Improved PET/MRI attenuation correction in the pelvic region using a statistical decomposition method on T2-weighted images.

BACKGROUND

Attenuation correction of PET/MRI is a remaining problem for whole-body PET/MRI. The statistical decomposition algorithm (SDA) is a probabilistic atlas-based method that calculates synthetic CTs from T2-weighted MRI scans. In this study, we evaluated the application of SDA for attenuation correction of PET images in the pelvic region.

MATERIALS AND METHOD

Twelve patients were retrospectively selected from an ongoing prostate cancer research study. The patients had same-day scans of [11C]acetate PET/MRI and CT. The CT images were non-rigidly registered to the PET/MRI geometry, and PET images were reconstructed with attenuation correction employing CT, SDA-generated CT, and the built-in Dixon sequence-based method of the scanner. The PET images reconstructed using CT-based attenuation correction were used as ground truth.

RESULTS

The mean whole-image PET uptake error was reduced from - 5.4% for Dixon-PET to - 0.9% for SDA-PET. The prostate standardized uptake value (SUV) quantification error was significantly reduced from - 5.6% for Dixon-PET to - 2.3% for SDA-PET.

CONCLUSION

Attenuation correction with SDA improves quantification of PET/MR images in the pelvic region compared to the Dixon-based method.