Algorithm Found to Reduce CT Scans for Diagnosis of Pediatric Appendicitis
By MedImaging International staff writers Posted on 12 Aug 2014 |
Image: Illustration of an inflamed appendix (Photo courtesy of the Mayo Clinic Children’s Center).
Implementation of an algorithm designed to diagnose pediatric patients with suspected appendicitis reduces the utilization of computed tomography (CT) imaging scans, without affecting diagnostic accuracy.
The Mayo Clinic Children’s Center (Rochester, MN, USA) researchers published their study’s findings online June 19, 2014, in the journal Surgery. Acute appendicitis is the most typical cause of acute abdominal pain in children. CT scans are frequently utilized to detect acute appendicitis because they are widely available, effective, and have the ability to provide clinicians with advanced data in appendicitis cases suspected of complications.
However, CT scans are costly and expose patients to ionizing radiation. “This algorithm was developed by a multidisciplinary group of pediatric emergency room physicians, pediatric surgeons, and radiologists to eliminate unnecessary exposure to radiation,” clarified Michael B. Ishitani, MD, lead author of the study.
The study compared pediatric patients, under the age of 18, who underwent an appendectomy for acute appendicitis pre-algorithm implementation and post-implementation. Researchers evaluated 331 pediatric patients over the period of five years, and found that CT use decreased from 39% to 18% after the algorithm was employed.
Researchers discovered that when the algorithm was implemented, use of CT scans in patients dropped by over 50%, without affecting diagnostic effectiveness, validating that reducing the use of CT scans when evaluating patients for appendicitis is safe and cost-effective. “Implementation of this algorithm across multiple centers is the ideal outcome of this study, followed by further evaluations over time to ensure that the low rate of CT scan use continues,” commented Dr. Ishitani.
Related Links:
Mayo Clinic Children’s Center
The Mayo Clinic Children’s Center (Rochester, MN, USA) researchers published their study’s findings online June 19, 2014, in the journal Surgery. Acute appendicitis is the most typical cause of acute abdominal pain in children. CT scans are frequently utilized to detect acute appendicitis because they are widely available, effective, and have the ability to provide clinicians with advanced data in appendicitis cases suspected of complications.
However, CT scans are costly and expose patients to ionizing radiation. “This algorithm was developed by a multidisciplinary group of pediatric emergency room physicians, pediatric surgeons, and radiologists to eliminate unnecessary exposure to radiation,” clarified Michael B. Ishitani, MD, lead author of the study.
The study compared pediatric patients, under the age of 18, who underwent an appendectomy for acute appendicitis pre-algorithm implementation and post-implementation. Researchers evaluated 331 pediatric patients over the period of five years, and found that CT use decreased from 39% to 18% after the algorithm was employed.
Researchers discovered that when the algorithm was implemented, use of CT scans in patients dropped by over 50%, without affecting diagnostic effectiveness, validating that reducing the use of CT scans when evaluating patients for appendicitis is safe and cost-effective. “Implementation of this algorithm across multiple centers is the ideal outcome of this study, followed by further evaluations over time to ensure that the low rate of CT scan use continues,” commented Dr. Ishitani.
Related Links:
Mayo Clinic Children’s Center
Latest Radiography News
- Novel Breast Imaging System Proves As Effective As Mammography
- AI Assistance Improves Breast-Cancer Screening by Reducing False Positives
- AI Could Boost Clinical Adoption of Chest DDR
- 3D Mammography Almost Halves Breast Cancer Incidence between Two Screening Tests
- AI Model Predicts 5-Year Breast Cancer Risk from Mammograms
- Deep Learning Framework Detects Fractures in X-Ray Images With 99% Accuracy
- Direct AI-Based Medical X-Ray Imaging System a Paradigm-Shift from Conventional DR and CT
- Chest X-Ray AI Solution Automatically Identifies, Categorizes and Highlights Suspicious Areas
- AI Diagnoses Wrist Fractures As Well As Radiologists
- Annual Mammography Beginning At 40 Cuts Breast Cancer Mortality By 42%
- 3D Human GPS Powered By Light Paves Way for Radiation-Free Minimally-Invasive Surgery
- Novel AI Technology to Revolutionize Cancer Detection in Dense Breasts
- AI Solution Provides Radiologists with 'Second Pair' Of Eyes to Detect Breast Cancers
- AI Helps General Radiologists Achieve Specialist-Level Performance in Interpreting Mammograms
- Novel Imaging Technique Could Transform Breast Cancer Detection
- Computer Program Combines AI and Heat-Imaging Technology for Early Breast Cancer Detection