A novel approach for direct reconstruction of parametric images for myocardial blood flow from PET imaging. Issue 10 (12th September 2013)

• Record Type: Journal Article
• Authors: Su, Kuan‐Hao; Yen, Tzu‐Chen; Fang, Yu‐Hua Dean
• Is Part Of: Medical physics. Volume 40:Issue 10(2013)
• Page Start: n/a
• Page End: n/a
• Publication Date: 2013-09-12
• Subjects: Positron emission tomography (PET) -- Fluid mechanics and rheology -- Hemodynamics; haemodynamics -- haemorheology -- image reconstruction -- medical image processing -- noise -- positron emission tomography; direct reconstruction -- parametric image; Biological material, e.g. blood, urine; Haemocytometers -- Digital computing or data processing equipment or methods, specially adapted for specific applications -- Image data processing or generation, in general -- Scintigraphy -- Measuring half‐life of a radioactive substance; Medical imaging -- Image reconstruction -- Medical image noise -- Medical image reconstruction -- Optimization -- Positron emission tomography -- Flow visualization -- Iteration theory -- Computed tomography -- Haemodynamics; Medical physics -- Periodicals; Medical physics; Geneeskunde; Natuurkunde; Toepassingen; Biophysics; Periodicals; Periodicals; Electronic journals; 610.153
• DOI: 10.1118/1.4819822
• Languages: English
• ISSNs: 0094-2405

Abstract

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 myocardial blood flow shows a high potential for improving the parametric image quality for clinical use.