Noise suppressed partial volume correction for cardiac SPECT/CT

Abstract

Purpose: Partial volume correction (PVC) methods typically improve quantification at the expense of increased image noise and reduced reproducibility. In this study, the authors developed a novel voxel-based PVC method that incorporates anatomical knowledge to improve quantification while suppressing noise for cardiac SPECT/CT imaging. Methods: In the proposed method, the SPECT images were first reconstructed using anatomicalbased maximum a posteriori (AMAP) with Bowsher's prior to penalize noise while preserving boundaries. A sequential voxel-by-voxel PVC approach (Yang's method) was then applied on the AMAP reconstruction using a template response. This template response was obtained by forward projecting a template derived from a contrast-enhanced CT image, and then reconstructed using AMAP to model the partial volume effects (PVEs) introduced by both the system resolution and the smoothing applied during reconstruction. To evaluate the proposed noise suppressed PVC (NS-PVC), the authors first simulated two types of cardiac SPECT studies: a 99m Tc-tetrofosmin myocardial perfusion scan and a 99m Tc-labeled red blood cell (RBC) scan on a dedicated cardiac multiple pinhole SPECT/CT at both high and low count levels. The authors then applied the proposed method on a canine equilibrium blood pool study following injection with 99m Tc-RBCs at different count levels by rebinning the list-mode data into shorter acquisitions. The proposed method was compared to MLEM reconstruction without PVC, two conventional PVC methods, including Yang's method and multitarget correction (MTC) applied on the MLEM reconstruction, and AMAP reconstruction without PVC. Results: The results showed that the Yang's method improved quantification, however, yielded increased noise and reduced reproducibility in the regions with higher activity. MTC corrected for PVE on high count data with amplified noise, although yielded the worst performance among all the methods tested on low-count data. AMAP effectively suppressed noise and reduced the spill-in effect in the low activity regions. However it was unable to reduce the spill-out effect in high activity regions. NS-PVC yielded superior performance in terms of both quantitative assessment and visual image quality while improving reproducibility. Conclusions:The results suggest that NS-PVC may be a promising PVC algorithm for application in low-dose protocols, and in gated and dynamic cardiac studies with low counts. C 2016 American Association of Physicists in Medicine. [http://dx

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“…16,17 PVC was performed using co-registered and phase-matched SPECT, contrast-enhanced CT, and attenuation mapping. The data were applied through the iterative Yang approach with high-resolution re-sliced ROI’s of the myocardium, blood pool, lung, liver, and background, and with boundary tissue fraction thresholds.…”

Fully automatic multi-atlas segmentation of CTA for partial volume correction in cardiac SPECT/CT

“…Reconstructed SPECT images were corrected for partial volume effects (PVE) using an iterative Yang approach. While the details for this PVC correction can be found in Chan et al (2016), an overview is given here. In each PVC iteration, voxel-wise PVC was performed by scaling the reconstructed SPECT image (A) using updated PVC factor image ( F ), i.e.…”

“…λ PVC =λ· F . The PVC factor image was obtained as a ratio of the template image, T , and the reconstructed response image, T recon (Chan et al 2016). The template image T was constructed using CT as follows: (1) the above described atlas-based segmentation of contrast-enhanced CT was performed to obtain each organ ROI.…”

A robust segmentation method with triple‐factor non‐negative matrix factorization for myocardial blood flow quantification from dynamic 82Rb positron emission tomography

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