Exploring The Use of AI in Adaptive Radiotherapy in Nasopharyngeal Cancer
A “one-size-fits-all” approach fails to account for individual differences, overlooking the unique characteristics and outliers that may influence treatment outcomes.
In the ever-evolving field of medicine, there is growing emphasis on developing inclusive, adaptive, patient-centred approaches to healthcare. Precision medicine embodies this shift by leveraging advances in big data analytics and artificial intelligence to better understand individual variability and tailor treatment strategies to each patient's unique characteristics, aiming to improve clinical outcomes across diverse populations.
With this concept in mind, this article presents research on the therapeutic applications of precision medicine in treating nasopharyngeal cancer, led by Prof. Dr. Jeannie Wong Hsiu Ding and her research team in the Department of Biomedical Imaging, Faculty of Medicine, Universiti Malaya.
What is Nasopharyngeal Cancer?
Nasopharyngeal cancer is a rare cancer of the nasopharynx, a site that connects the nasal passage to the throat. It accounts for less than 1% of cancers globally, but is endemic in Southern China and Southeast Asian countries. To put its endemicity into perspective, the Malaysian National Cancer Registry Report from 2017-2021 stated nasopharyngeal cancer as the fourth most common cancer in Malaysia, and the sixth most common cancer among males.
What Is The Current Treatment Approach?
Nasopharyngeal cancer (NPC) is traditionally treated with radiation therapy (otherwise known as radiotherapy). Current practice uses Intensity-Modulated Radiation Therapy (IMRT) or Volumetric Modulated Arc Therapy (VMAT) to target the tumour while sparing nearby structures precisely.
Treatment does not take place in a single session, and patients typically undergo radiotherapy over several weeks. Throughout the course of radiotherapy, changes in a patient’s weight, tumour size, and surrounding anatomy may cause discrepancies between the initial treatment plan and the patient’s current condition, as the accuracy of radiation reaching its intended target reduces.
This is where adaptive radiotherapy (ART) comes into play.
ART involves modifying the radiation treatment plan in response to significant changes in a patient’s anatomy, to maintain treatment accuracy and effectiveness.
However, current practice often relies on visual observations by clinical staff, without objective criteria and examinations to determine exactly when mask remodelling should take place. With the implementation of subjective measures of change, this approach indirectly depletes and deprives healthcare resources that could otherwise be allocated efficiently.
Utilising Data for Smarter Predictions
To address this challenge, Prof. Dr Jeannie and her research team are investigating a radiomics-based approach to predict the appropriate and precise trigger point for ART in patients with nasopharyngeal cancers. This approach has the potential to support clinical decision-making, facilitate timely treatment adaptation and improve resource allocation.
Radiomics: quantitative extractions from medical images e.g. tumour shape, volume, intensity and texture for big data analytics
Trigger points: an actionable threshold determined by predefined clinical, anatomical, or dosimetric boundary that signals the oncology team that the current radiation treatment plan no longer accurately fits the patient's real-time anatomy and must be adapted or restructured.
By combining these measurements with computer-based analysis, researchers hope to identify patterns associated with changes that could affect treatment accuracy. These patterns could eventually help predict when a patient may need a new scan or an adjusted treatment plan.
Looking Ahead
Though this research is at its preliminary stage as a pioneering project, with analytics based on retrospective data. It represents a stepping stone towards the advancement of AI and machine learning in healthcare. In Malaysia, this could support more consistent treatment decisions, improve the coordination of scans and treatment planning, and assist in efficient allocation of resources.
However, these technologies must be tested using larger quantities of data and patient loads to ensure their accuracy and reliability across different patient populations nationwide. With this, the research team endeavours to implement multi-centre studies across Malaysia, with clinical implementations in the future.
AI in Precision Medicine
Ultimately, the integration of artificial intelligence into precision medicine represents a promising step towards more personalised and effective healthcare. By turning complex medical data into meaningful insights, AI could help clinicians make well-informed decisions and tailor treatments to individual patients. While challenges remain in ensuring its accuracy, accessibility, and clinical reliability, continued research and collaboration could help translate these technologies into practical benefits for patients. As medicine continues to evolve, the goal is not to replace expertise, but to enhance it, hence moving beyond a “one-size-fits-all” approach towards care that reflects the needs of the individual.
SDGs Addressed:
 | SDG 3: Good health and well-being by improving patient outcomes and better targeted resource allocations in healthcare with the advent of technology introduced in this article |
 | SDG 9: Industry, innovation and infrastructure advanced in the development of approaches that facilitate effective provision of radiotherapy in the treatment of nasopharyngeal cancer |
Researcher featured:
Professor Dr. Jeannie Wong Hsiu Ding
Department of Biomedical Imaging
Faculty of Medicine
Universiti Malaya
For further inquiries, please contact:
Profile Info: https://umexpert.um.edu.my/jeannie_wong80
Email: jeannie_wong@80um.edu.my
Tel: +60379498550
Orcid id
Researcher ID: B-8705-2010
Scopus ID: 2808998200
Author:
Ms Eng Pink Huey – Student Writer
Pink Huey is currently a final-year medical student at the Universiti Malaya. Outside clinical wards, her enthusiasm for writing and classical music drives her appreciation for the harmonious union of art and life. For a tinge of adrenaline, she enjoys hiking and chasing sunsets!
Copy-editor:
Siti Farhana Bajunid Shakeeb Arsalaan Bajunid
Research Outreach & Visibility Centre (OVIS), JPP, UM
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