Spatiotemporal PET reconstruction using ML-EM with learned diffeomorphic deformation

Patient movement in emission tomography deteriorates reconstruction quality because of motion blur. Gating the data improves the situation somewhat: each gate contains a movement phase which is approximately stationary. A standard method is to use only the data from a few gates, with little movement between them. However, the corresponding loss of data entails an increase of noise. Motion correction algorithms have been implemented to take into account all the gated data, but they do not scale well, especially not in 3D. We propose a novel motion correction algorithm which addresses the scalability issue. Our approach is to combine an enhanced ML-EM algorithm with deep learning based movement registration. The training is unsupervised, and with artificial data. We expect this approach to scale very well to higher resolutions and to 3D, as the overall cost of our algorithm is only marginally greater than that of a standard ML-EM algorithm. We show that we can significantly decrease the noise corresponding to a limited number of gates

4D Image Reconstruction with Dual Respiratory and Cardiac Motion Correction for Cardiac PET

4D image reconstruction with motion correction is the solution to improve image quality and resolution degraded by respiratory motion (RM) and cardiac motion (CM) in cardiac PET scans. The improved image quality can potentially improve clinical diagnosis, and can be traded for reduced injected radiation dose or reduced imaging time for improving patient comfort. There are three steps for 4D image reconstruction with motion correction: 1) 4D data generation (gating), 2) 4D respiratory and cardiac (R&C) motion estimation, and 3) 4D R&C motion correction. We have developed and evaluated multiple methods for each step including (step 1) data-driven gating, MRI-navigator-gating, (step 2) 4 different methods for dual R&C motion estimation after reconstruction (MEAR), CM estimation during reconstruction (MEDR), RM estimation before reconstruction (MEBR), and (step 3) dual R&C motion correction after (MCAR), during (MCDR), and before (MCBR) image reconstruction. Realistic Monte Carlo simulated 4D cardiac PET data using the 4D XCAT phantom and accurate models of the scanner design parameters and performance characteristics and clinical patient data were used to evaluate all different methods. Data-driven gating method was shown to provide robust gating results in high myocardium uptake situations while MRI-navigator based gating showed better results in low myocardium uptake situations. Separate R&C MEAR with modeling of RM on CM estimation was shown to be the best option for accurate estimation of dual R&C motion estimation. The MCDR method yields the best performance for different noise situations for both patient and simulation, while MCBR reduces computational time dramatically but the resultant 4D cardiac gated PET images has overall inferior image quality when compared to that from the MCAR and MCDR approaches in the ‘almost’ noise free case. Also, the MCBR method has better noise handling properties when compared with MCAR and provides better quantitative result in high noise cases. In general, our developed methods demonstrated the importance of motion correction on image qualities, our work also provide a general guideline for different applications that requires either highly quantitative data or qualitative images. Our works also provide practical means for applying 4D image reconstruction with reasonable computational cost

Improving Quantification in Lung PET/CT for the Evaluation of Disease Progression and Treatment Effectiveness

Positron Emission Tomography (PET) allows imaging of functional processes in vivo by measuring the distribution of an administered radiotracer. Whilst one of its main uses is directed towards lung cancer, there is an increased interest in diffuse lung diseases, for which the incidences rise every year, mainly due to environmental reasons and population ageing. However, PET acquisitions in the lung are particularly challenging due to several effects, including the inevitable cardiac and respiratory motion and the loss of spatial resolution due to low density, causing increased positron range. This thesis will focus on Idiopathic Pulmonary Fibrosis (IPF), a disease whose aetiology is poorly understood while patient survival is limited to a few years only. Contrary to lung tumours, this diffuse lung disease modifies the lung architecture more globally. The changes result in small structures with varying densities. Previous work has developed data analysis techniques addressing some of the challenges of imaging patients with IPF. However, robust reconstruction techniques are still necessary to obtain quantitative measures for such data, where it should be beneficial to exploit recent advances in PET scanner hardware such as Time of Flight (TOF) and respiratory motion monitoring. Firstly, positron range in the lung will be discussed, evaluating its effect in density-varying media, such as fibrotic lung. Secondly, the general effect of using incorrect attenuation data in lung PET reconstructions will be assessed. The study will compare TOF and non-TOF reconstructions and quantify the local and global artefacts created by data inconsistencies and respiratory motion. Then, motion compensation will be addressed by proposing a method which takes into account the changes of density and activity in the lungs during the respiration, via the estimation of the volume changes using the deformation fields. The method is evaluated on late time frame PET acquisitions using ¹⁸F-FDG where the radiotracer distribution has stabilised. It is then used as the basis for a method for motion compensation of the early time frames (starting with the administration of the radiotracer), leading to a technique that could be used for motion compensation of kinetic measures. Preliminary results are provided for kinetic parameters extracted from short dynamic data using ¹⁸F-FDG

Motion Correction of Whole-Body PET Data with a Joint PET-MRI Registration Functional

Respiratory motion is known to degrade image quality in PET imaging. The necessary acquisition time of several minutes per bed position will inevitably lead to a blurring effect due to organ motion. A lot of research has been done with regards to motion correction of PET data. As full-body PET-MRI became available recently, the anatomical data provided by MRI is a promising source of motion information. Current PET-MRI-based motion correction approaches, however, do not take into account the available information provided by PET data. PET data, though, may add valuable additional information to increase motion estimation robustness and precision.In this work we propose a registration functional that is capable of performing motion detection in gated data of two modalities simultaneously. Evaluation is performed using phantom data. We demonstrate that performing a joint registration of both modalities does improve registration accuracy and PET image quality.<br

Dual gated PET/CT imaging of heart

Coronary artery disease (CAD) resulting from atherosclerotic arterial changes, plaques, is a progressive process, which can be asymptomatic for many years. Asymptomatic CAD can cause a heart attack that leads to sudden death if the vulnerable coronary plaque ruptures and causes artery occlusion. The plaque inflammation plays an important role in the rupture susceptibility. Reliable anticipation of rupture is still clinically impossible for a single patient. Detection of the vulnerable coronary plaques before clinical signs remains a significant scientific challenge where positron emission tomography (PET) can play an important role. The aim of this dissertation was to find out whether a small, coronary plaque size, heart structures could be detected by a clinically available positron emission tomography and computed tomography (PET/CT) hybrid camera in realistically moving cardiac phantoms, a minipig model, and patients with CAD. Due to cardiac motions accurate detection of small heart structures are known to be problematic in PET imaging. Due to absence of commercial application at the beginning of the study, new dual gating method for cardiac PET imaging was developed and programmed that takes into account both contraction and respiratory induced cardiac motions. Cardiac phantom PET studies showed that small, active and moving plaques can be distinguished from myocardium activity and the gating methods improved the detection sensitivity and resolution of the plaques. In minipig and CAD patient cardiac PET studies small structures of myocardium and coronary arteries was detected more sensitive and accurately when using dual gating method than manufacturer gating methods. In cardiac patient PET study respiratory induced cardiac motions were shown to be linearly dependent with spirometry-measured respiratory volumes. Standard 3-lead electrocardiogram (ECG) measurement can be filtered by anesthesia monitor to detect lung impedance signal. In cardiac patient PET study this lung impedance signal were applied for respiratory gating. In this study was observed that the 3-lead ECG derived impedance signal gating method detects respiratory induced cardiac motion in PET as well as other externally used respiratory gating methods. In summary, the dual gated cardiac PET method is more sensitive and accurate to detect small cardiac structures, as coronary vessel wall pathology, than the commercial methods used in the study.Sydämen kaksoisliiketahdistettu PET/CT kuvantaminen Ateroskleroottisten valtimomuutosten, plakkien, seurauksena asteittain kehittyvä sepelvaltimotauti voi olla vuosia oireeton. Oireeton sepelvaltimotauti voi aiheuttaa äkkikuolemaan johtavan sydäninfarktin, mikäli sepelvaltimon seinämäplakin repeytymisestä aiheutuu verisuonen tukkiva hyytymä. Tutkimuksissa on osoitettu, että plakin tulehduksella on merkittävä rooli repeytymisalttiudelle. Repeytymisen luotettava ennakointi on yksittäisen potilaan kohdalla edelleen kliinisesti mahdotonta. Tulehtuneiden ja repeytymisalttiiden sepelvaltimoplakkien toteaminen ennen kliinisiä oireita on edelleen merkittävä tieteellinen haaste, missä positroniemissiotomografia (PET) kuvantamisella voi olla merkittävä rooli. Väitöskirjan tavoitteena oli selvittää, voidaanko kliinisessä käytössä olevalla positroniemissiotomografia ja tietokonetomografia (PET/TT) yhdistelmäkameralla havaita pieniä, sepelvaltimoplakkien kokoisia, sydämen rakenteita koneellisesti toimivissa todenmukaisissa sydänmalleissa, eläinmallissa ja sepelvaltimotautia sairastavilla potilailla. Sydämen pienten rakenteiden tarkka havaitseminen PET/TTkameroilla on haasteellista sydämen liikkumisen vuoksi. Tutkimuksessa kehitettiin ja ohjelmoitiin uusi sydämen PET-kuvantamisen liiketahdistusmenetelmä, joka ottaa huomioon sekä sydämen supistusliikkeen että hengitysliikkeen vaikutuksen sydämen PET kuvantamissa. Koneellisilla sydänmalleilla osoitettiin, että PET on riittävän herkkä havaitsemaan pieniä ja liikkuvia radioaktiivisia ”sepelvaltimoplakkeja”, ja että liiketahdistusmenetelmät parantavat plakkien havaitsemisherkkyyttä ja tarkkuutta. Eläinmallissa ja sepelvaltimotautipotilailla kaksoisliiketahdistusmenetelmän herkkyys ja tarkkuus havaita pieniä sydänlihaksen ja sepelvaltimoiden rakenteita todettiin kaupallisia tahdistusmenetelmiä paremmaksi. Potilastutkimuksissa todettiin hengityksen aiheuttama sydämen liike PET-kuvissa lineaarisesti riippuvaiseksi spirometrialla mitattujen hengitystilavuuksien kanssa. Tavallisesta 3-johtoisesta sydänsähkökäyrästä voidaan anestesiamonitorin avulla suodattaa keuhkojen impedanssisignaalia. Hengitysliikkeen aiheuttama potilaiden sydämen liike PETkuvissa havaittiin yhtä hyvin käyttämällä tätä keuhkojen impedanssisignaalia kuin muita yleisesti käytettäviä ulkoisia hengitystahdistussignaaleja. Todetaan, että kaksoisliiketahdistettu sydämen PET-kuvantamismenetelmä on tutkimuksessa käytettyjä kaupallisia menetelmiä herkempi ja tarkempi havaitsemaan sydämen pieniä rakenteita sekä sepelvaltimon seinämän tulehdusplakkeja