We use cookies to understand how you use our site and to improve your experience. This includes personalizing content and advertising. To learn more, click here. By continuing to use our site, you accept our use of cookies. Cookie Policy.

MedImaging

Download Mobile App
Recent News Radiography MRI Ultrasound Nuclear Medicine General/Advanced Imaging Imaging IT Industry News

Algorithm Found to Reduce CT Scans for Diagnosis of Pediatric Appendicitis

By MedImaging International staff writers
Posted on 12 Aug 2014
Print article
Image: Illustration of an inflamed appendix (Photo courtesy of the Mayo Clinic Children’s Center).
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

Gold Member
Solid State Kv/Dose Multi-Sensor
AGMS-DM+
New
Ultrasound Table
Powered Ultrasound Table-Flat Top
Ultrasound Needle Guide
Ultra-Pro II
New
Ultrasound System
P20 Elite

Print article

Channels

Ultrasound

view channel
Image: The AI-powered Point Of Care Assisted Diagnosis (POCAD) solution is transforming the medical ultrasound industry (Photo courtesy of AISAP)

First AI-Powered POC Ultrasound Diagnostic Solution Helps Prioritize Cases Based On Severity

Ultrasound scans are essential for identifying and diagnosing various medical conditions, but often, patients must wait weeks or months for results due to a shortage of qualified medical professionals... Read more

Nuclear Medicine

view channel
Image: Whole-body maximum-intensity projections over time after [68Ga]Ga-DPI-4452 administration (Photo courtesy of SNMMI)

New PET Agent Rapidly and Accurately Visualizes Lesions in Clear Cell Renal Cell Carcinoma Patients

Clear cell renal cell cancer (ccRCC) represents 70-80% of renal cell carcinoma cases. While localized disease can be effectively treated with surgery and ablative therapies, one-third of patients either... Read more

Imaging IT

view channel
Image: The new Medical Imaging Suite makes healthcare imaging data more accessible, interoperable and useful (Photo courtesy of Google Cloud)

New Google Cloud Medical Imaging Suite Makes Imaging Healthcare Data More Accessible

Medical imaging is a critical tool used to diagnose patients, and there are billions of medical images scanned globally each year. Imaging data accounts for about 90% of all healthcare data1 and, until... Read more