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13 September 2022 | Story Andrè Damons | Photo Andrè Damons
Prof Motlalepula Matsabisa
This week, Prof Motlalepula Matsabisa, will give a keynote speech on Indigenous Knowledge Systems (IKS) and Health during a session at the eighth edition of the UNGA77 Science Summit around the 77th United Nations General Assembly (SSUNGA77).

Prof Motlalepula Matsabisa, Director of Pharmacology at the University of the Free State (UFS), has been invited to give a keynote speech on Indigenous Knowledge Systems (IKS) and Health during a session at the eighth edition of the UNGA77 Science Summit around the 77th United Nations General Assembly (SSUNGA77).

While in New York, Prof Matsabisa will also meet with officials from the Wellcome Trust – a global charitable foundation – where he will present a strong and compelling motivation for the Wellcome Trust to invest in traditional medicines. Says Prof Matsabisa: “I will deliver a compelling message for investment to be made in scientific research and development around traditional medicines. This development will be piloted in a hub-and-spoke model based on the African economic blocks, with the hub being in South Africa. The returns on the investment put in this initiative will be massive for the African continent, both socially and economically, and I believe it will lead to self-sustainability and Africa being a supplier of innovations based on the science of traditional medicines.” 

SSUNGA77 is organised by Intelligence in Science and will take place from 13 to 30 September 2022. It will bring together thought leaders, scientists, technologists, innovators, policy makers, decision makers, regulators, financiers, philanthropists, journalists and editors, and community leaders to increase health science and citizen collaboration across a broad spectrum of themes, including ICT, nutrition, agriculture, health, IKS, and the environment.

Prof Matsabisa, an expert in African traditional medicine (ATM) and Chairperson of the World Health Organisation’s (WHO) Regional Expert Advisory Committee on Traditional Medicines for COVID-19 (REACT), is also the convener of this session, following his successful proposal for such a session. The session will take place in person on 20 September at the UN headquarters in New York. It is an official side event of the UN General Assembly’s 77th anniversary and will be co-sponsored by the permanent missions of Ireland, Spain, South Africa, Brazil, and Bangladesh to the UN.

His message at Science Summit

“At the end of the summit, we are to make recommendations to the UN, EU, and AU on IKS and health developmental matters. This is exciting and nerve-wracking for me, but I will remain calm knowing that I have a message to deliver to the highest global decision-making body. There can be nothing greater than presenting my talk and proposals for consideration to such a body.” 

“I will convey three simple messages, namely the importance of traditional medicines in contributing to universal health coverage, the need for Africa – through the heads of state and governments – to take seriously the local manufacturing of traditional medicines for industrialisation, economic emancipation, and responding to poverty and inequality. The third message is the need for sustained and adequate financial support by African ministries of health for the development, commercialisation, and market access to quality and well-researched, safe, and effective traditional medicines in order to contribute to priority diseases as well as responding to pandemics,” says Prof Matsabisa. 

According to him, this address at SSUNGA77 is a chance to correctly position the story on IKS with arguments based on good scientific evidence. “It means we are getting much closer to the institutionalisation and formal economic contribution of IKS to health, and that the African IKS health system is getting international recognition and acceptance,” he says.
Prof Matsabisa says he hopes the message will emerge clearly from his talk that Africa has the resources for raw materials and that the science, as well as the infrastructure, exists to develop IKS and to contribute to new health products. The spin-off is the industrialisation, job creation, and wealth generation that Africa can offer to the rest of the world.

Overall information on the summit is available here

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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