PURPOSE: The combination of positron emission tomography (PET) and magnetic resonance (MR) tomography in a single device is anticipated to be the next step following PET/CT for future molecular imaging application. Compared to CT, the main advantages of MR are versatile soft tissue contrast and its capability to acquire functional information without ionizing radiation. However, MR is not capable of measuring a physical quantity that would allow a direct derivation of the attenuation values for high-energy photons. METHODS: To overcome this problem, we propose a fully automated approach that uses a dedicated T1-weighted MR sequence in combination with a customized image processing technique to derive attenuation maps for whole-body PET. The algorithm automatically identifies the outer contour of the body and the lungs using region-growing techniques in combination with an intensity analysis for automatic threshold estimation. No user interaction is required to generate the attenuation map. RESULTS: The accuracy of the proposed MR-based attenuation correction (AC) approach was evaluated in a clinical study using whole-body PET/CT and MR images of the same patients (n = 15). The segmentation of the body and lung contour (L-R directions) was evaluated via a four-point scale in comparison to the original MR image (mean values >3.8). PET images were reconstructed using elastically registered MR-based and CT-based (segmented and non-segmented) attenuation maps. The MR-based AC showed similar behaviour as CT-based AC and similar accuracy as offered by segmented CT-based AC. Standardized uptake value (SUV) comparisons with reference to CT-based AC using predefined attenuation coefficients showed the largest difference for bone lesions (mean value ± standard variation of SUV(max): -3.0% ± 3.9% for MR; -6.5% ± 4.1% for segmented CT). A blind comparison of PET images corrected with segmented MR-based, CT-based and segmented CT-based AC afforded identical lesion detectability, but slight differences in image quality were found. CONCLUSION: Our MR-based attenuation correction method offers similar correction accuracy as offered by segmented CT. According to the specialists involved in the blind study, these differences do not affect the diagnostic value of the PET images.
PURPOSE: The combination of positron emission tomography (PET) and magnetic resonance (MR) tomography in a single device is anticipated to be the next step following PET/CT for future molecular imaging application. Compared to CT, the main advantages of MR are versatile soft tissue contrast and its capability to acquire functional information without ionizing radiation. However, MR is not capable of measuring a physical quantity that would allow a direct derivation of the attenuation values for high-energy photons. METHODS: To overcome this problem, we propose a fully automated approach that uses a dedicated T1-weighted MR sequence in combination with a customized image processing technique to derive attenuation maps for whole-body PET. The algorithm automatically identifies the outer contour of the body and the lungs using region-growing techniques in combination with an intensity analysis for automatic threshold estimation. No user interaction is required to generate the attenuation map. RESULTS: The accuracy of the proposed MR-based attenuation correction (AC) approach was evaluated in a clinical study using whole-body PET/CT and MR images of the same patients (n = 15). The segmentation of the body and lung contour (L-R directions) was evaluated via a four-point scale in comparison to the original MR image (mean values >3.8). PET images were reconstructed using elastically registered MR-based and CT-based (segmented and non-segmented) attenuation maps. The MR-based AC showed similar behaviour as CT-based AC and similar accuracy as offered by segmented CT-based AC. Standardized uptake value (SUV) comparisons with reference to CT-based AC using predefined attenuation coefficients showed the largest difference for bone lesions (mean value ± standard variation of SUV(max): -3.0% ± 3.9% for MR; -6.5% ± 4.1% for segmented CT). A blind comparison of PET images corrected with segmented MR-based, CT-based and segmented CT-based AC afforded identical lesion detectability, but slight differences in image quality were found. CONCLUSION: Our MR-based attenuation correction method offers similar correction accuracy as offered by segmented CT. According to the specialists involved in the blind study, these differences do not affect the diagnostic value of the PET images.
Authors: Thomas Beyer; Markus Weigert; Harald H Quick; Uwe Pietrzyk; Florian Vogt; Christoph Palm; Gerald Antoch; Stefan P Müller; Andreas Bockisch Journal: Eur J Nucl Med Mol Imaging Date: 2008-02-19 Impact factor: 9.236
Authors: Axel Martinez-Möller; Michael Souvatzoglou; Gaspar Delso; Ralph A Bundschuh; Christophe Chefd'hotel; Sibylle I Ziegler; Nassir Navab; Markus Schwaiger; Stephan G Nekolla Journal: J Nucl Med Date: 2009-03-16 Impact factor: 10.057
Authors: A A Kohan; J A Kolthammer; J L Vercher-Conejero; C Rubbert; S Partovi; R Jones; K A Herrmann; P Faulhaber Journal: Eur Radiol Date: 2013-06-14 Impact factor: 5.315
Authors: Michael Souvatzoglou; Matthias Eiber; Axel Martinez-Moeller; Sebastian Fürst; Konstantin Holzapfel; Tobias Maurer; Sibylle Ziegler; Stephan Nekolla; Markus Schwaiger; Ambros J Beer Journal: Eur J Nucl Med Mol Imaging Date: 2013-05-24 Impact factor: 9.236
Authors: David Izquierdo-Garcia; Stephen J Sawiak; Karin Knesaurek; Jagat Narula; Valentin Fuster; Joseph Machac; Zahi A Fayad Journal: Eur J Nucl Med Mol Imaging Date: 2014-03-21 Impact factor: 9.236
Authors: Pieter Mollet; Vincent Keereman; Jason Bini; David Izquierdo-Garcia; Zahi A Fayad; Stefaan Vandenberghe Journal: J Nucl Med Date: 2014-01-16 Impact factor: 10.057
Authors: Jeffrey M C Lau; R Laforest; H Sotoudeh; X Nie; S Sharma; J McConathy; E Novak; A Priatna; R J Gropler; P K Woodard Journal: J Nucl Cardiol Date: 2015-10-23 Impact factor: 5.952