Search

Accurate estimates of tumor absorbed dose are essential for the evaluation of treatment efficacy in radiopharmaceutical cancer therapy. Although tumor dosimetry via the MIRD schema has been previously investigated, prior studies have been limited to the consideration of soft-tissue tumors. In the present study, specific absorbed fractions (SAFs) for monoenergetic photons, electrons, and alpha particles in tumors of varying compositions were computed using Monte Carlo simulations in MCNPX after which self-irradiation S-values for 22 radionuclides (along with 14 additional alpha-emitter progeny) were generated for tumors of both varying size and tissue composition. The tumors were modeled as spheres with radii ranging from 0.10 cm to 6.0 cm and with compositions varying from 100% soft tissue (ST) to 100% mineral bone (MB). The energies of the photons and electrons were varied on a logarithm energy grid from 10 keV to 10 MeV. The energies of alpha particles were varied along a linear energy grid from 0.5 MeV to 12 MeV. In all cases, a homogenous activity distribution was assumed throughout the tumor volume. Furthermore, to assess the effect of tumor shape, several ellipsoidal tumors of different compositions were modeled and absorbed fractions were computed for monoenergetic electrons and photons. S-values were then generated using detailed decay data from the 2008 MIRD Monograph on Radionuclide Data and Decay Schemes. Our study results demonstrate that a soft-tissue model yields relative errors of 25% and 71% in the absorbed fraction assigned to uniform sources of 1.5 MeV electrons and 100 keV photons, respectively, localized within a 1 cm diameter tumor of MB. The data further show that absorbed fractions for moderate ellipsoids can be well approximated by a spherical shape of equal mass within a relative error of < 8%. S-values for 22 radionuclides (and their daughter progeny) were computed with results demonstrating how relative errors in SAFs could propagate to relative errors in tumor dose estimates as high as 86%. A comprehensive data set of radionuclide S-values by tumor size and tissue composition is provided for application of the MIRD schema for tumor dosimetry in radiopharmaceutical therapy.

Digital phantoms and Monte Carlo (MC) simulations have become important tools for optimizing and evaluating instrumentation, acquisition and processing methods for myocardial perfusion SPECT (MPS). In this work, we designed a new adult digital phantom population and generated corresponding Tc-99m and Tl-201 projections for use in MPS research. The population is based on the three-dimensional XCAT phantom with organ parameters sampled from the Emory PET Torso Model Database. Phantoms included three variations each in body size, heart size, and subcutaneous adipose tissue level, for a total of 27 phantoms of each gender. The SimSET MC code and angular response functions were used to model interactions in the body and the collimator-detector system, respectively. We divided each phantom into seven organs, each simulated separately, allowing use of post-simulation summing to efficiently model uptake variations. Also, we adapted and used a criterion based on the relative Poisson effective count level to determine the required number of simulated photons for each simulated organ. This technique provided a quantitative estimate of the true noise in the simulated projection data, including residual MC simulation noise. Projections were generated in 1 keV wide energy windows from 48-184 keV assuming perfect energy resolution to permit study of the effects of window width, energy resolution, and crosstalk in the context of dual isotope MPS. We have developed a comprehensive method for efficiently simulating realistic projections for a realistic population of phantoms in the context of MPS imaging. The new phantom population and realistic database of simulated projections will be useful in performing mathematical and human observer studies to evaluate various acquisition and processing methods such as optimizing the energy window width, investigating the effect of energy resolution on image quality and evaluating compensation methods for degrading factors such as crosstalk in the context of single and dual isotope MPS.

Estimates of radiation absorbed dose to organs of the nuclear medicine patient are a requirement for administered activity optimization and for stochastic risk assessment. Pediatric patients, and in particular the newborn child, represent that portion of the patient population where such optimization studies are most crucial owing to the enhanced tissue radiosensitivities and longer life expectancies of this patient subpopulation. In cases where whole-body CT imaging is not available, phantom-based calculations of radionuclide S values--absorbed dose to a target tissue per nuclear transformation in a source tissue--are required for dose and risk evaluation. In this study, a comprehensive model of electron and photon dosimetry of the reference newborn child is presented based on a high-resolution hybrid-voxel phantom from the University of Florida (UF) patient model series. Values of photon specific absorbed fraction (SAF) were assembled for both the reference male and female newborn using the radiation transport code MCNPX v2.6. Values of electron SAF were assembled in a unique and time-efficient manner whereby the collisional and radiative components of organ dose--for both self- and cross-dose terms--were computed separately. Dose to the newborn skeletal tissues were assessed via fluence-to-dose response functions reported for the first time in this study. Values of photon and electron SAFs were used to assemble a complete set of S values for some 16 radionuclides commonly associated with molecular imaging of the newborn. These values were then compared to those available in the OLINDA/EXM software. S value ratios for organ self-dose ranged from 0.46 to 1.42, while similar ratios for organ cross-dose varied from a low of 0.04 to a high of 3.49. These large discrepancies are due in large part to the simplistic organ modeling in the stylized newborn model used in the OLINDA/EXM software. A comprehensive model of internal dosimetry is presented in this study for the newborn nuclear medicine patient based upon the UF hybrid computational phantom. Photon dose response functions, photon and electron SAFs, and tables of radionuclide S values for the newborn child--both male and female--are given in a series of four electronic annexes available at stacks.iop.org/pmb/57/1433/mmedia. These values can be applied to optimization studies of image quality and stochastic risk for this most vulnerable class of pediatric patients.

Simultaneous acquisition of dual-isotope SPECT data offers a number of advantages over separately acquired data; however, simultaneous acquisition can result in cross-contamination between isotopes. In this work we propose and evaluate two frameworks for iterative model-based compensation of cross-contamination in dual-isotope SPECT. The methods were applied to cardiac imaging with technetium-99m-sestamibi and thallium-201, and they were compared with a subtraction-based compensation method using a cross-talk estimate obtained from an auxiliary energy window. Monte Carlo simulations were performed to carefully study aspects of bias and noise for the methods, and a torso phantom with cardiac insert was used to evaluate the performance of the methods for experimentally acquired data. The cross-talk compensation methods substantially improved lesion contrast and significantly reduced quantitative errors for simultaneously acquired data. Thallium image normalized mean square error (NMSE) was reduced from 0.522 without cross-talk compensation to as low as 0.052 with model-based cross-talk compensation. This is compared with a NMSE of 0.091 for the subtraction-based compensation method. The application of a preliminary model for cross-talk arising from lead fluorescence x-rays and collimator scatter gave promising results, and the future development of a more accurate model for collimator interactions would probably benefit simultaneous Tc/Tl imaging. Model-based compensation methods provide feasible cross-talk compensation in clinically acceptable times, and they may ultimately make simultaneous dual-isotope protocols an effective alternative for many imaging procedures.

Accurate scatter compensation in SPECT can be performed by modelling the scatter response function during the reconstruction process. This method is called reconstruction-based scatter compensation (RBSC). It has been shown that RBSC has a number of advantages over other methods of compensating for scatter, but using RBSC for fully 3D compensation has resulted in prohibitively long reconstruction times. In this work we propose two new methods that can be used in conjunction with existing methods to achieve marked reductions in RBSC reconstruction times. The first method, coarse-grid scatter modelling, significantly accelerates the scatter model by exploiting the fact that scatter is dominated by low-frequency information. The second method, intermittent RBSC, further accelerates the reconstruction process by limiting the number of iterations during which scatter is modelled. The fast implementations were evaluated using a Monte Carlo simulated experiment of the 3D MCAT phantom with 99mTc tracer, and also using experimentally acquired data with 201Tl tracer. Results indicated that these fast methods can reconstruct, with fully 3D compensation, images very similar to those obtained using standard RBSC methods, and in reconstruction times that are an order of magnitude shorter. Using these methods, fully 3D iterative reconstruction with RBSC can be performed well within the realm of clinically realistic times (under 10 minutes for 64 x 64 x 24 image reconstruction).

Since scattered photons carry degraded spatial information, scatter is typically considered a source of contamination in SPECT. However, with the advent of scatter modelling methods and reconstruction-based scatter compensation (RBSC), it may be possible to utilize scattered data in a productive manner. In this work we analyse the reconstructibility of scattered photon projection data and investigate the potential for using scattered photons to reduce the noise levels of SPECT images. We have simulated projection data for an elliptical phantom containing three cold rods in a uniform background of 99mTc activity. A variety of photopeak and scatter energy windows were formed, as well as corresponding RBSC transfer matrices. Each statistically weighted matrix was decomposed using SVD and analysed in terms of reconstructibility and noise properties. Results indicate that scattered photons contain sufficient information to reconstruct the source activity, but the scatter-only matrices are very poorly conditioned. We have also evaluated several methods of utilizing scattered events via RBSC, and compared them with other, idealized methods of handling scatter. It was found that scattered photons can be used productively when photopeak and non-photopeak data are separated through the use of multiple energy windows. The RBSC methods outperformed ideal scatter subtraction, but fell short of methods which assume perfect discrimination between scattered and primary events. The knowledge gained by this study may help guide future research and lead to better approaches to handling scatter in SPECT.

Effects of different scatter compensation methods incorporated in fully 3D iterative reconstruction are investigated. The methods are: (i) the inclusion of an 'ideal scatter estimate' (ISE); (ii) like (i) but with a noiseless scatter estimate (ISE-NF); (iii) incorporation of scatter in the point spread function during iterative reconstruction ('ideal scatter model', ISM); (iv) no scatter compensation (NSC); (v) ideal scatter rejection (ISR), as can be approximated by using a camera with a perfect energy resolution. The iterative method used was an ordered subset expectation maximization (OS-EM) algorithm. A cylinder containing small cold spheres was used to calculate contrast-to-noise curves. For a brain study, global errors between reconstruction and 'true' distributions were calculated. Results show that ISR is superior to all other methods. In all cases considered, ISM is superior to ISE and performs approximately as well as (brain study) or better than (cylinder data) ISE-NF. Both ISM and ISE improve contrast-to-noise curves and reduce global errors, compared with NSC. In the case of ISE, blurring of the scatter estimate with a Gaussian kernel results in slightly reduced errors in brain studies, especially at low count levels. The optimal Gaussian kernel size is strongly dependent on the noise level.