Attenuation Correction In Hybrid Research Articles

Attenuation Correction Approaches for Serotonin Transporter Quantification With PET/MRI.

BackgroundSeveral MR-based attenuation correction (AC) approaches were developed to conquer the challenging AC in hybrid PET/MR imaging. These AC methods are commonly evaluated on standardized uptake values or tissue concentration. However, in neurotransmitter system studies absolute quantification is more favorable due to its accuracy. Therefore, our aim was to investigate the accuracy of segmentation- and atlas-based MR AC approaches on serotonin transporter (SERT) distribution volumes and occupancy after a drug challenge.Methods18 healthy subjects (7 male) underwent two [11C]DASB PET/MRI measurements in a double-blinded, placebo controlled, cross-over design. After 70 min the selective serotonin reuptake inhibitor (SSRI) citalopram or a placebo was infused. The parameters total and specific volume of distribution (VT, VS = BPP) and occupancy were quantified. All subjects underwent a low-dose CT scan as reference AC method. Besides the standard AC approaches DIXON and UTE, a T1-weighted structural image was recorded to estimate a pseudo-CT based on an MR/CT database (pseudoCT). Another evaluated AC approach superimposed a bone model on AC DIXON. Lastly, an approach optimizing the segmentation of UTE images was analyzed (RESOLUTE). PET emission data were reconstructed with all 6 AC methods. The accuracy of the AC approaches was evaluated on a region of interest-basis for the parameters VT, BPP, and occupancy with respect to the results of AC CT.ResultsVariations for VT and BPP were found with all AC methods with bias ranging from −15 to 17%. The smallest relative errors for all regions were found with AC pseudoCT (<|5%|). Although the bias between BPP SSRI and BPP placebo varied markedly with AC DIXON (<|12%|) and AC UTE (<|9%|), a high correlation to AC CT was obtained (r2∼1). The relative difference of the occupancy for all tested AC methods was small for SERT high binding regions (<|4%|).ConclusionThe high correlation might offer a rescaling from the biased parameters VT and BPP to the true values. Overall, the pseudoCT approach yielded smallest errors and the best agreement with AC CT. For SERT occupancy, all AC methods showed little bias in high binding regions, indicating that errors may cancel out in longitudinal assessments.

A Quantitative Evaluation of Joint Activity and Attenuation Reconstruction in TOF PET/MR Brain Imaging.

Time-of-flight (TOF) PET data provide an effective means for attenuation correction (AC) when no (or incomplete or inaccurate) attenuation information is available. Since MR scanners provide little information on photon attenuation of different tissue types, AC in hybrid PET/MR scanners has always been challenging. In this contribution, we aim at validating the activity reconstructions of the maximum-likelihood ordered-subsets activity and attenuation (OSAA) reconstruction algorithm on a patient brain data set. We present a quantitative comparison of joint reconstructions with the current clinical gold standard-ordered-subsets expectation maximization-using CT-based AC in PET/CT, as well as the current state of the art in PET/MR, that is, zero time echo (ZTE)-based AC. Methods: The TOF PET emission data were initially used in a preprocessing stage to estimate crystal maps of efficiencies, timing offsets, and timing resolutions. Applying these additional corrections during reconstructions, OSAA, ZTE-based, and the vendor-provided atlas-based AC techniques were analyzed and compared with CT-based AC. In our initial study, we used the CT-based estimate of the expected scatter and later used the ZTE-based and OSAA attenuation estimates to compute the expected scatter contribution of the data during reconstructions. In all reconstructions, a maximum-likelihood scaling of the single-scatter simulation estimate to the emission data was used for scatter correction. The reconstruction results were analyzed in the 86 segmented regions of interest of the Hammers atlas. Results: Our quantitative analysis showed that, in practice, a tracer activity difference of +0.5% (±2.1%) and +0.1% (±2.3%) could be expected for the state-of-the-art ZTE-based and OSAA AC methods, respectively, in PET/MR compared with the clinical gold standard in PET/CT. Conclusion: Joint activity and attenuation estimation methods can provide an effective solution to the challenging AC problem for brain studies in hybrid TOF PET/MR scanners. With an accurate TOF-based (timing offsets and timing resolutions) calibration, and similar to the results of the state-of-the-art method in PET/MR, regional errors of joint TOF PET reconstructions are within a few percentage points.

P.1.i.009 - Impact of attenuation correction in hybrid PET/MR imaging of serotonin transporter occupancy

P.1.i.009 - Impact of attenuation correction in hybrid PET/MR imaging of serotonin transporter occupancy

Fast Patch-Based Pseudo-CT Synthesis from T1-Weighted MR Images for PET/MR Attenuation Correction in Brain Studies.

Attenuation correction in hybrid PET/MR scanners is still a challenging task. This paper describes a methodology for synthesizing a pseudo-CT volume from a single T1-weighted volume, thus allowing us to create accurate attenuation correction maps. We propose a fast pseudo-CT volume generation from a patient-specific MR T1-weighted image using a groupwise patch-based approach and an MRI-CT atlas dictionary. For every voxel in the input MR image, we compute the similarity of the patch containing that voxel to the patches of all MR images in the database that lie in a certain anatomic neighborhood. The pseudo-CT volume is obtained as a local weighted linear combination of the CT values of the corresponding patches. The algorithm was implemented in a graphical processing unit (GPU). We evaluated our method both qualitatively and quantitatively for PET/MR correction. The approach performed successfully in all cases considered. We compared the SUVs of the PET image obtained after attenuation correction using the patient-specific CT volume and using the corresponding computed pseudo-CT volume. The patient-specific correlation between SUV obtained with both methods was high (R(2) = 0.9980, P < 0.0001), and the Bland-Altman test showed that the average of the differences was low (0.0006 ± 0.0594). A region-of-interest analysis was also performed. The correlation between SUVmean and SUVmax for every region was high (R(2) = 0.9989, P < 0.0001, and R(2) = 0.9904, P < 0.0001, respectively). The results indicate that our method can accurately approximate the patient-specific CT volume and serves as a potential solution for accurate attenuation correction in hybrid PET/MR systems. The quality of the corrected PET scan using our pseudo-CT volume is comparable to having acquired a patient-specific CT scan, thus improving the results obtained with the ultrashort-echo-time-based attenuation correction maps currently used in the scanner. The GPU implementation substantially decreases computational time, making the approach suitable for real applications.

Comparison of Template-Based Versus CT-Based Attenuation Correction for Hybrid MR/PET Scanners

Attenuation correction (AC) of cerebral PET data acquired in hybrid MR/PET scanners is still a challenge. To overcome this problem we previously proposed a correction method by obtaining template-based attenuation maps (AM) using MR and ECAT EXACT HR+ transmission scans. In the present study we investigated (a) the basic difference between template-based and CT-based AC methods and (b) their influence on reconstructed PET images. The data of 11 subjects undergoing $^{18}{\rm FDG}$ imaging in the Siemens 3T MR-BrainPET scanner were used. Additionally, from all participants a CT scan of the whole head was acquired at the same day. These CT images were transformed to CT-based AMs. They were filtered by a 3D Gaussian kernel with 3 mm (BrainPET resolution) filter width, which was considered as reference. Comparisons between both AMs (CT-based and template-based) were performed by estimating the Dice coefficients D and calculating the numbers of true positive, true negative and false negative voxels. The BrainPET emission data were reconstructed with both AMs ( ${\rm AM}_{{\rm CT}3{\rm mm}}$ and ${\rm AM}_{\rm Template}$ ). All reconstructed PET images were scaled to standardized uptake values (SUVs) and normalized to the MNI brain for using the AAL-VOI Atlas analysis. Correlation plots with regression equation, coefficients of determination ${{\rm R}^2}$ and relative differences (RD) between ${\rm AM}_{{\rm CT}3{\rm mm}}$ and the ${\rm AM}_{\rm Template}$ were derived. The fraction of the overall true positive voxels averaged over the 11 subjects was $80.4 \pm 7.5\% $ for ${\rm AM}_{\rm Template}$ compared to ${\rm AM}_{{\rm CT}3{\rm mm}}$ ( ${{\rm D}_{\rm bone}} = 0.63 \pm 0.08$ ; ${{\rm D}_{\rm soft - tissue}} = 0.85 \pm 0.08$ ; ${{\rm D}_{\rm air}} = 0.79 \pm 0.04$ ). A misclassification of bone as soft tissue and vice versa was evident in the comparison. The correlation plot of all VOIs considered (1,276 values) showed a mean ${{\rm R}^2}$ of 0.964 and a slope of 1.02. A mean RD of $1.33 \pm 0.95\%$ ( ${\min} = - 0.12\% $ , ${\max} = 2.85\% $ ) was found. The template-based AC method proposed by our group shows considerable differences in comparison to the higher resolution CT-based AM with respect to the Dice coefficients, in particular in the classification of bone and soft tissue. However, this has no major influence on the reconstructed $^{18}{\rm FDG}$ PET data.

Attenuation correction for hybrid MR/PET scanners: a comparison study.

Attenuation correction of PET data acquired in hybrid MR/PET scanners is still a challenge. Different methods have been adopted by several groups to obtain reliable attenuation maps (mu-maps). In this study we compare three methods: MGH, UCL, Neural-Network. The MGH method is based on an MR/CT template obtained with the SPM8 software. The UCL method uses a database of MR/CT pairs. Both generate mu-maps from MP-RAGE images. The feed-forward neural-network from Juelich (NN-Juelich) requires two UTE images; it generates segmented mu-maps. Data from eight subjects (S1-S8) measured in the Siemens 3T MR-BrainPET scanner were used. Corresponding CT images were acquired. The resulting mu-maps were compared against the CT-based mu-maps for each subject and method. Overlapped voxels and Dice similarity coefficients, D, for bone, soft-tissue and air regions, and relative differences images were calculated. The true positive (TP) recognized voxels for the whole head were 79.9% (NN-Juelich, S7) to 92.1% (UCL method, S1). D values of the bone were D=0.65 (NN-Juelich, S1) to D=0.87 (UCL method, S1). For S8 the MHG method failed (TP=76.4%; D=0.46 for bone). D values shared a common tendency in all subjects and methods to recognize soft-tissue as bone. The relative difference images showed a variation of -10.9% - +10.1%; for S8 and MHG method the values were -24.5% and +14.2%. A preliminary comparison of three methods for generation of mu-maps for MR/PET scanners is presented. The continuous methods (MGH, UCL) seem to generate reliable mu-maps, whilst the binary method seems to need further improvement. Future work will include more subjects, the reconstruction of corresponding PET data and their comparison.

Generation of a Four-Class Attenuation Map for MRI-Based Attenuation Correction of PET Data in the Head Area Using a Novel Combination of STE/Dixon-MRI and FCM Clustering.

The aim of this study is to generate a four-class magnetic resonance imaging (MRI)-based attenuation map (μ-map) for attenuation correction of positron emission tomography (PET) data of the head area using a novel combination of short echo time (STE)/Dixon-MRI and a dedicated image segmentation method. MR images of the head area were acquired using STE and two-point Dixon sequences. μ-maps were derived from MRI images based on a fuzzy C-means (FCM) clustering method along with morphologic operations. Quantitative assessment was performed to evaluate generated MRI-based μ-maps compared to X-ray computed tomography (CT)-based μ-maps. The voxel-by-voxel comparison of MR-based and CT-based segmentation results yielded an average of more than 95% for accuracy and specificity in the cortical bone, soft tissue, and air region. MRI-based μ-maps show a high correlation with those derived from CT scans (R (2) > 0.95). Results indicate that STE/Dixon-MRI data in combination with FCM-based segmentation yields precise MR-based μ-maps for PET attenuation correction in hybrid PET/MRI systems.

Hybrid PET/MR imaging: an algorithm to reduce metal artifacts from dental implants in Dixon-based attenuation map generation using a multiacquisition variable-resonance image combination sequence.

It was the aim of this study to implement an algorithm modifying Dixon-based MR imaging datasets for attenuation correction in hybrid PET/MR imaging with a multiacquisition variable resonance image combination (MAVRIC) sequence to reduce metal artifacts. After ethics approval, in 8 oncologic patients with dental implants data were acquired in a trimodality setup with PET/CT and MR imaging. The protocol included a whole-body 3-dimensional dual gradient-echo sequence (Dixon) used for MR imaging-based PET attenuation correction and a high-resolution MAVRIC sequence, applied in the oral area compromised by dental implants. An algorithm was implemented correcting the Dixon-based μ maps using the MAVRIC in areas of Dixon signal voids. The artifact size of the corrected μ maps was compared with the uncorrected MR imaging μ maps. The algorithm was robust in all patients. There was a significant reduction in mean artifact size of 70.5% between uncorrected and corrected μ maps from 697 ± 589 mm(2) to 202 ± 119 mm(2) (P = 0.016). The proposed algorithm could improve MR imaging-based attenuation correction in critical areas, when standard attenuation correction is hampered by metal artifacts, using a MAVRIC.

Comparison template-based with CT-based attenuation correction for hybrid MR/PET scanners.

Attenuation correction (AC) of PET data acquired in hybrid MR/PET scanners is still a challenge, even for brain imaging. A correction method previously proposed by our group and obtained with template-based attenuation maps (AM) used MR and ECAT HR+ images. In this study we investigated the influence of both template-based and CT-based AC methods on reconstructed images. The data of two volunteers, measured in the Siemens 3T MR-BrainPET scanner, were used. Corresponding CT images were acquired. Due to the different resolution of ECAT and CT-derived AMs 3D Gaussian kernels with 3, 5, 7, and 9 mm filter width were applied to the latter ones. The CT-based AM with 3 mm filter was considered as reference. The BrainPET emission data were reconstructed with the five AMs: AMtemplate and AMCTxmm (with x = 3, 5, 7, and 9). The reconstructed PET images were normalized to the MNI brain for using the AAL-VOI Atlas analysis. The final brain regions considered were the frontal, temporal, parietal, occipital, and cerebellum, whith the corresponding AAL-VOIs merged to one single VOI. Furthermore, caudate nucleus, putamen, and thalamus were considered. The relative differences between AMCT3mm and all other four AMs were calculated. Considering first only the CT-derived AMs the relative differences ranged between 0.11% (putamen area with AMCT9mm) and 2.70% (merged cerebellum area with AMCT9mm). The comparison of AMCT3mm with AMtemplate over all VOIs showed an overall, equally distributed underestimation of 8.0%. The template-based AC method proposed by our group does not show any remarkable differences when compared to ECAT data (results not shown here). At the same time provides a reliable AC method for brain imaging measured in MR-PET scanners. Nevertheless, the number of tested subjects is still low and an analysis of a larger dataset is an ongoing running project.

MRI-guided attenuation correction in whole-body PET/MR: assessment of the effect of bone attenuation

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. 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. 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. 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.

Metal artifact reduction strategies for improved attenuation correction in hybrid PET/CT imaging

Metallic implants are known to generate bright and dark streaking artifacts in x-ray computed tomography (CT) images, which in turn propagate to corresponding functional positron emission tomography (PET) images during the CT-based attenuation correction procedure commonly used on hybrid clinical PET/CT scanners. Therefore, visual artifacts and overestimation and/or underestimation of the tracer uptake in regions adjacent to metallic implants are likely to occur and as such, inaccurate quantification of the tracer uptake and potential erroneous clinical interpretation of PET images is expected. Accurate quantification of PET data requires metal artifact reduction (MAR) of the CT images prior to the application of the CT-based attenuation correction procedure. In this review, the origins of metallic artifacts and their impact on clinical PET/CT imaging are discussed. Moreover, a brief overview of proposed MAR methods and their advantages and drawbacks is presented. Although most of the presented MAR methods are mainly developed for diagnostic CT imaging, their potential application in PET/CT imaging is highlighted. The challenges associated with comparative evaluation of these methods in a clinical environment in the absence of a gold standard are also discussed.

MRI-Based Attenuation Correction for Hybrid PET/MRI Systems: A 4-Class Tissue Segmentation Technique Using a Combined Ultrashort-Echo-Time/Dixon MRI Sequence

Accurate γ-photon attenuation correction (AC) is essential for quantitative PET/MRI as there is no simple relation between MR image intensity and attenuation coefficients. Attenuation maps (μ-maps) can be derived by segmenting MR images and assigning attenuation coefficients to the compartments. Ultrashort-echo-time (UTE) sequences have been used to separate cortical bone and air, and the Dixon technique has enabled differentiation between soft and adipose tissues. Unfortunately, sequential application of these sequences is time-consuming and complicates image registration. A UTE triple-echo (UTILE) MRI sequence is proposed, combining UTE sampling for bone detection and gradient echoes for Dixon water-fat separation in a radial 3-dimensional acquisition (repetition time, 4.1 ms; echo times, 0.09/1.09/2.09 ms; field strength, 3 T). Air masks are derived mainly from the phase information of the first echo; cortical bone is segmented using a dual-echo technique. Soft-tissue and adipose-tissue decomposition is achieved using a 3-point Dixon-like decomposition. Predefined linear attenuation coefficients are assigned to classified voxels to generate MRI-based μ-maps. The results of 6 patients are obtained by comparing μ-maps, reciprocal sensitivity maps, reconstructed PET images, and brain region PET activities based on either CT AC, two 3-class MRI AC techniques, or the proposed 4-class UTILE AC. Using the UTILE MRI sequence, an acquisition time of 214 s was achieved for the head-and-neck region with 1.75-mm isotropic resolution, compared with 164 s for a single-echo UTE scan. MRI-based reciprocal sensitivity maps show a high correlation with those derived from CT scans (R(2) = 0.9920). The same is true for PET activities (R(2) = 0.9958). An overall voxel classification accuracy (compared with CT) of 81.1% was reached. Bone segmentation is inaccurate in complex regions such as the paranasal sinuses, but brain region activities in 48 regions across 6 patients show a high correlation after MRI-based and CT-based correction (R(2) = 0.9956), with a regression line slope of 0.960. All overall correlations are higher and brain region PET activities more accurate in terms of mean and maximum deviations for the 4-class technique than for 3-class techniques. The UTILE MRI sequence enables the generation of MRI-based 4-class μ-maps without anatomic priors, yielding results more similar to CT-based results than can be obtained with 3-class segmentation only.

MR‐based attenuation correction for hybrid PET‐MR brain imaging systems using deformable image registration

Realization of combined positron emission tomography (PET)--magnetic resonance (MR) scanners has the potential to significantly change healthcare and revolutionize clinical practice as it allows, simultaneously, visualization of molecular imaging and anatomical imaging. PET-MR, acquired in one imaging study, will likely become the advanced imaging modality of choice for neurological studies, certain forms of cancer, stroke, and the emerging study of stem cell therapy. A challenge toward the implementation and operation of combined PET-MR scanners is that attenuation corrections maps are not directly available due to space and cost constraints. This article presents a method to obtain accurate patient-specific PET attenuation coefficients maps in head imaging by warping an atlas computed tomography (CT) data set to the patient-specific MR data set using a deformable registration model. A multimodality optical flow deformable model has been developed that establishes a voxel-to-voxel correspondence between the CT atlas and patient MR images. Once the mapping is established, the atlas is warped with the deformation field obtained by the registration to create a simulated CT image study that matches the patient anatomy, which could be used for attenuation correction. To evaluate the accuracy of the deformable-based attenuation correction, 17 clinical brain tumor cases were studied using acquired MR-CT images. A simulated CT was compared to the patient's true CT to assess geometrical accuracy of the deformation module as well as voxel-to-voxel comparison of Hounsfield units (HUs). In all cases, mapping from the atlas CT to the individual MR was achieved with geometrical accuracy as judged using quantitative inspection tools. The mean distance between simulated and true CT external contour and bony anatomy was 1.26 and 2.15 mm, respectively. In terms of HU unit comparison, the mean voxel-to-voxel difference was less than 2 HU for all cases. Attenuation correction for hybrid PET-MR scanners was easily achieved by individualizing an atlas CT to the MR data set using a deformable model without requiring user interaction. The method provided clinical accuracy while eliminating the need for an additional CT scan for PET attenuation correction.

TU‐C‐332‐06: Attenuation Correction for Hybrid PET‐MRI System by Deformable Image Registration

Purpose: To develop an accurate patient‐specific PET attenuation coefficients map to be used in hybrid MRI‐PET systems for brain tumor imaging. The attenuation maps are obtained by warping a general (atlas) CT dataset to the patient‐specific MRI dataset using a deformable registration model. Method and Materials: Patient MR images and the atlas CT images are registered using a B‐Spline deformable model and the Mattes formulation of the mutual information metric as registration criterion. The registration establishes a voxel‐to‐voxel correspondence that maps each voxel in the CT atlas voxels to the MRI dataset, creating an artificial, individualized CT scan of the patient's anatomy as observed in the MRI dataset. To evaluate the accuracy of the deformable‐based attenuation correction, ten clinical brain tumor cases are studied with MR‐CT image sets. For each case an artificial CT is computed by warping the atlas to the MRI datasets. This artificial CT is compared to the true patient's CT in terms of geometrical accuracy of the deformation module as well as a voxel‐to‐voxel comparison of HU units. Results: In all cases, mapping form the atlas CT to the individual MR was achieved with great geometrical accuracy as visually judged using the qualitative visual inspection tools. The mean distance between the artificial and true CT's external contour and bony anatomy was 1 mm and 1.5 mm, respectively. In terms of HU unit comparison, the mean voxel‐to‐voxel difference was less than 5%. Conclusion: Attenuation correction for hybrid MRI‐PET scanners can be easily achieved by individualizing an atlas CT to the MRI dataset using the BSpline deformable model, with no user interaction required. The method provides clinical accuracy while eliminating the need for an additional CT scan for PET attenuation correction.