Improved clinical workflow for simultaneous whole-body PET/MRI using high-resolution CAIPIRINHA-accelerated MR-based attenuation correction.

PURPOSE

To explore the value and reproducibility of a novel magnetic resonance based attenuation correction (MRAC) using a CAIPIRINHA-accelerated T1-weighted Dixon 3D-VIBE sequence for whole-body PET/MRI compared to the clinical standard.

METHODS

The PET raw data of 19 patients from clinical routine were reconstructed with standard MRAC (MRAC) and the novel MRAC (MRAC), a prototype CAIPIRINHA accelerated Dixon 3D-VIBE sequence, both acquired in 19 s/bed position. Volume of interests (VOIs) for liver, lung and all voxels of the total image stack were created to calculate standardized uptake values (SUV) followed by inter-method agreement (Passing-Bablok regression, Bland-Altman analysis). A voxel-wise SUV comparison per patient was performed for intra-individual correlation between MRAC and MRAC. Difference images (MRAC-MRAC) of attenuation maps and SUV images were calculated. The image quality of in/opposed-phase water and fat images obtained from MRAC was assessed by two readers on a 5-point Likert-scale including intra-class coefficients for inter-reader agreement.

RESULTS

SUV correlations of VOIs demonstrated high linearity (0.95<Spearman's rho<1, p<0.0001, respectively), substantiated by voxel-wise SUV scatter-plots (1.79×10 pixels). Outliers could be explained by different physiological conditions between the scans such as different segmentation of air-containing tissue, lungs, kidneys, metal implants, diaphragm edge or small air bubbles in the gastrointestinal tracts that moved between MRAC acquisitions. Nasal sinuses and the trachea were better segmented in MRAC. High-resolution T1w Dixon 3D VIBE images were acquired in all cases and could be used for PET/MRI fusion. MRAC images were of high diagnostic quality (4.2±0.8) with 0.92-0.96 intra-class correlation.

CONCLUSIONS

The novel prototype MRAC extends the value for attenuation correction by providing a high spatial resolution DIXON-based dataset suited for diagnostic assessment towards time-efficient whole-body PET/MRI.