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Completed

NCT Number: NCT03151512

UNDISTORT Correction of Distortions in Diffusion MRI V1.0

This is a three-year project funded by a Cancer Research UK Multidisciplinary Award and brings together a team from UCL Division of Medicine, Computer Science and University College London Hospital. The aim is to develop Magnetic Resonance (MR) sequences and mathematical algorithms to reduce the distortions in MR images, especially of the prostate.

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Key information

Age range

18 year–120 year

Sex eligibility

All sexes

Study type

Observational

Primary location

University College London Hospital

London, NW1 2BU, United Kingdom

About this study

This is a three-year project funded by a Cancer Research UK Multidisciplinary Award and brings together a team from UCL Division of Medicine, Computer Science and University College London Hospital. The aim is to develop Magnetic Resonance (MR) sequences and mathematical algorithms to reduce the distortions in MR images, especially of the prostate. Current NICE guidelines include a type of MR imaging called Diffusion Weighted MRI for the detection of tumour within the prostate, and for active surveillance of low risk confirmed disease. However, approximately 40% of prostate diffusion images suffer from severe localised distortions and this is most marked in the peripheral zone of the prostate where 75% of prostate cancers occur. The source of these distortions is magnetic field imperfections due to the presence of rectal gas or metallic hip implants.

The research study will ask both healthy volunteers and patients to undergo research MR scans and use the acquired data for analysis. For patients, the scans may be either additional sequences acquired during an extended clinical session, or a separate additional session entirely for research.

The output from the research will be modified ways to run an MR scanner and compute the final images.

The work should lead to improved diagnostic accuracy and a reduced number of non-diagnostic studies. It will have broader impact through application to diffusion imaging of other body sites, including whole-body diffusion MRI and non-cancer applications. If successful, the results would provide evidence for a larger trial with the eventual outcome being manufacturers incorporating modified MR sequences and data processing into clinical systems worldwide.

Who can participate

Healthy volunteers accepted: Yes

Only the study team can determine whether someone qualifies for participation.

Inclusion criteria

  • For the development and testing phases, there are no specific inclusion criteria. Assessment of the primary outcome measure (reduced distortions) also does not require specific inclusion criteria. The intended application of our methods is to prostate cancer and this is reflected in some of the secondary outcome measures. Recruitment will come from the UCLH imaging bookings system. This list will include many men having prostate scans and many of these will subsequently be found to have at least a suspicion of cancer. Note there is no requirement for a suspicion of cancer to be recruited for the study.

Exclusion criteria

  • Subjects unable to have an MRI scan due to contraindications for MRI, for example, pacemaker and certain other implants, severe claustrophobia.
  • Subjects unable to give informed consent.
  • Children and vulnerable populations.

Treatment and study plan

Primary outcomes

  1. Dice similarity score to assess distortions

    Time frame: Three Years

    Dice score provides a measure of how similar is the distortion-corrected image to a reference.

Secondary outcomes

  1. Radiological scoring of image quality

    Time frame: Three Years

    Diffusion images will be scored blinded to correction scheme on a scale: 1 - undiagnostic, 2- distorted but diagnostic, 3 - undistorted. The change in score following the proposed method will be reported.

  2. Diffusion coefficient consistency

    Time frame: Three Years

    Diffusion coefficients (ADC) in relatively undistorted regions will be compared pre and post distortion correction to quantify any changes (if the algorithm is working correctly, none are expected in these regions).

Sponsors and collaborators

Lead sponsor

University College, London

Other

Registry information

Official study title

Correction of Distortions in Diffusion MRI

Acronym: UNDISTORT

Important dates

Study start
2017
Primary completion
2021
Study completion
2021
First posted
May 12, 2017
Registry last updated
Oct 15, 2021

OpenTrials presents study information sourced from ClinicalTrials.gov. The official registry record should be consulted for the latest information.

View the official ClinicalTrials.gov record (opens in a new tab)

This listing is for discovery and informational purposes only. It is not medical advice, does not guarantee that a study is recruiting, and does not determine eligibility. Contact the study team and a qualified healthcare professional when considering participation.

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