Cardiac PET / MRI acquisition presents novel clinical applications thanks to the combination of viability and metabolic imaging (PET) and functional and structural imaging (MRI). However, the resolution of PET, as well as cardiac and respiratory motion in non-gated cardiac imaging acquisition protocols, leads to a reduction in image quality and severe quantitative bias. Respiratory or cardiac motion is usually treated with gated reconstruction which results in higher noise.

Inspired by a method that has been used in brain PET, a practical correction approach, designed to overcome these existing limitations for quantitative PET imaging , was developed and applied in the context of cardiac PET / MRI. The correct method for PET data consists of computing the mean density map of each underlying moving region, as obtained with MRI, and translating them to the PET space taking into account the PET spatial and temporal resolution.

Using these tissue density maps, the method then constructs a system of linear equations that model the activity recovery and cross-contamination coefficients, which can be solved for the current activity values. Physical and numerical cardiac phantoms were employed to quantify the proposed correction. 


The full correction of the myocardium in 8 patients with acute myocardial infarction using [11 C] -acetate. Data from 10 additional patients, injected with [18 F] -FDG , were used to compare the method to the standard ECG-gated approach. The proposed method resulted in better recovery (from 32% to 95% on the simulated phantom model) and less residual activity than the standard approach.

Higher signal-to-noise and contrast-to-noise ratios than ECG-gating were also witnessed (SNR increased from 2.92 to 5.24, CNR rose from 62.9 to 145.9 when compared to 4-gate reconstruction).

Finally, the relevance of this correction using [11 C] -acetate PET patient data, for which erroneous physiological conclusions could have been made based on the uncorrected data, was established as the result of the correction to the expected clinical results. An efficient and simple method to correct for the quantitative biases in PET measurements produced by cardiac motion has been developed.

Validation experiments using phantom and patient data showed improved accuracy and reliability with this approach when compared to more straightforward strategies such as gated acquisition or optimal ROI. This article is protected by copyright. All rights reserved.