Published in:
01-10-2021 | Sarcoidosis | Original Article
Assessing the qualitative and quantitative impacts of simple two-class vs multiple tissue-class MR-based attenuation correction for cardiac PET/MR
Published in: Journal of Nuclear Cardiology | Issue 5/2021
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Background
Hybrid PET/MR imaging has significant potential in cardiology due to its combination of molecular PET imaging and cardiac MR. Multi-tissue-class MR-based attenuation correction (MRAC) is necessary for accurate PET quantification. Moreover, for thoracic PET imaging, respiration is known to lead to misalignments of MRAC and PET data that result in PET artifacts. These factors can be addressed by using multi-echo MR for tissue segmentation and motion-robust or motion-gated acquisitions. However, the combination of these strategies is not routinely available and can be prone to errors. In this study, we examine the qualitative and quantitative impacts of multi-class MRAC compared to a more widely available simple two-class MRAC for cardiac PET/MR.
Methods and Results
In a cohort of patients with cardiac sarcoidosis, we acquired MRAC data using multi-echo radial gradient-echo MR imaging. Water-fat separation was used to produce attenuation maps with up to 4 tissue classes including water-based soft tissue, fat, lung, and background air. Simultaneously acquired 18F-fluorodeoxyglucose PET data were subsequently reconstructed using each attenuation map separately. PET uptake values were measured in the myocardium and compared between different PET images. The inclusion of lung and subcutaneous fat in the MRAC maps significantly affected the quantification of 18F-fluorodeoxyglucose activity in the myocardium but only moderately altered the appearance of the PET image without introduction of image artifacts.
Conclusion
Optimal MRAC for cardiac PET/MR applications should include segmentation of all tissues in combination with compensation for the respiratory-related motion of the heart. Simple two-class MRAC is adequate for qualitative clinical assessment.