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

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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.




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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