Matthias Fenchel

Toward Implementing an MRI-Based PET Attenuation-Correction Method for Neurologic Studies on the MR-PET Brain Prototype

Several factors have to be considered for implementing an accurate attenuation-correction (AC) method in a combined MR-PET scanner. In this work, some of these challenges were investigated, and an AC method based entirely on the MRI data obtained with a single dedicated sequence was developed and used for neurologic studies performed with the MR-PET human brain scanner prototype. Methods: The focus was on the problem of bone–air segmentation, selection of the linear attenuation coefficient for bone, and positioning of the radiofrequency coil. The impact of these factors on PET data quantification was studied in simulations and experimental measurements performed on the combined MR-PET scanner. A novel dual-echo ultrashort echo time (DUTE) MRI sequence was proposed for head imaging. Simultaneous MR-PET data were acquired, and the PET images reconstructed using the proposed DUTE MRI–based AC method were compared with the PET images that had been reconstructed using a CT-based AC method. Results: Our data suggest that incorrectly accounting for the bone tissue attenuation can lead to large underestimations (>20%) of the radiotracer concentration in the cortex. Assigning a linear attenuation coefficient of 0.143 or 0.151 cm−1 to bone tissue appears to give the best trade-off between bias and variability in the resulting images. Not identifying the internal air cavities introduces large overestimations (>20%) in adjacent structures. On the basis of these results, the segmented CT AC method was established as the silver standard for the segmented MRI-based AC method. For an integrated MR-PET scanner, in particular, ignoring the radiofrequency coil attenuation can cause large underestimations (i.e., ≤50%) in the reconstructed images. Furthermore, the coil location in the PET field of view has to be accurately known. High-quality bone–air segmentation can be performed using the DUTE data. The PET images obtained using the DUTE MRI– and CT-based AC methods compare favorably in most of the brain structures. Conclusion: A DUTE MRI–based AC method considering all these factors was implemented. Preliminary results suggest that this method could potentially be as accurate as the segmented CT method and could be used for quantitative neurologic MR-PET studies.

Completion of a Truncated Attenuation Image From the Attenuated PET Emission Data

Positron emission tomographs (PET) are currently almost exclusively designed as hybrid systems. The current standard is the PET/CT combination, while prototype PET/MRI systems are being studied by several research groups. One problem in these systems is that the transaxial field of view of the second system is smaller than that of the PET camera. The problem is limited for PET/CT, it is more pronounced in PET/MRI. Because this second system provides the image for attenuation correction, the smaller field of view causes truncation of the attenuation map. In this paper, we propose a maximum-a-posteriori algorithm for estimating the missing part of the attenuation map from the PET emission data.

Whole-Body PET/MR Imaging: Quantitative Evaluation of a Novel Model-Based MR Attenuation Correction Method Including Bone

In routine whole-body PET/MR hybrid imaging, attenuation correction (AC) is usually performed by segmentation methods based on a Dixon MR sequence providing up to 4 different tissue classes. Because of the lack of bone information with the Dixon-based MR sequence, bone is currently considered as soft tissue. Thus, the aim of this study was to evaluate a novel model-based AC method that considers bone in whole-body PET/MR imaging. Methods: The new method (“Model”) is based on a regular 4-compartment segmentation from a Dixon sequence (“Dixon”). Bone information is added using a model-based bone segmentation algorithm, which includes a set of prealigned MR image and bone mask pairs for each major body bone individually. Model was quantitatively evaluated on 20 patients who underwent whole-body PET/MR imaging. As a standard of reference, CT-based μ-maps were generated for each patient individually by nonrigid registration to the MR images based on PET/CT data. This step allowed for a quantitative comparison of all μ-maps based on a single PET emission raw dataset of the PET/MR system. Volumes of interest were drawn on normal tissue, soft-tissue lesions, and bone lesions; standardized uptake values were quantitatively compared. Results: In soft-tissue regions with background uptake, the average bias of SUVs in background volumes of interest was 2.4% ± 2.5% and 2.7% ± 2.7% for Dixon and Model, respectively, compared with CT-based AC. For bony tissue, the −25.5% ± 7.9% underestimation observed with Dixon was reduced to −4.9% ± 6.7% with Model. In bone lesions, the average underestimation was −7.4% ± 5.3% and −2.9% ± 5.8% for Dixon and Model, respectively. For soft-tissue lesions, the biases were 5.1% ± 5.1% for Dixon and 5.2% ± 5.2% for Model. Conclusion: The novel MR-based AC method for whole-body PET/MR imaging, combining Dixon-based soft-tissue segmentation and model-based bone estimation, improves PET quantification in whole-body hybrid PET/MR imaging, especially in bony tissue and nearby soft tissue.

Field of view extension and truncation correction for MR-based human attenuation correction in simultaneous MR/PET imaging

PURPOSE In quantitative PET imaging, it is critical to accurately measure and compensate for the attenuation of the photons absorbed in the tissue. While in PET/CT the linear attenuation coefficients can be easily determined from a low-dose CT-based transmission scan, in whole-body MR/PET the computation of the linear attenuation coefficients is based on the MR data. However, a constraint of the MR-based attenuation correction (AC) is the MR-inherent field-of-view (FoV) limitation due to static magnetic field (B0) inhomogeneities and gradient nonlinearities. Therefore, the MR-based human AC map may be truncated or geometrically distorted toward the edges of the FoV and, consequently, the PET reconstruction with MR-based AC may be biased. This is especially of impact laterally where the patient arms rest beside the body and are not fully considered. METHODS A method is proposed to extend the MR FoV by determining an optimal readout gradient field which locally compensates B0 inhomogeneities and gradient nonlinearities. This technique was used to reduce truncation in AC maps of 12 patients, and the impact on the PET quantification was analyzed and compared to truncated data without applying the FoV extension and additionally to an established approach of PET-based FoV extension. RESULTS The truncation artifacts in the MR-based AC maps were successfully reduced in all patients, and the mean body volume was thereby increased by 5.4%. In some cases large patient-dependent changes in SUV of up to 30% were observed in individual lesions when compared to the standard truncated attenuation map. CONCLUSIONS The proposed technique successfully extends the MR FoV in MR-based attenuation correction and shows an improvement of PET quantification in whole-body MR/PET hybrid imaging. In comparison to the PET-based completion of the truncated body contour, the proposed method is also applicable to specialized PET tracers with little uptake in the arms and might reduce the computation time by obviating the need for iterative calculations of the PET emission data beyond those required for reconstructing images.

MR-based field-of-view extension in MR/PET: B0 homogenization using gradient enhancement (HUGE)

In whole‐body MR/PET, the human attenuation correction can be based on the MR data. However, an MR‐based field‐of‐view (FoV) is limited due to physical restrictions such as B0 inhomogeneities and gradient nonlinearities. Therefore, for large patients, the MR image and the attenuation map might be truncated and the attenuation correction might be biased. The aim of this work is to explore extending the MR FoV through B0 homogenization using gradient enhancement in which an optimal readout gradient field is determined to locally compensate B0 inhomogeneities and gradient nonlinearities. A spin‐echo‐based sequence was developed that computes an optimal gradient for certain regions of interest, for example, the patients arms. A significant distortion reduction was achieved outside the normal MR‐based FoV. This FoV extension was achieved without any hardware modifications. In‐plane distortions in a transaxially extended FoV of up to 600 mm were analyzed in phantom studies. In vivo measurements of the patients arms lying outside the normal specified FoV were compared with and without the use of B0 homogenization using gradient enhancement. In summary, we designed a sequence that provides data for reducing the image distortions due to B0 inhomogeneities and gradient nonlinearities and used the data to extend the MR FoV. Magn Reson Med, 70:1047–1057, 2013.

A multi-centre evaluation of eleven clinically feasible brain PET/MRI attenuation correction techniques using a large cohort of patients.

Aim: To accurately quantify the radioactivity concentration measured by PET, emission data need to be corrected for photon attenuation; however, the MRI signal cannot easily be converted into attenuation values, making attenuation correction (AC) in PET/MRI challenging. In order to further improve the current vendor‐implemented MR‐AC methods for absolute quantification, a number of prototype methods have been proposed in the literature. These can be categorized into three types: template/atlas‐based, segmentation‐based, and reconstruction‐based. These proposed methods in general demonstrated improvements compared to vendor‐implemented AC, and many studies report deviations in PET uptake after AC of only a few percent from a gold standard CT‐AC. Using a unified quantitative evaluation with identical metrics, subject cohort, and common CT‐based reference, the aims of this study were to evaluate a selection of novel methods proposed in the literature, and identify the ones suitable for clinical use. Methods: In total, 11 AC methods were evaluated: two vendor‐implemented (MR‐ACDIXON and MR‐ACUTE), five based on template/atlas information (MR‐ACSEGBONE (Koesters et al., 2016), MR‐ACONTARIO (Anazodo et al., 2014), MR‐ACBOSTON (Izquierdo‐Garcia et al., 2014), MR‐ACUCL (Burgos et al., 2014), and MR‐ACMAXPROB (Merida et al., 2015)), one based on simultaneous reconstruction of attenuation and emission (MR‐ACMLAA (Benoit et al., 2015)), and three based on image‐segmentation (MR‐ACMUNICH (Cabello et al., 2015), MR‐ACCAR‐RiDR (Juttukonda et al., 2015), and MR‐ACRESOLUTE (Ladefoged et al., 2015)). We selected 359 subjects who were scanned using one of the following radiotracers: [18F]FDG (210), [11C]PiB (51), and [18F]florbetapir (98). The comparison to AC with a gold standard CT was performed both globally and regionally, with a special focus on robustness and outlier analysis. Results: The average performance in PET tracer uptake was within ±5% of CT for all of the proposed methods, with the average±SD global percentage bias in PET FDG uptake for each method being: MR‐ACDIXON (−11.3±3.5)%, MR‐ACUTE (−5.7±2.0)%, MR‐ACONTARIO (−4.3±3.6)%, MR‐ACMUNICH (3.7±2.1)%, MR‐ACMLAA (−1.9±2.6)%, MR‐ACSEGBONE (−1.7±3.6)%, MR‐ACUCL (0.8±1.2)%, MR‐ACCAR‐RiDR (−0.4±1.9)%, MR‐ACMAXPROB (−0.4±1.6)%, MR‐ACBOSTON (−0.3±1.8)%, and MR‐ACRESOLUTE (0.3±1.7)%, ordered by average bias. The overall best performing methods (MR‐ACBOSTON, MR‐ACMAXPROB, MR‐ACRESOLUTE and MR‐ACUCL, ordered alphabetically) showed regional average errors within ±3% of PET with CT‐AC in all regions of the brain with FDG, and the same four methods, as well as MR‐ACCAR‐RiDR, showed that for 95% of the patients, 95% of brain voxels had an uptake that deviated by less than 15% from the reference. Comparable performance was obtained with PiB and florbetapir. Conclusions: All of the proposed novel methods have an average global performance within likely acceptable limits (±5% of CT‐based reference), and the main difference among the methods was found in the robustness, outlier analysis, and clinical feasibility. Overall, the best performing methods were MR‐ACBOSTON, MR‐ACMAXPROB, MR‐ACRESOLUTE and MR‐ACUCL, ordered alphabetically. These methods all minimized the number of outliers, standard deviation, and average global and local error. The methods MR‐ACMUNICH and MR‐ACCAR‐RiDR were both within acceptable quantitative limits, so these methods should be considered if processing time is a factor. The method MR‐ACSEGBONE also demonstrates promising results, and performs well within the likely acceptable quantitative limits. For clinical routine scans where processing time can be a key factor, this vendor‐provided solution currently outperforms most methods. With the performance of the methods presented here, it may be concluded that the challenge of improving the accuracy of MR‐AC in adult brains with normal anatomy has been solved to a quantitatively acceptable degree, which is smaller than the quantification reproducibility in PET imaging.

Automatic Labeling of Anatomical Structures in MR FastView Images Using a Statistical Atlas

We present a method for fast and automatic labeling of anatomical structures in MR FastView localizer images, which can be useful for automatic MR examination planning. FastView is a modern MR protocol, that provides larger planning fields of view than previously available with isotropic 3D resolution by scanning during continuous movement of the patient table. Hence, full 3D information is obtained within short acquisition time. Anatomical labeling is done by registering the images to a statistical atlas created from training image data beforehand. The statistical atlas consists of a statistical model of deformation and a statistical model of grey value appearance. It is generated by non-rigid registration and principal component analysis of the resulting deformation fields and registered images. Labeling of an unseen FastView image is done by non-rigid registration of the image to the statistical atlas and propagating the labels from the atlas to the image. In our implementation, the statistical models of deformation and appearance are both implemented on the GPU (graphics processing unit), which permits computing the atlas based labeling using GPU hardware acceleration. The running times of about 10 to 30 seconds are of the same magnitude as the image acquisition itself, which allows for practical usage in clinical MR routine.

Dixon Sequence with Superimposed Model-Based Bone Compartment Provides Highly Accurate PET/MR Attenuation Correction of the Brain.

Simultaneous PET/MR of the brain is a promising technology for characterizing patients with suspected cognitive impairment or epilepsy. Unlike CT, however, MR signal intensities do not correlate directly with PET photon attenuation correction (AC), and inaccurate radiotracer SUV estimation can limit future PET/MR clinical applications. We tested a novel AC method that supplements standard Dixon-based tissue segmentation with a superimposed model-based bone compartment. Methods: We directly compared SUV estimation between MR-based AC and reference CT AC in 16 patients undergoing same-day PET/CT and PET/MR with a single 18F-FDG dose for suspected neurodegeneration. Three Dixon-based MR AC methods were compared with CT: standard Dixon 4-compartment segmentation alone, Dixon with a superimposed model-based bone compartment, and Dixon with a superimposed bone compartment and linear AC optimized specifically for brain tissue. The brain was segmented using a 3-dimensional T1-weighted volumetric MR sequence, and SUV estimations were compared with CT AC for whole-image, whole-brain, and 91 FreeSurfer-based regions of interest. Results: Modifying the linear AC value specifically for brain and superimposing a model-based bone compartment reduced the whole-brain SUV estimation bias of Dixon-based PET/MR AC by 95% compared with reference CT AC (P < 0.05), resulting in a residual −0.3% whole-brain SUVmean bias. Further, brain regional analysis demonstrated only 3 frontal lobe regions with an SUV estimation bias of 5% or greater (P < 0.05). These biases appeared to correlate with high individual variability in frontal bone thickness and pneumatization. Conclusion: Bone compartment and linear AC modifications result in a highly accurate MR AC method in subjects with suspected neurodegeneration. This prototype MR AC solution appears equivalent to other recently proposed solutions and does not require additional MR sequences and scanning time. These data also suggest that exclusively model-based MR AC approaches may be adversely affected by common individual variations in skull anatomy.

PET/MRI for oncological brain imaging: A comparison of standard MR-based attenuation corrections with a novel, model-based approach for the Siemens mMR PET/MR system

The aim of this study was to compare attenuation-correction (AC) approaches for PET/MRI in clinical neurooncology. Methods: Forty-nine PET/MRI brain scans were included: brain tumor studies using 18F-fluoro-ethyl-tyrosine (18F-FET) (n = 31) and 68Ga-DOTANOC (n = 7) and studies of healthy subjects using 18F-FDG (n = 11). For each subject, MR-based AC maps (MR-AC) were acquired using the standard DIXON- and ultrashort echo time (UTE)–based approaches. A third MR-AC was calculated using a model-based, postprocessing approach to account for bone attenuation values (BD, noncommercial prototype software by Siemens Healthcare). As a reference, AC maps were derived from patient-specific CT images (CTref). PET data were reconstructed using standard settings after AC with all 4 AC methods. We report changes in diagnosis for all brain tumor patients and the following relative differences values (RDs [%]), with regards to AC-CTref: for 18F-FET (A)—SUVs as well as volumes of interest (VOIs) defined by a 70% threshold of all segmented lesions and lesion-to-background ratios; for 68Ga-DOTANOC (B)—SUVs as well as VOIs defined by a 50% threshold for all lesions and the pituitary gland; and for 18F-FDG (C)—RD of SUVs of the whole brain and 10 anatomic regions segmented on MR images. Results: For brain tumor imaging (A and B), the standard PET-based diagnosis was not affected by any of the 3 MR-AC methods. For A, the average RDs of SUVmean were −10%, −4%, and −3% and of the VOIs 1%, 2%, and 7% for DIXON, UTE, and BD, respectively. Lesion-to-background ratios for all MR-AC methods were similar to that of CTref. For B, average RDs of SUVmean were −11%, −11%, and −3% and of the VOIs 1%, −4%, and −3%, respectively. In the case of 18F-FDG PET/MRI (C), RDs for the whole brain were −11%, −8%, and −5% for DIXON, UTE, and BD, respectively. Conclusion: The diagnostic reading of PET/MR patients with brain tumors did not change with the chosen AC method. Quantitative accuracy of SUVs was clinically acceptable for UTE- and BD-AC for group A, whereas for group B BD was in accordance with CTref. Nevertheless, for the quantification of individual lesions large deviations to CTref can be observed independent of the MR-AC method used.

Reconstructing liver shape and position from MR image slices using an active shape model

We present an algorithm for fully automatic reconstruction of 3D position, orientation and shape of the human liver from a sparsely covering set of