Evaluation of a more optimal initial attenuation image estimate in TOF-MLAA for PET/MR

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Abstract

We describe an evaluation of a more optimal initial attenuation image or μ-map estimate in TOF-MLAA for PET/MR. Typically, the initial μ-map estimate used in TOF-MLAA is an image filled with the μ-value of water uniformly within the object, and an additional calibration is required during or post reconstruction to produce a quantitative μ-map since TOF PET data determine the attenuation sinogram up to a constant offset. In this work, a more optimal initial μ-value was selected to fill the object such that the forward-projection of the initial μ-map is already very close to that of the reference μ-map thus reducing/minimizing the offset during the early iterations of TOF-MLAA. Consequently, the estimated μ-map is expected to reach the reference quickly and naturally without any calibration. A more optimal initial μ-value which can be practically obtained is the average μ-value within the object (prior information from MR and patient database). The Initial Average Mu (μ)-value approach is referred to as the IAM approach, and the IAM-TOF-MLAA was evaluated using 2D simulations. The performances of other initial μ-map estimates were also compared. It was observed that the estimated μ-map reached the reference more quickly and naturally for IAM-TOF-MLAA as compared to all other cases. Furthermore, starting with the correct 'magnitude' (i.e. average μ-value) was observed to be more important than starting with the correct spatial μ-distribution in terms of reaching the reference μ-map with a low number of TOF-MLAA iterations. In addition, the estimated μ-value from IAM-TOF-MLAA was still reasonably quantitative even with a 5% error in the IAM. However, overestimation bias in estimated μ-value was observed for noisy data sets. Nevertheless, noise reduction was demonstrated to be able to decrease the bias as expected. In conclusion, the proposed IAM-TOF-MLAA can produce quantitative μ-map without any calibration when there are sufficient counts in the data, and the accuracy of the estimated IAM can be further improved.

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Cheng, J. C. K., Salomon, A., Yaqub, M., & Boellaard, R. (2016). Evaluation of a more optimal initial attenuation image estimate in TOF-MLAA for PET/MR. In 2015 IEEE Nuclear Science Symposium and Medical Imaging Conference, NSS/MIC 2015. Institute of Electrical and Electronics Engineers Inc. https://doi.org/10.1109/NSSMIC.2015.7582051

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