Automated diagnostic model for identifying appendicitis using CT scans

Prospective Randomized Control Study for Exclusion of Negative Appendicitis; Deep Learning Model, Information of Appendix (IA) Versus Non-radiologists

This study is testing a new computer program that uses CT scans to quickly and accurately tell if someone has appendicitis or not.

Quick facts

• Phase: NA
• Study type: Interventional
• Enrollment: 568 (estimated)
• Ages: 12 Years and up
• Sex: All
• Sponsor: Hallym University Medical Center (other)
• Drugs / interventions: radiation
• Locations: 1 site (Anyang, Gyeonggi-do)
• Trial ID: NCT06175169 on ClinicalTrials.gov

What this trial studies

This study develops a fully automated diagnostic framework utilizing a 3D convolutional neural network (CNN) to classify CT scan images into three categories: non-appendicitis, simple appendicitis, and complicated appendicitis. The model is trained on a large dataset of patients who underwent CT scans for abdominal pain, employing a two-stage binary classification algorithm to enhance diagnostic accuracy. The IA model has been externally validated and aims to demonstrate a negative appendicitis rate of less than 10% while reducing interpretation time compared to traditional methods.

Who should consider this trial

Good fit: Ideal candidates for this study are patients who visit the emergency department with abdominal pain and undergo contrast-enhanced abdominopelvic CT scans.

Not a fit: Patients who do not meet the CT imaging protocol or those with conditions unrelated to appendicitis may not benefit from this study.

Why it matters

Potential benefit: If successful, this model could significantly improve the accuracy and efficiency of diagnosing appendicitis, potentially reducing unnecessary surgeries.

How similar studies have performed: Other studies utilizing deep learning for medical imaging have shown promising results, indicating that this approach may be effective in diagnosing appendicitis.

Eligibility criteria

Inclusion Criteria:

Inclusion criteria for broad eligibility were applied to reflect that the CT utilization rate in the emergency room has rapidly expanded, presumably in many other institutions where physicians maintain a reasonably sensitive standpoint in raising a clinical suspicion of appendicitis as a cause of abdominal pain and then use CT as an imaging test to confirm or rule out appendicitis.

When the imaging protocol parameters were as follows: abdomen or pelvis (intravenous contrast, 2 mg/kg, maximum 160 mL), scan timing (portal venous phase), range (from 4 cm above the liver dome to 1 cm below the ischial tuberosity), radiation dose (tube potential, KVP from 100 to 120), pitch 1.75:1, and reconstruction (5 mm, cut slice for adults; 3 mm, cut slice for children under 12 years old), anonymized CT images of patients were referred to a randomized dataset.

Exclusion Criteria:

Patients who did not fulfill the CT imaging protocol were excluded in detail as follows:

i) Failure to meet the CT protocol criteria of this study: liver CT, biliary CT, etc. (if contrast phase was different); ureter CT, etc. (if contrast media was not used and the reconstruction method was different); non-enhanced CT (when contrast media was not used); and appendix CT or low-dose CT (when radiation dose was low).

ii) When the quality of the CT image is significantly reduced, as follows: when blurring occurs (motion artifact) or metal artifact (when internal fixation is performed due to spinal surgery).

iii) when it was evident from the medical record review that clinical information suggested that APCT was performed due to the suspicion of a condition other than appendicitis, as follows: suspected acute cholecystitis due to RUQ tenderness and Murphy's sign; suspected urolithiasis due to flank pain and gross hematuria; suspected pancreatitis due to a history of pancreatitis; alcohol abuse; and suspected gynecological diseases due to vaginal discharge. Suspected panperitonitis due to whole abdominal tenderness, rebound tenderness, and unstable vital signs. Patients with acute cholecystitis, ureteral stones, pancreatitis, or acute peritonitis due to small bowel or colon perforation were also excluded.

iv) Patients younger than 10 years were excluded. Adolescent patients from 11 to 18 years old were included in the study if the exclusion criteria were not applicable.

v) diagnosed by ultrasound sonography vi) Patients who were transferred to the emergency department after a diagnosis of appendicitis at an outside hospital or ambulatory care were excluded.

vii) Patients with appendicitis who did not undergo surgical treatment because of the enrollment protocol of other ongoing studies.

viii) patients who had undergone an appendectomy

Where this trial is running

Anyang, Gyeonggi-do

• Hallym University Medical Center — Anyang, Gyeonggi-do, Korea, Republic of (RECRUITING)

Study contacts

• Principal investigator: Iltae Son — Hallym University Medical Center
• Study coordinator: Iltae Son

Conditions: Acute Appendicitis, deep learning