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26 September 2018
The Cardiac Simulation lab in action

There’s an electric atmosphere in the operating theatre of the Faculty of Health Sciences, as Dr Taha Gwila and his team focus with intense concentration on the fleshy exposed heart beating rhythmically in the opened chest of the patient lying in front of them. The enormous demands of open-heart surgery are evident to everyone looking on. But there’s a catch. 

The patient is faceless and rubberised. The red liquid flowing in the pipes that network from the body is not blood. And the pulsating heart was beating in the body of a pig not too long ago. 

Cutting edge technology
 
This Cardiac Simulation laboratory supplied by Medtronic is the newest addition to the School of Biomedical Sciences’ clinical simulation and skills unit. 

“There’s nothing like this in Africa, and only a few in the world,” says a beaming Prof Francis Smit, Head of Cardiothoracic Surgery at the Faculty of Health Sciences.
He explains that this new cutting edge medical technology will revolutionise the way cardiac surgeons and other health professionals are trained and assessed.

Practicing specific procedures

The simulation facilities give students with various levels of competency the opportunity to practice specific procedures in their own time and at their own pace.
“Traditionally training followed the apprentice model, where surgeons started with simple tasks and worked their way up. They assisted senior personnel and their exposure to procedures depended on the conditions presented by the patients before them,” explains Prof Smit.

The simulation technology now enables them to repeatedly practise a certain procedure without any risk to a patient. A sophisticated electronic grading system gives detailed feedback after each session, so they know in which areas to improve.  

Simulated emergencies

The system also allows trainers to create a medical emergency that the trainees then have to deal with.

“Assisting senior surgeons with high levels of competency means that in the past, trainees would often never get the chance to experience these kinds of complications during operating procedures. Now we give them a chance to build that confidence so they’ll be able to handle different situations.”  

Training hub for Africa
 

The UFS cardiothoracic programme is being designed to become a training hub for the whole of Southern Africa, combining distance learning with an on-site high-fidelity simulation and assessment centre.

“This is 100% real!” says an excited Dr Gwila after successfully completing his first simulation session. “As a Senior Registrar at the Cardiothoracic Department I’ve done similar procedures on real patients and there’s really no difference at all. Every registrar should do this before ever touching a real body.”

News Archive

Mathematical methods used to detect and classify breast cancer masses
2016-08-10

Description: Breast lesions Tags: Breast lesions

Examples of Acho’s breast mass
segmentation identification

Breast cancer is the leading cause of female mortality in developing countries. According to the World Health Organization (WHO), the low survival rates in developing countries are mainly due to the lack of early detection and adequate diagnosis programs.

Seeing the picture more clearly

Susan Acho from the University of the Free State’s Department of Medical Physics, breast cancer research focuses on using mathematical methods to delineate and classify breast masses. Advancements in medical research have led to remarkable progress in breast cancer detection, however, according to Acho, the methods of diagnosis currently available commercially, lack a detailed finesse in accurately identifying the boundaries of breast mass lesions.

Inspiration drawn from pioneer

Drawing inspiration from the Mammography Computer Aided Diagnosis Development and Implementation (CAADI) project, which was the brainchild Prof William Rae, Head of the department of Medical Physics, Acho’s MMedSc thesis titled ‘Segmentation and Quantitative Characterisation of Breast Masses Imaged using Digital Mammography’ investigates classical segmentation algorithms, texture features and classification of breast masses in mammography. It is a rare research topic in South Africa.

 Characterisation of breast masses, involves delineating and analysing the breast mass region on a mammogram in order to determine its shape, margin and texture composition. Computer-aided diagnosis (CAD) program detects the outline of the mass lesion, and uses this information together with its texture features to determine the clinical traits of the mass. CAD programs mark suspicious areas for second look or areas on a mammogram that the radiologist might have overlooked. It can act as an independent double reader of a mammogram in institutions where there is a shortage of trained mammogram readers. 

Light at the end of the tunnel

Breast cancer is one of the most common malignancies among females in South Africa. “The challenge is being able to apply these mathematical methods in the medical field to help find solutions to specific medical problems, and that’s what I hope my research will do,” she says.

By using mathematics, physics and digital imaging to understand breast masses on mammograms, her research bridges the gap between these fields to provide algorithms which are applicable in medical image interpretation.

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