Abstract
Objective
Hybrid PET/MRI presents many advantages in comparison with its counterpart PET/CT in terms of improved soft-tissue contrast, decrease in radiation exposure, and truly simultaneous and multi-parametric imaging capabilities. However, the lack of well-established methodology for MR-based attenuation correction is hampering further development and wider acceptance of this technology. We assess the impact of ignoring bone attenuation and using different tissue classes for generation of the attenuation map on the accuracy of attenuation correction of PET data.
Methods
This work was performed using simulation studies based on the XCAT phantom and clinical input data. For the latter, PET and CT images of patients were used as input for the analytic simulation model using realistic activity distributions where CT-based attenuation correction was utilized as reference for comparison. For both phantom and clinical studies, the reference attenuation map was classified into various numbers of tissue classes to produce three (air, soft tissue and lung), four (air, lungs, soft tissue and cortical bones) and five (air, lungs, soft tissue, cortical bones and spongeous bones) class attenuation maps.
Results
The phantom studies demonstrated that ignoring bone increases the relative error by up to 6.8 % in the body and up to 31.0 % for bony regions. Likewise, the simulated clinical studies showed that the mean relative error reached 15 % for lesions located in the body and 30.7 % for lesions located in bones, when neglecting bones. These results demonstrate an underestimation of about 30 % of tracer uptake when neglecting bone, which in turn imposes substantial loss of quantitative accuracy for PET images produced by hybrid PET/MRI systems.
Conclusion
Considering bones in the attenuation map will considerably improve the accuracy of MR-guided attenuation correction in hybrid PET/MR to enable quantitative PET imaging on hybrid PET/MR technologies.
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References
Schmidt GP, Schmid R, Hahn K, Reiser MF. Whole-body MRI and PET/CT in tumor diagnosis. Der Radiologe. 2004;44:1079–87.
Seemann MD, Meisetschlaeger G, Gaa J, Rummeny EJ. Assessment of the extent of metastases of gastrointestinal carcinoid tumors using whole-body PET, CT, MRI, PET/CT and PET/MRI. Eur J Med Res. 2006;11:58–65.
Antoch G, Vogt FM, Freudenberg LS, Nazaradeh F, Goehde SC, Barkhausen J, et al. Whole-body dual-modality PET/CT and whole-body MRI for tumor staging in oncology. JAMA. 2003;290:3199–206.
Antoch G, Bockisch A. Combined PET/MRI: a new dimension in whole-body oncology imaging? Eur J Nuc Med Mol Imaging. 2009;36(Suppl 1):S113–20.
Heiss W-D. The potential of PET/MR for brain imaging. Eur J Nuc Med Mol Imaging. 2009;36(Suppl 1):S105–12.
Zaidi H, Del Guerra A. An outlook on future design of hybrid PET/MRI systems. Med Phys. 2011;38:5667.
Kinahan PE, Hasegawa BH, Beyer T. X-ray-based attenuation correction for positron emission tomography/computed tomography scanners. Semin Nucl Med. 2003;33:166–79.
Ay MR, Shirmohammad M, Sarkar S, Rahmim A, Zaidi H. Comparative assessment of energy-mapping approaches in CT-based attenuation correction for PET. Mol Imaging Biol. 2011;13:187–98.
Zaidi H. Is MRI-guided attenuation correction a viable option for dual-modality PET/MR imaging? Radiology. 2007;244:639–42.
Hofmann M, Pichler B, Schölkopf B, Beyer T. Towards quantitative PET/MRI: a review of MR-based attenuation correction techniques. Eur J Nuc Med Mol Imaging. 2009;36(Suppl 1):S93–104.
Schulz V, Torres-Espallardo I, Renisch S, Hu Z, Ojha N, Börnert P, et al. Automatic, three-segment, MR-based attenuation correction for whole-body PET/MR data. Eur J Nucl Med Mol Imaging. 2011;38:138–52.
Zaidi H, Ojha N, Morich M, Griesmer J, Hu Z, Maniawski P, et al. Design and performance evaluation of a whole-body Ingenuity TF PET-MRI system. Phys Med Biol. 2011;56:3091–106.
Martinez-Moller A, Souvatzoglou M, Delso G, Bundschuh RA, Chefd’hotel C, Ziegler SI, et al. Tissue classification as a potential approach for attenuation correction in whole-body PET/MRI: evaluation with PET/CT data. J Nucl Med. 2009;50:520–6.
Keereman V, Fierens Y, Broux T, De Deene Y, Lonneux M, Vandenberghe S. MRI-based attenuation correction for PET/MRI using ultrashort echo time sequences. J Nucl Med. 2010;51:812–8.
Catana C, van der Kouwe A, Benner T, Michel CJ, Hamm M, Fenchel M, et al. Toward implementing an MRI-based PET attenuation-correction method for neurologic studies on the MR-PET brain prototype. J Nucl Med. 2010;51:1431–8.
Berker Y, Franke J, Salomon A, Palmowski M, Donker HC, Temur Y, et al. MRI-based attenuation correction for hybrid PET/MRI systems: A 4-class tissue segmentation technique using a combined Ultrashort-Echo-Time/Dixon MRI sequence. J Nucl Med. 2012;53:796–804.
Johansson A, Karlsson M, Nyholm T. CT substitute derived from MRI sequences with ultrashort echo time. Med Phys. 2011;38:2708–14.
Kinahan PE, Townsend DW, Beyer T, Sashin D. Attenuation correction for a combined 3D PET/CT scanner. Med Phys. 1998;25:2046–53.
Visvikis D, Costa DC, Croasdale I, Lonn AH, Bomanji J, Gacinovic S, et al. CT-based attenuation correction in the calculation of semi-quantitative indices of [18F]FDG uptake in PET. Eur J Nucl Med Mol Imaging. 2003;30:344–53.
Hu Z, Ojha N, Renisch S, Schulz V, Torres I, Pal D, et al. MR-based attenuation correction for a whole-body sequential PET/MR system. In: M11-6, editor. IEEE nuclear science symposium and medical imaging conference. 25–31 October 2009, Orlando (FL), USA: IEEE, 2009, pp. 3508–12.
Zaidi H, Montandon M-L, Slosman DO. Magnetic resonance imaging-guided attenuation and scatter corrections in three-dimensional brain positron emission tomography. Med Phys. 2003;30:937–48.
Keereman V, Holen RV, Mollet P, Vandenberghe S. The effect of errors in segmented attenuation maps on PET quantification. Med Phys. 2011;38:6010–9.
Segars WP, Mahesh M, Beck TJ, Frey EC, Tsui BMW. Realistic CT simulation using the 4D XCAT phantom. Med Phys. 2008;35:3800–8.
Segars WP, Sturgeon G, Mendonca S, Grimes J, Tsui BM. 4D XCAT phantom for multimodality imaging research. Med Phys. 2010;37:4902–15.
Raylman RR, Kison PV, Wahl RL. Capabilities of two- and three-dimensional FDG-PET for detecting small lesions and lymph nodes in the upper torso: a dynamic phantom study. Eur J Nucl Med. 1999;26:39–45.
Zasadny KR, Wahl RL. Standardized uptake values of normal tissues at PET with 2-[fluorine-18]-fluoro-2-deoxy-d-glucose: variations with body weight and a method for correction. Radiology. 1993;189:847–50.
Thie JA. Understanding the standardized uptake value, its methods, and implications for usage. J Nucl Med. 2004;45:1431–4.
Valk PE, Delbeke D, Bailey DL, editors. Positron Emission Tomography: Clinical Practice. Chapter 5 ed. London: Springer; 2006
Thielemans K, Tsoumpas C, Mustafovic S, Beisel T, Aguiar P, Dikaios N, et al. STIR: software for tomographic image reconstruction release 2. Phys Med Biol. 2012;57:867–83.
Carney JP, Townsend DW, Rappoport V, Bendriem B. Method for transforming CT images for attenuation correction in PET/CT imaging. Med Phys. 2006;33:976–83.
Yoo TS, Ackerman MJ, Lorensen WE, Schroeder W, Chalana V, Aylward S, et al. Engineering and algorithm design for an image processing Api: a technical report on ITK-the Insight Toolkit. Stud Health Technol Inform. 2002;85:586–92.
Nahmias C, Wahl LM. Reproducibility of standardized uptake value measurements determined by 18F-FDG PET in malignant tumors. J Nucl Med. 2008;49:1804–8.
Hofmann M, Bezrukov I, Mantlik F, Aschoff P, Steinke F, Beyer T, et al. MRI-based attenuation correction for whole-body PET/MRI: quantitative evaluation of segmentation- and Atlas-based methods. J Nucl Med. 2011;52:1392–9.
Samarin A, Burger C, Wollenweber SD, Crook DW, Burger IA, Schmid DT, et al. PET/MR imaging of bone lesions—implications for PET quantification from imperfect attenuation correction. Eur J Nucl Med Mol Imaging. 2012;39:1154–60.
Akbarzadeh A, Ay MR, Ahmadian A, Riahi Alam N, Zaidi H. Impact of using different tissue classes on the accuracy of MR-based attenuation correction in PET-MRI. IEEE Nuclear Science Symposium and Medical Imaging Conference (NSS/MIC), 2011, pp. 2524–30.
Kim SK, Allen-Auerbach M, Goldin J, Fueger BJ, Dahlbom M, Brown M, et al. Accuracy of PET/CT in characterization of solitary pulmonary lesions. J Nucl Med. 2007;48:214–20.
Murakami R, Uozumi H, Hirai T, Nishimura R, Shiraishi S, Ota K, et al. Impact of FDG-PET/CT imaging on nodal staging for head-and-neck squamous cell carcinoma. Int J Radiat Oncol Biol Phys. 2007;68:377–82.
Hubner KF, Buonocore E, Gould HR, Thie J, Smith GT, Stephens S, et al. Differentiating benign from malignant lung lesions using “quantitative” parameters of FDG PET images. Clin Nucl Med. 1996;21:941–9.
Nguyen NC, Kaushik A, Wolverson MK, Osman MM. Is there a common SUV threshold in oncological FDG PET/CT, at least for some common indications? A retrospective study. Acta Oncol. 2011;50:670–7.
Ay M, Zaidi H. Computed Tomography-based attenuation correction in neurological positron emission tomography: evaluation of the effect of X-ray tube voltage on quantitative analysis. Nucl Med Commun. 2006;27:339–46.
Ay M, Zaidi H. Assessment of errors caused by x-ray scatter and use of contrast medium when using CT-based attenuation correction in PET. Eur J Nucl Med Mol Imaging. 2006;33:1301–13.
Teimourian B, Ay MR, Zafarghandi MS, Ghafarian P, Ghadiri H, Zaidi H. A novel energy mapping approach for CT-based attenuation correction in PET. Med Phys. 2012;39:2078–89.
Acknowledgments
This work was supported by Tehran University of Medical Sciences under Grant No. 10934, the Swiss National Science Foundation under grants SNSF 31003A-135576, 33CM30-124114, and Geneva Cancer League. The authors are indebted to Dr. Paul Segars for providing the XCAT phantom.
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Akbarzadeh, A., Ay, M.R., Ahmadian, A. et al. MRI-guided attenuation correction in whole-body PET/MR: assessment of the effect of bone attenuation. Ann Nucl Med 27, 152–162 (2013). https://doi.org/10.1007/s12149-012-0667-3
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DOI: https://doi.org/10.1007/s12149-012-0667-3