A novel approach for direct reconstruction of parametric images for myocardial blood flow from PET imaging

Kuan Hao Su, Tzu Chen Yen, Yu-Hua Dean Fang

Research output: Contribution to journalArticle

15 Citations (Scopus)

Abstract

Purpose: The aim of this study is to develop and evaluate a novel direct reconstruction method to improve the signal-to-noise ratio (SNR) of parametric images in dynamic positron-emission tomography (PET), especially for applications in myocardial perfusion studies. Methods: Simulation studies were used to test the performance in SNR and computational efficiency for different methods. The NCAT phantom was used to generate simulated dynamic data. Noise realization was performed in the sinogram domain and repeated for 30 times with four different noise levels by varying the injection dose (ID) from standard ID to 1/8 of it. The parametric images were calculated by (1) three direct methods that compute the kinetic parameters from the sinogram and (2) an indirect method, which computes the kinetic parameter with pixel-by-pixel curve fitting in image space using weighted least-squares. The first direct reconstruction maximizes the likelihood function using trust-region-reflective (TRR) algorithm. The second approach uses tabulated parameter sets to generate precomputed time-activity curves for maximizing the likelihood functions. The third approach, as a newly proposed method, assumes separable complete data to derive the M-step for maximizing the likelihood. Results: The proposed method with the separable complete data performs similarly to the other two direct reconstruction methods in terms of the SNR, providing a 5%-10% improvement as compared to the indirect parametric reconstruction under the standard ID. The improvement of SNR becomes more obvious as the noise level increases, reaching more than 30% improvement under 1/8 ID. Advantage of the proposed method lies in the computation efficiency by shortening the time requirement to 25% of the indirect approach and 3%-6% of other direct reconstruction methods. Conclusions: With results provided from this simulation study, direct reconstruction of myocar-dial blood flow shows a high potential for improving the parametric image quality for clinical use.

Original languageEnglish
Article number102505
JournalMedical Physics
Volume40
Issue number10
DOIs
Publication statusPublished - 2013 Jan 1

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Computer-Assisted Image Processing
Positron-Emission Tomography
Signal-To-Noise Ratio
Likelihood Functions
Noise
Injections
Least-Squares Analysis
Perfusion

All Science Journal Classification (ASJC) codes

  • Biophysics
  • Radiology Nuclear Medicine and imaging

Cite this

Su, Kuan Hao ; Yen, Tzu Chen ; Fang, Yu-Hua Dean. / A novel approach for direct reconstruction of parametric images for myocardial blood flow from PET imaging. In: Medical Physics. 2013 ; Vol. 40, No. 10.
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abstract = "Purpose: The aim of this study is to develop and evaluate a novel direct reconstruction method to improve the signal-to-noise ratio (SNR) of parametric images in dynamic positron-emission tomography (PET), especially for applications in myocardial perfusion studies. Methods: Simulation studies were used to test the performance in SNR and computational efficiency for different methods. The NCAT phantom was used to generate simulated dynamic data. Noise realization was performed in the sinogram domain and repeated for 30 times with four different noise levels by varying the injection dose (ID) from standard ID to 1/8 of it. The parametric images were calculated by (1) three direct methods that compute the kinetic parameters from the sinogram and (2) an indirect method, which computes the kinetic parameter with pixel-by-pixel curve fitting in image space using weighted least-squares. The first direct reconstruction maximizes the likelihood function using trust-region-reflective (TRR) algorithm. The second approach uses tabulated parameter sets to generate precomputed time-activity curves for maximizing the likelihood functions. The third approach, as a newly proposed method, assumes separable complete data to derive the M-step for maximizing the likelihood. Results: The proposed method with the separable complete data performs similarly to the other two direct reconstruction methods in terms of the SNR, providing a 5{\%}-10{\%} improvement as compared to the indirect parametric reconstruction under the standard ID. The improvement of SNR becomes more obvious as the noise level increases, reaching more than 30{\%} improvement under 1/8 ID. Advantage of the proposed method lies in the computation efficiency by shortening the time requirement to 25{\%} of the indirect approach and 3{\%}-6{\%} of other direct reconstruction methods. Conclusions: With results provided from this simulation study, direct reconstruction of myocar-dial blood flow shows a high potential for improving the parametric image quality for clinical use.",
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A novel approach for direct reconstruction of parametric images for myocardial blood flow from PET imaging. / Su, Kuan Hao; Yen, Tzu Chen; Fang, Yu-Hua Dean.

In: Medical Physics, Vol. 40, No. 10, 102505, 01.01.2013.

Research output: Contribution to journalArticle

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