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Dr. Ka-Loh Li is a research only research associate in the university of Manchester. Her major research interests are to use MRI techniques to better characterize and monitor therapy response of brain tumours and specifically in developing imaging processing technique using contrast-enhanced MRI. The goal is to transform clinically collected image data into useful medical information to benefit patient management.


Research interests

Gadolinium deposition in normal tissues has been found associated with potential long-term health risks. There is an international drive to try and reduce the use of gadolinium. Her research over the past 5-10 has formed a strong position in the development of approaches which would allow the application of low-dose gadolinium contrast studies, which is a key advantage benefiting CNS patients undergoing repeated exposures.

Her current work is focused on:

1) Improving accuracy of kinetic parameter estimates in whole brain high-spatial resolution DCE-MRI

Whilst highly desirable in neuro-oncology, derivation of accurate, high-spatial resolution, whole brain coverage microvascular parameters with DCE-MRI remains challenging. This study sought to address this through developing and evaluating a novel dual-temporal resolution (DTR) DCE-based technique. 

2) low Gd dose high temporal high spatial DCE-MRI

The requirement for full-dose administration of the gadolinium-based contrast agent (GBCA) has been recognized as a key concern in patient management, especially in patients with more benign CNS tumors, such as the vestibular schwannoma (VS) patients, who may receive serial contrast-enhanced scans. We aim to develop technique for:

  • The segmentation of tumours from the low dose T1W structural. 
  • Accurate kinetic parameter estimates in whole brain high-spatial resolution low dose DCE-MRI

My collaborations

Professor Timothy Cootes, Division of Informatics, Imaging & Data Sciences, The University of Manchester

Dr. Daniel Lewis, MRCS, MRCP, MA, Manchester Centre for Clinical Neurosciences, Salford Royal NHS Foundation Trust, Manchester Academic Health Science Centre, United Kingdom

Dr. Sha Zhao, MRI spin physicist, Division of Informatics, Imaging & Data Sciences, The University of Manchester

Dr. Xiaoping Zhu, Honorary Senior Lecturer, Division of Informatics, Imaging & Data Sciences, The University of Manchester

Professor Alan Jackson, Division of Informatics, Imaging & Data Sciences, The University of Manchester


Ka-loh received PhD degree in chemistry/NMR from Clark University, Worcester, MA, USA, and one year postdoctoral training at City University of New York, Staten Island, NY, USA. She worked as a scientific associate at Department of Radiology, New England Deaconess Hospital and research fellow in Radiology of Harvard Medical School 1991-1996. She worked as a research fellow at Department of Clinical Radiology, University of Manchester 1997 – 2000. She worked in the department of Radiology, UCSF, San Francisco, USA 2000 – 2009, as assistant research scientist with PI status. From 2010 to present, she has worked at the University of Manchester. In past 20 years Kaloh has a specific interest in quantitative magnetic resonance imaging (MRI) with a focus on tracer kinetic analysis of data acquired using dynamic contrast-enhanced MRI.

Expertise related to UN Sustainable Development Goals

In 2015, UN member states agreed to 17 global Sustainable Development Goals (SDGs) to end poverty, protect the planet and ensure prosperity for all. This person’s work contributes towards the following SDG(s):

  • SDG 3 - Good Health and Well-being

Research Beacons, Institutes and Platforms

  • Digital Futures
  • Christabel Pankhurst Institute


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