Latest News Archive

Please select Category, Year, and then Month to display items
Previous Archive
18 October 2023 | Story André Damons | Photo André Damons
Prof Mathys Labuschagne
Prof Chris Viljoen, Head of the School of Biomedical Sciences; Prof Gert van Zyl, Dean of the Faculty of Health Sciences; Prof Francis Petersen, UFS Vice-Chancellor and Principal; and Prof Mathys Labuschagne, Head of the Clinical Simulation and Skills Unit (CSSU), during the unit’s 10-year anniversary celebration.

In just 10 years, the Clinical Simulation and Skills Unit (CSSU) at the University of the Free State (UFS) went from being just a dream to becoming a national and international leader in medical simulation training.

The CSSU forms part of the School of Biomedical Sciences and was officially opened on 21 February 2013. The CSSU celebrated its 10-year anniversary on Thursday, 12 October 2023.

Prof Mathys Labuschagne, Head of the CSSU, said at the evening’s celebration that the vision and dream came true 10 years ago. “I think the requirement for the successful integration of simulation into a curriculum is first and foremost that it is based on research evidence. It is not a thumb-sucking exercise”.

“It is really seated in research and then you need passion and dedication. You cannot be successful without that, and for that I need to thank my staff – without your passion and dedication it would not be possible to excel,” said Prof Labuschagne.

Simulation important for patient safety

According to the professor, good networking is also important – between departments, professions and companies outside the university and hospital. He said simulation is important for improving patient safety and expanding the training platform.

“By doing simulation, we can train students who cannot always be accommodated on the training platform. There are also a lot of educational advantages to using simulation. Our training activities in the past 10 years grew tremendously. At the moment we have about 4000 undergraduate and postgraduate student contacts a year. Then we do a lot of certification and Continuing Professional Development (CPD) courses. During COVID-19 we did PPE training and ICU training for hospital and clinical staff in a safe environment.

“I am really proud of our research output. In the past 10 years we published 34 articles, and have another six articles currently in press. We have successfully completed eight master’s and seven PhD dissertations and there are now five students who are enrolled and all of them are simulation-associated. I cannot believe it has already been 10 years. I am very proud of the unit, and we strive for excellence in simulation education and training.”

Highlights of unit

Prof Gert van Zyl, Dean of the UFS Faculty of Health Sciences, congratulated the unit on achieving this milestone. Taking a trip down memory lane, he mentioned the names of colleagues who played a role in establishing the unit and said their contributions might not be visible in name in the unit, but they are recognised by them in achieving this milestone.

“It is an excellent achievement to have seven PhDs in 10 years. Well done. Another highlight is supporting the establishing of other simulation units at Nelson Mandela University who came to learn from us. They didn’t have to go the US. The training of staff and students during COVID-19, we had the facility. Let us not forget our simulation role at undergraduate and postgraduate training.

Cutting edge of simulation-based education and training

Prof Francis Petersen, UFS Vice-Chancellor and Principal, who gave a toast at the celebration, said the occasion is an opportunity to reflect on the excellent work done over the past decade and to consider how the unit is ideally placed to meet the aspirations that the UFS has for Vision 130 and the strategy of the university.

“The work of this unit has put the University of the Free State at the cutting edge of simulation-based education and training and the ongoing efforts of all of our staff in the unit who assist with the planning, the development, the setup, and the running of scenarios are acknowledged and greatly appreciated. I want to congratulate the leadership and the staff of the unit for the excellent work you are doing,” said Prof Petersen.

According to him, simulation education has numerous advantages such as improved patient safety, skills development, learning without involving real patients and the transfer of knowledge to the clinical environment. It creates a well-structured teaching and learning framework where simulation can be used as an educational tool assist in grasping the practical aspects of learning.

The training of specialised skills and deliberate practice are the key drivers behind clinical simulation as a training technique. It can also be applied as a tool to prepare students for a crisis situation, which requires high levels of preparedness and that is a very important aspect, said Prof Petersen.

“All these aspects of simulation-based education are something that relates very much to our vision and strategy. We want to be a research-led university, which means that it is not only doing research, but we try to focus on evidence and the research also helps us in the undergraduate programme to make it much more competitive.

“It also brings to the fore some qualities of our values, value of quality, value of impact and value of care. In addition, clinical simulation creates a vibrant learning experience for students and contributes towards our goal to meet the highest standards of excellence and impact in our teaching, learning and research.”

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.

We use cookies to make interactions with our websites and services easy and meaningful. To better understand how they are used, read more about the UFS cookie policy. By continuing to use this site you are giving us your consent to do this.

Accept