Medical physics · 2017
A blind deconvolution method incorporated with anatomical-based filtering for partial volume correction: Validations with 123 I-mIBG cardiac SPECT/CT.
СтатьяВалидационное исследованиеНазвание и аннотация: Перевод пока не подготовлен
Обработка статьи · этапы, ошибки и управление
Загрузка состояния…
Ошибки и ограничения
История · было → стало
Состояние обновляется каждые 5 секунд, пока блок открыт. Процент показывается только там, где известен объём работы. Пауза останавливает продолжение этапа; текущий запрос к источнику может завершиться.
Wu Jing, Liu Hui, Hashemi Zonouz Taraneh, Sandoval Veronica M, Mohy-Ud-Din Hassan, Lampert Rachel J, Sinusas Albert J, Liu Chi, Liu Yi-Hwa
Аннотация
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 123 I-metaiodobenzylguanidine (123 I-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 123 I-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.
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 123 I-metaiodobenzylguanidine (123 I-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 123 I-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.