CCP PET-MR

Collaborative Computational Project in Positron Emission Tomography
and Magnetic Resonance imaging

Exchange Programme

Funded researcher exchange scheme

The CCP for synergistic PET-MR reconstruction has funding to facilitate the exchange of staff and students between institutions, one of which must be a UK institution. Proposals are invited for full or part funding to enable the short term (up to 2 weeks) exchange of students and postdoctoral researchers. Such exchanges should further the aims for the CCP as detailed on the website. Proposals for exchanges should be submitted to Julian Matthews and should include:

  • A description of the purpose, the activities planned, and how the exchange will benefit the CCP (1 page max).
  • A short CV of the student or postdoctoral researcher.
  • The costs being requested with justification (1 page max).
  • A PDF letter or email of support from the host institution.
  • A PDF letter or email of support from the student’s supervisor or postdoctoral researcher’s line manager.

Ideally you should allow for 6-8 weeks from your request to notification of the funding decision. Following your visit we will ask you for a short report including a statement of outcomes for dissemination to the EPSRC as a case study and possible website publication.

Successful applications MUST submit the report within 2 months after the visit

Successful Grant Reports

Report for Exchange programme at UCL Daniel Deidda, Division of Biomedical Imaging and Department of Statistics, University of Leeds: Q1 2016

Abstract: The purpose of the exchange programme was to process and reconstruct list-mode data acquired from the Siemens PET-MR scanner as processing data from a PET-MR scanner is not straightforward, generally due to the incompatibility between the format of the scanner and the user software. In addition, Reconstruction taking into account attenuation, normalisation, random and scatter effects is an essential step. During the visit to UCL the main achievements were: that all necessary datasets are now readable; a script now exists for di erent reconstruction algorithms; and that reconstructions were successfully performed creating a range of images. We plan to make this script available to other users of the Siemens PET-MR scanner.

Full pdf report. 

Report for Exchange programme at the Frédéric Joliot Hospital (SHFJ) at CEA, Orsay, France by Ottavia Bertolli University College London January 12, 2017

Summary: The purpose of the exchange was to become familiar with the data acquisition process with the GE PET-MR system and with the use of the respiratory tracking device currently utilized in the centre (that is a pressure belt), and to acquire patient data with MR sequences that could allow the detection of an MR navigator (as representative of the internal respiratory motion of the organs). Moreover, data acquired with the GE PET-MR scanner were meant to be used as test datasets for the utilization of a feature of the STIR code, that allows the user to unlist the listmode files into sinograms (after the recent addition of the scanner to the library).

Full pdf report.

Report for Exchange programme at the Medical Imaging Research Center, Katholieke Universiteit Leuven (KUL), Leuven, Belgium, 18-30 April 2017, by Yu-Jung Tsai, a PhD student of UCL, London, UK

Summary:The main intention of the visit was to explore the use of a spatially variant penalty strength in penalized image reconstruction using anatomical information. As Parallel Level Sets (PLS) has shown promising results in literature, it was chosen to be incorporated into the previously proposed preconditioned algorithm (L-BFGS-B-PC) for achieving both good image quality and fast convergence rate. Since the penalty function has been well-studied by the host group, the other purpose of this exchange was to learn from their knowledge and experience on parameter optimization for PLS. The software developed (on top of STIR) during the visit can be used as a starting-point for integration into the CCP PETMR software which would allow users to utilize PLS with anatomical information derived from MR images during PET reconstructions. During this visit I interacted with several members of the group of Prof. J. Nuyts, most intensively with Dr Anna Turco and Dr Georg Schramm. In addition to helping me build up essential knowledge for the proposed joint project, they also provided plenty information regarding live in the center and the city so that I could get used to the new environment quickly and have a productive visit.

Full pdf report.

Report for exchange programme at University College London, UK, 17 October 2017, by Palak Wadhwa, University of Leeds.

Summary: This exchange programme was proposed to contribute towards the current devel-opments in Synergistic Image Reconstruction Framework (SIRF) to read and reconstruct positron emission tomography (PET) raw data from GE SIGNA PET/magnetic resonance (MR) scanner. There were three main challenges that were faced during PET data reconstruction with SIRF for real data produced by GE SIGNA PET/MR scanner prior to this exchange programme. These challenges included:
1. Random data correction: Randoms correction could not be carried out for the data acquired by GE SIGNA scanner.
2. Rotated images: There was a view angle o set between GE reconstructed image and SIRF for reconstructed images.
3. Time of Flight (ToF) reconstructions: Reconstructions with recent ToF code (to be included in SIRF) for real phantom data from the scanner was not validated. This ToF code will allow SIRF users to be able to reconstruct real ToF-PET data from GE SIGNA PET/MR (a scanner with 390 ps timing resolution) with all data corrections.
This visit was aimed to resolve all the above challenges. Additionally, PET/MR datasets were acquired using VQC calibration phantom provided by GE with GE SIGNA scanner located at Imanova, UK with the help of Dr. Gaspar Delso. This VQC phantom data was used to validate the rotation angle between GE and STIR. The dataset was also used to validate the random correction after the code was included in STIR. This dataset will prove to be bene cial for PET and MR data alignment that will be included within SIRF and will be made open source via Dementia Platform United Kingdom (DPUK). Another dataset with 2 GE-68 spheres as discussed in section 2.2, was collected at Imanova and this was used to validate the ToF code as discussed later in this report. Finally, all the code-based developments and outcomes of the visit are aimed to be available within SIRF as a part of this exchange programme.

Full pdf report.