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      3D quantitative myocardial perfusion imaging with hyperpolarized HP001(bis‐1,1‐(hydroxymethyl)‐[1‐ 13C]cyclopropane‐d8): Application of gradient echo and balanced SSFP sequences

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          Abstract

          Purpose

          This study aims to show the viability of conducting three‐dimensional (3D) myocardial perfusion quantification covering the entire heart using both GRE and bSSFP sequences with hyperpolarized HP001.

          Methods

          A GRE sequence and a bSSFP sequence, both with a stack‐of‐spirals readout, were designed and applied to three pigs. The images were reconstructed using C coil sensitivity maps measured in a phantom experiment. Perfusion was quantified using a constrained decomposition method, and the estimated rest/stress perfusion values from C GRE/bSSFP and Dynamic contrast‐enhanced MRI (DCE‐MRI) were individually analyzed through histograms and the mean perfusion values were compared with reference values obtained from PET( O‐water). The Myocardial Perfusion Reserve Index (MPRI) was estimated for C GRE/bSSFP and DCE‐MRI and compared with the reference values.

          Results

          Perfusion values, estimated by both DCE and C MRI, were found to be lower than reference values. However, DCE‐MRI's estimated perfusion values were closer to the reference values than those obtained from C MRI. In the case of MPRI estimation, the C estimated MPRI values (GRE/bSSFP: 2.3/2.0) more closely align with the literature value (around 3) than the DCE estimated MPRI value (1.6).

          Conclusion

          This study demonstrated the feasibility of 3D whole‐heart myocardial perfusion quantification using hyperpolarized HP001 with both GRE and bSSFP sequences. The C perfusion measurements underestimated perfusion values compared to the O PET literature value, while the C estimated MPRI value aligned better with the literature. This preliminary result indicates C imaging may more accurately estimate MPRI values compared to DCE‐MRI.

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          Most cited references37

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          Global, regional, and national life expectancy, all-cause mortality, and cause-specific mortality for 249 causes of death, 1980–2015: a systematic analysis for the Global Burden of Disease Study 2015

          Summary Background Improving survival and extending the longevity of life for all populations requires timely, robust evidence on local mortality levels and trends. The Global Burden of Disease 2015 Study (GBD 2015) provides a comprehensive assessment of all-cause and cause-specific mortality for 249 causes in 195 countries and territories from 1980 to 2015. These results informed an in-depth investigation of observed and expected mortality patterns based on sociodemographic measures. Methods We estimated all-cause mortality by age, sex, geography, and year using an improved analytical approach originally developed for GBD 2013 and GBD 2010. Improvements included refinements to the estimation of child and adult mortality and corresponding uncertainty, parameter selection for under-5 mortality synthesis by spatiotemporal Gaussian process regression, and sibling history data processing. We also expanded the database of vital registration, survey, and census data to 14 294 geography–year datapoints. For GBD 2015, eight causes, including Ebola virus disease, were added to the previous GBD cause list for mortality. We used six modelling approaches to assess cause-specific mortality, with the Cause of Death Ensemble Model (CODEm) generating estimates for most causes. We used a series of novel analyses to systematically quantify the drivers of trends in mortality across geographies. First, we assessed observed and expected levels and trends of cause-specific mortality as they relate to the Socio-demographic Index (SDI), a summary indicator derived from measures of income per capita, educational attainment, and fertility. Second, we examined factors affecting total mortality patterns through a series of counterfactual scenarios, testing the magnitude by which population growth, population age structures, and epidemiological changes contributed to shifts in mortality. Finally, we attributed changes in life expectancy to changes in cause of death. We documented each step of the GBD 2015 estimation processes, as well as data sources, in accordance with Guidelines for Accurate and Transparent Health Estimates Reporting (GATHER). Findings Globally, life expectancy from birth increased from 61·7 years (95% uncertainty interval 61·4–61·9) in 1980 to 71·8 years (71·5–72·2) in 2015. Several countries in sub-Saharan Africa had very large gains in life expectancy from 2005 to 2015, rebounding from an era of exceedingly high loss of life due to HIV/AIDS. At the same time, many geographies saw life expectancy stagnate or decline, particularly for men and in countries with rising mortality from war or interpersonal violence. From 2005 to 2015, male life expectancy in Syria dropped by 11·3 years (3·7–17·4), to 62·6 years (56·5–70·2). Total deaths increased by 4·1% (2·6–5·6) from 2005 to 2015, rising to 55·8 million (54·9 million to 56·6 million) in 2015, but age-standardised death rates fell by 17·0% (15·8–18·1) during this time, underscoring changes in population growth and shifts in global age structures. The result was similar for non-communicable diseases (NCDs), with total deaths from these causes increasing by 14·1% (12·6–16·0) to 39·8 million (39·2 million to 40·5 million) in 2015, whereas age-standardised rates decreased by 13·1% (11·9–14·3). Globally, this mortality pattern emerged for several NCDs, including several types of cancer, ischaemic heart disease, cirrhosis, and Alzheimer's disease and other dementias. By contrast, both total deaths and age-standardised death rates due to communicable, maternal, neonatal, and nutritional conditions significantly declined from 2005 to 2015, gains largely attributable to decreases in mortality rates due to HIV/AIDS (42·1%, 39·1–44·6), malaria (43·1%, 34·7–51·8), neonatal preterm birth complications (29·8%, 24·8–34·9), and maternal disorders (29·1%, 19·3–37·1). Progress was slower for several causes, such as lower respiratory infections and nutritional deficiencies, whereas deaths increased for others, including dengue and drug use disorders. Age-standardised death rates due to injuries significantly declined from 2005 to 2015, yet interpersonal violence and war claimed increasingly more lives in some regions, particularly in the Middle East. In 2015, rotaviral enteritis (rotavirus) was the leading cause of under-5 deaths due to diarrhoea (146 000 deaths, 118 000–183 000) and pneumococcal pneumonia was the leading cause of under-5 deaths due to lower respiratory infections (393 000 deaths, 228 000–532 000), although pathogen-specific mortality varied by region. Globally, the effects of population growth, ageing, and changes in age-standardised death rates substantially differed by cause. Our analyses on the expected associations between cause-specific mortality and SDI show the regular shifts in cause of death composition and population age structure with rising SDI. Country patterns of premature mortality (measured as years of life lost [YLLs]) and how they differ from the level expected on the basis of SDI alone revealed distinct but highly heterogeneous patterns by region and country or territory. Ischaemic heart disease, stroke, and diabetes were among the leading causes of YLLs in most regions, but in many cases, intraregional results sharply diverged for ratios of observed and expected YLLs based on SDI. Communicable, maternal, neonatal, and nutritional diseases caused the most YLLs throughout sub-Saharan Africa, with observed YLLs far exceeding expected YLLs for countries in which malaria or HIV/AIDS remained the leading causes of early death. Interpretation At the global scale, age-specific mortality has steadily improved over the past 35 years; this pattern of general progress continued in the past decade. Progress has been faster in most countries than expected on the basis of development measured by the SDI. Against this background of progress, some countries have seen falls in life expectancy, and age-standardised death rates for some causes are increasing. Despite progress in reducing age-standardised death rates, population growth and ageing mean that the number of deaths from most non-communicable causes are increasing in most countries, putting increased demands on health systems. Funding Bill & Melinda Gates Foundation.
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            Nonuniform fast fourier transforms using min-max interpolation

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              Advances in sensitivity encoding with arbitrary k-space trajectories.

              New, efficient reconstruction procedures are proposed for sensitivity encoding (SENSE) with arbitrary k-space trajectories. The presented methods combine gridding principles with so-called conjugate-gradient iteration. In this fashion, the bulk of the work of reconstruction can be performed by fast Fourier transform (FFT), reducing the complexity of data processing to the same order of magnitude as in conventional gridding reconstruction. Using the proposed method, SENSE becomes practical with nonstandard k-space trajectories, enabling considerable scan time reduction with respect to mere gradient encoding. This is illustrated by imaging simulations with spiral, radial, and random k-space patterns. Simulations were also used for investigating the convergence behavior of the proposed algorithm and its dependence on the factor by which gradient encoding is reduced. The in vivo feasibility of non-Cartesian SENSE imaging with iterative reconstruction is demonstrated by examples of brain and cardiac imaging using spiral trajectories. In brain imaging with six receiver coils, the number of spiral interleaves was reduced by factors ranging from 2 to 6. In cardiac real-time imaging with four coils, spiral SENSE permitted reducing the scan time per image from 112 ms to 56 ms, thus doubling the frame-rate. Copyright 2001 Wiley-Liss, Inc.
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                Author and article information

                Contributors
                jhar@dtu.dk
                Journal
                Magn Reson Med
                Magn Reson Med
                10.1002/(ISSN)1522-2594
                MRM
                Magnetic Resonance in Medicine
                John Wiley and Sons Inc. (Hoboken )
                0740-3194
                1522-2594
                30 September 2024
                February 2025
                : 93
                : 2 ( doiID: 10.1002/mrm.v93.2 )
                : 814-827
                Affiliations
                [ 1 ] Department of Health Technology Technical University of Denmark Kgs. Lyngby Denmark
                [ 2 ] MR Research Centre Aarhus University Aarhus Denmark
                [ 3 ] Danish Research Centre for Magnetic Resonance, Centre for Functional and Diagnostic Imaging and Research Copenhagen University Hospital Hvidovre Hvidovre Denmark
                Author notes
                [*] [* ] Correspondence

                Jan Henrik Ardenkjær‐Larsen, Department of Health Technology, Danmarks Tekniske Universitet, Ørsteds Plads, Building 345B, DK‐2800 Kgs. Lyngby, Denmark.

                Email: jhar@ 123456dtu.dk

                Author information
                https://orcid.org/0000-0002-3736-7063
                https://orcid.org/0000-0003-1718-8196
                https://orcid.org/0000-0001-5512-9870
                https://orcid.org/0000-0002-0317-2911
                https://orcid.org/0000-0002-8204-6912
                https://orcid.org/0000-0001-6167-6926
                Article
                MRM30320
                10.1002/mrm.30320
                11604847
                39344297
                4bdd8906-208f-4a53-8938-61e2affa102f
                © 2024 The Author(s). Magnetic Resonance in Medicine published by Wiley Periodicals LLC on behalf of International Society for Magnetic Resonance in Medicine.

                This is an open access article under the terms of the http://creativecommons.org/licenses/by/4.0/ License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

                History
                : 10 September 2024
                : 14 March 2024
                : 11 September 2024
                Page count
                Figures: 8, Tables: 2, Pages: 14, Words: 5762
                Funding
                Funded by: The European Union's Horizon 2020 Research and Innovation Program
                Award ID: 858149
                Categories
                Research Article
                Preclinical and Clinical Imaging
                Custom metadata
                2.0
                February 2025
                Converter:WILEY_ML3GV2_TO_JATSPMC version:6.5.1 mode:remove_FC converted:29.11.2024

                Radiology & Imaging
                balanced ssfp,gradient echo,hyperpolarized hp001,mri,quantitative myocardial perfusion imaging

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