SPECT Imaging of Muscle Injury with [99mTc]MDP in a Mouse Model of Muscular Dystrophy.

PURPOSE: Tc-99m methylene diphosphonate ([99mTc]MDP) is an in vivo bone imaging agent that also accumulates in injured skeletal muscle cells. The objective of this study was to investigate if [99mTc]MDP could be used to detect muscle injury in the mdx mouse model of Duchenne muscular dystrophy (DMD). PROCEDURES: Static whole-body single-photon emission computed tomography/computed tomography (CT) scans were acquired at 2 h post-injection of [99mTc]MDP in two cohorts of animals at different sites: one cohort of mice at 6, 15, and 19 weeks of age, and a separate cohort at 16 weeks. The second cohort was also imaged with high-resolution CT at 8 weeks. RESULTS: mdx mice had higher [99mTc]MDP uptake and significantly higher [99mTc]MDP concentrations in muscle than controls. CONCLUSIONS: Higher uptake of [99mTc]MDP in muscle of mdx mice agrees with histological reports of muscle calcification in mdx mice, and suggests the potential translational use of [99mTc]MDP imaging for tracking DMD progression and therapeutic response.

The Expansion of Heterotopic Bone in Fibrodysplasia Ossificans Progressiva Is Activin A-Dependent.

Fibrodysplasia ossificans progressiva (FOP) is a rare autosomal dominant disorder that is characterized by episodic yet cumulative heterotopic ossification (HO) in skeletal muscles, tendons, and ligaments over a patient's lifetime. FOP is caused by missense mutations in the type I bone morphogenetic protein (BMP) receptor ACVR1. We have determined that the formation of heterotopic bone in FOP requires activation of mutant ACVR1 by Activin A, in part by showing that prophylactic inhibition of Activin A blocks HO in a mouse model of FOP. Here we piece together a natural history of developing HO lesions in mouse FOP, and determine where in the continuum of HO Activin A is required, using imaging (T2-MRI, µCT, 18 F-NaF PET/CT, histology) coupled with pharmacologic inhibition of Activin A at different times during the progression of HO. First, we show that expansion of HO lesions comes about through growth and fusion of independent HO events. These events tend to arise within a neighborhood of existing lesions, indicating that already formed HO likely triggers the formation of new events. The process of heterotopic bone expansion appears to be dependent on Activin A because inhibition of this ligand suppresses the growth of nascent HO lesions and stops the emergence of new HO events. Therefore, our results reveal that Activin A is required at least up to the point when nascent HO lesions mineralize and further demonstrate the therapeutic utility of Activin A inhibition in FOP. These results provide evidence for a model where HO is triggered by inflammation but becomes "self-propagating" by a process that requires Activin A. © 2017 The Authors. Journal of Bone and Mineral Research Published by Wiley Periodicals Inc.

The Influence of Photon Attenuation on Tumor-to-Background and Signal-to-Noise Ratios for SPECT Imaging.

Expanding on the work of Nuyts et. al [1], Bai et. al. [2], and Bai and Shao [3], who all studied the effects of attenuation and attenuation correction on tumor-to-background ratios and signal detection, we have derived a general expression for the tumor-to-background ratio (TBR) for SPECT attenuated data that have been reconstructed with a linear, non-iterative reconstruction operator O. A special case of this is when O represents discrete filtered back-projection (FBP). The TBR of the reconstructed, uncorrected attenuated data (TBR(no-AC)) can be written as a weighted sum of the TBR of the FBP-reconstructed unattenuated data (TBR(FBP)) and the TBR of the FBP-reconstructed "difference" projection data (TBR(diff)). We evaluated the expression for TBR(no-AC) for a variety of objects and attenuation conditions. The ideal observer signal-to-noise ratio (SNR(ideal)) was also computed in projection space, in order to obtain an upper bound on signal detectability for a signal-known-exactly/background-known-exactly (SKE/BKE) detection task. The results generally show that SNR(ideal) is lower for tumors located deeper within the attenuating medium and increases for tumors nearer the edge of the object. In addition, larger values for the uniform attenuation coefficient µ lead to lower values for SNR(ideal). The TBR for FBP-reconstructed, uncorrected attenuated data can both under- and over-estimate the true TBR, depending on several properties of the attenuating medium, including the shape of the attenuator, the uniformity of the attenuator, and the degree to which the data are attenuated.

Reconstruction of 2D PET data with Monte Carlo generated system matrix for generalized natural pixels.

In discrete detector PET, natural pixels are image basis functions calculated from the response of detector pairs. By using reconstruction with natural pixel basis functions, the discretization of the object into a predefined grid can be avoided. Here, we propose to use generalized natural pixel reconstruction. Using this approach, the basis functions are not the detector sensitivity functions as in the natural pixel case but uniform parallel strips. The backprojection of the strip coefficients results in the reconstructed image. This paper proposes an easy and efficient way to generate the matrix M directly by Monte Carlo simulation. Elements of the generalized natural pixel system matrix are formed by calculating the intersection of a parallel strip with the detector sensitivity function. These generalized natural pixels are easier to use than conventional natural pixels because the final step from solution to a square pixel representation is done by simple backprojection. Due to rotational symmetry in the PET scanner, the matrix M is block circulant and only the first blockrow needs to be stored. Data were generated using a fast Monte Carlo simulator using ray tracing. The proposed method was compared to a listmode MLEM algorithm, which used ray tracing for doing forward and backprojection. Comparison of the algorithms with different phantoms showed that an improved resolution can be obtained using generalized natural pixel reconstruction with accurate system modelling. In addition, it was noted that for the same resolution a lower noise level is present in this reconstruction. A numerical observer study showed the proposed method exhibited increased performance as compared to a standard listmode EM algorithm. In another study, more realistic data were generated using the GATE Monte Carlo simulator. For these data, a more uniform contrast recovery and a better contrast-to-noise performance were observed. It was observed that major improvements in contrast recovery were obtained with MLEM when the correct system matrix was used instead of simple ray tracing. The correct modelling was the major cause of improved contrast for the same background noise. Less important factors were the choice of the algorithm (MLEM performed better than ART) and the basis functions (generalized natural pixels gave better results than pixels).

Noise characterization of block-iterative reconstruction algorithms: II. Monte Carlo simulations.

In Soares et al. (2000), the ensemble statistical properties of the rescaled block-iterative expectation-maximization (RBI-EM) reconstruction algorithm and rescaled block-iterative simultaneous multiplicative algebraic reconstruction technique (RBI-SMART) were derived. Included in this analysis were the special cases of RBI-EM, maximum-likelihood EM (ML-EM) and ordered-subset EM (OS-EM), and the special case of RBI-SMART, SMART. Explicit expressions were found for the ensemble mean, covariance matrix, and probability density function of RBI reconstructed images, as a function of iteration number. The theoretical formulations relied on one approximation, namely that the noise in the reconstructed image was small compared to the mean image. In this paper, we evaluate the predictions of the theory by using Monte Carlo methods to calculate the sample statistical properties of each algorithm and then compare the results with the theoretical formulations. In addition, the validity of the approximation will be justified.

Characterization of tomographic sampling in hybrid PET using the Fourier crosstalk matrix.

Hybrid positron emission tomography (PET) cameras can be used to measure the distribution of positron emitting radionuclides. An important system parameter for Hybrid PET is the appropriate tomographic sampling requirements. In this paper, a previously developed theoretical formulation for quantifying sampling in continuous-to-discrete tomographic systems, termed the "crosstalk matrix," is used to provide information on the recoverability of the Fourier coefficients that represent the continuous object. In addition, the crosstalk matrix can be related to image quality assessment. Here, we use the crosstalk matrix to evaluate tomographic sampling for Hybrid PET systems. Dual-and triple-head systems were compared, with emphasis placed on studying how system performance changes as the number of gantry stops is increased, and as the line-of-response acceptance angle is reduced. Examination of the crosstalk matrix, as well as figures-of-merit measuring task performance that are computed using the crosstalk matrix, show that increasing angular sampling improves Fourier coefficient recoverability and reduces aliasing.