Improved Regional Activity Quantitation in Nuclear Medicine Using a New Approach to Correct for Tissue Partial Volume and Spillover Effects

Abstract

We have developed a new method of compensating for effects of partial volume and spillover in dual-modality imaging. The approach requires segmentation of just a few tissue types within a small VOI surrounding a lesion; the algorithm estimates simultaneously, from projection data, the activity concentration within each segmented tissue inside the VOI. Measured emission projections were fitted to the sum of resolution-blurred projections of each such tissue, scaled by its unknown activity concentration, plus a global background contribution obtained by reprojection through the reconstructed image volume outside the VOI. The method was evaluated using multiple-pinhole μSPECT data simulated for the MOBY mouse phantom containing two spherical lung tumors and one liver tumor, as well as using multiple-bead phantom data acquired on μSPECT and μCT scanners. Each VOI in the simulation study was 4.8 mm (12 voxels) cubed and, depending on location, contained up to four tissues (tumor, liver, heart, lung) with different values of relative 99mTc concentration. All tumor activity estimates achieved <3% bias after ~15 OSEM iterations (× 10 subsets), with better than 8% precision (≤25% greater than the Cramer-Rao lower bound). The projection-based fitting approach also outperformed three SUV-like metrics, one of which was corrected for count spillover. In the bead phantom experiment, the mean ± standard deviation of the bias of VOI estimates of bead concentration were 0.9 ± 9.5%, comparable to those of a perturbation geometric transfer matrix (pGTM) approach (-5.4 ± 8.6%); however, VOI estimates were more stable with increasing iteration number than pGTM estimates, even in the presence of substantial axial misalignment between μCT and μSPECT image volumes.

Hybrid Imaging: Instrumentation and Data Processing

“…Other post-reconstruction corrections consist of voxel-based methods, such as the popular Mueller-Gaertner method (MGM) [170], image deconvolution [171], and the "region-based voxel-wise correction" (RBV) [172]. Alternative approaches for PVC operate in sinogram space, where statistical noise is spatially uncorrelated and easier to incorporate in the PVC procedure [173][174][175][176]. Reconstruction-based methods enhance the spatial resolution by using the implicit PVC compensation through system-response modeling [177].…”

Evaluation of a method for projection-based tissue-activity estimation within small volumes of interest

“…g (k) out represents the contributions to the projections from the background outside the VOI. $${\lambda }_i=\sum _{j=1}^J{A}_j{p}_{ij}+g_{out,i}^{\left(k\right)}$$ Assuming that (1) the activity within the J compartments is uniform, (2) a high-resolution, local segmentation of the compartments can be obtained using a registered anatomical image, (3) projections of the individual compartments can be separately computed from unit-activity tissue templates, incorporating all relevant physical effects, and (4) an accurate, low-noise projection through all of the activity outside of the VOI can be obtained from a reconstructed image of the object, then the true activity concentration values A can be determined by fitting the noisy measured projection data to the model in Equation 1 (Moore et al , 2012). …”

“…For the work presented here, we have evaluated a new approach (Moore et al , 2012) to compensate for both partial-volume and spillover effects that can, potentially, be integrated into the image-analysis framework currently used in the clinic. The method requires the segmentation of tissues within a small volume approximately centered on a tumour or other lesion of primary interest.…”

“…Activity estimates for each tissue within the small volume are obtained by fitting a model to ’raw’ projection data, for which the statistical noise is known and uncorrelated. We have previously evaluated this method (Moore et al , 2012) for a multiple-pinhole microSPECT system. For the current work, the technique was applied to a simulated clinical SPECT system, and validation results from a multiple-sphere phantom are presented.…”

Noise suppressed partial volume correction for cardiac SPECT/CT

“…Other studies have also investigated approaches that only require segmentation of the target organ and a couple of adjacent organs or regions for oncology applications. 43,50,51 This type of approach could reduce the complexity and potentially increase the robustness of the proposed PVC method. However, minimum regions that need to be segmented for cardiac imaging require further investigation.…”