Clinical Assessment of MR-Guided 3-Class and 4-Class Attenuation Correction in PET/MR

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• 作者：Hossein Arabi ; Olivier Rager ; Asma Alem ; Arthur Varoquaux…
• 关键词：PET/MRI ; PET/CT ; Attenuation correction ; SUV ; Quantification
• 刊名：Molecular Imaging and Biology
• 出版年：2015
• 出版时间：April 2015
• 年：2015
• 卷：17
• 期：2
• 页码：264-276
• 全文大小：4,260 KB
• 参考文献：1. Judenhofer, MS, Wehrl, HF, Newport, DF (2008) Simultaneous PET-MRI: a new approach for functional and morphological imaging. Nat Med 14: pp. 459-465 p://dx.doi.org/10.1038/nm1700" target="_blank" title="It opens in new window">CrossRef
  2. Zukotynski, KA, Fahey, FH, Kocak, M (2011) Evaluation of 18F-FDG PET and MRI associations in pediatric diffuse intrinsic brain stem glioma: a report from the pediatric brain tumor consortium. J Nucl Med 52: pp. 188-195 p://dx.doi.org/10.2967/jnumed.110.081463" target="_blank" title="It opens in new window">CrossRef
  3. Hirsch, FW, Sattler, B, Sorge, I (2013) PET/MR in children. Initial clinical experience in paediatric oncology using an integrated PET/MR scanner. Pediatr Radiol 43: pp. 860-875 p://dx.doi.org/10.1007/s00247-012-2570-4" target="_blank" title="It opens in new window">CrossRef
  4. Zaidi, H, Guerra, A (2011) An outlook on future design of hybrid PET/MRI systems. Med Phys 38: pp. 5667-5689 p://dx.doi.org/10.1118/1.3633909" target="_blank" title="It opens in new window">CrossRef
  5. Varoquaux, A, Rager, O, Poncet, A (2014) Detection and quantification of focal uptake in head and neck tumours: (18)F-FDG PET/MR versus PET/CT. Eur J Nucl Med Mol Imaging 41: pp. 462-475 p://dx.doi.org/10.1007/s00259-013-2580-y" target="_blank" title="It opens in new window">CrossRef
  6. Wiesmuller, M, Quick, HH, Navalpakkam, B (2013) Comparison of lesion detection and quantitation of tracer uptake between PET from a simultaneously acquiring whole-body PET/MR hybrid scanner and PET from PET/CT. Eur J Nucl Med Mol Imaging 40: pp. 12-21 p://dx.doi.org/10.1007/s00259-012-2249-y" target="_blank" title="It opens in new window">CrossRef
  7. Becker, M, Zaidi, H (2014) Imaging in head and neck squamous cell carcinoma: the potential role of PET/MRI. Br J Radiol 87: pp. 20130677 p://dx.doi.org/10.1259/bjr.20130677" target="_blank" title="It opens in new window">CrossRef
  8. Zaidi, H (2007) Is MRI-guided attenuation correction a viable option for dual-modality PET/MR imaging?. Radiology 244: pp. 639-642 p://dx.doi.org/10.1148/radiol.2443070092" target="_blank" title="It opens in new window">CrossRef
  9. Bezrukov, I, Mantlik, F, Schmidt, H (2013) MR-based PET attenuation correction for PET/MR imaging. Semin Nucl Med 43: pp. 45-59 p://dx.doi.org/10.1053/j.semnuclmed.2012.08.002" target="_blank" title="It opens in new window">CrossRef
  10. Zaidi, H, Montandon, M-L, Slosman, DO (2003) Magnetic resonance imaging-guided attenuation and scatter corrections in three-dimensional brain positron emission tomography. Med Phys 30: pp. 937-948 p://dx.doi.org/10.1118/1.1569270" target="_blank" title="It opens in new window">CrossRef
  11. Martinez-Moller, A, Souvatzoglou, M, Delso, G (2009) Tissue classification as a potential approach for attenuation correction in whole-body PET/MRI: evaluation with PET/CT data. J Nucl Med 50: pp. 520-526 p://dx.doi.org/10.2967/jnumed.108.054726" target="_blank" title="It opens in new window">CrossRef
  12. Schulz, V, Torres-Espallardo, I, Renisch, S (2011) Automatic, three-segment, MR-based attenuation correction for whole-body PET/MR data. Eur J Nucl Med Mol Imaging 38: pp. 138-152 p://dx.doi.org/10.1007/s00259-010-1603-1" target="_blank" title="It opens in new window">CrossRef
  13. Montandon, M-L, Zaidi, H (2005) Atlas-guided non-uniform attenuation correction in cerebral 3D PET imaging. Neuroimage 25: pp. 278-286 p://dx.doi.org/10.1016/j.neuroimage.2004.11.021" target="_blank" title="It opens in new window">CrossRef
  14. Hofmann, M, Bezrukov, I, Mantlik, F (2011) MRI-based attenuation correction for whole-body PET/MRI: quantitative evaluation of segmentation- and atlas-based methods. J Nucl Med 52: pp. 1392-1399 p://dx.doi.org/10.2967/jnumed.110.078949" target="_blank" title="It opens in new window">CrossRef
  15. Catana, C, Kouwe, A, Benner, T (2010) Toward implementing an MRI-based PET attenuation-correction method for neurologic studies on the MR-PET brain prototype. J Nucl Med 51: pp. 1431-1438 p://dx.doi.org/10.2967/jnumed.109.069112" target="_blank" title="It opens in new window">CrossRef
  16. Keereman, V, Fierens, Y, Broux, T (2010) MRI-based attenuation correction for PET/MRI using ultrashort echo time sequences. J Nucl Med 51: pp. 812-818 p://dx.doi.org/10.2967/jnumed.109.065425" target="_blank" title="It opens in new window">CrossRef
  17. Berker, Y, Franke, J, Salomon, A (2012) MR
• 刊物主题：Imaging / Radiology;
• 出版者：Springer US
• ISSN：1860-2002

文摘

Purpose We compare the quantitative accuracy of magnetic resonance imaging (MRI)-based attenuation correction (AC) using the 3-class attenuation map (PET-MRAC3c) implemented on the Ingenuity TF PET/MRI and the 4-class attenuation map (PET-MRAC4c) similar to the approach used on the Siemens mMR PET/MR considering CT-based attenuation-corrected PET images (PET-CTAC) as standard of reference. Procedures Fourteen patients with malignant tumors underwent whole-body sequential 2-deoxy-2-[18F]fluoro-d-glucose (18F-FDG) positron emission tomography (PET)/X-ray computed tomography (CT) and PET/MR imaging. A 3-class attenuation map was obtained from segmentation of T1-weighted MR images followed by assignment of attenuation coefficients (air 0?cm?, lung 0.022?cm?, soft tissue 0.096?cm?), whereas a 4-class attenuation map was derived from a MR Dixon sequence (air 0?cm?, lung 0.018?cm?, fat 0.086?cm?, soft tissue 0.096?cm?). Additional adipose tissue class and inner body air cavities (e.g., sinus and abdomen) were also considered. Different attenuation coefficients were assigned to the lungs since the two techniques were implemented as they were proposed without any modification. Standardized uptake value (SUV)mean and SUVmax metrics were calculated for volumes of interest in various organs/tissues and malignant lesions. Well-established metrics were used for the analysis of SUVs estimated using both PET-MRAC techniques and PET-CTAC including relative error, Spearman rank correlation, and Bland and Altman analysis. Results PET-MRAC3c and PET-MRAC4c revealed significant underestimation of SUV for normal organs (?7.4?±-.5 and ?2.0?±-.8?%, respectively) compared to PET-CTAC. Lesions-SUV presented the same trend with larger underestimation for PET-MRAC4c (?.2?±-.1?%) compared to PET-MRAC3c (?.9?±-.0). The different attenuation coefficients assigned to the lungs with both techniques resulted in significant positive bias on PET-MRAC3c (18.6?±-5.3?%) and low negative bias on PET-MRAC4c (?.5?±-3.3?%). Both approaches yielded the largest differences in and near bony structures. Despite the large bias, there was good correlation between PET-MRAC3c (R--.97, P--.01) and PET-CTAC, and PET-MRAC4c (R--.97, P--.01) and PET-CTAC, respectively. Conclusions PET-MRAC3c resulted in significant systematic positive bias in the lungs owing to the lower attenuation coefficient used and negative bias in other regions. PET-MRAC4c slightly underestimated tracer uptake in the lungs and led to even larger negative bias than PET-MRAC3c in other body regions. The presence of artifacts in the MRAC might lead to misinterpretation of clinical studies. As such, the attenuation map needs to be checked for artifacts as part of the reading procedure to avoid misinterpretation of SUV measurements.