PET/CT Motion Correction Exploiting Motion Models Fit on Coarsely Gated Data Applied to Finely Gated Data

Motion correction is imperative to the reduction of blurring and artefacts inherent in PET; due to the relatively long acquisition time, and the temporal difference in the attenuation map acquisition. Registration literature contains many examples of spatial regularisers, however there are few temporal regularisers. Motion models can act as such a temporal regulariser, as well as allowing for the interpolation of unseen motion correction results. In our previous work, we applied a motion modelling approach to high TOF resolution non-attenuation corrected data; where the data was corrected to the space of the attenuation map. However, this approach was challenging, especially when low contrast lung tumours are present. This work seeks to extend previous work, by incorporating an approach suggested by Y. Lu et al. (JNM 2018), to perform an initial MLACF reconstruction for the motion estimation. In this work, we combine these two approaches, with several improvements, including; µ-map alignment, as well as, fitting the motion model on low noise low temporal/gate resolution data, and applying it to high noise high temporal/gate resolution data. To test this, XCAT volumes are constructed, and TOF data simulated. Evaluation compares the results of the proposed method against, where the motion model was fit on data gated more finely, where the motion model was fit on noiseless data, and finally non-motion corrected examples. Results indicate that the incorporation of MLACF, and fitting of the motion model on low noise low temporal/gate resolution data, improves contrast and quantification, while allowing for a relatively fast execution time

Pseudo-Bayesian DIP Denoising as a Preprocessing Step for Kinetic Modelling in Dynamic PET

Noise (among other artefacts) could be considered to be the bane of PET. Many methods have been proposed to alleviate the worst annoyances of noise, however, not many take into account the temporal nature of dynamically acquired PET. Here, we propose an adaption of a method, which has seen increasing attention in more traditional imaging denoising circles. Deep Image Prior exploits the initialisation of a carefully designed neural network, so as to treat it as a bank of custom filters, which are to be trained and used afresh on each new image, independently. Deep Image Prior has seen adaptation to PET previously (including dynamic PET), however, many of these adaptations do not take into account the large memory requirements of the method. Additionally, most previous work does not address the main weakness of the Deep Image Prior, its stopping criteria. Here, we propose a method which is both memory efficient, and includes a smoothing regularisation. In addition, we provide uncertainty estimates by incorporating a Bayesian approximation (using dropout), and prototype a training scheme by which the model is fit on all data simultaneously. The denoised images are then used as input for kinetic modelling. To evaluate the method, dynamic XCAT simulations have been produced, with a field of view of the lung and liver. The results of the new methods (along with total variation and the old Deep Image Prior) have been compared by; a visual analysis, SSIM, and K i values. Results indicate that the new methods potentially outperform the old methods, without increasing computation time, while reducing system requirements

Chemical composition of Desulfovibrio desulfuricans lipid A

Lipopolysaccharides also called endotoxins are an integral component of the outer membrane of Gram-negative bacteria. When released from the bacterial surface, they interact with a host immune system, triggering excessive inflammatory response. Lipid A is the biologically most active part of endotoxin, and its activity is modulated by the quantity, quality and arrangement of its fatty acids. Desulfovibrio desulfuricans is sulfate-reducing, Gram-negative bacterium that is supposed to be opportunistic pathogens of humans and animals. In the present study, chemical composition of lipid A from various strains of D. desulfuricans was analyzed by gas chromatography/mass spectrometry. It was found that the fatty acid component of the lipid A contains dodecanoic, tetradecanoic, 3-hydroxytetradecanoic and hexadecanoic acids, and its carbohydrate core is composed of glucosamine. The analysis of 3-acyloxyacyl residue of the lipid A revealed the presence of amide-bound 3-(dodecanoyloxy)tetradecanoic and 3-(hexadecanoyloxy)tetradecanoic acids and ester-bound 3-(tetradecanoyloxy)tetradecanoic acid. It was concluded that both fatty acid and 3-acyloxyacyl residue profiles of the lipid A from the studied bacteria were similar to those of E. coli and S.enterica

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)

Comparison of Motion Correction Methods Incorporating Motion Modelling for PET/CT Using a Single Breath Hold Attenuation Map

Introducing motion models into respiratory motion correction methods can lead to a reduction in blurring and artefacts. However, the pool of research where motion modelling methods are applied to combined positron emission tomography and computed tomography is relatively shallow. Previous work used non-attenuation corrected time-of-flight data to fit motion models, not only to motion correct the volumes themselves, but also to warp a single attenuation map to the positions of the initial gated data. This work seeks to extend previous work to offer a comparison of respiratory motion correction methods, not only with and without motion models, but also to compare pair-wise and group-wise registration techniques, on simulation data, in a low count scenario, where the attenuation map is from a pseudo-breath hold acquisition. To test the methods, 4-Dimensional Extended Cardiac Torso images are constructed, simulated and reconstructed without attenuation correction, then motion corrected using one of pair-wise, pair-wise with motion model, group-wise and group-wise with motion model registration. Next these motion corrected volumes are registered to the breath hold attenuation map. The positron emission tomography data are then reconstructed using deformed attenuation maps and motion corrected. Evaluation compares the results of these methods against non-motion corrected and motion free examples. Results indicate that the incorporation of motion models and group-wise registration, improves contrast and quantification

Performance of a BGO PET/CT with Higher Resolution PET Detectors

A new PET detector block has been designed to replace the standard detector of the Discovery ST PET/CT system. The new detector block is the same size as the original, but consists of an 8/spl times/6 (tangential× axial) matrix of crystals rather than the original 6/spl times/6. The new crystal dimensions are 4.7× 6.3× 30 mm/sup 3/ (tangential× axial× radial). Full PET/CT systems have been built with these detectors (Discovery STE). Most other aspects of the system are identical to the standard Discovery ST, with differences including the low energy threshold for 3D imaging (now 425 keV) and front-end electronics. Initial performance evaluation has been done, including NEMA NU2-2001 tests and imaging of the 3D Hoffman brain phantom and a neck phantom with small lesions. The system sensitivity was 1.90 counts/s/kBq in 2D, and 9.35 counts/s/kBq in 3D. Scatter fractions measured for 2D and 3D, respectively, were 18.6% and 34.5%. In 2D, the peak NEC of 89.9 kcps occurred at 47.0 kBq/cc. In 3D, the peak NEC of 74.3 kcps occurred at 8.5 kBq/cc. Spatial resolution (all expressed in mm FWHM) measured in 2D for 1 cm off-axis source 5.06 transaxial, 5.14 axial and for 10 cm source 5.45 radial, 5.86 tangential, and 6.23 axial. In 3D for 1 cm off-axis source 5.13 transaxial, 5.74 axial, and for 10 cm source 5.92 radial, 5.54 tangential, and 6.16 axial. Images of the brain and neck phantom demonstrate some improvement, compared to measurements on a standard Discovery ST

Prevalence and Outcomes of Concomitant Aortic Stenosis and Cardiac Amyloidosis

Background: Older patients with severe aortic stenosis (AS) are increasingly identified to have cardiac amyloidosis (CA). It is unknown whether dual AS-CA has worse outcomes or results in futility of transcatheter aortic valve replacement (TAVR). / Objective: To identify clinical characteristics and outcomes of AS-CA compared to lone AS. / Methods: TAVR referrals at three international sites underwent blinded research-corelab 99mTc-DPD bone scintigraphy (Perugini Grade-0 negative, 1–3 increasingly positive) prior to intervention. Transthyretin-CA (ATTR) was diagnosed by DPD and absence of a clonal immunoglobulin, and light-chain-CA (AL) via tissue biopsy. National registries captured all-cause mortality. / Results: 407 patients (83.4±6.5 years, 49.8% male) were recruited. DPD was positive in n=48 (11.8%, Grade-1 3.9%[n=16] Grade-2/3 7.9%[n=32]); AL was diagnosed in one Grade-1. Grade-2/3 patients had worse functional capacity, biomarkers (NT-proBNP/hsTnT), and bi-ventricular remodeling. A clinical score (RAISE) using left-ventricular Remodeling (hypertrophy/diastolic dysfunction), Age, Injury (hsTnT), Systemic involvement, and Electrical abnormalities (RBBB/low-voltages) was developed to predict AS-CA presence (AUC 0.86, 95%CI 0.78-0.94, p<0.001). Heart Team decision (DPD-blinded) resulted in TAVR (333[81.6%]), surgical-AVR (10[2.5%]), or medical management (65[15.9%]). After median 1.7 years, 23% of patients had died. 1-year mortality was worse in all-comers AS-CA (Grade-1-3) than lone AS (24.5 vs 13.9%, p=0.05). TAVR improved survival versus medical management with AS-CA survival post-TAVR no different to lone AS (p=0.36). / Conclusion: Dual pathology of AS-CA is common in older AS patients and can be predicted clinically. AS-CA has worse clinical presentation and a trend towards worse prognosis, unless treated. TAVR should therefore not be withheld in AS-CA

Prevalence and Outcomes of Concomitant Aortic Stenosis and Cardiac Amyloidosis

BACKGROUND: Older patients with severe aortic stenosis (AS) are increasingly identified as having cardiac amyloidosis (CA). It is unknown whether concomitant AS-CA has worse outcomes or results in futility of transcatheter aortic valve replacement (TAVR). OBJECTIVES: This study identified clinical characteristics and outcomes of AS-CA compared with lone AS. METHODS: Patients who were referred for TAVR at 3 international sites underwent blinded research core laboratory 99mtechnetium-3,3-diphosphono-1,2-propanodicarboxylic acid (DPD) bone scintigraphy (Perugini grade 0: negative; grades 1 to 3: increasingly positive) before intervention. Transthyretin-CA (ATTR) was diagnosed by DPD and absence of a clonal immunoglobulin, and light-chain CA (AL) was diagnosed via tissue biopsy. National registries captured all-cause mortality. RESULTS: A total of 407 patients (age 83.4 6.5 years; 49.8% men) were recruited. DPD was positive in 48 patients (11.8%; grade 1: 3.9% [n ¼ 16]; grade 2/3: 7.9% [n ¼ 32]). AL was diagnosed in 1 patient with grade 1. Patients with grade 2/3 had worse functional capacity, biomarkers (N-terminal pro-brain natriuretic peptide and/or high-sensitivity troponin T), and biventricular remodeling. A clinical score (RAISE) that used left ventricular remodeling (hypertrophy/diastolic dysfunction), age, injury (high-sensitivity troponin T), systemic involvement, and electrical abnormalities (right bundle branch block/low voltages) was developed to predict the presence of AS-CA (area under the curve: 0.86; 95% confidence interval: 0.78 to 0.94; p < 0.001). Decisions by the heart team (DPD-blinded) resulted in TAVR (333 [81.6%]), surgical AVR (10 [2.5%]), or medical management (65 [15.9%]). After a median of 1.7 years, 23% of patients died. One-year mortality was worse in all patients with AS-CA (grade: 1 to 3) than those with lone AS (24.5% vs. 13.9%; p ¼ 0.05). TAVR improved survival versus medical management; AS-CA survival post-TAVR did not differ from lone AS (p ¼ 0.36). CONCLUSIONS: Concomitant pathology of AS-CA is common in older patients with AS and can be predicted clinically. AS-CA has worse clinical presentation and a trend toward worse prognosis, unless treated. Therefore, TAVR should not be withheld in AS-CA. (J Am Coll Cardiol 2021;77:128–39) © 2021 The Authors. Published by Elsevier on behalf of the American College of Cardiology Foundation. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)