Intussusception Management in Pediatric Patients

Intussusception, the telescoping of one segment of the intestine into another, represents a common surgical emergency in infancy and early childhood. Rapid diagnosis and prompt reduction are essential to avoid ischaemia, necrosis, bowel resection and associated morbidity. Management strategies span non-operative techniques—principally hydrostatic or pneumatic enema under image guidance—and surgical intervention when reduction fails or complications arise. Ultrasound has become the cornerstone of both diagnosis and guided reduction, offering real-time visualisation without ionising radiation. Developments in artificial intelligence have begun to augment sonographer interpretation, improving accuracy and efficiency in identifying both the presence of intussusception and criteria for surgical referral. Surgical methods remain vital when nonsurgical reduction is contraindicated or unsuccessful, with resection reserved for ischaemic or perforated bowel. Global variations in access to imaging, trained personnel and equipment continue to drive research into simplified diagnostic protocols and safer, more effective reduction techniques. Ongoing innovations aim to standardise care pathways, reduce recurrence rates and optimise outcomes across diverse healthcare settings.

Research from Nature Portfolio

Two recent studies have applied deep-learning approaches to plain abdominal radiographs to enhance early detection of ileocolic intussusception in young children. A first algorithm based on a single-shot object detector and convolutional neural network achieved superior sensitivity compared with radiologists, with maintained specificity, facilitating rapid triage in emergency settings. A subsequent convolutional neural network model demonstrated robust internal validation across multiple centres, yielding high areas under the receiver operating characteristic curve and promising Youden indices. Both systems offer automated localisation of the right lower abdomen and classification of intussusception, indicating that integrating artificial intelligence into routine radiographic review could expedite diagnosis and support decision-making in resource-constrained environments.

Intussusception Management in Pediatric Patients publication trend

The graph below shows the total number of articles in intussusception management in pediatric patients across all publications each year (not limited to Nature Index journals).

Technical terms

Intussusception: Telescoping of one bowel segment into an adjacent segment leading to obstruction and potential ischaemia.

Hydrostatic reduction: Non-operative technique using fluid (usually saline) instilled via enema under imaging to unfold the intussuscepted bowel.

Fluoroscopy-guided air reduction: Pneumatic enema performed under continuous X-ray to reduce intussusception by air pressure.

Point-of-care ultrasound (POCUS): Portable, bedside sonographic examination conducted by frontline clinicians for rapid assessment.

Deep-learning algorithm: Artificial intelligence model using neural networks trained on imaging data to detect and classify pathology.

Pathological lead point: Structural abnormality (such as a polyp or Meckel’s diverticulum) that initiates intussusception in older children.

References

1. Performance of deep learning-based algorithm for detection of ileocolic intussusception on abdominal radiographs of young children. Scientific Reports (2019).
2. Deep learning algorithms for detecting and visualising intussusception on plain abdominal radiography in children: a retrospective multicenter study. Scientific Reports (2020).
3. Ultrasound-guided hydrostatic reduction versus fluoroscopy-guided air reduction for pediatric intussusception: a multi-center, prospective, cohort study. World Journal of Emergency Surgery (2021).
4. Diagnostic Accuracy of Point-of-Care Ultrasound for Intussusception in Children Presenting to the Emergency Department: A Systematic Review and Meta-analysis. Western Journal of Emergency Medicine (2020).
5. A deep-learning pipeline to diagnose pediatric intussusception and assess severity during ultrasound scanning: a multicenter retrospective-prospective study. npj Digital Medicine (2023).