9 March 2017 MLAA-based RF surface coil attenuation estimation in hybrid PET/MR imaging
Author Affiliations +
Attenuation correction (AC) for both patient and hardware attenuation of the 511 keV annihilation photons is required for accurate PET quantification. In hybrid PET/MR imaging, AC for stationary hardware components such as patient table and MR head coil is performed using CT{derived attenuation templates. AC for flexible hardware components such as MR radiofrequency (RF) surface coils is more challenging. Registration{based approaches, aligning scaled CT{derived attenuation templates with the current patient position, have been proposed but are not used in clinical routine. Ignoring RF coil attenuation has been shown to result in regional activity underestimation values of up to 18 %. We propose to employ a modified version of the maximum{ likelihood reconstruction of attenuation and activity (MLAA) algorithm to obtain an estimate of the RF coil attenuation. Starting with an initial attenuation map not including the RF coil, the attenuation update of MLAA is applied outside the body outline only, allowing to estimate RF coil attenuation without changing the patient attenuation map. Hence, the proposed method is referred to as external MLAA (xMLAA). In this work, xMLAA for RF surface coil attenuation estimation is investigated using phantom and patient data acquired with a Siemens Biograph mMR. For the phantom data, average activity errors compared to the ground truth was reduced from -8:1% to +0:8% when using the proposed method. Patient data revealed an average activity underestimation of -6:1% for the abdominal region and -5:3% for the thoracic region when ignoring RF coil attenuation.
Conference Presentation
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Thorsten Heußer, Thorsten Heußer, Christopher M. Rank, Christopher M. Rank, Martin T. Freitag, Martin T. Freitag, Marc Kachelrieß, Marc Kachelrieß, } "MLAA-based RF surface coil attenuation estimation in hybrid PET/MR imaging", Proc. SPIE 10132, Medical Imaging 2017: Physics of Medical Imaging, 101321F (9 March 2017); doi: 10.1117/12.2255658; https://doi.org/10.1117/12.2255658

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