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Vol 23, No. 11, November 2019For e-subscribers (PDF)
BIOBOARD - ASIA-PACIFIC
Improving radiotherapy treatment for nose cancer with artificial intelligence
The result of a collaborative effort between scientists from the National Cancer Centre Singapore (NCCS) and Sun Yat-sen University Cancer Centre (SYSUCC).

The artificial intelligence (AI) tool aims to reduce inter-physician biases and inaccuracies that can affect the control of and treatment planning of nose cancer.

Nasopharyngeal carcinoma (NPC) or more commonly known as nose cancer, is the eighth most common cancer amongst Singaporean men affecting predominantly the Chinese community. There are about 150 to 200 new NPC cases a year at the NCCS. Treatment of NPC is primarily through radiotherapy due to its sensitivity.

Prior to radiotherapy treatment, oncologists will have to outline the tumour on diagnostic images from MRI or CT scans. This process of tumour contouring is particularly important in radiotherapy treatment planning. Precise outlining of the tumour will help radiation oncologists calculate the radiation dose in the designated area, to ensure eradication of the tumour and avoid side effects from the toxicities of the treatment.

β€œIt has been shown that a good quality radiation plan can actually influence 10% of survival in head and neck cancer.” Said Dr. Melvin Chua, senior consultant radiation oncologist at NCCS.

Currently, this process is done manually by the treating physician which can result in variation in recognition of anatomy and abnormalities between radiation oncologists. This manual process is also time-consuming and labour intensive as it entails a thorough review and comparison of the tumour on multiple diagnostic images.

In a prospective evaluation of the AI tool, the study found that AI outperforms five out of eight radiation oncologists in terms of accuracy. It also reduced inter-physician variation in tumour contouring by 50% and cut contouring time by 50% compared to manual contouring. Manual contouring time was 30 minutes compared to 18 minutes with AI assistance.

The AI system imports and draws the entire tumour target and automatically transposes the image to the CT scan. The AI tool is also able to compute a tumour that has spread to other regions.

The tool is now being implemented for use in NCCS and several centres internationally as phase 2 of this project aims to investigate the transferability of this AI tool that was developed based on a single large dataset.

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LIFE OF A SCIENTIST  

APBN Editorial Calendar 2019
January:
Taiwan Medical tourism
February:
Marijuana as medicine — Legal marijuana will open up scientific research
March:
Driven by curiosity
April:
Career developments for researchers
May:
What's cracking — Antibodies in ostrich eggs
June:
Clinical trials — What's in a name?
July:
Traditional Chinese medicine in modern healthcare — Integrating both worlds
August:
Digitalization vs Digitization — Exploring Emerging Trends in Healthcare
September:
Healthy Ageing — How Science is chipping in
October:
Disruptive Urban Farming — Microbes, Plasmids, and Recycling
November:
Evaluating cost effectiveness of genomic profiling
Editorial calendar is subjected to changes.
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