Patient involvement in early identification of haemochromatosis

Area of work


Imaging modality


Size of data set



Project lead

Dr Steve Masson

Industry partners

Number of NHS partners


Unmet need

Haemochromatosis, also known as iron overload, is the most common genetic disorder, affecting 0.5% of the UK, and leads to symptoms of fatigue and joint pain, and damage to internal organs manifesting as cardiac and liver failure. If detected early, by MRI or genetic testing, it is completely preventable by venesection.

For every one patient diagnosed and at risk, there are 8-10 who are undiagnosed and unaware of their risk.  As the symptoms are shared with many other conditions, it is difficult for clinicians to know who should be screened, and conflicting therapies are often offered to treat the non-unique symptoms; such as treating haemochromatosis patients presenting with symptoms of fatigue with iron tablets.  

If genetic haemochromatosis is diagnosed early and treatment implemented before serious complications develop, people living with haemochromatosis can expect to have a normal life expectancy.  The current diagnostic tests are inadequate, with painful and invasive biopsy to measure the liver iron content as the gold standard. Blood tests are available, such as serum ferritin level, but these can be influenced by liver damage and inflammation, and in many cases do not correlate well with liver iron stores.

Perspectum Diagnostics (PD) developed LiverMultiScan (LMS) which uses T2* imaging to assess liver iron content (LIC) in order to generate corrected T1 images to measure fibrosis and inflammation in the liver; however, PD’s focus has been fatty liver disease rather than iron quantification. In this project, we will optimise our LIC quantification technology through LMS-IRON for the identification and management of iron overload. 

Project aim

Using our existing ability to quantify liver damage, LMS-IRON will be able to provide a precise, non-invasive assessment of iron overload and associated liver damage over the duration of the condition as well as the response to treatment. This, in turn, will allow doctors and patients to make more informed care decisions, improving outcomes for patients and care pathways for healthcare providers as well as providing crucial understanding on the development of the pathology.

The aim of this project is to build a registry containing prospectively acquired MR images and associated clinical data from healthcare records of 1000 haemochromatosis patients. We will acquire the data over three years to better understand the development of the condition. This registry, along with control data from a large, healthy population from the UK BioBank dataset will then be used to develop artificial intelligence and computer vision techniques to automatically analyse LIC in the liver. 

This will mean that we can use automated and advanced image processing to screen for the disease in asymptomatic individuals that undergo an otherwise unrelated thoraco-abdominal MRI scan in the future. Automatic identification of patients with a LIC of above 1.8mg/g will result in a report generated and communicated to the GP of the individual to flag these findings as an early diagnosis of haemochromatosis. 


  • Demonstrate the capacity of the NCIMI to collect and share clinical data with commercial partners, under strict regulation.
  • Demonstrate the ability of developing computer vision techniques in analysing real-world MRI data.
  • Improve the monitoring of iron overload in the liver during therapy.

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