Programme(s) to which this project applies:

☒ MPhil/PhD ☑ MRes[Med] ☒ URIS

Objective and Significance:

Neck and low back pain are the world’s most disabling conditions. The development of such pain remains largely unknown. Numerous spinal phenotypes (e.g. disc degeneration and herniation, endplate changes, spinal stenosis, etc) may play a role in the development and prediction of such pain. However, a common language, standardized nomenclature and precise identification of spinal phenotypes does not exist. Furthermore, the implication of such precise spinal phenotyping in association with clinical outcomes remains unknown.

The Objectives will be as follows:

1) To determine and identify unique spinal phenotypes on traditional and novel imaging (x-ray, MRI, CT)

2) To develop new classification schemes of spinal degenerative and developmental imaging findings

3) To conduct cross-sectional and prospective studies assessing spinal imaging phenotypes with clinical outcomes (e.g. low back pain)

4) Development of supervised and unsupervised deep learning for image manipulation 5) Utilize AI for novel imaging

The significance of this work has the potential to change clinical practice in Hong Kong and worldwide by contributing to a more personalized approach to patient management. This can lead to refined clinical decision-making, more cost-effective health-care utilization and decreased costs, and improved patient outcomes.

Professor JPY Cheung, Department of Orthopaedics and Traumatology

Graduated from the University of Hong Kong with a Bachelor of Medicine and Bachelor of Surgery (MBBS), Professor Jason Cheung trained as an Orthopaedic Surgeon at the Queen Mary Hospital. He is a Clinical Professor with the Department of Orthopaedics and Traumatology at the University of Hong Kong. His main research interests are paediatric growth and spinal deformity, developmental lumbar spinal stenosis, management of cervical myelopathy and orthopaedic infections.

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For more information or to express interest for this project, please email the supervisor or the specified contact point in the project description.  Interested candidates are advised to enclose with your email:

  1. your CV,
  2. a brief description of your research interest and experience, and
  3. two reference letters (not required for HKUMed UG students seeking MRes[Med]/URIS projects).

Information on the research programme, funding support and admission documentations could be referenced online at the Research Postgraduate Admissions website. General admission enquiries should be directed to

HKUMed MBBS students interested in the Master of Research in Medicine (MRes[Med]) programme may visit the programme website for more information.  

HKUMed UG students interested in the Undergraduate Research Internship Scheme (URIS) may visit the scheme’s website for more information.