gms | German Medical Science

Transabdominal ultrasound (US) examination is an accurate method of pregnancy diagnosis in sheep from about 35 days of pregnancy. The early determination of pregnancy and detection of multiple fetuses have a major influence on economic and managemental decisions in the sheep farming industry, which is the predominant livestock industry in large parts of central and western South Africa. Pregnancy diagnosis by US is therefore an important day 1 skill for South African veterinary graduates. Hands-on training opportunities for undergraduate veterinary students are limited and not every final year student has sufficient opportunity to perform the procedure. There is therefore a clear need for a simulator which could assist students in attaining these skills. The objective of the project was to develop a life-like model combining manual and electronic components which could be used in teaching for correct probe placement and interpretation of images.

A collaboration between the Faculty of Veterinary Science and the Faculty of Engineering, Built Environment and Information Technology of the University of Pretoria, South Africa, resulted in the development of a simulated scanning environment that combines an Automated Diagnostic System (ADS) with iButton technology and a Graphic User Interface (GUI). A life-size sheep model with a mobile right hindleg giving access to the right groin for scanning purposes was preserved by a taxidermist and iButton tags were fitted into the model. A simulated US probe with iButton sensors interacts with the iButton tags in the sheep model and is connected to a computer or laptop with the device software for the ADS. The GUI represents the US device. During the scanning procedure, correct placement of the probe results in real-time display of a randomly selected grey scale ultrasound image on the computer. Images are randomly chosen from the image library within the ADS. The operator can evaluate the image and make their own diagnosis of pregnancy, gestational age, and fetal number (singleton vs multiples) before allowing the system to make the diagnosis. The ADS has been found to be 76%–84% accurate. The system also evaluates probe contact strength and probe placement as indicators of good operator technique. If the probe is not placed in the correct anatomical region an error message is displayed on the screen.

In conclusion, the system has been found to be easy to use and educational, and to successfully replicate a sheep scanning environment. Further development and validation of the system is underway.