ACRIPET

ACcurate Reconstruction In PET: Fully 3D PET reconstruction with compressed scatter system matrix

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 Obiettivo del progetto (Objective)

'In the fight against cancer, Positron Emission Tomography (PET) can provide 3D images of metabolic processes (i.e. of cells in action) in the body and contributes to diagnosis and treatment. Two-dimensional PET scanners (2D PET) have been replaced by three-dimensional PET machines combined with a CT (3D PET/CT). This led to complementary anatomical information (from the CT) and increased sensitivity (less noise in the images). However, the increased sensitivity comes along with an increased detection of scattered radiations that impair accurate quantitative measurements necessary for diagnosis and follow-up. PET images are usually reconstructed iteratively from the signal detected by the scanner using a system matrix that models the imaging process. In clinical 3D PET/CT, this huge system matrix (order of Terabytes) is highly simplified to make the problem tractable. Based on previous proof-of-principle studies in 2D PET by the applicant, the ACRIPET project proposes to develop a novel and accurate 3D reconstruction method based on an accurate (unlike approximate) system matrix obtained through Monte Carlo modelling of all patient and detector related effects interfering with the imaging process. The method uses compression schemes to reduce Monte Carlo noise and allow storage of the system matrix. These compression schemes will be extended to 3D PET and parallelized on multi node computer architecture to make accurate 3D PET reconstruction clinically feasible. By using the most modern computer resources to fully exploit the potential of 3D PET/CT scanners, PET image accuracy should be significantly increased, contributing to earlier detection and more precise characterization of the disease and of its evolution. The host laboratory has a high expertise and recognition in all fields involved the project and will contribute to enhance the researcher professional maturity for the development of his career in the field.'

Introduzione (Teaser)

Better imaging for cancer may mean that the disease is caught earlier on and treated more effectively. New scanning technology may also help diagnose heart and neurological problems more accurately.

Descrizione progetto (Article)

Imaging technology can be crucial for detecting at an early stage potentially fatal diseases such as cancer. In recent years, two-dimensional (2D) positron emission tomography (PET) scanning was replaced by more powerful 3D PET scanning, combined with computerised tomography (CT) scanning. However, scattered radiation resulting from increased sensitivity compromises accuracy, opening the door for improvements regarding this technology.

The EU-funded project 'Accurate Reconstruction in PET: Fully 3D PET reconstruction with compressed scatter system matrix' (Acripet) worked on new technology to improve scanning capabilities. It developed a more accurate 3D system using a new system matrix to reconstruct the imaging process.

This new method employs compression technology that reduces image 'noise' based on multi-node computer architecture, while remaining cost-effective and clinically feasible. The idea is that new computer power has the potential to improve PET image accuracy considerably, making it possible to diagnose cancer and similar diseases at an earlier stage.

With this in mind, new particle tracking algorithms were developed and applied to the software needed. The process of photons entering detection systems was also improved, as were the speed of calculation and memory storage. All these improvements and upgrades led to better reconstruction of images during preliminary trials.

Overall, project research and results have advanced the cause of highly accurate PET imaging greatly, which will be of great benefit in cancer diagnosis and patient follow-up. The technology looks very promising as well for patients within the fields of neurology and cardiology. The results may even be applied to small animal scanners, improving pre-clinical imaging used to develop pharmaceuticals and treatment.