Hybrid Kernelised Expectation Maximisation Reconstruction Algorithms for Quantitative Positron Emission Tomography

Positron emission tomography (PET) imaging is commonly used in clinical practice to diagnose different diseases. However, the limited spatial resolution sometimes prevents the desired diagnostic accuracy. This work examines some of the issues related to PET image reconstruction in the context of PET-magnetic resonance (MR) imaging, and proposes a novel PET iterative reconstruction algorithm, hybrid kernelised expectation maximisation (HKEM), to overcome these issues by exploiting synergistic information from PET and MR images. When the number of detected events is low, the reconstructed images are often biased and noisy. Anatomically-guided PET image reconstruction techniques have been demonstrated to reduce partial volume effect (PVE), noise, and improve quantification, but, they have also been shown to rely on the accurate registration between the anatomical image and the PET image, otherwise they may suppress important PET information that may lead to false negative detection of disease. The aim of the HKEM algorithm is to maintain the benefits of the anatomically-guided methods and overcome their limitations by incorporating synergistic information iteratively. The findings obtained using simulated and real datasets, by performing region of interest (ROI) analysis and voxel-wise analysis are as follows: first, anatomically-guided techniques provide reduced PVE and higher contrast compared to standard techniques, and HKEM provides even higher contrast in almost all the cases; second, the absolute bias and the noise affecting low-count datasets is reduced; third, HKEM reduces PET unique features suppression due to PET-MR spatial inconsistency. This thesis, therefore argues that using synergistic information, via the kernel method, increases the accuracy and precision of the PET clinical diagnostic examination. The promising quantitative features of the HKEM method give the opportunity to explore many possible clinical applications, such as cancer and inflammation

Triple modality image reconstruction of PET data using SPECT, PET, CT information increases lesion uptake in images of patients treated with radioembolization with [Formula: see text] micro-spheres.

PURPOSE: Nuclear medicine imaging modalities like computed tomography (CT), single photon emission CT (SPECT) and positron emission tomography (PET) are employed in the field of theranostics to estimate and plan the dose delivered to tumors and the surrounding tissues and to monitor the effect of the therapy. However, therapeutic radionuclides often provide poor images, which translate to inaccurate treatment planning and inadequate monitoring images. Multimodality information can be exploited in the reconstruction to enhance image quality. Triple modality PET/SPECT/CT scanners are particularly useful in this context due to the easier registration process between images. In this study, we propose to include PET, SPECT and CT information in the reconstruction of PET data. The method is applied to Yttrium-90 ([Formula: see text]Y) data. METHODS: Data from a NEMA phantom filled with [Formula: see text]Y were used for validation. PET, SPECT and CT data from 10 patients treated with Selective Internal Radiation Therapy (SIRT) were used. Different combinations of prior images using the Hybrid kernelized expectation maximization were investigated in terms of VOI activity and noise suppression. RESULTS: Our results show that triple modality PET reconstruction provides significantly higher uptake when compared to the method used as standard in the hospital and OSEM. In particular, using CT-guided SPECT images, as guiding information in the PET reconstruction significantly increases uptake quantification on tumoral lesions. CONCLUSION: This work proposes the first triple modality reconstruction method and demonstrates up to 69% lesion uptake increase over standard methods with SIRT [Formula: see text]Y patient data. Promising results are expected for other radionuclide combination used in theranostic applications using PET and SPECT

Hybrid kernelised expectation maximisation for Bremsstrahlung SPECT reconstruction in SIRT with 90Y micro-spheres

BACKGROUND: Selective internal radiation therapy with Yttrium-90 microspheres is an effective therapy for liver cancer and liver metastases. Yttrium-90 is mainly a high-energy beta particle emitter. These beta particles emit Bremsstrahlung radiation during their interaction with tissue making post-therapy imaging of the radioactivity distribution feasible. Nevertheless, image quality and quantification is difficult due to the continuous energy spectrum which makes resolution modelling, attenuation and scatter estimation challenging and therefore the dosimetry quantification is inaccurate. As a consequence a reconstruction algorithm able to improve resolution could be beneficial. METHODS: In this study, the hybrid kernelised expectation maximisation (HKEM) is used to improve resolution and contrast and reduce noise, in addition a modified HKEM called frozen HKEM (FHKEM) is investigated to further reduce noise. The iterative part of the FHKEM kernel was frozen at the 72nd sub-iteration. When using ordered subsets algorithms the data is divided in smaller subsets and the smallest algorithm iterative step is called sub-iteration. A NEMA phantom with spherical inserts was used for the optimisation and validation of the algorithm, and data from 5 patients treated with Selective internal radiation therapy were used as proof of clinical relevance of the method. RESULTS: The results suggest a maximum improvement of 56% for region of interest mean recovery coefficient at fixed coefficient of variation and better identification of the hot volumes in the NEMA phantom. Similar improvements were achieved with patient data, showing 47% mean value improvement over the gold standard used in hospitals. CONCLUSIONS: Such quantitative improvements could facilitate improved dosimetry calculations with SPECT when treating patients with Selective internal radiation therapy, as well as provide a more visible position of the cancerous lesions in the liver

Attenuation Correction Using Template PET Registration for Brain PET: A Proof-of-Concept Study

NeuroLF is a dedicated brain PET system with an octagonal prism shape housed in a scanner head that can be positioned around a patient's head. Because it does not have MR or CT capabilities, attenuation correction based on an estimation of the attenuation map is a crucial feature. In this article, we demonstrate this method on [18F]FDG PET brain scans performed with a low-resolution proof of concept prototype of NeuroLF called BPET. We perform an affine registration of a template PET scan to the uncorrected emission image, and then apply the resulting transform to the corresponding template attenuation map. Using a whole-body PET/CT system as reference, we quantitively show that this method yields comparable image quality (0.893 average correlation to reference scan) to using the reference µ-map as obtained from the CT scan of the imaged patient (0.908 average correlation). We conclude from this initial study that attenuation correction using template registration instead of a patient CT delivers similar results and is an option for patients undergoing brain PET. Keywords: Nifty-Reg; PET; STIR; attenuation correction; brain; image reconstruction; registration; tomography

Attenuation Correction Using Template PET Registration for Brain PET:A Proof-of-Concept Study

NeuroLF is a dedicated brain PET system with an octagonal prism shape housed in a scanner head that can be positioned around a patient’s head. Because it does not have MR or CT capabilities, attenuation correction based on an estimation of the attenuation map is a crucial feature. In this article, we demonstrate this method on [18F]FDG PET brain scans performed with a low-resolution proof of concept prototype of NeuroLF called BPET. We perform an affine registration of a template PET scan to the uncorrected emission image, and then apply the resulting transform to the corresponding template attenuation map. Using a whole-body PET/CT system as reference, we quantitively show that this method yields comparable image quality (0.893 average correlation to reference scan) to using the reference µ-map as obtained from the CT scan of the imaged patient (0.908 average correlation). We conclude from this initial study that attenuation correction using template registration instead of a patient CT delivers similar results and is an option for patients undergoing brain PET.</p

Attenuation Correction Using Template PET Registration for Brain PET:A Proof-of-Concept Study

NeuroLF is a dedicated brain PET system with an octagonal prism shape housed in a scanner head that can be positioned around a patient’s head. Because it does not have MR or CT capabilities, attenuation correction based on an estimation of the attenuation map is a crucial feature. In this article, we demonstrate this method on [18F]FDG PET brain scans performed with a low-resolution proof of concept prototype of NeuroLF called BPET. We perform an affine registration of a template PET scan to the uncorrected emission image, and then apply the resulting transform to the corresponding template attenuation map. Using a whole-body PET/CT system as reference, we quantitively show that this method yields comparable image quality (0.893 average correlation to reference scan) to using the reference µ-map as obtained from the CT scan of the imaged patient (0.908 average correlation). We conclude from this initial study that attenuation correction using template registration instead of a patient CT delivers similar results and is an option for patients undergoing brain PET.</p

Attenuation Correction Using Template PET Registration for Brain PET:A Proof-of-Concept Study

NeuroLF is a dedicated brain PET system with an octagonal prism shape housed in a scanner head that can be positioned around a patient’s head. Because it does not have MR or CT capabilities, attenuation correction based on an estimation of the attenuation map is a crucial feature. In this article, we demonstrate this method on [18F]FDG PET brain scans performed with a low-resolution proof of concept prototype of NeuroLF called BPET. We perform an affine registration of a template PET scan to the uncorrected emission image, and then apply the resulting transform to the corresponding template attenuation map. Using a whole-body PET/CT system as reference, we quantitively show that this method yields comparable image quality (0.893 average correlation to reference scan) to using the reference µ-map as obtained from the CT scan of the imaged patient (0.908 average correlation). We conclude from this initial study that attenuation correction using template registration instead of a patient CT delivers similar results and is an option for patients undergoing brain PET.</p

Attenuation Correction Using Template PET Registration for Brain PET:A Proof-of-Concept Study

NeuroLF is a dedicated brain PET system with an octagonal prism shape housed in a scanner head that can be positioned around a patient’s head. Because it does not have MR or CT capabilities, attenuation correction based on an estimation of the attenuation map is a crucial feature. In this article, we demonstrate this method on [18F]FDG PET brain scans performed with a low-resolution proof of concept prototype of NeuroLF called BPET. We perform an affine registration of a template PET scan to the uncorrected emission image, and then apply the resulting transform to the corresponding template attenuation map. Using a whole-body PET/CT system as reference, we quantitively show that this method yields comparable image quality (0.893 average correlation to reference scan) to using the reference µ-map as obtained from the CT scan of the imaged patient (0.908 average correlation). We conclude from this initial study that attenuation correction using template registration instead of a patient CT delivers similar results and is an option for patients undergoing brain PET.</p

Evaluation of the Healthy Start Voucher Scheme in UK: a natural experiment using the Growing Up in Scotland record linkage study and the Infant Feeding Survey

Background: Having a good start in life during pregnancy and infancy has been shown to be important for living both a healthy life and a longer life. Despite the introduction of many policies for the early-years age group, including voucher schemes, with the aim of improving nutrition, there is limited evidence of their impact on health. Objectives: To assess the effectiveness of the Healthy Start voucher scheme on infant, child and maternal outcomes, and to capture the lived experiences of the Healthy Start voucher scheme for low-income women. Design: This was a natural experiment study using existing data sets, linked to routinely collected health data sets, with a nested qualitative study of low-income women and an assessment of the health economics. Setting: Representative sample of Scottish children and UK children. Participants: Growing Up in Scotland cohort 2 (n = 2240), respondents to the 2015 Infant Feeding Study (n = 8067) and a sample of 40 participants in the qualitative study. Interventions: The Health Start voucher, a means-tested scheme that provides vouchers worth £3.10 per week to spend on liquid milk, formula milk, fruit and vegetables. Main outcome measures: Infant and child outcomes – breastfeeding initiation and duration; maternal outcomes – vitamin use pre and during pregnancy. Results: The exposed group were women receiving the Healthy Start voucher (R), with two control groups: eligible and not claiming the Healthy Start voucher (E) and nearly eligible. There was no difference in vitamin use during pregnancy for either comparison (receiving the Healthy Start voucher, 82%; eligible and not claiming the Healthy Start voucher, 86%; p = 0.10 vs. receiving the Healthy Start voucher, 87%; nearly eligible, 88%; p = 0.43) in the Growing Up in Scotland cohort. Proportions were similar for the Infant Feeding Study cohort (receiving the Healthy Start voucher, 89%; eligible and not claiming the Healthy Start voucher, 86%; p = 0.01 vs. receiving the Healthy Start voucher, 89%; nearly eligible, 87%; p = 0.01); although results were statistically significantly different, these were small effect sizes. There was no difference for either comparison in breastfeeding initiation or breastfeeding duration in months in Growing Up in Scotland, but there was a negative effect of the Healthy Start voucher in the Infant Feeding Survey. This contrast between data sets indicates that results are inconclusive for breastfeeding. The qualitative study found that despite the low monetary value the women valued the Healthy Start voucher scheme. However, the broader lives of low-income women are crucial to understand the constraints to offer a healthy diet. Limitations: Owing to the policy being in place, it was difficult to identify appropriate control groups using existing data sources, especially in the Infant Feeding Study. Conclusions: As the Healthy Start voucher scheme attempts to influence health behaviour, this evaluation can inform other policies aiming to change behaviour and use voucher incentives. The null effect of Healthy Start vouchers on the primary outcomes may be due to the value of the vouchers being insufficient to change the broader lives of low-income women to offer a healthy diet. Future work: The methods developed to undertake an economic evaluation alongside a natural experiment using existing data can be used to explore the cost-effectiveness of the Healthy Start voucher scheme. Funding: This project was funded by the National Institute for Health and Care Research (NIHR) Public Health Research programme and will be published in full in Public Health Research; Vol. 11, No. 11. See the NIHR Journals Library website for further project information