Imaging

This Theme’s Focus

Developing new, more sensitive imaging methods, especially for MRI (magnetic resonance imaging) and PET (positron emission tomography)
Creating and testing new AI (artificial intelligence) techniques for better imaging and disease detection
Translating these new methods into patient care through collaborations across the UK and with industry

The NIHR Cambridge BRC Imaging theme uses key medical imaging tools to improve:

clinical diagnosis and earlier detection
patient stratification (categorising patients who share similar characteristics)
predicting and detecting response to therapy, and
personalising health care (what to expect for an individual’s disease course).

Improving current medical imaging techniques will have substantial benefits to patients, including those with coronary heart disease, stroke or cancer, improving their outcomes, saving lives and reducing NHS costs. Combining new imaging methods with clinical data, AI techniques and data science will help deliver the NHS Long-Term Plan to diagnose disease earlier and treat it more precisely.

Imaging is central to the diagnosis of many major health conditions, and we are working with themes across the NIHR Cambridge BRC and specialists in academia and industry, from MRI and PET physicists to machine-learning experts in the Cambridge Mathematics of Information in Healthcare Hub (CMIH) and GE Healthcare, to improve diagnosis and prognosis through the integration of information from the patients’ electronic health record (EHR) with advanced image analysis and understanding methods.

We are also involved in several local and national networks, including the National Cancer Imaging Translational Accelerator and the UK7T national network, working together to bring these new imaging techniques to patients in the clinic.

The University of Cambridge Department of Radiology and Wolfson Brain Imaging Centre (WBIC) have a strong track record of clinical research, high-impact publications and academic and industrial collaborations, with over £20 million invested in state-of-the-art equipment since 2017.

Theme Lead

Professor Ferdia Gallagher

Cancer Research UK Senior Research Fellow, Head of the Department of Radiology at the University of Cambridge, and an Honorary Consultant Radiologist at Cambridge University Hospitals
Email: fag1000@cam.ac.uk

Meet our researchers

Here are some of the areas we are currently investigating:

Pushing the boundaries of imaging technology

Magnetic resonance imaging (MRI) is an excellent diagnostic imaging tool, however examinations can be quite long and costly.

We are developing new techniques to accelerate MRI acquisitions without compromising diagnostic value, combining them with AI to characterise disease more accurately, and using them to advance our understanding of how diseases develop and spread.

Positron emission tomography (PET) is a sensitive tool for imaging normal and abnormal metabolic activity. We are researching new radiotracers that can image specific diseases more accurately. This will help us to improve patient diagnosis and treatment.

Personalised screening

We are developing advanced mathematical techniques to analyse medical images to provide clinicians with more detailed information about particular diseases and their progression, allowing them to refine treatments for patients throughout their care pathway.

We are also investigating new magnetic resonance imaging (MRI) methods that help clinicians to visualise how diseases consume energy to develop.

This process is altered in many diseases – in oncology, for example, we can directly see and quantify the way in which cancers use energy. This allows us to more precisely monitor the effects of anti-cancer therapies.

The right treatment for the right patient

We are developing new imaging methods that allow us to obtain images with higher resolution and better quality, giving clinicians greater confidence in diagnosis.

These new novel methods, combined with advanced mathematical analysis, will help us to diagnose disease earlier, and classify disease more accurately, allowing for more personalised treatment and follow-up.

Advanced imaging combined with therapy is called ‘theranostics’ and our research has shown that using radionuclides (radioactive chemical elements in the body) we can target tumours more accurately.

This has the potential to revolutionise patient management and treatment of many cancers, including renal, prostate, ovary, breast and neuroendocrine cancer.

Latest News

Celebrating the role of patients in improving radiotherapy services

September 22, 2022

A new display in Addenbrooke’s Hospital highlights how patients have helped shape radiotherapy treatment.

Cambridge researchers awarded Fellow status

May 11, 2022

Eight Cambridge researchers are elected as Fellows of the Academy of Medical Sciences.

Thoughtful woman receiving cancer treatment: Image purchased with lifetime use from Adobe Stock.

Consensus opens door to worldwide improvements in breast cancer radiotherapy treatment

December 30, 2021

A panel of European experts and patients has identified a way to achieve major changes in the way radiotherapy treatment for breast cancer patients is delivered around the world.

Scientists identify the cause of Alzheimer’s progression in the brain

November 1, 2021

New research has used human data to quantify the speed of different processes that lead to Alzheimer’s disease and found that it develops in a very different way than previously thought.

Patient having their blood test taken at NIHR Cambridge CRF - NIHR Cambridge BRC image

Researchers at NIHR Cambridge BRC instrumental in developing new treatment that offers quick cure for common cause of high blood pressure

February 10, 2025

Researchers from NIHR Cambridge BRC, University of Cambridge…

Breast screening - NIHR Cambridge BRC image

New study to test personalised breast cancer screening

October 16, 2024

A new international trial will investigate whether a personalised…

Three nurses looking at a screen - Image from Cambridge University Health Partners

World first for AI and machine learning to treat Covid patients worldwide

October 16, 2024

In a ground-breaking study supported by the NIHR Cambridge…

Well-planned patient preparation before their scans improves imaging quality and cancer detection rates

October 16, 2024

An NIHR Cambridge BRC-supported review of existing studies…

Prostate Cancer Diagnostic Pathways

October 16, 2024

After skin cancer, prostate cancer is the most common cancer…

3 T: the good, the bad and the ugly

November 16, 2021

Federated Learning used for predicting outcomes in SARS-COV-2 patients

September 15, 2021

Dynamic contrast-enhanced MRI of synovitis in knee osteoarthritis: repeatability, discrimination and sensitivity to change in a prospective experimental study

March 3, 2021

Quantitative 3D imaging parameters improve prediction of hip osteoarthritis outcome

March 5, 2020

Multi-site repeatability and reproducibility of MR fingerprinting of the healthy brain at 1.5 and 3.0 T

July 15, 2019

The NIHR Cambridge BRC is part of the NIHR and hosted by Cambridge University Hospitals NHS Foundation Trust in partnership with the University of Cambridge. We are at the heart of the Cambridge Biomedical Campus, Europe’s largest health research area.

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Contact Us

Cambridge Biomedical Research Centre
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Tel: 01223 348490

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Happy #InternationalDayofWomenandGirlsinScience
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Imaging

This Theme’s Focus

Theme Lead

Professor Ferdia Gallagher

Here are some of the areas we are currently investigating:

Pushing the boundaries of imaging technology

Personalised screening

The right treatment for the right patient

Latest News

Celebrating the role of patients in improving radiotherapy services

Cambridge researchers awarded Fellow status

Consensus opens door to worldwide improvements in breast cancer radiotherapy treatment

Scientists identify the cause of Alzheimer’s progression in the brain

Imaging Case Studies

Researchers at NIHR Cambridge BRC instrumental in developing new treatment that offers quick cure for common cause of high blood pressure

New study to test personalised breast cancer screening

World first for AI and machine learning to treat Covid patients worldwide

Well-planned patient preparation before their scans improves imaging quality and cancer detection rates

Prostate Cancer Diagnostic Pathways

Imaging Publications

3 T: the good, the bad and the ugly

Federated Learning used for predicting outcomes in SARS-COV-2 patients

Dynamic contrast-enhanced MRI of synovitis in knee osteoarthritis: repeatability, discrimination and sensitivity to change in a prospective experimental study

Quantitative 3D imaging parameters improve prediction of hip osteoarthritis outcome

Multi-site repeatability and reproducibility of MR fingerprinting of the healthy brain at 1.5 and 3.0 T

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