Bias Atlases for Segmentation-Based PET Attenuation Correction Using PET-CT and MR

Ouyang, Jinsong; Chun, Se Young; Petibon, Yoann; Bonab, Ali; Alpert, Nathaniel M.; Fakhri, Georges El

doi:10.1109/tns.2013.2278624

Cited by 44 publications

(58 citation statements)

References 33 publications

(41 reference statements)

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“…In one example demonstrated by Samarin et al, (32) classifying bone as soft tissue resulted in less than 6% difference for PET voxels in the heart region. Ouyang et al (33) also concluded that three‐class segmentation can be sufficient for PET quantification in the heart, as it yields less than 5% quantification difference after compensation. These studies indicate that bone segmentation may not be necessary for cardiac PET/MR.…”

Section: Discussionmentioning

confidence: 99%

Feasibility of using respiration‐averaged MR images for attenuation correction of cardiac PET/MR imaging

Pan

2015

J Applied Clin Med Phys

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Cardiac imaging is a promising application for combined PET/MR imaging. However, current MR imaging protocols for whole‐body attenuation correction can produce spatial mismatch between PET and MR‐derived attenuation data owing to a disparity between the two modalities' imaging speeds. We assessed the feasibility of using a respiration‐averaged MR (AMR) method for attenuation correction of cardiac PET data in PET/MR images. First, to demonstrate the feasibility of motion imaging with MR, we used a 3T MR system and a two‐dimensional fast spoiled gradient‐recalled echo (SPGR) sequence to obtain AMR images of a moving phantom. Then, we used the same sequence to obtain AMR images of a patient's thorax under free‐breathing conditions. MR images were converted into PET attenuation maps using a three‐class tissue segmentation method with two sets of predetermined CT numbers, one calculated from the patient‐specific (PS) CT images and the other from a reference group (RG) containing 54 patient CT datasets. The MR‐derived attenuation images were then used for attenuation correction of the cardiac PET data, which were compared to the PET data corrected with average CT (ACT) images. In the myocardium, the voxel‐by‐voxel differences and the differences in mean slice activity between the AMR‐corrected PET data and the ACT‐corrected PET data were found to be small (less than 7%). The use of AMR‐derived attenuation images in place of ACT images for attenuation correction did not affect the summed stress score. These results demonstrate the feasibility of using the proposed SPGR‐based MR imaging protocol to obtain patient AMR images and using those images for cardiac PET attenuation correction. Additional studies with more clinical data are warranted to further evaluate the method.PACS number: 87.57.uk

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Section: Discussionmentioning

confidence: 99%

Feasibility of using respiration‐averaged MR images for attenuation correction of cardiac PET/MR imaging

Pan

2015

J Applied Clin Med Phys

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“…and to assign a single value to each class. Using discretized attenuation values for μ-maps instead of a continuous attenuation image was evaluated in [28,29] and the accuracy of reconstructed images is dependent on locations. It was claimed that it is feasible to use discretized μ-maps clinically.…”

Section: Sources Of Attenuation/scatter Informationmentioning

confidence: 99%

“…It was claimed that it is feasible to use discretized μ-maps clinically. Segmentation is performed on T1-weighted or T2-weighted MR images [29,85,86] or on ultrashort echo time (UTE) sequence MR images for better imaging bones with very short T 2 values [87,88]. The other is to use atlasbased methods with machine learning techniques [27,89].…”

Section: Sources Of Attenuation/scatter Informationmentioning

confidence: 99%

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The Use of Anatomical Information for Molecular Image Reconstruction Algorithms: Attenuation/Scatter Correction, Motion Compensation, and Noise Reduction

Chun

2016

Nucl Med Mol Imaging

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PET and SPECT are important tools for providing valuable molecular information about patients to clinicians. Advances in nuclear medicine hardware technologies and statistical image reconstruction algorithms enabled significantly improved image quality. Sequentially or simultaneously acquired anatomical images such as CT and MRI from hybrid scanners are also important ingredients for improving the image quality of PET or SPECT further. High-quality anatomical information has been used and investigated for attenuation and scatter corrections, motion compensation, and noise reduction via post-reconstruction filtering and regularization in inverse problems. In this article, we will review works using anatomical information for molecular image reconstruction algorithms for better image quality by describing mathematical models, discussing sources of anatomical information for different cases, and showing some examples.

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“…To achieve reliable PET quantification, MR images should ideally be segmented into 6 tissue classes, namely, soft-tissue, fat, lung, air, cortical and spongeous bones (Ouyang et al, 2013, Akbarzadeh et al, 2013a). However, a major challenge is the differentiation between bones and air cavities in the skull and surrounding soft-tissue in the vertebra, since bones do not exhibit detectable signals when using conventional MRI sequences mainly due to their short T2 relaxation time.…”

Section: Introductionmentioning

confidence: 99%

Quantitative analysis of MRI-guided attenuation correction techniques in time-of-flight brain PET/MRI

2016

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Purpose: In quantitative PET/MR imaging, attenuation correction (AC) of PET data is markedly challenged by the need of deriving accurate attenuation maps from MR images. A number of strategies have been developed for MRI-guided attenuation correction with different degrees of success. In this work, we compare the quantitative performance of three generic AC methods, including standard 3-class MR segmentation-based, advanced atlasregistration-based and emission-based approaches in the context of brain time-of-flight (TOF) PET/MRI. Materials and methods: Fourteen patients referred for diagnostic MRI and 18 F-FDG PET/CT brain scans were included in this comparative study. For each study, PET images were reconstructed using four different attenuation maps derived from CT-based AC (CTAC) serving as reference, standard 3-class MR-segmentation, atlas-registration and emission-based AC methods. To generate 3-class attenuation maps, T1-weighted MRI images were segmented into background air, fat and soft-tissue classes followed by assignment of constant linear attenuation coefficients of 0, 0.0864 and 0.0975 cm −1 to each class, respectively. A robust atlas-registration based AC method was developed for pseudo-CT generation using local weighted fusion of atlases based on their morphological similarity to target MR images. Our recently proposed MRI-guided maximum likelihood reconstruction of activity and attenuation (MLAA) algorithm was employed to estimate the attenuation map from TOF emission data. The performance of the different AC algorithms in terms of prediction of bones and quantification of PET tracer uptake was objectively evaluated with respect to reference CTAC maps and CTAC-PET images.Results: Qualitative evaluation showed that the MLAA-AC method could sparsely estimate bones and accurately differentiate them from air cavities. It was found that the atlas-AC method can accurately predict bones with variable errors in defining air cavities. Quantitative assessment of bone extraction accuracy based on Dice similarity coefficient (DSC) showed that MLAA-AC and atlas-AC resulted in DSC mean values of 0.79 and 0.92, respectively, in all patients. The MLAA-AC and atlas-AC methods predicted mean linear attenuation coefficients of 0.107 and 0.134 cm . The evaluation of the relative change in tracer uptake within 32 distinct regions of the brain with respect to CTAC PET images showed that the 3-class MRAC, MLAA-AC and atlas-AC methods resulted in quantification errors of −16.2 ± 3.6%, −13.3 ± 3.3% and 1.0 ± 3.4%, respectively. Linear regression and Bland-Altman concordance plots showed that both 3-class MRAC and MLAA-AC methods result in a significant systematic bias in PET tracer uptake, while the atlas-AC method results in a negligible bias. Conclusion: The standard 3-class MRAC method significantly underestimated cerebral PET tracer uptake. While current state-of-the-art MLAA-AC methods look promising, they were unable to noticeably reduce quantification errors in the context of brain imaging. Conversely, the propose...

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Bias Atlases for Segmentation-Based PET Attenuation Correction Using PET-CT and MR

Cited by 44 publications

References 33 publications

Feasibility of using respiration‐averaged MR images for attenuation correction of cardiac PET/MR imaging

Feasibility of using respiration‐averaged MR images for attenuation correction of cardiac PET/MR imaging

The Use of Anatomical Information for Molecular Image Reconstruction Algorithms: Attenuation/Scatter Correction, Motion Compensation, and Noise Reduction

Quantitative analysis of MRI-guided attenuation correction techniques in time-of-flight brain PET/MRI

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