Deep Learning in Classifying Bowel Obstruction Radiographs

Soochow University

Status: Active, not recruiting

Conditions: Bowel Disease; Polyp of Colon; Digestive System Disease

Study type: Observational

Funder types: Other

Identifiers

NCT06321614

2022098

Details and patient eligibility

About

Background: Accurate labeling of obstruction site on upright abdominal radiograph is a challenging task. The lack of ground truth leads to poor performance on supervised learning models. To address this issue, self-supervised learning (SSL) is proposed to classify normal, small bowel obstruction (SBO), and large bowel obstruction (LBO) radiographs using a few confirmed samples.

Methods: A few number of confirmed and a large number of unlabeled radiographs were categorized based on the ground truth. The SSL model was firstly trained on the unlabeled radiographs, and then fine-tuned on the confirmed radiographs. ResNet50 and VGG16 were used for the embedded base encoders, whose weights and parameters were adjusted during training process. Furthermore, it was tested on an independent dataset, compared with supervised learning models and human interpreters. Finally, the t-SNE and Grad-CAM were used to visualize the model's interpretation.

Enrollment: 4,500 estimated patients

Sex: All

Ages: 18 to 80 years old

Volunteers: No Healthy Volunteers

Inclusion criteria

1. The hospital imaging system looked for plain abdominal standing films diagnosed as intestinal obstruction or normal between 2022 and 2024
2. Aged 18 to 80 years
3. The main complaint was gastrointestinal symptoms

Exclusion criteria

1. Image interference, fuzzy performance, difficult to distinguish
2. Non-gastrointestinal symptoms were the main complaint
3. Supine, prone, or lateral decubitus radiography
4. Paralytic obstruction, closed loop obstruction, et al

Trial design

4,500 participants in 3 patient groups

patients with normal abdominal radiographs

Description:

patients with normal abdominal radiographs, which were confirmed by extra imaging examinations and clinical data. The imaging examinations comprised CT, magnetic resonance imaging (MRI) and colonoscopy in the subsequent 72 hours, while clinical data included recent hospital admission information and surgical operation notes.

patients with small bowel obstruction radiographs

Description:

patients with small bowel obstruction radiographs, which were confirmed by extra imaging examinations and clinical data. The imaging examinations comprised CT, magnetic resonance imaging (MRI) and colonoscopy in the subsequent 72 hours, while clinical data included recent hospital admission information and surgical operation notes. In terms of location, small-bowel obstruction (SBO) involves the duodenum, jejunum, and ileum

patients with large bowel obstruction radiographs

Description:

patients with large bowel obstruction radiographs, which were confirmed by extra imaging examinations and clinical data. The imaging examinations comprised CT, magnetic resonance imaging (MRI) and colonoscopy in the subsequent 72 hours, while clinical data included recent hospital admission information and surgical operation notes. In terms of location, large-bowel obstruction (SBO), involves the cecum, colon, and rectum.