinal fibrotic strictures represent a severe complication of Crohn's disease (CD), affecting over half of the patients. Despite the continuous emergence of novel medications, effective treatment options remain scarce. Endoscopy fails to identify the full-thickness fibrosis of the bowel wall, and standardized assessment for cross-sectional imaging has yet to be established. Previous studies have demonstrated that radiomics models based on computed tomography and deep learning models exhibit commendable diagnostic capability. Thus, this project seeks to conduct a prospective multicenter study, with plans to recruit 234 CD patients requiring bowel resection from five medical centers. The aim is to develop and validate a deep learning model based on magnetic resonance enterography (MRE) to accurately characterize intestinal fibrosis.
Eligibility
Sex
ALL
Min age
18 Years
Max age
75 Years
Healthy volunteers
No
Inclusion Criteria:
1. Patients Over 18 years old with a confirmed diagnosis of CD based on the criteria of ECCO guideline.
2. Planning to receive a bowel resection due to stricture in ileum or colon, and availability of histological specimens of resected intestinal walls matched with MRE are expected to be available.
3. Clear boundaries of the target bowel tract enable accurate semi-automatic or fully automatic intestinal segmentation
Exclusion Criteria:
1. Cannot undergo MRI examination
2. Difficult to obtain suitable tissue after surgery
3. MRE imaging is of poor quality or contains artifacts
4. The target bowel is located at the anastomosis (ie, anastomotic stricture)
5. Intestinal lesions concurrent with other diseases
Primary outcome measure(s)
histologic inflammation score — 1 week after surgery Histologic evaluation of intestinal surgical specimens from enrolled patients was performed using hematoxylin and eosin (H\&E) staining for the histologic inflammation score. The scoring system is graded on a 0-3 scale, with higher scores indicating a greater degree of inflammatory infiltration.
histologic fibrosis score — 1 week after surgery Histologic evaluation of intestinal surgical specimens from enrolled patients was performed using Masson's trichrome staining for the histologic fibrosis score. The scoring system is graded on a 0-3 scale, with higher scores indicating a greater degree of fibrosis severity.
Magnetization Transfer Ratio — 4 weeks before surgery All enrolled patients underwent Magnetic Resonance Enterography examinations four weeks prior to surgery. Magnetization Transfer Ratio (MTR) is calculated as MTR = \[1 - (Msat / M0)\] × 100, where Msat represents the signal intensity with the magnetization transfer pulse applied, and M0 represents the signal intensity without the MT pulse. To minimize individual variability, MTR is normalized using the skeletal muscle MTR, making it a reliable indicator for assessing intestinal fibrosis.
Apparent Diffusion Coefficient — 4 weeks before surgery All enrolled patients underwent Magnetic Resonance Enterography examinations four weeks prior to surgery. The Apparent Diffusion Coefficient (ADC) is derived from diffusion-weighted imaging (DWI) and measures the movement of water molecules in tissues, indirectly reflecting inflammation and fibrosis severity. Lower ADC values suggest restricted diffusion, which is associated with fibrosis, allowing differentiation between fibrotic and non-fibrotic bowel walls.
Percentage of Enhancement Gain — 4 weeks before surgery All enrolled patients underwent Magnetic Resonance Enterography examinations four weeks prior to surgery. The Percentage of Enhancement Gain is calculated using % Gain = \[(WSI\_7min - WSI\_70s) / WSI\_70s\] × 100, where WSI\_70s and WSI\_7min are the bowel wall signal intensities at 70 seconds and 7 minutes post-contrast injection, respectively. This parameter evaluates hemodynamic changes in the bowel wall, reflecting tissue perfusion characteristics related to inflammation and fibrosis.
Trial sites (5)
Facility
City
Region
Status
The First Affiliated Hospital,Sun Yat-sen University
Guangzhou
Guangdong
Recruiting
Sixth Affiliated Hospital of Sun Yat-sen University
Guangzhou
Guangdong
Not Yet Recruiting
Jinling Hospital, Affiliated Hospital of Medical School, Nanjing University
Nanjing
Jiangsu
Not Yet Recruiting
Ruijin Hospital, Shanghai Jiaotong University School of Medicine
Huangpu
Shanghai Municipality
Not Yet Recruiting
Sir Run Run Shaw Hospital, Zhejiang University School of Medicine
This page summarises publicly available registry data for informational purposes — not medical advice. Eligibility is determined by each study team; patients should discuss participation with their clinician.
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