A blind deconvolution method incorporated with anatomical-based filtering for partial volume correction: Validations with 123I-mIBG cardiac SPECT/CT

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Abstract

Purpose:

Segmentation of contrast-enhanced CT and measurement of SPECT point spread function (PSF) are usually required for conventional partial volume correction (PVC). This study was to develop a segmentation-free method with blind deconvolution (BD) and anatomical-based filtering for SPECT PVC.

Methods:

The proposed method was implemented using an iterative BD algorithm to estimate the restored image and the PSF simultaneously. An anatomical-based filtering was implemented at each iteration to reduce Gibbs artifact and suppress noise amplification in the deconvolution process. The proposed method was validated with 123I-metaiodobenzylguanidine (123I-mIBG) SPECT/CT imaging of NCAT phantoms with and without myocardial perfusion defect and a physical cardiac phantom. Fifteen heart-to-mediastinum ratios (HMRs) were configured in the NCAT and physical phantoms. Correlations between SPECT-quantified and true HMRs were calculated from images without PVC as well as from BD restored images. The proposed method was also performed on a human 123I-mIBG study.

Results:

Relative bias and standard deviation images of NCAT phantoms showed that the proposed method reduced both bias and noise. Mean relative bias in the simulated normal myocardium was markedly improved (−16.8% ± 0.4% versus −0.8% ± 0.6% for low noise level; −16.7% ± 0.7% versus −2.3% ± 0.9% for high noise level). Mean relative bias in the simulated myocardial defect was also noticeably improved (−12.7% ± 1.2% versus 1.2% ± 1.6% for low noise level; −13.5% ± 2.4% versus −0.9% ± 2.8% for high noise level). The signal to noise ratio (SNR) of the defect was improved from 2.95 ± 0.09 to 4.07 ± 0.16 for low noise level (38% increase of mean), and from 2.56 ± 0.15 to 3.62 ± 0.22 for high noise level (41% increase of mean). For both NCAT and physical phantoms, HMRs calculated from images without PVC were underestimated (correlations between SPECT-quantified and true HMRs: y = 0.81x + 0.1 for NCAT phantom; y = 0.82x + 0.14 for physical phantom). HMRs from BD restored images were markedly improved (correlations between SPECT-quantified and true HMRs: y = x + 0.05 for NCAT phantom; y = 0.97x − 0.12 for physical phantom). After applying the proposed PVC method, the estimation error between the SPECT-quantified and true HMRs was significantly reduced from −0.75 ± 0.57 to 0.04 ± 0.17 for NCAT phantom (P = 8e-05), and from −0.68 ± 0.67 to −0.26 ± 0.42 for physical phantom (P = 0.005). The human study demonstrated that the HMR increased by 8% with PVC.

Conclusions:

The proposed segmentation-free PVC method has the potential of improving SPECT quantification accuracy and reducing noise without the need for premeasuring the image PSF.

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