New compartment model analysis of lean-mass and fat-mass growth with overfeeding

Objectives: Mathematical models of lean- and fat-mass growth with diet are useful to help describe and potentially predict the fat- and lean-mass change with different diets as a function of consumed protein and fat calories. Most of the existing models do not explicitly account for interdependence of fat-mass on the lean-mass and vice versa. The aim of this study was to develop a new compartmental model to describe the growth of lean and fat mass depending on the input of dietary protein and fat, and accounting for the interdependence of adipose tissue and muscle growth. Methods: The model was fitted to existing clinical data of an overfeeding trial for 23 participants (with a high-protein diet, a normal-protein diet, and a low-protein diet) and compared with the existing Forbes model. Results: Qualitatively and quantitatively, the compartment model data fit was smoother with less overall error than the Forbes model. The root means square error were 0.39, 0.93 and 0.72 kg for the new model, the Forbes model, and the modified Forbes model, respectively. Additionally, for the present model, the differences between some of the coefficients (on the cross dependence of fat and lean mass as well as on the intake diet dependence) across different diets were statistically significant (P \u3c 0.05). Conclusions: Our new Dey-model showed excellent fit to overfeeding data for 23 normal participants with some significant differences of model coefficients across diets, enabling further studies of the model coefficients for larger groups of participants with obesity or other diseases

Investigation of Axial and Angular Sampling in Multi-Detector Pinhole-SPECT Brain Imaging

We designed a dedicated multi-detector multi-pinhole brain SPECT scanner to generate images of higher quality compared to general-purpose systems. The system, AdaptiSPECT-C, is intended to adapt its sensitivity-resolution trade-off by varying its aperture configurations allowing both high-sensitivity dynamic and high-spatial-resolution static imaging. The current system design consists of 23 detector heads arranged in a truncated spherical geometry. In this work, we investigated the axial and angular sampling capability of the current stationary system design. Two data acquisition schemes using limited rotation of the gantry and two others using axial translation of the imaging bed were also evaluated concerning their impact on image quality through improved sampling. Increasing both angular and axial sampling in the current prototype system resulted in quantitative improvements in image quality metrics and qualitative appearance of the images as determined in studies with specifically selected phantoms. Visual improvements for the brain phantoms with clinical distributions were less pronounced but presented quantitative improvements in the fidelity (normalized root-mean-square error (NRMSE)) and striatal specific binding ratio (SBR) for a dopamine transporter (DAT) distribution, and in NRMSE and activity recovery for a brain perfusion distribution. More pronounced improvements with increased sampling were seen in contrast recovery coefficient, bias, and coefficient of variation for a lesion in the brain perfusion distribution. The negligible impact of the most cranial ring of detectors on axial sampling, but its significant impact on sensitivity and angular sampling in the cranial portion of the imaging volume-of-interest were also determined

Inclusion of quasi-vertex views in a brain-dedicated multi-pinhole SPECT system for improved imaging performance

With brain-dedicated multi-detector systems employing pinhole apertures the usage of detectors facing the top of the patient\u27s head (i.e., quasi-vertex views) can provide the advantage of additional viewing from close to the brain for improved detector coverage. In this paper, we report the results of simulation and reconstruction studies to investigate the impact of the quasi-vertex views on the imaging performance of AdaptiSPECT-C, a brain-dedicated stationary SPECT system under development. In this design, both primary and scatter photons from regions located inferior to the brain can contribute to SPECT projections acquired by the quasi-vertex views, and thus degrade AdaptiSPECT-C imaging performance. In this work, we determined the proportion, origin, and nature (i.e., primary, scatter, and multiple-scatter) of counts emitted from structures within the head and throughout the body contributing to projections from the different AdaptiSPECT-C detector rings, as well as from a true vertex view detector. We simulated phantoms used to assess different aspects of image quality (i.e., uniform sphere and Derenzo), as well as anthropomorphic phantoms with multiple count levels emulating clinical(123)I activity distributions (i.e., DaTscan and perfusion). We determined that attenuation and scatter in the patient\u27s body greatly diminish the probability of the photons emitted outside the volume of interest reaching to detectors and being recorded within the 15% photopeak energy window. In addition, we demonstrated that the inclusion of the residual of such counts in the system acquisition does not degrade visual interpretation or quantitative analysis. The addition of the quasi-vertex detectors increases volumetric sensitivity, angular sampling, and spatial resolution leading to significant enhancement in image quality, especially in the striato-thalamic and superior regions of the brain. Besides, the use of quasi-vertex detectors improves the recovery of clinically relevant metrics such as the striatal binding ratio and mean activity in selected cerebral structures

Investigation of energy weighting using an energy discriminating photon counting detector for breast CT

PURPOSE: Breast CT is an emerging imaging technique that can portray the breast in 3D and improve visualization of important diagnostic features. Early clinical studies have suggested that breast CT has sufficient spatial and contrast resolution for accurate detection of masses and microcalcifications in the breast, reducing structural overlap that is often a limiting factor in reading mammographic images. For a number of reasons, image quality in breast CT may be improved by use of an energy resolving photon counting detector. In this study, the authors investigate the improvements in image quality obtained when using energy weighting with an energy resolving photon counting detector as compared to that with a conventional energy integrating detector. METHODS: Using computer simulation, realistic CT images of multiple breast phantoms were generated. The simulation modeled a prototype breast CT system using an amorphous silicon (a-Si), CsI based energy integrating detector with different x-ray spectra, and a hypothetical, ideal CZT based photon counting detector with capability of energy discrimination. Three biological signals of interest were modeled as spherical lesions and inserted into breast phantoms; hydroxyapatite (HA) to represent microcalcification, infiltrating ductal carcinoma (IDC), and iodine enhanced infiltrating ductal carcinoma (IIDC). Signal-to-noise ratio (SNR) of these three lesions was measured from the CT reconstructions. In addition, a psychophysical study was conducted to evaluate observer performance in detecting microcalcifications embedded into a realistic anthropomorphic breast phantom. RESULTS: In the energy range tested, improvements in SNR with a photon counting detector using energy weighting was higher (than the energy integrating detector method) by 30%-63% and 4%-34%, for HA and IDC lesions and 12%-30% (with Al filtration) and 32%-38% (with Ce filtration) for the IIDC lesion, respectively. The average area under the receiver operating characteristic curve (AUC) for detection of microcalcifications was higher by greater than 19% (for the different energy weighting methods tested) as compared to the AUC obtained with an energy integrating detector. CONCLUSIONS: This study showed that breast CT with a CZT photon counting detector using energy weighting can provide improvements in pixel SNR, and detectability of microcalcifications as compared to that with a conventional energy integrating detector. Since a number of degrading physical factors were not modeled into the photon counting detector, this improvement should be considered as an upper bound on achievable performance

GPU-accelerated generic analytic simulation and image reconstruction platform for multi-pinhole SPECT systems

We introduce a generic analytic simulation and image reconstruction software platform for multi-pinhole (MPH) SPECT systems. The platform is capable of modeling common or sophisticated MPH designs as well as complex data acquisition schemes. Graphics processing unit (GPU) acceleration was utilized to make a high-performance computing software. Herein, we describe the software platform and provide verification studies of the simulation and image reconstruction software.This item from the UA Faculty Publications collection is made available by the University of Arizona with support from the University of Arizona Libraries. If you have questions, please contact us at [email protected]

Investigation of a Monte Carlo simulation and an analytic-based approach for modeling the system response for clinical I-123 brain SPECT imaging

The use of accurate system response modeling has been proven to be an essential key of SPECT image reconstruction, with its usage leading to overall improvement of image quality. The aim of this work was to investigate the imaging performance using an XCAT brain perfusion phantom of two modeling strategies, one based on analytic techniques and the other one based on GATE Monte-Carlo simulation. In addition, an efficient forced detection approach to improve the overall simulation efficiency was implemented and its performance was evaluated. We demonstrated that accurate modeling of the system matrix generated by Monte-Carlo simulation for iterative reconstruction leads to superior performance compared to analytic modeling in the case of clinical I-123 brain imaging. It was also shown that the use of the forced detection approach provided a quantitative and qualitative enhancement of the reconstruction.This item from the UA Faculty Publications collection is made available by the University of Arizona with support from the University of Arizona Libraries. If you have questions, please contact us at [email protected]

Performance analysis of a high-sensitivity multi-pinhole cardiac SPECT system with hemi-ellipsoid detectors

PURPOSE: Single-photon emission computed tomography (SPECT) is a noninvasive imaging modality, used in myocardial perfusion imaging. The challenges facing the majority of clinical SPECT systems are low sensitivity, poor resolution, and the relatively high radiation dose to the patient. New generation systems (GE Discovery, DSPECT) dedicated to cardiac imaging improve sensitivity by a factor of 5-8. This improvement can be used to decrease acquisition time and/or dose. However, in the case of ultra-low dose (~3 mCi) injections, acquisition times are still significantly long, taking 10-12 min. The purpose of this work is to investigate a new gamma camera design with 21 hemi-ellipsoid detectors each with a pinhole collimator for cardiac SPECT for further improvement in sensitivity and resolution and reduced patient exposures and imaging times. METHODS: To evaluate the resolution of our hemi-ellipsoid system, GATE Monte-Carlo simulations were performed on point-sources, rod-sources, and NCAT phantoms. For average full-width-half-maximum (FWHM) equivalence with base flat-detector, the pinhole-diameter for the curved hemi-ellipsoid detector was found to be 8.68 mm, an operating pinhole-diameter nominally expected to be ~3 times more sensitive than state-of-the-art systems. Rod-sources equally spaced within the region of interest were acquired with a 21-detector system and reconstructed with our multi-pinhole (MPH) iterative OSEM algorithm with collimator resolution recovery. The results were compared with the results of a state-of-the-art system (GE Discovery) available in the literature. The system was also evaluated using the mathematical anthropomorphic NCAT (NURBS-based Cardiac Torso; Segars et al. IEEE Trans Nucl Sci. 1999;46:503-506) phantom with a full (clinical)-dose acquisition (25 mCi) for 2 min and an ultra-low dose acquisition of 3 mCi for 5.44 min. The estimated left ventricle (LV) counts were compared with the available literature on a state-of-the-art system (DSPECT). FWHM of the LV wall on MPH-OSEM-reconstructed images with collimator resolution recovery was estimated. RESULTS: On acquired rod-sources, the average resolution (FWHM) after reconstruction with resolution recovery in the entire region of interest (ROI) for cardiac imaging was on the average 4.44 mm (+/-2.84), compared to 6.9 mm (+/-1 mm) reported for GE Discovery (Kennedy et al., J Nucl Cardiol. 2014:21:443-452). For NCAT studies, improved sensitivity allowed a full-dose (25 mCi) 2-min acquisition (Ell8.68mmFD) which yielded 3.79 M LV counts. This is ~3.35 times higher compared to 1.13 M LV counts acquired in 2 min for clinical full dose for state-of-the-art DSPECT. The increased sensitivity also allowed an ultra-low dose acquisition protocol (Ell8.68 mmULD), 3 mCi (eight times less injected dose) in 5.44 min. This ultra-low dose protocol yielded ~1.23 M LV counts which was comparable to the full-dose 2-min acquisition for DSPECT. The estimated NCAT average FWHM at the LV wall after 12 iterations of the OSEM reconstruction was 4.95 and 5.66 mm around the mid-short-axis slices for Ell8.68mmFD and Ell8.68mmULD, respectively. CONCLUSION: Our Monte-Carlo simulation studies and reconstruction suggest using (inverted wineglass sized) hemi-ellipsoid detectors with pinhole collimators can increase the sensitivity ~3.35 times over the new generation of dedicated cardiac SPECT systems, while also improving the reconstructed resolution for rod-sources with an average of 4.44 mm in region of interest. The extra sensitivity may be used for ultra-low dose imaging (3 mCi) at ~5.44 min for comparable clinical counts as state-of-the-art systems

New compartment model analysis of lean-mass and fat-mass growth with overfeeding

OBJECTIVES: Mathematical models of lean- and fat-mass growth with diet are useful to help describe and potentially predict the fat- and lean-mass change with different diets as a function of consumed protein and fat calories. Most of the existing models do not explicitly account for interdependence of fat-mass on the lean-mass and vice versa. The aim of this study was to develop a new compartmental model to describe the growth of lean and fat mass depending on the input of dietary protein and fat, and accounting for the interdependence of adipose tissue and muscle growth. METHODS: The model was fitted to existing clinical data of an overfeeding trial for 23 participants (with a high-protein diet, a normal-protein diet, and a low-protein diet) and compared with the existing Forbes model. RESULTS: Qualitatively and quantitatively, the compartment model data fit was smoother with less overall error than the Forbes model. The root means square error were 0.39, 0.93 and 0.72 kg for the new model, the Forbes model, and the modified Forbes model, respectively. Additionally, for the present model, the differences between some of the coefficients (on the cross dependence of fat and lean mass as well as on the intake diet dependence) across different diets were statistically significant (P \u3c 0.05). CONCLUSIONS: Our new Dey-model showed excellent fit to overfeeding data for 23 normal participants with some significant differences of model coefficients across diets, enabling further studies of the model coefficients for larger groups of participants with obesity or other diseases

Investigation of a Monte Carlo simulation and an analytic-based approach for modeling the system response for clinical I-123 brain SPECT imaging

The use of accurate system response modeling has been proven to be an essential key of SPECT image reconstruction, with its usage leading to overall improvement of image quality. The aim of this work was to investigate the imaging performance using an XCAT brain perfusion phantom of two modeling strategies, one based on analytic techniques and the other one based on GATE Monte-Carlo simulation. In addition, an efficient forced detection approach to improve the overall simulation efficiency was implemented and its performance was evaluated. We demonstrated that accurate modeling of the system matrix generated by Monte-Carlo simulation for iterative reconstruction leads to superior performance compared to analytic modeling in the case of clinical I-123 brain imaging. It was also shown that the use of the forced detection approach provided a quantitative and qualitative enhancement of the reconstruction.This item from the UA Faculty Publications collection is made available by the University of Arizona with support from the University of Arizona Libraries. If you have questions, please contact us at [email protected]

Primary, scatter, and penetration characterizations of parallel-hole and pinhole collimators for I-123 SPECT

Multi-pinhole (MPH) collimators are known to provide better trade-off between sensitivity and resolution for preclinical, as well as for smaller regions in clinical SPECT imaging compared to conventional collimators. In addition to this geometric advantage, MPH plates typically offer better stopping power for penetration than the conventional collimators, which is especially relevant for I-123 imaging. The I-123 emits a series of high-energy ( \u3e 300 keV, ~2.5% abundance) gamma photons in addition to the primary emission (159 keV, 83% abundance). Despite their low abundance, high-energy photons penetrate through a low-energy parallel-hole (LEHR) collimator much more readily than the 159 keV photons, resulting in large downscatter in the photopeak window. In this work, we investigate the primary, scatter, and penetration characteristics of a single pinhole collimator that is commonly used for I-123 thyroid imaging and our two MPH collimators designed for I-123 DaTscan imaging for Parkinson\u27s Disease, in comparison to three different parallel-hole collimators through a series of experiments and Monte Carlo simulations. The simulations of a point source and a digital human phantom with DaTscan activity distribution showed that our MPH collimators provide superior count performance in terms of high primary counts, low penetration, and low scatter counts compared to the parallel-hole and single pinhole collimators. For example, total scatter, multiple scatter, and collimator penetration events for the LEHR were 2.5, 7.6 and 14 times more than that of MPH within the 15% photopeak window. The total scatter fraction for LEHR was 56% where the largest contribution came from the high-energy scatter from the back compartments (31%). For the same energy window, the total scatter for MPH was 21% with only 1% scatter from the back compartments. We therefore anticipate that using MPH collimators, higher quality reconstructions can be obtained in a substantially shorter acquisition time for I-123 DaTscan and thyroid imaging