期刊
JOURNAL OF NUCLEAR MEDICINE
卷 57, 期 6, 页码 913-917出版社
SOC NUCLEAR MEDICINE INC
DOI: 10.2967/jnumed.115.164822
关键词
PET/MR; attenuation correction; amyloid imaging
资金
- Charles F. and Joanne Knight Alzheimer's Research Initiative [NIH/NIA P50 AG05681, NIH/NIA P01AG026276, NIH/NIA P01AG003991, NIH 5P30NS048056, NIH 2UL1TR000448]
- Avid Radiopharmaceuticals (Eli Lilly)
Hybrid PET and MR scanners have become a reality in recent years, with the benefits of reduced radiation exposure, reduction of imaging time, and potential advantages in quantification. Appropriate attenuation correction remains a challenge. Biases in PET activity measurements were demonstrated using the current MR based attenuation-correction technique. We aimed to investigate the impact of using a standard MR-based attenuation correction technique on the clinical and research utility of a PET/MR hybrid scanner for amyloid imaging. Methods: Florbetapir scans were obtained for 40 participants on a hybrid scanner with simultaneous MR acquisition. PET images were reconstructed using both MR and CT-derived attenuation maps. Quantitative analysis was performed for both datasets to assess the impact of MR-based attenuation correction to absolute PET activity measurements as well as target-to-reference ratio (SUVR). Clinical assessment was also performed by a nuclear medicine physician to determine amyloid status based on the criteria in the Food and Drug Administration prescribing information for florbetapir. Results: MR-based attenuation correction led to underestimation of PET activity for most parts of the brain, with a small overestimation for deep brain regions. There was also an overestimation of SUVRs with cerebellar reference. SUVR measurements obtained from the 2 attenuation correction methods were strongly correlated. Clinical assessment of amyloid status resulted in identical classification as positive or negative regardless of the attenuation-correction methods. Conclusion: MR-based attenuation correction causes biases in quantitative measurements. The biases may be accounted for by a linear model, although the spatial variation cannot be easily modeled. The quantitative differences, however, did not affect clinical assessment as positive or negative.
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