We report results from a reanalysis of data from the Cryogenic Dark Matter Search (CDMS II) experiment at the Soudan Underground Laboratory. Data taken between October 2006 and September 2008 using ...eight germanium detectors are reanalyzed with a lowered, 2 keV recoil-energy threshold, to give increased sensitivity to interactions from weakly interacting massive particles (WIMPs) with masses below ∼10 GeV/c(2). This analysis provides stronger constraints than previous CDMS II results for WIMP masses below 9 GeV/c(2) and excludes parameter space associated with possible low-mass WIMP signals from the DAMA/LIBRA and CoGeNT experiments.
Background
Whereas filtered back projection algorithms for voxel‐based CT image reconstruction have noise properties defined by the filter, iterative algorithms must stop at some point in their ...convergence and do not necessarily produce consistent noise properties for images with different degrees of heterogeneity.
Purpose
A least‐squares iterative algorithm for proton CT (pCT) image reconstruction converges toward a unique solution for relative stopping power (RSP) that optimally fits the protons. We present a stopping criterion that delivers solutions with the property that correlations of RSP noise between voxels are relatively low. This provides a method to produce pCT images with consistent noise properties useful for proton therapy treatment planning, which relies on summing RSP along lines of voxels. Consistent noise properties will also be useful for future studies of image quality using metrics such as contrast to noise ratio, and to compare RSP noise and dose of pCT with other modalities such as dual‐energy CT.
Methods
With simulated and real images with varying heterogeneity from a prototype clinical proton imaging system, we calculate average RSP correlations between voxel pairs in uniform regions‐of‐interest versus distance between voxels. We define a parameter r, the remaining distance to the unique solution relative to estimated RSP noise, and our stopping criterion is based on r falling below a chosen value.
Results
We find large correlations between voxels for larger values of r, and anticorrelations for smaller values. For r in the range of 0.5–1, voxels are relatively uncorrelated, and compared to smaller values of r have lower noise with only slight loss of spatial resolution.
Conclusions
Iterative algorithms not using a specific metric or rationale for stopping iterations may produce images with an unknown and arbitrary level of convergence or smoothing. We resolve this issue by stopping iterations of a least‐squares iterative algorithm when r reaches the range of 0.5–1. This defines a pCT image reconstruction method with consistent statistical properties optimal for clinical use, including for treatment planning with pCT images.
Astrophysical observations indicate that dark matter constitutes most of the mass in our universe, but its nature remains unknown. Over the past decade, the Cryogenic Dark Matter Search (CDMS II) ...experiment has provided world-leading sensitivity for the direct detection of weakly interacting massive particle (WIMP) dark matter. The final exposure of our low-temperature germanium particle detectors at the Soudan Underground Laboratory yielded two candidate events, with an expected background of 0.9 ± 0.2 events. This is not statistically significant evidence for a WIMP signal. The combined CDMS II data place the strongest constraints on the WIMP-nucleon spin-independent scattering cross section for a wide range of WIMP masses and exclude new parameter space in inelastic dark matter models.
We report results from the Cryogenic Dark Matter Search at the Soudan Underground Laboratory (CDMS II) featuring the full complement of 30 detectors. A blind analysis of data taken between October ...2006 and July 2007 sets an upper limit on the weakly interacting massive particle (WIMP) nucleon spin-independent cross section of 6.6x10;{-44} cm;{2} (4.6x10;{-44} cm;{2} when combined with previous CDMS II data) at the 90% confidence level for a WIMP mass of 60 GeV/c;{2}. This achieves the best sensitivity for dark matter WIMPs with masses above 44 GeV/c;{2}, and significantly restricts the parameter space for some favored supersymmetric models.
Purpose
To demonstrate a proton‐imaging system based on well‐established fast scintillator technology to achieve high performance with low cost and complexity, with the potential of a straightforward ...translation into clinical use.
Methods
The system tracks individual protons through one (X, Y) scintillating fiber tracker plane upstream and downstream of the object and into a 13‐cm ‐thick scintillating block residual energy detector. The fibers in the tracker planes are multiplexed into silicon photomultipliers (SiPMs) to reduce the number of electronics channels. The light signal from the residual energy detector is collected by 16 photomultiplier tubes (PMTs). Only four signals from the PMTs are output from each event, which allows for fast signal readout. A robust calibration method of the PMT signal to residual energy has been developed to obtain accurate proton images. The development of patient‐specific scan patterns using multiple input energies allows for an image to be produced with minimal excess dose delivered to the patient.
Results
The calibration of signals in the energy detector produces accurate residual range measurements limited by intrinsic range straggling. We measured the water‐equivalent thickness (WET) of a block of solid water (physical thickness of 6.10 mm) with a proton radiograph. The mean WET from all pixels in the block was 6.13 cm (SD 0.02 cm). The use of patient‐specific scan patterns using multiple input energies enables imaging with a compact range detector.
Conclusions
We have developed a prototype clinical proton radiography system for pretreatment imaging in proton radiation therapy. We have optimized the system for use with pencil beam scanning systems and have achieved a reduction of size and complexity compared to previous designs.
Purpose
Verification of patient‐specific proton stopping powers obtained in the patient’s treatment position can be used to reduce the distal and proximal margins needed in particle beam planning. ...Proton radiography can be used as a pretreatment instrument to verify integrated stopping power consistency with the treatment planning CT. Although a proton radiograph is a pixel by pixel representation of integrated stopping powers, the image may also be of high enough quality and contrast to be used for patient alignment. This investigation quantifies the accuracy and image quality of a prototype proton radiography system on a clinical proton delivery system.
Methods
We have developed a clinical prototype proton radiography system designed for integration into efficient clinical workflows. We tested the images obtained by this system for water‐equivalent thickness (WET) accuracy, image noise, and spatial resolution. We evaluated the WET accuracy by comparing the average WET and rms error in several regions of interest (ROI) on a proton radiograph of a custom peg phantom. We measured the spatial resolution on a CATPHAN Line Pair phantom and a custom edge phantom by measuring the 10% value of the modulation transfer function (MTF). In addition, we tested the ability to detect proton range errors due to anatomical changes in a patient with a customized CIRS pediatric head phantom and inserts of varying WET placed in the posterior fossae of the brain. We took proton radiographs of the phantom with each insert in place and created difference maps between the resulting images. Integrated proton range was measured from an ROI in the difference maps.
Results
We measured the WET accuracy of the proton radiographic images to be ±0.2 mm (0.33%) from known values. The spatial resolution of the images was 0.6 lp/mm on the line pair phantom and 1.13 lp/mm on the edge phantom. We were able to detect anatomical changes producing changes in WET as low as 0.6 mm.
Conclusion
The proton radiography system produces images with image quality sufficient for pretreatment range consistency verification.
Purpose: Currently, calculations of proton range in proton therapy patients are based on a conversion of CT Hounsfield units of patient tissues into proton relative stopping power. Uncertainties in ...this conversion necessitate larger proximal and distal planned target volume margins. Proton CT can potentially reduce these uncertainties by directly measuring proton stopping power. We aim to demonstrate proton CT imaging with complex porcine samples, to analyze in detail three‐dimensional regions of interest, and to compare proton stopping powers directly measured by proton CT to those determined from x‐ray CT scans.
Methods: We have used a prototype proton imaging system with single proton tracking to acquire proton radiography and proton CT images of a sample of porcine pectoral girdle and ribs, and a pig's head. We also acquired close in time x‐ray CT scans of the same samples and compared proton stopping power measurements from the two modalities. In the case of the pig's head, we obtained x‐ray CT scans from two different scanners and compared results from high‐dose and low‐dose settings.
Results: Comparing our reconstructed proton CT images with images derived from x‐ray CT scans, we find agreement within 1% to 2% for soft tissues and discrepancies of up to 6% for compact bone. We also observed large discrepancies, up to 40%, for cavitated regions with mixed content of air, soft tissue, and bone, such as sinus cavities or tympanic bullae.
Conclusions: Our images and findings from a clinically realistic proton CT scanner demonstrate the potential for proton CT to be used for low‐dose treatment planning with reduced margins.
Clinically useful proton computed tomography images will rely on algorithms to find the 3-D proton stopping power distribution that optimally fits the measured proton data. We present a least squares ...iterative method with many features to put proton imaging into a more quantitative framework. These include the definition of a unique solution that optimally fits the protons, the definition of an iteration vector that takes into account proton measurement uncertainties, the definition of an optimal step size for each iteration individually, the ability to simultaneously optimize the step sizes of many iterations, the ability to divide the proton data into arbitrary numbers of blocks for parallel processing and use of graphical processing units, and the definition of stopping criteria to determine when to stop iterating. We find that it is possible, for any object being imaged, to provide assurance that the image is quantifiably close to an optimal solution, and the optimization of step sizes reduces the total number of iterations required for convergence. We demonstrate the use of these algorithms on real data.
The CDMS II Data Acquisition System Bauer, D.A.; Burke, S.; Cooley, J. ...
Nuclear instruments & methods in physics research. Section A, Accelerators, spectrometers, detectors and associated equipment,
05/2011, Letnik:
638, Številka:
1
Journal Article
Recenzirano
Odprti dostop
The Data Acquisition System for the CDMS II dark matter experiment was designed and built when the experiment moved to its new underground installation at the Soudan Lab. The combination of remote ...operation and increased data load necessitated a completely new design. Elements of the original LabView system remained as stand-alone diagnostic programs, but the main data processing moved to a VME-based system with custom electronics for signal conditioning, trigger formation and buffering. The data rate was increased 100-fold and the automated cryogenic system was linked to the data acquisition. A modular server framework with associated user interfaces was implemented in Java to allow control and monitoring of the entire experiment remotely.
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