Energy Absorption Composite Ansys

The Dark Energy Survey♣

T. Abbott1, G. Aldering2, J. Annis3, M. Barlow4, C. Bebek2, B. Bigelow5, C. Beldica6, R. Bernstein5, S. Bridle4, R. Brunner7, J. Carlstrom8,9, M. Campbell10, F. Castander11, C. Cunha8,9, H. Diehl3, S. Dodelson3,8, P. Doel4, G. Efstathiou12, J. Estrada3, A. Evrard10, E. Fernández13, B. Flaugher3, P. Fosalba11, J. Frieman3,8,9, E. Gaztañaga11, D. Gerdes10, M. Gladders8,14, W. Hu8,9, D. Huterer8,9, B. Jain15, I.

Karliner16, S. Kent3,8, O. Lahav4, M. Levi2, M. Lima8,9, H. Lin3, P. Limon3, M. Martínez13, T. McKay10, R. McMahon12, K. W. Merritt3, C. Miller1, J. Miralda-Escude11, J. Mohr7,16, R. Nichol17, H. Oyaizu8,9, J. Peacock18, J. Peoples3, S. Perlmutter2, R. Plante6, P. Ricker16, N. Roe2, V. Scarpine3, M. Schubnell10, M.

Selen16, E. Sheldon8,9, C. Smith1, A. Stebbins3, C. Stoughton3, N. Suntzeff1,W. Sutherland12, M. Takada19, G. Tarle10, M. Tecchio10, J. Thaler16, D. Tucker3, S. Viti4, A. Walker1, R. Wechsler8,9 , J. Weller3,4, W.

Wester3

1Cerro Tololo Inter-American Observatory, National Optical Astronomy Observatory, La Serena, Chile 11Institut d’Estudis Espacials de Catalunya/CSIC, Barcelona, Spain 13Institut de Fisica d’Altes Energies, Barcelona, Spain

Overview

We describe the Dark Energy Survey (DES), a proposed optical-near infrared survey of 5000 sq. deg of the South Galactic Cap to ~24th magnitude in SDSS griz, that would use a new 3 deg2 CCD camera to be mounted on the Blanco 4-m telescope at Cerro Telolo Inter-American Observatory (CTIO). The survey data will allow us to measure the dark energy and dark matter densities and the dark energy equation of state through four independent methods: galaxy clusters, weak gravitational lensing tomography, galaxy angular clustering, and supernova distances. These methods are doubly complementary: they constrain different combinations of cosmological model parameters and are subject to different systematic errors. By deriving the four sets of measurements from the same data set with a common analysis framework, we will obtain important cross checks of the systematic errors and thereby make a substantial and robust advance in the precision of dark energy measurements.

♣ slightly modified version of a White Paper submitted to the Dark Energy Task Force, June 15, 2005.

Background

The National Optical Astronomy Observatory (NOAO) issued an announcement of opportunity (AO) in December 2003 for an open competition to partner with NOAO in building an advanced instrument for the Blanco telescope in exchange for awarding the instrument collaboration up to 30% of the observing time over a five-year period for a compelling science project. In response to this AO, the Dark Energy Survey (DES) Collaboration was formed and submitted a proposal to NOAO in July 2004 to build DECam, a new wide-field imager for the Blanco, with the goal of carrying out a survey to address the nature of the dark energy using the four primary techniques described below in Sec. 2. The Blanco Instrumentation Review Panel convened by NOAO to review the DES proposal concluded that the scientific goals are exciting and timely. Subsequently, the NOAO Director asked the CTIO Director and the DES Project Director to draft a MOU among the Parties that would define the terms of the partnership.

The major components of DECam are a 519 megapixel optical CCD camera, a wide-field optical corrector (2.2 deg. field of view), a 4-band filter system with SDSS g, r, i, and z filters, guide and focus sensors mounted on the focal plane, low-noise CCD readout, a cryogenic cooling system to maintain the focal plane at 180 K, as well as a data acquisition and instrument control system to connect to the Blanco observatory infrastructure. The camera focal plane will consist of sixty-two 2k x 4k CCDs (0.27''/pixel) arranged in a hexagon covering an imaging area of 3 sq. degrees. Smaller format CCDs for guiding and focusing will be located at the edges of the focal plane. More details about the instrument are given below in Sec. 7 and in the Supplements.

To carry out the Dark Energy Survey with DECam, we have requested 525 nights of observing on the Blanco telescope over 5 years, concentrated between September and February, beginning in Sept. 2009. With that time, we expect to reach photometric limits of g=24.6, r=24.1, i=24.3, and z=23.9 over 5000 sq.

deg of sky. These are 10σ limits in 1.5” apertures assuming 0.9” seeing and are appropriate for faint galaxies; the corresponding 5σ limit for point sources is 1.5 mags fainter. These limits and adopted median delivered seeing are derived from detailed survey simulations that incorporate weather and seeing data at CTIO over a 30-year baseline.

The survey strategy is designed to optimize the photometric calibration by tiling each region of the survey with at least four overlapping pointings in each band. This provides uniformity of coverage and control of systematic photometric errors via relative photometry on scales up to the survey size. This strategy will enable us to determine photometric redshifts (photo-z’s) of galaxies to an accuracy of σ(z)~0.07 out to z>1, with some dependence on redshift and galaxy type, cluster photometric redshifts to σ(z)~0.02 or better out to z~1.3, and shapes for approximately 200 million galaxies; these measurements will be sufficient to meet the survey science requirements. 4000 deg2 of the survey region will overlap the South Pole Telescope Sunyaev-Zel’dovich survey region; the remainder will provide coverage of spectroscopic redshift training sets, including the SDSS southern equatorial stripe, and more complete coverage near the South Galactic pole.

This white paper is organized as follows. Section 2 briefly describes the four main techniques that DES will use, alone and in conjunction with the South Pole Telescope Sunyaev-Zel’dovich effect survey, to probe the dark energy. Section 3 presents forecast statistical constraints on the dark energy equation of state for several choices of priors on other parameters, followed by discussion of the additional assumptions that enter these forecasts. In Section 4, we discuss the primary envisioned systematic errors for each method and outline the methods of controlling them. Section 5 lists the precursor and concurrent observations and developments upon which DES will rely. In Section 6, we briefly describe DECam, the survey instrument, and Section 7 outlines the data management plans. Section 8 presents a timeline for the project, and we conclude in Section 9. The Supplement sections that follow are appendices that provide more detailed technical information on various aspects of the project.

A more comprehensive though less up-to-date description of the project is available at https://decam.fnal.gov/NOAO04/A_Proposal_to_NOAO.pdf

Ark Energy Survey Techniques

Here, we briefly summarize the four proposed techniques for probing dark energy. The forecast dark energy constraints are described in the following section. We describe these techniques and their associated uncertainties in greater detail in the Supplements for the Dark Energy Survey.

Galaxy clusters: The evolution of the galaxy cluster mass function and cluster spatial correlations provide a sensitive probe of the dark energy; these observables are affected by cosmology through both the growth of density perturbations and the evolution of the volume element (Haiman, Mohr, & Holder 2000, Battye & Weller 2003). Clusters make promising cosmological probes, because the formation of these large potential wells involves only the gravitational dynamics of dark matter to good approximation. The primary design driver of the DES is the detailed optical measurement of galaxy clusters, including photometric redshifts, in conjunction with the South Pole Telescope (SPT) Survey. The SPT (Ruhl et al 2004) will use the Sunyaev-Zel’dovich effect (SZE) to detect galaxy clusters out to large distances, providing a census of tens of thousands of clusters over a 4000 square degree region south of declination δ = −30o. The integrated SZE flux decrement is expected to be a robust indicator of cluster mass, because it is a measure of the total thermal energy of the electrons residing in the gravitational potential well; in particular, it should be insensitive to gas dynamics in the cluster core (Motl et al 2005, Nagai 2005). The DES is designed to measure efficiently and accurately photometric redshifts for all SPT clusters to z=1.3.

It will also cross-check the completeness of the SPT cluster selection function by optically identifying clusters below the SPT mass threshold and will statistically calibrate SZE cluster mass estimates using the cluster-mass correlation function inferred from weak lensing (Johnston et al 2005). Existing cameras would require decades to cover the SPT survey area to the requisite depth.

Weak lensing tomography: The DES will measure the weak lensing (WL) shear of galaxies as a function of photometric redshift. The evolution of the statistical pattern of WL distortions—for example, the shear- shear (S-S) angular power spectrum—and of the cross-correlation between foreground galaxies and background galaxy shear (galaxy-shear correlations, G-S), are sensitive to the cosmic expansion history through both geometry and the growth rate of structure (Hu 2002, Huterer 2002). In the course of surveying 5000 sq. deg. to the depth required for cluster photo-z’s, the DES will measure shapes and photometric redshifts for ~300 million galaxies and, with improved control of the optical image quality, enable accurate measurement of lensing by large-scale structure.

Galaxy angular clustering: The DES will measure the angular clustering of galaxies (denoted G-G in Table 1) in photometric redshift shells out to z~1.1. The matter power spectrum as a function of wave- number shows characteristic features, a broad peak as well as baryon wiggles arising from the same acoustic oscillations that give rise to the Doppler peaks in the CMB power spectrum; these features were recently detected in the SDSS (Eisenstein et al 2005). In combination with CMB observations, they serve as standard rulers for distance measurements, providing a geometric test of cosmological parameters. This approach will provide cosmological information from the shape of the power spectrum transfer function and physically calibrated distance measurements to each redshift shell (e.g., Hu & Haiman 2003, Seo & Eisenstein 2003, Blake & Bridle 2004).

Supernova luminosity distances: In addition to the wide-area survey, the DES will use 10% of its allocated time to discover and measure well-sampled riz light curves for ~1900 Type Ia supernovae in the redshift range 0.3

In addition to these methods, cross-correlation of CMB data sets with DES galaxies as tracers of potential wells will probe the dark energy through the integrated Sachs-Wolfe (ISW) effect; this effect is included in the forecast constraints below (Hu & Scranton 2004). Finally, we note that accurate photometric redshifts are critical to the DES science goals; as a relatively shallow survey, a major advantage of the DES will be the availability of spectroscopic redshift calibration (training) samples that extend out to the flux limit of the survey.

Forecast Dark Energy Constraints

In this section, we quantify how the DES will improve our understanding of dark energy, focusing on the dark energy equation of state parameter w. Such forecasts generally depend upon priors assumed for marginalized parameters and on assumptions about whether w evolves. The marginalized parameters include cosmological parameters other than w, uncertain astrophysical parameters that characterize a particular probe, and possible parameters describing uncorrected systematic errors associated with a particular observational method. As a result, caution must be exercised in comparing the projected dark energy sensitivity of different methods and experiments. For this discussion, we assume constant w and consider 3 cases of cosmological priors: uniform, present CMB (WMAP 1-year), and future CMB (Planck); these priors are specified in the Supplements. While models with constant w ≠ −1 are not theoretically well motivated, they nevertheless provide a convenient metric for comparison. A few examples of forecasts with time-varying w are discussed in the Supplements. We also note that for varying w, for the redshift zp at which w(z) is best constrained, the constraints on w(zp) are the same as those on constant w shown below.

Table 1: Example forecast marginalized 68% CL statistical DES constraints on constant equation of state parameter w.

Supernovae Ia

In all cases considered in Table 1, we assume cold dark matter, negligible neutrino masses, adiabatic Gaussian initial perturbations with power-law primordial power spectrum, and a spatially flat Universe. We use a fiducial model with w = −1 and other parameters close to the WMAP concordance values.

Further assumptions for each method are given in the remainder of this section. The numbers in Table 1 can change as those assumptions are varied within reasonable limits and are meant to be representative. These numbers, based on Fisher matrix and Monte Carlo analyses, indicate that each of the four methods can probe constant w with statistical errors at the 3-20% (2-11%) level for WMAP (Planck) priors, assuming reasonable uncertainties in the appropriate astrophysical parameters as noted below. In fact, we expect these methods will likely be limited by systematic errors; a description of their expected impact on the cosmological parameter error budget is presented in the Supplements.

For the cluster results, we have used the cluster counts above the 5σ SPT detection limit (1.9mJy, with a beam of 1’ FWHM) in redshift bins of Δz=0.1 out to z=1.5, which results in ~12,000 clusters over 4000 deg2 for the fiducial cosmology and a weakly redshift-dependent mass threshold of ~2×1014Msun. The SZE detection threshold was set this high (as opposed to, say, 3σ) in order to minimize the effects of sample contamination by radio point sources. We have marginalized over a 3-parameter model for the mass-SZE flux relation that includes power-law evolution with redshift beyond that expected from self-similarity, but no scatter in that relation. While this mass-SZE flux relation is rather simple, there is additional information contained in the cluster angular power spectrum and in the shape of the mass function (rather than just its integral above a threshold) that can be used to help ``self-calibrate” a more complex relation (Majumdar & Mohr 2004, Lima & Hu 2004, 2005). Moreover, the second row of cluster constraints in Table 1 includes the statistical calibration of the mass-observable relation using the weak lensing cluster- shear cross-correlation over the mass range 4×1014 −2×1015 Msun in redshift bins from z=0.4−0.9. Finally, we have assumed that the theoretical uncertainties in the halo mass function, in the halo bias as a function of mass, and in the identification of SZE-detected clusters with dark halos are subdominant compared to the other errors; recent N-body simulations indicate that the first two assumptions are justified and planned future simulations will be needed to ensure the third (see the Supplements for further discussion).

The forecast weak lensing constraints assume that the shear and galaxy power spectra are each measured in 5 photometric redshift bins out to z=2 (for background galaxy shear) and z=1 (for foreground galaxy positions), with a simplified but reasonable model for the photo-z errors, σ(z)=0.05(1+z). The statistical errors come from cosmic variance and from shot noise (shape noise) corresponding to an effective background density of 10 galaxies/arcmin2 (with shape noise per shear component of 0.16); artificially degrading higher resolution images yields this source density for the DES depth and the 0.9” median seeing delivered by the Mosaic II Camera on the Blanco. If the delivered seeing can be reduced to ~0.7’’, close to the median site seeing for the DES observing months, the effective background density will increase by ~35%, with the shot noise errors in the shear-shear power spectrum correspondingly reduced.

The results in Table 1 use angular information and assume Gaussian errors up to multipoles l < 1000, beyond which non-linearities in the density field become important at the typical survey depth; a more conservative (aggressive) limit of l =300 (l =3000) increases (decreases) the w constraints by ~50%. In these forecasts, the non-linear mass power spectrum is modeled by the halo model (Hu & Jain 2004), which reproduces the results of high-resolution N-body simulations. For constraints that include foreground galaxies (i.e., G-G and G-S), 5 halo occupation parameters per foreground galaxy photo-z bin are marginalized over. These parameterize the bias of galaxies with respect to the dark matter in a manner consistent with high-resolution N-body simulations (Kravtsov et al 2004) and with the observed clustering of galaxies at low redshift in the SDSS (Zehavi et al 2004). For constraints including (G-G), the foreground galaxy power spectrum is only used to provide constraints on these halo occupation parameters.

The galaxy angular clustering constraint assumes measurement of the angular power spectrum for the foreground galaxy sample with photo-z binning and errors as above. However, it uses a more conservative range of angular information, l < 300, since baryon wiggles are washed out in the non-linear regime; compared to the first two methods, this result is more robust to uncertainties in non-linear perturbation evolution. Since this clustering constraint mainly uses the shape of the power spectrum, it is not very sensitive to the galaxy bias model. As a result, its use here is complementary to its use above in constraining galaxy bias for lensing.

The forecast supernova constraints assume SNe Ia are standardizable candles with an intrinsic dispersion in peak luminosity of 0.25 mag; this is larger than the usually adopted value of 0.15 mag and reflects an expected increase in errors due to the fact that only photometric redshifts will be available for the majority of the sample. These constraints also assume an irreducible systematic error floor in peak magnitude dispersion of 0.02(1+z)/1.8 mag in redshift bins of Δz=0.1 (e.g., Frieman et al 2003). Under this assumption, the error floor dominates over the intrinsic dispersion in the derived dark energy constraints, so there is little gain from reducing the intrinsic dispersion; with no systematic error floor, the w constraints improve to 0.24, 0.14, and 0.03 for uniform, WMAP, and Planck priors. In all cases, we have also assumed a well-measured set of 300 nearby (z<0.1) SNe Ia (being accumulated by on-going surveys) anchors the low-redshift part of the Hubble diagram.

Systematic Errors

Table 2 lists the expected dominant systematic error sources for each method, ordered approximately from most to least important, along with the presently envisioned primary methods for controlling them. A more detailed discussion is presented in the Supplements.

For the cluster technique, the cluster sample must be both complete (above some threshold) and free of contamination, i.e., the cluster selection function must be well understood. For the SZE, cluster selection is complicated by point source confusion, dusty galaxies, radio galaxies, primary CMB anisotropy, and chance projection of clusters at different redshifts. The systematics for DES optical cluster selection are quite different, so the two methods can be compared to understand the selection function. Prior to SPT, the SZA (now operational) will carry out deep SZE imaging over a smaller area of sky with higher angular resolution; this will provide improved calibration of the mass-SZE flux relation and probe the SZE selection function below the SPT threshold. Prior to DES, members of our collaboration will carry out a 100 sq. deg. multi-band imaging survey with Mosaic II on the Blanco (recently approved as a 3-year survey program beginning in Fall 2005) that overlaps several planned SZE surveys (including APEX, ACT, and SPT); this survey will enable cross-comparison of the SZE and optical cluster selection functions for a fraction of the sample. In addition, we will quantify the SZE cluster selection function through a program of hydrodynamic simulations (Melin et al 2004, Vale & White 2005) and Monte Carlo simulations based on radio source catalogs to evaluate contamination. The cluster technique also relies on an accurate mass-observable relation; as noted above, this will be calibrated by statistical weak lensing, the cluster angular power spectrum, and the shape of the cluster mass function.

For weak lensing, the dominant systematic errors are additive and multiplicative shear systematics (Huterer, Takada, Bernstein, & Jain 2005, hereafter HTBJ), uncorrected biases in photo-z estimates (HTBJ 2005; Ma, Hu, & Huterer 2005), and theoretical uncertainties in the small-scale mass power spectrum (White 2004, Zhan & Knox 2004, Huterer & Takada 2004). Theoretical uncertainties can be controlled by nulling the small-scale information (Huterer & White 2005) and by using improved high- resolution N-body simulations incorporating baryons. Photo-z biases will be controlled to an acceptable level by using a pre-existing spectroscopic redshift sample large and deep enough to accurately determine the photo-z error distribution as a function of redshift. The Supplements summarize the acceptable error budget for additive and multiplicative shear systematics (HTBJ) and the techniques we will pursue to reduce them to acceptable levels.

For angular clustering, the dominant systematic errors are potential inadequacy of the halo occupation description of galaxy bias (affecting the baryon wiggles), photometric calibration errors or uncorrected Galactic dust extinction correlated over large scales (leading to artificial large-scale power), and photo-z biases. Since the angular bispectrum and power spectrum have different dependences on the galaxy bias parameters, combining them will constrain those uncertainties (Dolney et al 2004, Gaztanaga & Frieman 1996). In addition, since galaxy bias depends on galaxy type (color and luminosity) measuring angular clustering for different types will constrain the large-scale behavior of the bias. Correlated photometric errors will be controlled by a survey strategy that incorporates multiple visits to each field, by clustering vs. galaxy color, and by checking consistency of results across different angular sub samples.

Table 2: Dominant sources of systematic error and methods for controlling them; see text. For supernovae, the major systematic errors are evolution of the supernova population, systematic photometric errors, uncorrected host-galaxy extinction, inaccurate K-corrections, and photo-z errors and biases for the part of the sample without spectroscopic redshifts. Evolution is generally controlled by comparing light-curves, colors, and spectra of high- and low-z supernovae and using the fact that the low- z sample, if large enough, should span the range of physical conditions encountered in the sample to z~1.

Photometric errors will be minimized by a survey strategy optimized for uniform calibration and cross- checked by overlap with SDSS photometry on the celestial equator. K-correction uncertainties will be mitigated by having a large, nearby comparison SN sample with multi-epoch spectrophotometry.

Extinction errors will be addressed by using host galaxy colors to identify a low-extinction sub sample of early-type galaxies. The impact of photo-z errors is discussed in The Supplements and is expected to be small.

5. Precursor and Concurrent Observations and Developments The Dark Energy Survey will make use of a number of other observations and developments that are

Planned Or Underway:

1. Spectroscopic redshift data sets to the DES flux limit to calibrate empirical photo-z estimators, to measure photo-z error distributions, and to provide a sample of SN host galaxy redshifts. These will be in place prior to DES from on-going surveys (including SDSS, 2dFGRS, VIMOS VLT Deep Survey, and DEEP2). The overlap of DES with a planned VISTA NIR survey will improve galaxy photo-z estimates but is not required to satisfy the DES science requirements.

2. The SPT survey for SZE measurements of galaxy clusters. SPT and DES plan joint analyses. SPT, which will start survey operations in 2007, expects to have 1-2 years of survey data by the time DES

Sn Spectroscopic Calib. Sub Sample

starts operations. A precursor 100 deg2 survey with Mosaic II commencing fall 2005 will overlap several planned SZE surveys, including SPT, and help constrain the cluster selection function. 3. Follow-up spectroscopy of a subsample of ~25% of the SNe Ia on 8m-class telescopes, relying primarily on competitive time applications in collaboration with the supernova community. This will use 8m-class resources at a rate comparable to or less than current high-z SN follow-up; it will reduce cosmological errors from and test the purity of the SN sample. A low-redshift sample of well-measured SNe Ia to anchor the Hubble diagram and provide spectroscopic and photometric templates for SN light- curve fitting and K-corrections will be done by ongoing surveys (KAIT, CSP, SDSS-II, SNF).

4. Suites of large N-body simulations incorporating hydrodynamics by collaboration members to precisely calibrate the theoretical cluster mass function and better model SZE and optical cluster selection. Simulations will also determine with greater precision the effects of clustering non-linearity and baryons on weak lensing and galaxy angular clustering.

Ecam, The Survey Instrument

The philosophy of the DECam project is to assemble proven technologies into a powerful survey instrument and mount the instrument on an optimally configured Blanco, thereby exploiting an excellent, existing facility. Figure 1 shows a cross section of DECam with the key elements identified. A discussion of the Blanco performance and upgrades are given in the Supplements.

The major components of DECam are listed in Section 1 and are summarized below in Table 3. To efficiently obtain z-band images for high-redshift (z~1) galaxies, we have selected the fully depleted, high-resistivity, 250 micron thick silicon devices that were designed and developed at the Lawrence important implications for DES: fringing is eliminated, and the QE of these devices is > 50% in the z band, a factor of ~10 higher than traditional thinned astronomical devices. Several of the LBNL 2k x 4k CCDs of this design have been successfully used on telescopes, including the Mayall 4m at Kitt Peak and the Shane 3m at Lick. The DES CCDs will be packaged and tested at Fermilab, capitalizing on the experience and infrastructure associated with construction of silicon strip detectors for the Fermilab Tevatron program. The CCD packaging plan for the four side buttable 2k x 4k devices builds on techniques developed by LBNL and Lick Observatory.

The optical corrector reference design consists of five fused silica lenses that produce an unvignetted 2.2o diameter image area, which is calculated to contribute < 0.4'' FWHM to the point-spread function. Element 1, the largest, is 1.1m in diameter and the surface of another is aspheric. The spacing between elements 3 and 4 will allow the 600 mm diameter filters to be individually flipped in and out of the optical path. DECam will be installed in a new prime focus cage.

A Fermilab Director’s Review (June 2004) and an NOAO Blanco Instrumentation Panel Review (August 2004) evaluated DECam, and both reviews identified the yield of the CCDs, the front end electronics (FEE), and the large optics as the major risks to the project cost and schedule. We have focused our R&D efforts on the mitigation of these risks. The Supplements present further details of the R&D program. In particular, we adopted a proven CCD device design and placed the first DES CCD wafer order. The first test devices were delivered to LBNL in early June 2005 and have been successfully read out on cold probe station. We anticipate delivery of the first thinned fully processed devices this fall. The production of the DES devices by LBNL provides an excellent precursor to the production of devices for the SNAP/JDEM project.

Figure 1: Decam Reference Design

To benefit from the on-going development at NOAO, we have adopted the Monsoon CCD readout system as a starting point. UIUC and Fermilab each have a Monsoon system and are preparing to read out LBNL CCDs in the near future. As we gain experience with Monsoon in the testing setups, we will build on the design and make the modifications necessary to meet the prime focus cage space and heat restrictions.

The risks associated with the optical design result from the size of the elements. We are investigating alternative designs with smaller first elements (~0.9m) and better image quality, with the goal of cost and schedule reduction. We have joined a group organized by George Jacoby to collaborate on the development of large filters for imaging cameras (WIYN, LSST, PanSTARRS). We are also following the development of large colored glass filters at Schott.

Mm

Table 3: Expected performance of DECam, Blanco, and CTIO site

/5 (Nights/Years)

Median Site Seeing Sept. – Feb.

Arcsec

Median Delivered Seeing with Mosaic II on the Blanco

-1.0 Arcsec (V Band)

Limiting Magnitude: 10σ in 1.5” aperture assuming 0.9”

G=24.6, R=24.1, I=24.3, Z=23.9

Limiting Magnitude: 5σ for point sources assuming 0.9”

Ata Management

The DES data management system (DM) is designed to enable efficient, automated grid processing, quality assurance, and long-term archiving of the ~1 Petabyte DES dataset. The raw and processed data will be archived and, after one year, distributed to the public. The survey data will move from CTIO to the National Center for Supercomputing Applications (NCSA) in Illinois, the primary data processing center, over data lines provided by NOAO. The images will be processed, combined into deeper co- added images, and reduced to science-ready data at the catalog level at NCSA. DM is a collaborative effort led by U. Illinois that includes major contributions from Fermilab and the NOAO Data Products Program (DPP). The DM development project will include yearly data challenges that involve testing the system with simulated DES data. Our fourth and final data challenge will end in January 2009, several months before first light for the DES camera.

The DM system includes a pipeline processing environment and data access framework to enable automated and modular processing of this large dataset. This framework will be provided by NCSA and is closely coupled to their large, middleware development effort for the LSST data management project.

The DM system includes astronomy modules for processing and data quality assurance, which will come from the collaboration. The primary image archive will employ the NOAO Science Archive software, which is being developed by NOAO DPP. The development of the DES catalog database and server is being led by NCSA.

October 2004

Start DECam R&D and continue the preliminary design

April 2006

Hold preliminary design review, obtain DOE project approval, and place long lead procurements with non-DOE funds

October 2006

Place long lead procurements with DOE funds, begin production

October 2008

Complete construction of DECam and Data Management System (DM)

Ay 2009

Begin commissioning of DECam on the Blanco with the completed DM

Onclusions

The Dark Energy Survey will employ four complementary techniques to study dark energy: galaxy clusters, weak lensing, galaxy angular clustering, and supernova distances. The statistical reach of these techniques is well understood; in the DES, each of them will deliver statistical constraints on dark energy that are stronger than the best combined constraints available today (Spergel et al 2003, Tegmark et al 2004, Seljak et al 2004). Moreover, our collaboration is making substantial progress toward identifying and understanding the dominant astrophysical uncertainties and observational systematic errors for each of these methods and one of our important goals is to further explore and develop methods to control these systematic errors. Since the more ambitious surveys of the future will reach even smaller statistical errors than the DES, they will have to exercise even finer control of systematic errors in order to achieve their science goals. We believe that a large-scale, near-term survey that provides a major step forward in precision such as DES is the logical next step in that process.

The DES will employ DECam, a powerful new wide-field survey instrument, and the Blanco, a 4m telescope that has already contributed to many of the pioneering measurements of dark energy and that has the capacity for improvements that will strengthen the DES measurements. As a relatively shallow survey, the DES makes use of source galaxies that are large enough to be well resolved in the conditions routinely achieved with MOSAIC II, the current Blanco imager, and bright enough so that their photometric redshifts can be well calibrated by spectroscopic surveys of comparable depth. The collaboration institutions have a proven record in astronomical data management and have the capacity to manage large data sets. Collaboration members have made important contributions to developing the survey science, and include a strong science team that will rise to the challenge of carrying out the astrophysical and cosmological simulations that will be needed to precisely interpret the data from this large survey. The DES promises significant scientific returns, although it is a relatively low-risk project of intermediate scope and cost, which requires only modest advances beyond the hardware and software used in current astronomical projects.

DES will also provide the astronomical community with a wide field, 4 band digital survey of the southern sky with excellent image quality, uniform photometry and unprecedented depth for its sky coverage. It will cover the largest volume of the universe to date (complete to tens of Gpc^3) and it will be a "legacy survey" that will provide the scientific and educational communities with an extraordinary catalog for multipurpose projects.

The DES and the SPT projects provide a unique opportunity to combine two strong surveys into a single survey that will be greater than the sum of its parts. The very strong impact that they can make together on cosmology will be much greater if the observations are made in a timely way. The SPT project will begin observations in 2007, thus it is important for DES to start its build phase soon.

Authors:

Peder EZ Larson 1, 2,* , Jenna ML Bernard1, James A Bankson 3, Nikolaj Bøgh 4, Robert A Bok1, Albert P. Chen 5, Charles H Cunningham 6,7, Jeremy Gordon1, Jan-Bernd Hövener 8, Christoffer Laustsen 4, Dirk Mayer 9,10, Mary A McLean11 12, Franz Schilling13, James Slater1, Jean-Luc Vanderheyden5, 14, Cornelius von Morze 15, Daniel B Vigneron1, 2, Duan Xu1, 2, and the HP 13C

94143, Usa.

Denmark. 5 GE Healthcare, Menlo Park, California, USA. 6 Physical Sciences, Sunnybrook Research Institute, Toronto, Ontario, Canada.

8 Section Biomedical Imaging, Molecular Imaging North Competence Center (MOIN CC), Medicine, Baltimore, MD, USA. Cambridge, United Kingdom.

14Jlvmi Consulting Llc, Dousman, Wi, Usa

#See Acknowledgements for a list of all HP 13C MRI Consensus Group Members This work was supported by the ISMRM Hyperpolarized Media MR Study Group, the ISMRM Hyperpolarization Methods & Equipment Study Group, and the Hyperpolarized MRI Technology Resource Center (NIH/NIBIB grant P41EB013598).

Abstract

MRI with hyperpolarized (HP) 13C agents, also known as HP 13C MRI, can measure processes such as localized metabolism that is altered in numerous cancers, liver, heart, kidney diseases, and more. It has been translated into human studies during the past 10 years, with recent rapid growth in studies largely based on increasing availability of hyperpolarized agent preparation methods suitable for use in humans. This paper aims to capture the current successful practices for HP MRI human studies with [1-13C]pyruvate - by far the most commonly used agent, which sits at a key metabolic junction in glycolysis. The paper is divided into four major topic areas: (1) HP 13C-pyruvate preparation, (2) MRI system setup and calibrations, (3) data acquisition and image reconstruction, and (4) data analysis and quantification. In each area, we identified the key components for a successful study, summarized both published studies and current practices, and discuss evidence gaps, strengths, and limitations. This paper is the output of the “HP 13C MRI Consensus Group” as well as the ISMRM Hyperpolarized Media MR and Hyperpolarized Methods & Equipment study groups. It further aims to provide a comprehensive reference for future consensus building as the field continues to advance human studies with this metabolic imaging modality.

Keywords: Hyperpolarized MRI, metabolic imaging, carbon-13, pyruvate, dissolution dynamic

Introduction

MRI with hyperpolarized 13C agents, also known as hyperpolarized (HP) 13C MRI, has shown great potential as a novel imaging modality, particularly for its ability to probe metabolic processes in real time. The first human studies with HP [1-13C]pyruvate were performed in 2011 in prostate cancer patients (1).

Since then, there have been over 60 papers published with imaging results of human subjects from 13 different sites, with applications including prostate cancer, brain tumors, breast cancer, kidney cancer, pancreatic cancer, metastatic disease, liver disease, ischemic heart disease, diabetes and cardiomyopathies. The vast majority of these studies used [1-13C]pyruvate (1–63), where [2-13C]pyruvate (64) and 13C-urea (56) have been demonstrated too.

As clinical HP 13C MRI advances, there is a growing need to build consensus for best practices, which are critical for comparing data across sites, performing multi-site trials,deploying methods to new sites, partnering with vendors, and potentially for obtaining broader regulatory approvals.

In March 2022, we initiated an effort to build consensus within the HP 13C MRI community with this opportunity in mind, and it was greeted with strong enthusiasm. The “HP 13C MRI Consensus Group”, containing over 55 members from 27 sites, identified the area of greatest need and opportunity for consensus building to be HP [1-13C]pyruvate human

●

Pyruvate is the most mature and widely used HP agent and has the most significant translational evidence emphasizing the potential clinical impact.

●

Clinical trials, particularly multi-site trials, have the strongest need for consensus methods to ensure that data can be combined across sites. This work is a Position Paper for which the goal is to describe current successful practices and study methods for HP [1-13C]pyruvate human studies along with justification to support those practices. This is divided into four major topic areas: (1) HP 13C-pyruvate preparation, (2) MRI system setup and calibrations, (3) data acquisition and image reconstruction, and (4) data analysis and quantification (Fig. 1). The current successful practices and study methods include a literature review of published peer-reviewed journal papers showing human HP [1-13C]pyruvate study data, up to September 2022 (1–63), as well as new unpublished information from surveys of HP 13C study sites. Based on this information, we also highlight the evidence gaps, strengths, and limitations of current practices which are summarized at the end of each section.

Figure 1: Illustration of the HP 13C MRI human study process, including the 4 major areas covered in this paper: Hyperpolarized 13C-pyruvate preparation, MRI system setup and calibration, Acquisition and Reconstruction, and Data Analysis and Quantification.

Figure 2: Anatomical targets of HP [1-13C]pyruvate MRI human studies published up to September 2022.

Hyperpolarized 13C-Pyruvate Preparation

This section covers the processes for creating the HP agent, 13C pyruvate, and will include many aspects and considerations that are needed to safely and effectively prepare doses for metabolic imaging studies in human subjects. These include material, personnel, equipment and facility, fluid path preparation, quality control, and release.

It is helpful to understand that the specifications of a dose of 13C pyruvate suitable for in vivo MR HP metabolic imaging were shaped in part by early preclinical studies performed by GE HealthCare summarized in Ref. (65). In short, the safety of the two novel drug components, 13C pyruvate and the electron paramagnetic agent (EPA) AH111501, were demonstrated in those studies. The more precise formulation of the dose suitable for human use was then determined from clinical studies (66) that included two Phase 1 clinical trials in young and elderly healthy volunteers without hyperpolarization of the 13C nuclei and another Phase 1/2a dose escalation and imaging feasibility study with HP 13C pyruvate in 31 prostate cancer patients at the With the exception of the first HP 13C imaging clinical trial, which utilized a prototype device in a cleanroom (1), all HP 13C studies performed in humans to date have utilized the SPINlab polarizer (manufactured by GE HealthCare). Consequently all doses of the HP 13C pyruvate delivered by SPINlab have been produced using the “SPINlab Pharmacy Kit” that serves as the container-closure system for the various drug components (13C pyruvic acid and EPA mixture, dissolution medium, and neutralization and dilution medium) during sample polarization, dissolution and quality control (QC) processes. Thus many aspects of the HP sample preparation considerations discussed below are related to the SPINlab instrument and the consumables designed to be used with it (67).

General Considerations

While more than 860 patients or healthy subjects having been injected with HP 13C pyruvate as of January 2022 without reports of any serious adverse events (68), HP 13C pyruvate injection remains an investigational MR contrast agent and can only be administered by those with Investigational New Drug (IND) exemption from the Food and Drug Administration (FDA) in the USA, a Clinical Trial Application (CTA) in Canada, approval from National Research Ethics Committee Services in the UK, or approval from the relevant local regulatory body. Thus, methods and processes involved to produce a dose should have patient safety as the first priority. Since utilizing dissolution dynamic nuclear polarization (dissolution-DNP) for human use is still a relatively new development, there are no existing published regulatory guidelines specifically for this method.

There are two major production styles that determine how various sites approach the agent preparation. In the US, the most common approach is to rely on a sterilizing filter (“Terminal Sterilization”) to ensure sterility of the final product, akin to PET tracer production, where a starting molecule with a radioisotope is processed using various other ingredients to make the final, desired and injectable contrast agent within a necessarily short amount of time (69). For these sites, sterilization of the components and accessories upstream of this filter are not required, although many of them were manufactured and tested following Good Manufacturing Practice (GMP) or Good Laboratory Practice (GLP) requirements. The filling process is usually performed under an ISO 5 laminar flow hood, but a clean room or an isolator is not required.

This approach is typically accompanied by testing the integrity of the sterilizing filter prior to release of the dose for injection. Typically, post release endotoxin and sterility tests are performed using an aliquot reserved from each released dose.

In the UK and EU, the most common approach is to more-closely follow sterile pharmaceutical compounding guidelines (70), where all components and ingredients are required to be sterile or manufactured under GMP guidelines and are assembled and filled within a clean room environment or an isolator system (“Sterile Preparation”). Typically a batch of Pharmacy Kits for HP 13C pyruvate injection are prepared together. The sterility of the final dose is also ensured by batch validation testing, in addition to the sterility of the ingredients and the sterile compounding process. The endotoxin and sterility testing are performed for the process validation but are not performed for each injected dose.

Some institutions fill and assemble the Pharmacy Kit required for a specific study on the same day or the day prior to polarization, dissolution, and patient administration, but others have also demonstrated the feasibility of preparing a batch of kits, keeping them in a -20ºC freezer and using them over a period of a few months.

Beyond the obvious requirements that the process and the facility has to ultimately produce a dose that is safe to inject into a human, regulatory authorities will also focus on the question “Are you in control of your processes?”. To be in control of your process requires an in-depth and broad understanding of all processes involved in pre, post, and during the production process.

Personnel

It is typical and may be required to have licensed personnel involved in the production process depending on local regulations.Typically a pharmacist, radiopharmacist or other similarly qualified person (QP), in charge of the facility where the Pharmacy Kit filling and preparation is taking place, is responsible for the overall process and the release of the injectable dose.

Qualified cleanroom technicians are often involved in the Pharmacy Kit filling under the supervision of the pharmacist or QP. As is required for pharmaceutical compounding or PET tracer production, training requirements and training records for all personnel need to be maintained and available for audit by the FDA or equivalent.

Equipment And Facility

The facility and all equipment need to have standard operating procedures (SOPs) that describe how equipment is used, maintained, and calibrated to comply with relevant legislation. Currently, almost all the filling of the Pharmacy Kit takes place within a compounding laminar flow hood or isolator (typically ISO 5). At some sites, the filling is conducted within a cleanroom, while at others, it is conducted in a dedicated non-cleanroom space, reflecting differences in cleanroom approach and specifications between regulators worldwide (71). Some equipment or facilities, such as the compounding hood or cleanroom, may require external certified laboratories for testing.

Material Handling

Material handling guidelines (69,70) require SOPs detailing a system to track all of the materials involved in the HP production process for a particular patient dose, similar to current good manufacturing practice (cGMP) requirements for material handling for drug compounding. This includes acceptance standards, storage conditions, amount used in the patient dose for each ingredient and materials used in the assembly of the fluid path and Pharmacy Kit. Currently some users choose to open and inspect and sometimes modify the Pharmacy Kits upon arrival, but some users keep them in the sealed packaging until they are required for dose preparation.

Pharmacy Kit Filling And Assembling

As required by an IND or its equivalent, the preparation of the doses of HP 13C agent are detailed in the Chemistry, Manufacturing, and Control (CMC) section of an applicable regulatory submission; an example of this has been made available (72). It describes the processes of filling the Pharmacy Kit with the different components that make up the final drug product, and of assembling the final kit for either storage or immediate use in the polarizer. Special attention should be given to the laser welding process in order to satisfy installation qualification (IQ) and operational qualification (OQ). Typically, the final developed process is validated by process qualification (PQ) runs, during which 3 or more Pharmacy Kits are filled and used and the final HP 13C products are tested for endotoxin and sterility and to confirm that they meet the dose specifications for injections (usually including pyruvate concentration, residual EPA concentration, pH, liquid state polarization level and dose temperature). The data from 3 consecutive PQ runs are submitted as part of the IND submission (or its equivalent), and are often also reviewed by the Institutional Review Board (IRB) where the studies are conducted.

Quality Control And Dose Release

The quality control (QC) and dose release can be separated into two aspects: one is the QC and release of the filled Pharmacy Kit, and second is the QC and release of the HP 13C agent for injection, after polarization and dissolution. For institutions filling a batch of kits and storing them to use over a period of time, typically the batch can be released based on initial validation, environmental monitoring data from the day of kit production, and if filters are used during preparation of any of the components, filter integrity testing. But in some cases one or more kits are used for validation before the batch of kits are released for future use. For institutions that fill only the kits required for specific studies shortly before the experiment, the filled kits often do not go through separate release tests before they are used.

The quality control of the HP 13C pyruvate solution post dissolution is primarily performed to ensure that the agent meets the dose specifications (Table 1) before it is administered to the subject. These specifications target both safety (pH, residual EPA, temperature) and efficacy (pyruvate concentration, polarization, volume). Typically, the pyruvate concentration, residual EPA concentration, pH, dose temperature, dose volume, and liquid state polarization are measured by the QC accessory associated with the SPINlab polarizer. Some users perform a secondary measurement for one of the parameters, such as pH, using a different instrument or pH paper. For sites that do not go through a separate release testing process for batch filled kits, the integrity of the sterilization assurance filter, a part of the Pharmacy Kit, is typically tested as a part of the dose release. It is also common for these users to preserve an aliquot of the final HP 13C pyruvate solution for post-release endotoxin and sterility testing. This testing cannot be completed fast enough to test an individual dose prior to injection, but this is why other processes such as PQ runs and validation testing are done to minimize the chance a subject could be injected with a contaminated dose.

The Final Dose Release And Injection

should be done under the supervision of a licensed professional, based on local regulations.

Some Key Challenges

Many of the challenges associated with HP 13C pyruvate preparation can be attributed to the conditions required for the dissolution-DNP method of high magnetic field (~3-7 T) and very low temperature (~1 K) during polarization, with pressurized and superheated water necessary for the rapid dissolution event. These extreme conditions are quite challenging for the design of the container-closure and fluid path system. In particular, the cryogenic temperature in the polarizer requires special attention to any moisture or ambient (moist) air introduced into that portion of the fluid path, which can form an ice block at ~1 K. This ice can lead to flow restriction during the dissolution event and reduce the strength of the laser welded bond between the cryovial and its cap. This can ultimately produce failures in the dissolution step, including variations in final pyruvate concentration and pH that may fail to meet QC release criteria as well as fluid path ruptures that provide no available dose and result in polarizer down-time.

The polarization of the HP 13C pyruvate sample decays quickly over the span of a few minutes after dissolution, and thus the process of dissolution, QC for release, and injection should be completed as fast as possible to preserve the high polarization level achieved. Any delays in the preparation process, such as transportation time or equipment malfunction, can significantly reduce the final polarization and result in lower quality imaging data.

Current Practices

A summary of data collected from all sites performing clinical trials with HP 13C-pyruvate is shown in Fig. 3 and Table 1, including the specification of the final dose and how the quality control and release of the final dose are performed. There is a split in the Production Style, described in the General Considerations section above, with 8/13 sites using Sterile Preparation versus 5/13 using Terminal Sterilization. While many of the dose specifications show notable differences in acceptable ranges, all of these variations listed in tables have been successfully and safely been used to perform HP 13C pyruvate studies in humans. Their differences depend on the institutions’ preferences, resources and their particular regulatory situation. There is high similarity in pyruvate ranges, temperature ranges, EPA limits, and volume limits. There is modest variability in pH ranges and large variability in the endotoxin test limit. There is a 3-fold difference in acceptable polarization levels, which are measured to ensure a futile dose is not injected since the polarization is directly proportional to SNR. This reflects the decision by several sites to believe that useful data can be still be obtained with suboptimal polarizations.

Figure 3: Hyperpolarized agent preparation methods reported by sites currently performing HP

In House

Table 1: HP 13C-pyruvate preparation parameters, methods, and dose specifications used for quality control testing and release as well as validation. These were obtained from a survey of all sites performing clinical trials with HP [1-13C]pyruvate. The parameters used for product release are noted in bold text, otherwise these parameters are measured for batch validation or other QC measurements. The endotoxin and sterility testing are performed during process validation of the batch and/or post-injection, and largely depends on the agent production approach.

Summary

The overall safety record of HP 13C-pyruvate has been very strong, and the SPINlab hyperpolarizer has proven to provide high polarizations at human sized doses while meeting numerous QC and release criteria. A weakness remains the failure modes of the SPINlab Phamacy Kits (e.g. ice blocks, path ruptures), which are placed under extreme requirements particularly during dissolution. The preparation process still requires a high degree of expertise.

Therefore, there is a significant need to improve the reliability, robustness, and ease of operation for generating HP 13C-pyruvate doses for human studies. Furthermore, there is a divide between manufacturing and sterile compounding style preparation as well as other site-specific practices, resulting in variations in SOPs and justification required to relevant regulatory bodies. There have also been no comparisons between these approaches. It is also unclear what release criteria and QC parameters are truly required to ensure patient safety.

However, all of the reported methods are acceptable and approved by the appropriate regulatory authorities, and have led to the rapid expansion of successful human studies in recent years.

Mri System Setup And Calibrations

This section covers the MRI system setup, including the imaging system, RF coils, phantoms, and prescan calibration methods.

Imaging System

The main prerequisite for a given MRI scanner to be capable of supporting studies with HP 13C is its “broadband” capability to transmit and receive radiofrequency (RF) signal at the frequency of 13C, which is around 4 times lower than 1H. This does not come as a default on clinical MR devices. The transmit power of the broadband amplifier should also be sufficient to support the intended flip angle and RF pulse shape with the employed transmission RF coil(s) for 13C. Most studies to date use relatively low flip angles (< 90 degrees) for HP 13C in order to preserve polarization for time-resolved imaging. The capability to receive 13C signal on multiple channels is also desirable to increase SNR, as discussed further in the “RF coils” section.

The choice of magnetic field strength is primarily dependent on the metabolites’ frequency separation due to chemical shift dispersion and 1H imaging. High field strengths do not enhance hyperpolarized 13C signal as they do for 1H because the signal strength in a HP experiment relies on manipulating the population of quantum energy states outside of the MRI scanner.

However, the injected HP 13C-pyruvate and its metabolic products have greater frequency separation at higher fields, and it may thus be easier to separate and quantify these resonances at higher fields. This comes at the cost of a reduction in the achievable T2* and often reduced T1. As the initial polarization is independent of the imaging field strength it has been proposed that the increased T2* at 1.5T can potentially be exploited to increase SNR by adapting the acquisition bandwidth or reduce off-resonance imaging effects in cases when the decay of the transverse magnetization is dominated by T2* (73). In practice, 3T has been used in all published human 13C-pyruvate studies surveyed (Supporting Table S1), and comprises the majority of scanners currently in use for human studies (Table 3). A field strength of 3T is well-suited for 1H MRI anatomical reference and correlative imaging.

Stronger and more rapidly slewing magnetic field gradients support more rapid spatial encoding, particularly for metabolite-specific single-shot imaging using echo-planar imaging (EPI) or spiral imaging (See “Acquisition and Reconstruction”). Although the spatial resolution acquired for HP 13C imaging is typically much coarser than for 1H MRI, the factor of ~4 in gyromagnetic ratio leads to the same reduction factor in performance of the gradient system, so 13C experiments are potentially more limited by gradient hardware performance. To date, all human studies have used the commercially-available integrated gradient systems provided in clinical MRI scanners.

Optimization of scanner design has understandably focused on minimization of artifacts in 1H MRI, where devices such as room lights, the gradient amplifiers, and the motors driving the patient bed are checked to ensure that they do not produce RF interference at the 1H frequency, but artifacts may arise at other frequencies. Eddy current compensation is also not always appropriately adjusted for nuclei at other frequencies (74). In order to optimize for 13C, many sites have performed checks on phantoms for RF interference, gradient artifacts, and eddy currents (74), including the use of post-hoc gradient impulse response function characterisation and correction, and some vendors have fixed these issues as well.

Rf Coils

For HP 13C imaging studies in humans, RF coils for both 1H and 13C nuclei are needed, with 1H MRI providing an anatomical reference for registration and optional additional multiparametric MRI readouts. At the Larmor frequency of 13C nuclei, the relative contributions from coil noise compared to sample noise increase compared to 1H (73,75), although sample noise still is likely the dominant contributor for human-sized coils at 32.1MHz - the resonance frequency of 13C nuclei at 3T.

The key requirement for human 13C-pyruvate RF coils are that the coil geometry and sensitive volume must cover the volume of interest in the subject. Table 2 and Figure 4 shows coil configurations that have been used and optimized for applications in different anatomic regions.

Volume resonators are most commonly used for transmit, as they surround the subject to

Provide B1 Transmit Across The Fov (B1

+). While 1H relies on a large birdcage (“body”) coil built into the scanner, 13C transmit coils must be placed inside the bore. This takes up valuable space within the magnet, and also has led to the use of designs with relatively inhomogeneous

B1

+. Many human studies have used Helmholz pair resonators for transmit, including the “clamshell coil”, which has a notably inhomogeneous B1

+ Profile But Has Been Used Because Of

relatively easy integration into the scanner bore. B1

+ Variation Results In Variations In The Flip

angles that control the use of the hyperpolarized magnetization and creates errors in common HP metrics (9,76). The exception are head coils, where birdcage designs with highly

Homogeneous B1

+ can be placed around the head while easily fitting inside the bore. As with 1H MRI, higher SNR can typically be achieved by smaller receive coil elements, such as surface coils or phased arrays, and the majority of 13C receive coils used have layouts similar to 1H phased arrays.

RF coil quality control is important to ensure proper functioning of the coils to provide consistent imaging quality, especially with limited natural abundance 13C signal in vivo. It typically involves 1) a physical integrity check of the coil cables and connectors and 2) phantom SNR tests to check the coil’s performance and to monitor it over time (see Phantoms below). An useful reference for RF coil quality control is outlined in the MRI accreditation program of the American College of Radiology (77) and can be adapted for 13C coils.

Notably, configurations for brain and prostate studies used dual-tuned 1H/13C coil designs, which greatly simplify workflow and registration of 1H and 13C images, as no switching of coils is needed.

(1)

Table 2: RF coil configurations reported for human HP [1-13C]pyruvate studies.

Tx = Transmit

coil, RX = receive coil. The commonly used “clamshell” TX coil is a Helmholz pair design. For 1H RF configurations, all used the Body coil for TX unless otherwise noted, and “repositioned” indicates the 13C coil was removed for 1H imaging. One representative reference is listed for each configuration. The RF coil configurations reported in the reviewed papers are shown in Supporting Table S1.

Figure 4: Examples of RF coil configurations used for human HP [1-13C]pyruvate brain studies. (A,B) 13C Clamshell TX (Helmholz pair) and 2× 4-channel paddle RX arrays. (C) 13C Birdcage volume TX and 32-channel RX array (RX array slides into TX coil). (D) 13C Birdcage volume TX and 24-channel RX array, combined with a 1H 8-channel RX array. Image reproduced with permission from Ref (16).

Phantoms

Since hyperpolarized magnetization is non-renewable, phantoms containing 13C nuclei are important to: 1) test the multi-nuclear capabilities of the imaging system, including all parts of the signal excitation and receive chain; 2) perform calibration measurements before a scan with hyperpolarized nuclei; and 3) perform necessary pre-scan adjustments (see “Prescan Calibration” section). The phantoms currently in use are listed in Table 3. Their composition must provide sufficient 13C signal, with additional considerations of conductivity, stability, chemical shift(s) present, potential for dynamic imaging, and cost. The phantom geometries are typically either compact, in order to be used alongside the subject during a HP scan, or large enough to mimic the inner volume of a RF coil for system testing.

One popular compact design contains enriched 13C-urea at high concentration, typically 8 M, which provides a single resonance, placed inside a small container ~1 mL. The most common recipe mixes 13C-urea in a 90% water/10% glycerol solution, with glycerol used to increase the urea solubility and doping with a Gd-based contrast agent to shorten T1 which increases the potential SNR per unit time. For example, when Dotarem is added at a 3:1000 volume ratio the 13C-urea T1 is around 500 ms and T2 is around 100 ms. However, when testing pulse sequences influenced by T1 and T2, doping should be used carefully. This phantom is suitable for frequency calibration, transmit gain calibration, sequence testing, and as a fiducial marker when placed next to a patient. However, enriched 13C-urea has a relatively high cost compared to natural abundance compounds.

For larger volumes (>100 ml), the phantoms most often used contain undiluted ethylene glycol, glycerol, or dimethyl silicone. These compounds have sufficiently high carbon concentrations to provide sufficient 13C signal even with the 1.1% natural abundance of 13C. These larger phantoms matching the inner volume of an RF coil are useful for coil testing, including transmit

+) And Receive (B1

-) coil profile mapping, as well as to mimic acquisitions using in vivo FOV requirements. In this case, size and conductivity should match the expected subject size in order to mimic coil loading and get a realistic estimation of B1+. Large-volume natural abundance urea phantoms have also been used by some sites, but suffer from higher conductivity compared to biological tissues. Typically, it is easier to increase the conductivity and hence coil loading of the non-conductive phantom by adding NaCl to match physiological loading (16,78).

Dynamic phantoms that aim to mimic metabolite kinetics have also been developed (79–81), and have the potential to more closely mimic the HP experiment, but so far these are not widely used.

Prescan Calibration

Prior to performing an MRI acquisition, the so-called prescan procedure is used to set the shim parameters to maximize B0 homogeneity over the field of view (FOV) or a specific region of interest (ROI), the scanner center frequency (CF), the RF transmit gain, and the receiver gain.

While this calibration procedure is usually automated for 1H, the lack of sufficient natural abundance 13C signal prevents use of automated methods. (Although natural abundance 13C lipid signal has been detected, there are so far no reports on using this signal for prescan.) Table 3 shows current practices across sites.

Maximizing B0 homogeneity is independent of the nucleus and is therefore performed prior to 13C imaging using the 1H water signal and existing shimming tools, such as by a standard automated process (“Auto Shimming”) or using high order shimming routines. Similarly, the 13C CF can be calculated from the 1H CF using a predetermined scaling factor that depends on the target chemical shift (82). Another common approach used is to have a small, high-concentration 13C phantom, e.g. 8M 13C-urea, integrated in the RF coil or placed next to the scan subject (1). The reference frequency can also be based on real-time measurements after the HP injection but prior to imaging (83). Both the CF and B0 shimming are critical when using spectrally-selective RF pulses, as inmetabolite-specific imaging methods, where the desired excitation bandwidths are typically very narrow and frequency offsets can lead to a failure mode that is only apparent after injection.

The calibration of the RF transmit power is typically performed on a small, high-concentration 13C phantom placed near the region of interest during the scan or on a large 13C phantom of similar size and coil loading as the subject, prior to the subject scan. Reference power is often done by sweeping the power in a pulse-acquire sequence (53,62), or the Bloch-Siegert method (52,84). When using a small phantom, the location of the phantom, B1

+ Inhomogeneity As Well

as any shielding effects, e.g., when the phantom is integrated into a coil (1), may degrade the accuracy. Other methods include real-time Bloch-Siegert method measurements after the HP injection (83), and using the stronger natural abundance 23Na signal that is close enough to the 13C resonance frequency to be detected by 13C coils (82).

The receiver gain is predetermined, either systematically based on independent phantom measurements and assuming the dose and polarization of the HP compound is known prior to injection, or based on past HP imaging studies.

Power [Kw]

Phantom(s) - during study Phantom(s) - before study 13C Frequency

8

13C-bicarbonate doped with dimethyl silicone, various

Power [Kw]

Phantom(s) - during study Phantom(s) - before study 13C Frequency

Maximum Values

Table 3: Summary of the imaging systems, phantoms, and prescan procedures used at sites currently performing HP 13C-pyruvate human studies. These were obtained from a survey of all sites performing clinical trials with HP [1-13C]pyruvate. *Previously performed studies with a Siemens 3T Tim Trio. The imaging systems, phantoms, and prescan procedures reported in the reviewed papers are shown in Supporting Table S1.

Summary

Commercially available 3T MRI systems are by far the most commonly used for human HP 13C-pyruvate studies, although a systematic investigation of the impact of B0 has only recently been investigated (73). The multi-nuclear RF transmit and receive chain has proven sufficient for current acquisition strategies, although many sites have observed artifacts due to RF interference, gradient interference, and residual eddy currents when operating at the 13C frequency. A variety of 13C RF coils, tailored for numerous anatomical targets, have been successfully demonstrated, with the main limitation that most transmit coils take up a lot of additional space inside the bore and provide relatively inhomogeneous B1

+ Profiles. The

phantoms used have converged into generally 2 categories - small phantoms containing 13C-enriched compounds that can be used during the study and human-sized phantoms containing compounds with high carbon concentrations but without 13C enrichment that are used to test and calibrate the coils. There are no standardized compositions or geometry, and dynamic phantoms that recapitulate in vivo kinetics would be desirable but are still an emerging area. Prescan calibration procedures were not well defined in most publications, so we surveyed individual sites to determine current practices. Calibration procedures for the B0 field (13C CF and shimming) for most sites take advantage of 1H signal and methods, while methods

For Calibration Of B1

+ is more variable across sites, likely a reflection of remaining challenges in how to perform this calibration. Standardization of both phantoms and calibration procedures would synergistically improve the robustness and reproducibility of HP 13C studies.

Acquisition And Reconstruction

Data acquisition strategies in human HP [1-13C]pyruvate MRI studies must account for multiple chemical shifts, efficiently utilize the non-renewable HP magnetization, and acquire data quickly relative to metabolism and relaxation decay processes. These studies require spectral encoding to separate metabolites, necessitating pulse sequences that efficiently encode up to 5D data (3 spatial + 1 spectral + 1 temporal dimension). RF pulses must efficiently sample without immediately saturating the non-renewable HP magnetization, and sequences must acquire data quickly and be robust to both experimental and physiologic variation (e.g. B1

+ Inhomogeneity,

variation in perfusion) to ensure reproducibility and minimize scan-to-scan variability. This section covers current successful practices for data acquisition in human [1-13C]pyruvate studies, and accompanying 1H imaging, from different anatomic regions, including scan parameters and image reconstruction.

Acquisition And Reconstruction Methods

The acquisition methods used in human [1-13C]pyruvate studies can be classified into 3 categories: 1) MR spectroscopy or MR spectroscopic imaging (“MRS/I”), 2) chemical shift encoding methods, and 3) metabolite-specific imaging (Fig. 5).

Mrs/I Methods Specifically

resolve a spectrum that can be analyzed to extract expected as well as unexpected resonances, making this approach very robust. It was used in many initial studies (1).

Chemical Shift

encoding methods, most commonly the Iterative Decomposition of water and fat with Echo Asymmetry and Least-squares estimation (IDEAL) method, use imaging sequences acquired with multiple TEs and rely on a model-based separation of expected chemical shifts (85).

Metabolite-specific imaging methods use specialized RF pulses that are spatially and spectrally selective to excite individual metabolites which are then typically imaged with fast k-space trajectories such as echo planar imaging (EPI) or spirals (86).

Their Application To Different

organ systems is described below. The image reconstruction methods used in human [1-13C]pyruvate studies have typically been conventional methods (e.g. FFT, non-uniform FFT, or equivalent). The incorporation of accelerated imaging and advanced reconstruction methods including parallel imaging (4,57,87) and compressed sensing (7) has also been applied in human studies for improved spatial resolution, temporal resolution and coverage, but have the potential for additional artifacts as well as SNR losses due to ill-conditioning of the reconstruction (e.g. g-factor).

The Majority Of

published studies do not use accelerated imaging indicating the resolution and coverage achievable without acceleration is currently adequate for successful data collection. Performing coil combination, even with fully sampled data has also been shown to have specific challenges for HP human images: using naive sum-of-squares methods suffer from high noise amplification in the relatively low SNR regime of HP [1-13C]pyruvate (compared to 1H), motivating several HP 13C-specific methods that include data-driven coil sensitivity estimation which have shown obvious improvements over sum-of-squares (11).

More recently denoising techniques have been applied as post-processing of human HP data(41,42,44). The techniques applied are based on spatial-temporal singular value decomposition for unsupervised estimation of signal and noise components. They have shown improvements in apparent SNR in the brain and liver, while care must be taken to choose parameters such as the rank threshold to avoid oversmoothing and overfitting to the estimated signal components.

Prostate Studies

Prostate cancer was the first human application of HP [1-13C]pyruvate (1), and data was acquired with MRS/I methods: 1D dynamic MRS, single-slice 2D dynamic echo-planar spectroscopic imaging (EPSI), and single time point 3D EPSI. Advances in imaging strategies led to the development and application of new acquisition schemes, including undersampled 3D EPSI with compressed-sensing (7), model-based chemical shift encoding methods that use a priori information (47,59), and metabolite-specific EPI (10), all of which can provide volumetric whole-organ coverage and dynamic acquisitions.

The pyruvate bolus arrival in the prostate can vary by ± 10 s between patients, necessitating dynamic imaging to reliably and consistently capture the pyruvate bolus (18). For this reason, all currently ongoing studies acquire dynamic data. While MRS/I, chemical shift encoding, and metabolite-specific imaging can all achieve dynamic imaging, chemical shift encoding and metabolite-specific imaging provide greater dynamic and volumetric coverage (85). For scan prescriptions, the FOV is designed to provide full prostate coverage and typically to match the orientation of the anatomic imaging used for registration. Flip angles used in current studies are constant through time, as quantification with a variable-through-time flip scheme is highly sensitive to bolus timing (8) and errors in the RF transmit (B1 +) field (76).

Heart Studies

Data acquisition methods for 13C imaging in the heart must be designed to meet the demands of significant cardiac motion and blood flow. To cope with the periodic cardiac motion, most human heart studies to date used gating to the diastolic window, the longest cardiac cycle interval, which has reduced motion (2,22,28,30,35,36,38,45,52). The duration of the diastolic window limits the available data sampling time, making cardiac acquisitions the most time-constrained of the HP 13C MRI applications. The most common acquisition approach is metabolite-specific imaging with spiral k-space trajectories (2). Their single-shot imaging capability makes these methods particularly robust to motion effects. Furthermore, spiral k-space trajectories provide rapid k-space coverage and relatively benign flow and motion artifacts. The majority of studies have used 2D multi-slice acquisitions, but 3D encoding has also been used successfully (35).

Brain Studies

For HP 13C MRI of the human brain, the majority of studies have also used 2D (slice selective) acquisitions (10–12,14,16,28,33,40,41,44,51,53,60), with a trend toward volumetric coverage using 2D multi-slice metabolite-specific imaging. 3D metabolite-specific imaging of the whole brain, with phase encoding of the slice direction (34,57), has been shown to provide similar SNR efficiency (88) compared with multislice imaging. A number of studies have employed MRS/I (5,6,29,31–33,50,55) resulting in a spectrum from each voxel, which has the advantage of not requiring a priori information about which peaks to encode. This was important in early brain studies when it was not known which peaks would be detectable. Chemical shift encoding, using a set of images with different echo times and an iterative reconstruction of the individual resonances (i.e. the IDEAL approach (85)), has also been used (12,49,54), with the drawback that coverage in the slice direction was limited due to the time required to acquire multiple echo time images.

Abdomen And Breast Studies

The fundamental approaches to data acquisition and reconstruction in the abdomen and breast are largely similar to the aforementioned applications, but demand attention to particular challenges associated with these anatomic regions, especially relating to respiratory motion.

Although it has been shown that a basic 2D MRSI approach based on phase encoding and FID readout can be successfully applied for HP 13C imaging in breast (15) and kidney (13), major advantages in terms of spatiotemporal resolution and coverage have been realized using tailored approaches based on metabolite-specific imaging (43,62) and chemical shift encoding (43), which have facilitated multi-slice or 3D dynamic acquisitions over large FOVs in the abdomen (4,37,46).

The significant respiratory motion encountered in these regions can directly blur 13C images, and has further favored these rapid acquisition strategies. Motion also degrades B0 homogeneity, which can shift frequency-selective excitation profiles and introduce artifacts into rapid imaging readouts. This makes accurate determination of the acquisition center frequency and shimming essential in these regions which often cover large FOVs. (See “Prescan Calibration” section for more information). In some studies, breath-holding was used to minimize motion effects and enforce frame-to-frame data consistency (42). A pragmatic and reasonably effective approach for dealing with respiratory motion during 13C data acquisition is an initial breath-hold (as long as can be tolerated), followed by free-breathing (46,62).

1H Imaging

Collection of 1H imaging data is essential both for prescribing the 13C acquisition and for interpretation of the resulting 13C data. Multi-planar 1H scouts are acquired prior to 13C acquisition to enable graphical prescription of the 13C imaging region. All human HP 13C-pyruvate imaging studies acquire conventional MRI scans (e.g. T1- and T2-weighted volumes) for anatomic reference, aiming to cover at least the full 13C FOV. Acquiring these anatomic scans as close as possible to the time of 13C imaging (immediately before or after) minimizes potential misregistration between the data sets. Depending on the application, other advanced 1H sequences are also acquired (e.g. diffusion-weighted imaging for cancer imaging).

When contrast-enhanced data is acquired, it is done after 13C imaging, as paramagnetic contrast agents will accelerate 13C relaxation.

Reported Study Parameters

Figures 5 and 6, and Supporting Table S2 shows the reported acquisition study parameters for human HP [1-13C]pyruvate studies published as of September 2022. Figure 5 shows a mixture of MRS/I, metabolite-specific imaging, and chemical shift encoding methods have been successfully used, where spectroscopy-based methods have become less prevalent in recent studies. Figure 6 shows the acquisition timing, including the important start time and interval/temporal resolution, is quite variable across studies.

Figure 5: Acquisition methods used in published HP [1-13C]pyruvate human studies published up to September 2022, classified into: MR spectroscopy and spectroscopy imaging (MRS/I); chemical shift encoding methods, such as IDEAL, that use multiple TEs and model-based reconstructions; and metabolite-specific imaging methods that use spectrally-selective excitation to image a single resonance at a time.

Figure 6: Temporal acquisition characteristics reported in HP [1-13C]pyruvate human studies published up to September 2022. (a) Reported referencing of acquisition start times.

(B)

Acquisition start times reported when using dynamic imaging and when timing was reported relative to the end of the injection. (c) Temporal resolutions. “Not Applicable” indicates dynamic imaging was not used.

Summary

Three general categories of acquisition strategies have been used successfully for human HP 13C-pyruvate studies: MRS/I, model-based chemical shift encoding (e.g. IDEAL) methods, and metabolite-specific imaging methods. These have enabled successful studies in the prostate, heart, brain, abdomen, and breast. Recent studies increasingly have used the imaging-based strategies of metabolite-specific imaging and chemical shift encoding which are the fastest methods, although a heads-to–head comparison between techniques has not been performed.

Metabolite-specific imaging is quite popular because of its speed and compatibility with single-shot imaging, but is sensitive to B0 field variations and thus requires careful calibrations. Nearly all studies surveyed acquired data dynamically, allowing measurement of the bolus and metabolite kinetics. The exact timings and associated flip angles vary quite widely across reported studies, with no consensus yet as to how to choose these parameters. Image reconstruction is typically done directly using Fourier Transform methods, and accelerated imaging strategies are uncommon.

Data Analysis And Quantification

This section covers the analysis of data from human HP [1-13C]pyruvate studies, including modeling and metrics, visualization, as well as considerations for how to store data and metadata. Depending on study design, the analysis may need to give quantitative or semi-quantitative output reflecting a biological process or may just reflect a contrast between different regions of interest for quantitative evaluation.

Metrics

Figure 7: HP [1-13C]pyruvate raw data (A) have typically been quantified using four categories of metrics depending on the acquisition. Data acquired as a single time point are often quantified using normalized metabolite images or metabolite ratios (B). Dynamic data can be quantified using normalized metabolite images or metabolite ratios (B), or with metabolite timings such as time-to-peak (TTP) or pharmacokinetic (PK) models (C). The latter two require the data to be time-resolved. [1-13C]alanine and 13C-bicarbonate are analyzed similarly to [1-13C]lactate but omitted here for display.

Metabolite images are commonly used as summary metrics for HP MRI data, often including some form of normalization as well as summed over time as an area under the time curve (AUC) (17). These are analogous to the visual evaluation that is most used for routine clinical work (89,90). In these metabolite images, we expect that the [1-13C]pyruvate AUC signal is predominantly weighted towards perfusion and uptake, while [1-13C]lactate, [1-13C]alanine and 13C-bicarbonate AUCs represent metabolic conversion. The strength of this approach lies in its simplicity and relatively few underlying assumptions. Limitations to the use of single-metabolite images or AUCs include sensitivity to inhomogeneous coil profiles (57,87,91), the acquisition strategy and acquisition parameters, pyruvate polarization and concentration level, and signal relaxation rates (92). Further, the reader must be careful to interpret all the images in conjunction to better understand the underlying biology; for example, increased [1-13C]lactate in the presence of decreased [1-13C]pyruvate delivery can have a very different meaning compared to increased [1-13C]lactate with increased [1-13C]pyruvate delivery.

In an attempt to address variations in coil sensitivity, polarization level, and pyruvate delivery, AUC images are often computed by normalizing to a specified parameter, such as the maximum pyruvate or average lactate signals, or presented as a ratio such as lactate/pyruvate or divided by “total Carbon” - the sum total of HP 13C signal observed across all metabolites. The AUC ratios between metabolites and pyruvate are proportional to the corresponding forward kinetic rates (81,93), but are not directly comparable to rate constants when magnetization loss rates (e.g. relaxation and losses due to signal excitation) differ between studies. Similarly, the ratios between the produced metabolites (e.g. bicarbonate/lactate) can reflect the balance between downstream metabolic pathways (12,55). Care must be taken to consider how AUC images are calculated and normalized before comparing values between studies.

To further quantify the interpretation, pharmacokinetic (PK) modeling approaches were developed to compute the apparent kinetics of pyruvate-to-metabolite exchange (92,94–99). These yield semi-quantitative to quantitative apparent rate constants, given in s-1. Some models require a vascular input function, while others avoid this requirement (95). PK models can explicitly account for acquisition-specific details such as excitation angle and repetition time, and thus may reduce the effects of these details on quantification. An input-less model, provided in the Hyperpolarized-MRI-Toolbox (https://github.com/LarsonLab/hyperpolarized-mri-toolbox) (100) and thus frequently employed for human data, has been shown to fit well and robustly to prostate and brain data (8,20). PK models are quantitative in nature, arguably provide more relevant biological information (8,20), and appear to be reproducible across sites (51). However, rate constants derived from PK models are still apparent rates, and likely do not reflect a single biological characteristic.

Some additional considerations include whether complex or magnitude data is used, as the noise behaviors will impact the analysis differently. Additionally, cut-off thresholds or other criteria may be used to identify and avoid voxels with insufficient SNR before analysis to improve robustness (20,41).

Regardless of the analysis approach, the underlying biology is not always clearly represented by the data; instead, the metrics may be influenced by perfusion, barrier permeability, intercellular shuttles, enzyme activities, co-substrate concentrations, or combinations thereof, depending on the organ and disease of interest (19,43,94,101–103). This may be addressed by incorporating complementary information. As an example, HP 13C pyruvate data is influenced by perfusion, and thus addition of perfusion MRI could be important for interpretation (98,104,105).

All the methods outlined above have been explored in clinical studies, described in Supporting Table 3 and summarized in Figure 8. As of September 2022, approximately 52% of studies involving human subjects report rate constants derived from a PK model with a few different models reported. A nearly equal fraction (51%) of the studies report AUC ratio values.

Approximately 66% of these studies report metabolite-specific images or AUC values. About 40% report SNR values; this metric is particularly frequent in manuscripts that describe technical developments for clinical HP MRI. Approximately 16% of these studies summarize model-free metrics, and 10% report measurements from a single timepoint. Most studies report a combination of quantities.

Figure 8: Reported metrics used for analysis in HP [1-13C]pyruvate human studies published up to September 2022.

Visualization

A wide variety of approaches have been used for visualizing data from human HP 13C-MRI studies. The challenges and practical considerations are: 1) choosing the appropriate metrics to display, 2) how to encode the parameters (e.g. the colormap), and 3) choosing how to provide anatomical context and other multi-parametric data. The choice of visualization also depends on the goal which could be for diagnostic interpretation, but also quality control, reproducibility among readers and publication.

Metrics

The choice of HP 13C metrics is described in detail above. At this stage in HP 13C development where there is no standardized metric, often a combination of metabolite images and ratios or PK model parameters are shown.

Parameter Encoding

The mapping function chosen should provide an adequate, often quantitative, impression of the parameter mapped. There is a consensus in the visualization field that perceptually uniform maps are best suited to visualize continuous parameters, like the greyscale typically used by radiologists as well as other monochrome (black to blue) and color ranges (fire-type, rainbow-type) (106,107). Multi-color heatmaps have been the most frequently employed method for HP 13C data, while greyscale has infrequently been used but it ensures there is no coloring-based bias as well as facilitating later reuse (Fig. 9a). Among the color schemes employed in the clinical HP 13C literature, fire-type scheme seems to be the most common [similar to “Plasma” or “Inferno” in matplotlib.org]. Next most commonly employed is the rainbow-type scheme [similar to “Rainbow” in matplotlib.org].

Anatomical Context

HP MRI faces the challenge that it does not necessarily depict the anatomical features, similar to PET, and thus requires an anatomical reference. Most often, a grayscale anatomical image is overlaid with a HP colormap (Fig. 9c,d). This approach is very intuitive, but can skew perception as the grey-scale anatomical reference may affect the brightness of the HP data (e.g. signal in the skull). This bias does not occur when showing adjacent maps (Fig. 9a, b). Here, anatomical outlines may help to provide reference (Fig. 9b).

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