Correction of quantification errors in pelvic and spinal lesions caused by ignoring higher photon attenuation of bone in [18F]NaF PET/MR

Georg Schramm, Jens Maus, Frank Hofheinz, Jan Petr, Alexandr Lougovski, Bettina Beuthien-Baumann, Liane Oehme, Ivan Platzek, Jörg van den Hoff
Medical Physics 2015, 42 (11): 6468-76

PURPOSE: MR-based attenuation correction (MRAC) in routine clinical whole-body positron emission tomography and magnetic resonance imaging (PET/MRI) is based on tissue type segmentation. Due to lack of MR signal in cortical bone and the varying signal of spongeous bone, standard whole-body segmentation-based MRAC ignores the higher attenuation of bone compared to the one of soft tissue (MRACnobone). The authors aim to quantify and reduce the bias introduced by MRACnobone in the standard uptake value (SUV) of spinal and pelvic lesions in 20 PET/MRI examinations with [18F]NaF.

METHODS: The authors reconstructed 20 PET/MR [18F]NaF patient data sets acquired with a Philips Ingenuity TF PET/MRI. The PET raw data were reconstructed with two different attenuation images. First, the authors used the vendor-provided MRAC algorithm that ignores the higher attenuation of bone to reconstruct PETnobone. Second, the authors used a threshold-based algorithm developed in their group to automatically segment bone structures in the [18F]NaF PET images. Subsequently, an attenuation coefficient of 0.11 cm(-1) was assigned to the segmented bone regions in the MRI-based attenuation image (MRACbone) which was used to reconstruct PETbone. The automatic bone segmentation algorithm was validated in six PET/CT [18F]NaF examinations. Relative SUVmean and SUVmax differences between PETbone and PETnobone of 8 pelvic and 41 spinal lesions, and of other regions such as lung, liver, and bladder, were calculated. By varying the assigned bone attenuation coefficient from 0.11 to 0.13 cm(-1), the authors investigated its influence on the reconstructed SUVs of the lesions.

RESULTS: The comparison of [18F]NaF-based and CT-based bone segmentation in the six PET/CT patients showed a Dice similarity of 0.7 with a true positive rate of 0.72 and a false discovery rate of 0.33. The [18F]NaF-based bone segmentation worked well in the pelvis and spine. However, it showed artifacts in the skull and in the extremities. The analysis of the 20 [18F]NaF PET/MRI examinations revealed relative SUVmax differences between PETnobone and PETbone of (-8.8%±2.7%, p=0.01) and (-8.1%±1.9%, p=2.4×10(-8)) in pelvic and spinal lesions, respectively. A maximum SUVmax underestimation of -13.7% was found in lesion in the third cervical spine. The averaged SUVmean differences in volumes of interests in lung, liver, and bladder were below 3%. The average SUVmax differences in pelvic and spinal lesions increased from -9% to -18% and -8% to -17%, respectively, when increasing the assigned bone attenuation coefficient from 0.11 to 0.13 cm(-1).

CONCLUSIONS: The developed automatic [18F]NaF PET-based bone segmentation allows to include higher bone attenuation in whole-body MRAC and thus improves quantification accuracy for pelvic and spinal lesions in [18F]NaF PET/MRI examinations. In nonbone structures (e.g., lung, liver, and bladder), MRACnobone yields clinically acceptable accuracy.

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