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Magnetic Resonance Imaging in Obesity

University College London (UCL) logo

University College London (UCL)

Status

Completed

Conditions

Obesity

Treatments

Other: Written Consent
Other: MRI

Study type

Observational

Funder types

Other

Identifiers

NCT03528187
17/0703

Details and patient eligibility

About

Obesity and its related conditions account for up to 5%of all health care spending in the UK and this is expected to double by 2030. Following weight loss, significant improvement in these obesity-related illnesses has been reported. However, there is limited understanding of how these improvements happen and in particular, little dedicated work has been done using imaging in the obese population to look at the effects of treatment.

Magnetic resonance imaging (MRI) is an imaging technique that allows assessment of fat concentration and volume without the use of ionising radiation. It is safe, non-invasive and well-tolerated by most patients.

There are several MRI imaging techniques that be can used for fat quantification. These include MR spectroscopy and Dixon methods with measurement of fat fraction. These techniques measure the fat in the body organs and also the fat in the abdomen and skin. Recent technical developments mean that the whole body can be scanned relatively quickly (typically 30-40 minutes).

Full description

Obesity and its related conditions are a significant cause of death and ill health. There have been a number of studies showing that weight loss, in particular that achieved by bariatric (weight-loss) surgery, results in improvement in obesity-related conditions such as type 2 diabetes mellitus. A large case-control study demonstrated a mean weight loss of 23.4% by 2 years and sustained mean weight loss of 16.1% compared to matched controls. 72% of patients with type 2 diabetes were in remission at 2 years and this was 36% at 10 years. Bariatric surgery also results in recovery from lipid disturbances with 62% of patients demonstrating normalisation of hypertriglyceridaemia (high fat levels in the blood) at 2 years and 46% at 10 years. There is also a smaller cohort of patients who, despite significant weight loss, do not experience remission of their obesity-related comorbidities.

The mechanisms for the improvement in obesity-related ill health are not well understood and little dedicated work has been undertaken on imaging in the obese population before and after treatment. For example, increased fat content in the liver, bone and pancreas is well described in obesity but it is unclear whether response to treatment is uniform across all these organs, or if there are specific patients who would benefit from additional or alternative interventions for hard to treat organ fat. The effect on remaining organ fat following treatment on clinical parameters such as body shape, and metabolism, is also unknown. Furthermore, it is not known if there are certain patterns of organ fat which may respond better to one type of therapy such as surgery compared to medical treatment for example, and choosing the best treatment for patients may be improved by a better understanding of organ fat. The effect of obesity on bone structure and strength, bone hormonal activity and metabolism is poorly understood. Finally, the link, if any, between patterns of organ fat and patients' genes, body shape and metabolism before and after treatment and is also unclear.

Treatment options for obesity continue to develop. Several novel medical (non-surgical) treatments for obesity have become available and the number of patients undergoing bariatric surgery continues to increase. There is therefore need to understand the mechanisms behind both weight loss (and the contribution of individual organs to this) and the improvement in obesity-related conditions. By gaining greater understanding of this, we aim to better predict outcomes for individual patients and better select the most appropriate treatment for them.

There has been recent research into MRI as a method of quantifying fat in abdominal organs such as the liver and pancreas. MRI has the advantages of being non-invasive (for example when compared to liver biopsy) and does not use ionising radiation unlike other imaging modalities.

Enrollment

49 patients

Sex

All

Ages

18 to 75 years old

Volunteers

Accepts Healthy Volunteers

Inclusion and exclusion criteria

Cohort 1

Inclusion Criteria:

  • Age 18 or over
  • BMI greater than or equal to 30
  • Due to undergo or referred for a formal treatment intervention for obesity, as part of their usual clinical care.
  • Informed consent

Cohort 2

Inclusion Criteria:

  • Age 18 or over
  • Attending the weight management service at UCLH
  • Informed consent

Controls

  • Age 18 or over
  • BMI less than 25
  • Informed consent

Exclusion Criteria for all cohorts:

  • Absolute contraindication to MRI scan (e.g. metal foreign object)
  • Unable to tolerate MRI scan (e.g. due to claustrophobia)
  • MRI bore size inadequate to accommodate the patient
  • Previous weight loss surgery (e.g. gastric band, gastric bypass, sleeve gastrectomy) [Cohort 1 only]
  • Unable to give consent
  • Pregnancy

Trial design

49 participants in 3 patient groups

Patient Cohort 1
Description:
Age 18 or over BMI greater than or equal to 30 (greater than or equal to 27.5 for patients of Asian origin) Due to undergo or referred for a formal treatment intervention for obesity (lifestyle modifications [dietary change, behavioural therapy, increased physical activity], surgical intervention or pharmacological treatment) as part of their usual clinical care Informed written consent Able to tolerate MRI
Treatment:
Other: MRI
Other: Written Consent
Patient Cohort 2
Description:
Age 18 or over Attending weight management service at UCLH Informed written consent Able to tolerate MRI
Treatment:
Other: MRI
Other: Written Consent
Controls
Description:
Age 18 or over BMI less than 25 Informed written consent Able to tolerate MRI
Treatment:
Other: MRI
Other: Written Consent

Trial contacts and locations

1

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Central trial contact

Katerina Soteriou, BSc; Naomi Sakai, MRCS MA MB BChir

Data sourced from clinicaltrials.gov

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