Data Driven Surrogate Signal Extraction for Dynamic PET Using Selective PCA

Respiratory motion correction is beneficial in PET. Methods of motion correction include gated reconstruction, where the acquisition is binned, based on a respiratory trace. To acquire these respiratory traces, an external device, like the Real Time Position Management System, or a data driven method, such as PCA, can be used. Data driven methods have the advantage that they are non-invasive, and can be performed post-acquisition. However, data driven methods have the disadvantage that they are adversely affected by the tracer kinetics of a dynamic acquisition. This work seeks to evaluate several adaptions of the PCA method, through which it can be used with dynamic data. The methods explored in this work include, using a moving window (similar to the KRG method of Schleyer et al. (PMB 2014)), extrapolation of the principal component from later time points to earlier time points, as well as a method to select and combine multiple respiratory components. The respiratory traces acquired, were evaluated on 21 patients, by calculating their correlation with a Real Time Position Management System surrogate signal. The results indicate that all methods produce better surrogate signals than when applying static PCA to dynamic data. Extrapolating a late principal component, produced more promising results than using a moving window, and selecting and combining components held benefits for all methods

Data driven surrogate signal extraction for dynamic PET using selective PCA: time windows versus the combination of components

Objective. Respiratory motion correction is beneficial in positron emission tomography (PET), as it can reduce artefacts caused by motion and improve quantitative accuracy. Methods of motion correction are commonly based on a respiratory trace obtained through an external device (like the real time position management system) or a data driven method, such as those based on dimensionality reduction techniques (for instance principal component analysis (PCA)). PCA itself being a linear transformation to the axis of greatest variation. Data driven methods have the advantage of being non-invasive, and can be performed post-acquisition. However, their main downside being that they are adversely affected by the tracer kinetics of the dynamic PET acquisition. Therefore, they are mostly limited to static PET acquisitions. This work seeks to extend on existing PCA-based data-driven motion correction methods, to allow for their applicability to dynamic PET imaging. Approach. The methods explored in this work include; a moving window approach (similar to the Kinetic Respiratory Gating method from Schleyer et al (2014)), extrapolation of the principal component from later time points to earlier time points, and a method to score, select, and combine multiple respiratory components. The resulting respiratory traces were evaluated on 22 data sets from a dynamic [18F]-FDG study on patients with idiopathic pulmonary fibrosis. This was achieved by calculating their correlation with a surrogate signal acquired using a real time position management system. Main results. The results indicate that all methods produce better surrogate signals than when applying conventional PCA to dynamic data (for instance, a higher correlation with a gold standard respiratory trace). Extrapolating a late time point principal component produced more promising results than using a moving window. Scoring, selecting, and combining components held benefits over all other methods. Significance. This work allows for the extraction of a surrogate signal from dynamic PET data earlier in the acquisition and with a greater accuracy than previous work. This potentially allows for numerous other methods (for instance, respiratory motion correction) to be applied to this data (when they otherwise could not be previously used)

How does reviewing the evidence change veterinary surgeons' beliefs regarding the treatment of ovine footrot? A quantitative and qualitative study

Footrot is a widespread, infectious cause of lameness in sheep, with major economic and welfare costs. The aims of this research were: (i) to quantify how veterinary surgeons’ beliefs regarding the efficacy of two treatments for footrot changed following a review of the evidence (ii) to obtain a consensus opinion following group discussions (iii) to capture complementary qualitative data to place their beliefs within a broader clinical context. Grounded in a Bayesian statistical framework, probabilistic elicitation (roulette method) was used to quantify the beliefs of eleven veterinary surgeons during two one-day workshops. There was considerable heterogeneity in veterinary surgeons’ beliefs before they listened to a review of the evidence. After hearing the evidence, seven participants quantifiably changed their beliefs. In particular, two participants who initially believed that foot trimming with topical oxytetracycline was the better treatment, changed to entirely favour systemic and topical oxytetracycline instead. The results suggest that a substantial amount of the variation in beliefs related to differences in veterinary surgeons’ knowledge of the evidence. Although considerable differences in opinion still remained after the evidence review, with several participants having non-overlapping 95% credible intervals, both groups did achieve a consensus opinion. Two key findings from the qualitative data were: (i) veterinary surgeons believed that farmers are unlikely to actively seek advice on lameness, suggesting a proactive veterinary approach is required (ii) more attention could be given to improving the way in which veterinary advice is delivered to farmers. In summary this study has: (i) demonstrated a practical method for probabilistically quantifying how veterinary surgeons’ beliefs change (ii) revealed that the evidence that currently exists is capable of changing veterinary opinion (iii) suggested that improved transfer of research knowledge into veterinary practice is needed (iv) identified some potential obstacles to the implementation of veterinary advice by farmers

Delineating associations of progressive pleuroparenchymal fibroelastosis in patients with pulmonary fibrosis

BACKGROUND: Computer quantification of baseline computed tomography (CT) radiological pleuroparenchymal fibroelastosis (PPFE) associates with mortality in idiopathic pulmonary fibrosis (IPF). We examined mortality associations of longitudinal change in computer-quantified PPFE-like lesions in IPF and fibrotic hypersensitivity pneumonitis (FHP). METHODS: Two CT scans 6-36 months apart were retrospectively examined in one IPF (n=414) and one FHP population (n=98). Annualised change in computerised upper-zone pleural surface area comprising radiological PPFE-like lesions (Δ-PPFE) was calculated. Δ-PPFE >1.25% defined progressive PPFE above scan noise. Mixed-effects models evaluated Δ-PPFE against change in visual CT interstitial lung disease (ILD) extent and annualised forced vital capacity (FVC) decline. Multivariable models were adjusted for age, sex, smoking history, baseline emphysema presence, antifibrotic use and diffusion capacity of the lung for carbon monoxide. Mortality analyses further adjusted for baseline presence of clinically important PPFE-like lesions and ILD change. RESULTS: Δ-PPFE associated weakly with ILD and FVC change. 22-26% of IPF and FHP cohorts demonstrated progressive PPFE-like lesions which independently associated with mortality in the IPF cohort (hazard ratio 1.25, 95% CI 1.16-1.34, p<0.0001) and the FHP cohort (hazard ratio 1.16, 95% CI 1.00-1.35, p=0.045). INTERPRETATION: Progression of PPFE-like lesions independently associates with mortality in IPF and FHP but does not associate strongly with measures of fibrosis progression

Optimisation of the air fraction correction for lung PET/CT: addressing resolution mismatch

Abstract Background Increased pulmonary $$^{18}{}$$ 18 F-FDG metabolism in patients with idiopathic pulmonary fibrosis, and other forms of diffuse parenchymal lung disease, can predict measurements of health and lung physiology. To improve PET quantification, voxel-wise air fractions (AF) determined from CT can be used to correct for variable air content in lung PET/CT. However, resolution mismatches between PET and CT can cause artefacts in the AF-corrected image. Methods Three methodologies for determining the optimal kernel to smooth the CT are compared with noiseless simulations and non-TOF MLEM reconstructions of a patient-realistic digital phantom: (i) the point source insertion-and-subtraction method, $$h_{pts}$$ h pts ; (ii) AF-correcting with varyingly smoothed CT to achieve the lowest RMSE with respect to the ground truth (GT) AF-corrected volume of interest (VOI), $$h_{AFC}$$ h AFC ; iii) smoothing the GT image to match the reconstruction within the VOI, $$h_{PVC}$$ h PVC . The methods were evaluated both using VOI-specific kernels, and a single global kernel optimised for the six VOIs combined. Furthermore, $$h_{PVC}$$ h PVC was implemented on thorax phantom data measured on two clinical PET/CT scanners with various reconstruction protocols. Results The simulations demonstrated that at $$<200$$ < 200 iterations (200 i), the kernel width was dependent on iteration number and VOI position in the lung. The $$h_{pts}$$ h pts method estimated a lower, more uniform, kernel width in all parts of the lung investigated. However, all three methods resulted in approximately equivalent AF-corrected VOI RMSEs (<10%) at $$\ge$$ ≥ 200i. The insensitivity of AF-corrected quantification to kernel width suggests that a single global kernel could be used. For all three methodologies, the computed global kernel resulted in an AF-corrected lung RMSE <10%  at $$\ge$$ ≥ 200i, while larger lung RMSEs were observed for the VOI–specific kernels. The global kernel approach was then employed with the $$h_{PVC}$$ h PVC method on measured data. The optimally smoothed GT emission matched the reconstructed image well, both within the VOI and the lung background. VOI RMSE was <10%, pre-AFC, for all reconstructions investigated. Conclusions Simulations for non-TOF PET indicated that around 200i were needed to approach image resolution stability in the lung. In addition, at this iteration number, a single global kernel, determined from several VOIs, for AFC, performed well over the whole lung. The $$h_{PVC}$$ h PVC method has the potential to be used to determine the kernel for AFC from scans of phantoms on clinical scanners

Investigating the role of platelets and platelet-derived transforming growth factor-β in idiopathic pulmonary fibrosis

Transforming growth factor-β1 (TGFβ1) is the key pro-fibrotic cytokine in idiopathic pulmonary fibrosis (IPF), but the primary source of this cytokine in this disease is unknown. Platelets have abundant stores of TGFβ1, although the role of these cells in IPF is ill-defined. In this study, we investigated whether platelets, and specifically platelet-derived TGFβ1, mediate IPF disease progression. IPF and non-IPF patients were recruited to determine platelet reactivity and separate cohorts of IPF patients were followed for mortality. To study whether platelet-derived TGFβ1 modulates pulmonary fibrosis (PF), mice with a targeted deletion of TGFβ1 in megakaryocytes and platelets (TGFβ1fl/fl.PF4-Cre) were used in the well-characterized bleomycin-induced pulmonary fibrosis (PF) animal model. In a discovery cohort, we found significantly higher mortality in IPF patients with elevated platelet counts within the normal range. However, our validation cohort did not confirm this observation, despite significantly increased platelets, neutrophils, active TGFβ1 and CCL5, a chemokine produced by inflammatory cells, in the blood, lung and bronchoalveolar lavage (BAL) of IPF patients. In vivo, we showed that despite platelets being readily detected within the lungs of bleomycin-treated mice, neither the degree of pulmonary inflammation or fibrosis were significantly different between TGFβ1fl/fl.PF4-Cre and control mice. Our results demonstrate for the first-time that platelet-derived TGFβ1 does not significantly mediate inflammation or fibrosis in a PF animal model. Furthermore, our human studies revealed blood platelet counts do not consistently predict mortality in IPF but other platelet-derived mediators, such as CCL5, may promote neutrophil recruitment and human IPF

Data driven surrogate signal extraction for dynamic PET using selective PCA: time windows versus the combination of components.

Acknowledgements: This research was supported by GE Healthcare, the NIHR UCLH Biomedical Research Centre and the UCL EPSRC Centre for Doctoral Training in Intelligent, Integrated Imaging in Healthcare (i4health) Grant (EP/L016478/1). The software used was partly produced by the Computational Collaborative Project on Synergistic Biomedical Imaging, CCP SyneRBI, UK EPSRC Grant (EP/T026693/1). Jamie R McClelland is supported by a Cancer Research UK Centres Network Accelerator Award Grant (A21993) to the ART-NET consortium and a CRUK Multi-disciplinary Grant (CRC 521).Funder: NIHR UCLH Biomedical Research CentreFunder: GE Healthcare; doi: http://dx.doi.org/10.13039/100006775Objective.Respiratory motion correction is beneficial in positron emission tomography (PET), as it can reduce artefacts caused by motion and improve quantitative accuracy. Methods of motion correction are commonly based on a respiratory trace obtained through an external device (like the real time position management system) or a data driven method, such as those based on dimensionality reduction techniques (for instance principal component analysis (PCA)). PCA itself being a linear transformation to the axis of greatest variation. Data driven methods have the advantage of being non-invasive, and can be performed post-acquisition. However, their main downside being that they are adversely affected by the tracer kinetics of the dynamic PET acquisition. Therefore, they are mostly limited to static PET acquisitions. This work seeks to extend on existing PCA-based data-driven motion correction methods, to allow for their applicability to dynamic PET imaging.Approach.The methods explored in this work include; a moving window approach (similar to the Kinetic Respiratory Gating method from Schleyeret al(2014)), extrapolation of the principal component from later time points to earlier time points, and a method to score, select, and combine multiple respiratory components. The resulting respiratory traces were evaluated on 22 data sets from a dynamic [18F]-FDG study on patients with idiopathic pulmonary fibrosis. This was achieved by calculating their correlation with a surrogate signal acquired using a real time position management system.Main results.The results indicate that all methods produce better surrogate signals than when applying conventional PCA to dynamic data (for instance, a higher correlation with a gold standard respiratory trace). Extrapolating a late time point principal component produced more promising results than using a moving window. Scoring, selecting, and combining components held benefits over all other methods.Significance.This work allows for the extraction of a surrogate signal from dynamic PET data earlier in the acquisition and with a greater accuracy than previous work. This potentially allows for numerous other methods (for instance, respiratory motion correction) to be applied to this data (when they otherwise could not be previously used)

Plant natriuretic peptide active site determination and effects on cGMP and cell volume regulation

Natriuretic peptides (NP) were first identified in animals where they play a role in the regulation of salt and water balance. This regulation is partly mediated by intracellular changes in cyclic GMP (cGMP). NP immunoanalogues occur in many plants and have been isolated, with two NP encoding genes characterised in Arabidopsis thaliana L. (AtPNP-A and AtPNP-B). Part of AtPNP-A contains the region with homology to human atrial (A)NP. We report here on the effects of recombinant AtPNP-A and smaller synthetic peptides within the ANP-homologous region with a view to identifying the biologically active domain of the molecule. Furthermore, we investigated interactions between AtPNP-A and the hormone, abscisic acid (ABA). ABA does not significantly affect Arabidopsis mesophyll protoplast volume regulation, whereas AtPNP-A and synthetic peptides promote water uptake into the protoplasts causing swelling. This effect is promoted by the membrane permeable cGMP analogue, 8-Br-cGMP, and inhibited by guanylate cyclase inhibitors indicating that increases in cGMP are an essential component of the plant natriuretic peptides (PNP) signalling cascade. ABA does not induce cGMP transients and does not affect AtPNP-A dependent cGMP increases, hence the two regulators differ in their second messenger signatures. Interestingly, AtPNP-A significantly delays and reduces the extent of ABA stimulated stomatal closure that is also based on cell volume regulation. We conclude that a complex interplay between observed PNP effects (stomatal opening and protoplast swelling) and ABA is likely to be cell type specific.<br /