Simultaneous reconstruction of activity and attenuation for PET/MR

MLAA-based attenuation correction of flexible hardware components in hybrid PET/MR imaging

BACKGROUND

Accurate PET quantification demands attenuation correction (AC) for both patient and hardware attenuation of the 511 keV annihilation photons. In hybrid PET/MR imaging, AC for stationary hardware components such as patient table and MR head coil is straightforward, employing CT-derived attenuation templates. AC for flexible hardware components such as MR-safe headphones and MR radiofrequency (RF) surface coils is more challenging. Registration-based approaches, aligning CT-based attenuation templates with the current patient position, have been proposed but are not used in clinical routine. Ignoring headphone or RF coil attenuation has been shown to result in regional activity underestimation values of up to 18%. We propose to employ the maximum-likelihood reconstruction of attenuation and activity (MLAA) algorithm to estimate the attenuation of flexible hardware components. Starting with an initial attenuation map not including flexible hardware components, the attenuation update of MLAA is applied outside the body outline only, allowing to estimate hardware attenuation without modifying the patient attenuation map. Appropriate prior expectations on the attenuation coefficients are incorporated into MLAA. The proposed method is investigated for non-TOF PET phantom and ¹⁸F-FDG patient data acquired with a clinical PET/MR device, using headphones or RF surface coils as flexible hardware components.

RESULTS

Although MLAA cannot recover the exact physical shape of the hardware attenuation maps, the overall attenuation of the hardware components is accurately estimated. Therefore, the proposed algorithm significantly improves PET quantification. Using the phantom data, local activity underestimation when neglecting hardware attenuation was reduced from up to 25% to less than 3% under- or overestimation as compared to reference scans without hardware present or to CT-derived AC. For the patient data, we found an average activity underestimation of 7.9% evaluated in the full brain and of 6.1% for the abdominal region comparing the uncorrected case with MLAA.

CONCLUSIONS

MLAA is able to provide accurate estimations of the attenuation of flexible hardware components and can therefore be used to significantly improve PET quantification. The proposed approach can be readily incorporated into clinical workflow.

PET/MRI in the Presence of Metal Implants: Completion of the Attenuation Map from PET Emission Data

We present a novel technique for accurate whole-body attenuation correction in the presence of metallic endoprosthesis, on integrated non-time-of-flight (non-TOF) PET/MRI scanners. The proposed implant PET-based attenuation map completion (IPAC) method performs a joint reconstruction of radioactivity and attenuation from the emission data to determine the position, shape, and linear attenuation coefficient (LAC) of metallic implants. Methods: The initial estimate of the attenuation map was obtained using the MR Dixon method currently available on the Siemens Biograph mMR scanner. The attenuation coefficients in the area of the MR image subjected to metal susceptibility artifacts are then reconstructed from the PET emission data using the IPAC algorithm. The method was tested on 11 subjects presenting 13 different metallic implants, who underwent CT and PET/MR scans. Relative mean LACs and Dice similarity coefficients were calculated to determine the accuracy of the reconstructed attenuation values and the shape of the metal implant, respectively. The reconstructed PET images were compared with those obtained using the reference CT-based approach and the Dixon-based method. Absolute relative change (aRC) images were generated in each case, and voxel-based analyses were performed. Results: The error in implant LAC estimation, using the proposed IPAC algorithm, was 15.7% ± 7.8%, which was significantly smaller than the Dixon- (100%) and CT- (39%) derived values. A mean Dice similarity coefficient of 73% ± 9% was obtained when comparing the IPAC- with the CT-derived implant shape. The voxel-based analysis of the reconstructed PET images revealed quantification errors (aRC) of 13.2% ± 22.1% for the IPAC- with respect to CT-corrected images. The Dixon-based method performed substantially worse, with a mean aRC of 23.1% ± 38.4%. Conclusion: We have presented a non-TOF emission-based approach for estimating the attenuation map in the presence of metallic implants, to be used for whole-body attenuation correction in integrated PET/MR scanners. The Graphics Processing Unit implementation of the algorithm will be included in the open-source reconstruction toolbox Occiput.io.

Clinical evaluation of TOF versus non-TOF on PET artifacts in simultaneous PET/MR: a dual centre experience

PURPOSE

Our objective was to determine clinically the value of time-of-flight (TOF) information in reducing PET artifacts and improving PET image quality and accuracy in simultaneous TOF PET/MR scanning.

METHODS

A total 65 patients who underwent a comparative scan in a simultaneous TOF PET/MR scanner were included. TOF and non-TOF PET images were reconstructed, clinically examined, compared and scored. PET imaging artifacts were categorized as large or small implant-related artifacts, as dental implant-related artifacts, and as implant-unrelated artifacts. Differences in image quality, especially those related to (implant) artifacts, were assessed using a scale ranging from 0 (no artifact) to 4 (severe artifact).

RESULTS

A total of 87 image artifacts were found and evaluated. Four patients had large and eight patients small implant-related artifacts, 27 patients had dental implants/fillings, and 48 patients had implant-unrelated artifacts. The average score was 1.14 ± 0.82 for non-TOF PET images and 0.53 ± 0.66 for TOF images (p < 0.01) indicating that artifacts were less noticeable when TOF information was included.

CONCLUSION

Our study indicates that PET image artifacts are significantly mitigated with integration of TOF information in simultaneous PET/MR. The impact is predominantly seen in patients with significant artifacts due to metal implants.

The Effect of Susceptibility Artifacts Related to Metallic Implants on Adjacent-Lesion Assessment in Simultaneous TOF PET/MR

Metalic implants may affect attenuation correction (AC) in PET/MR imaging. The purpose of this study was to evaluate the effect of susceptibility artifacts related to metallic implants on adjacent metabolically active lesions in clinical simultaneous PET/MR scanning for both time-of-flight (TOF) and non-TOF reconstructed PET images. Methods: We included 27 patients without implants but with confirmed ¹⁸F-FDG-avid lesions adjacent to common implant locations. In all patients, a clinically indicated whole-body ¹⁸F-FDG PET/MR scan was acquired. Baseline non-TOF and TOF PET images were reconstructed. Reconstruction was repeated after the introduction of artificial signal voids in the AC map to simulate metallic implants in standard anatomic areas. All reconstructed images were qualitatively and quantitatively assessed and compared with the baseline images. Results: In total, 51 lesions were assessed. In 40 and 50 of these cases (non-TOF and TOF, respectively), the detectability of the lesions did not change; in 9 and 1 cases, the detectability changed; and in 2 non-TOF cases, the lesions were no longer visible after the introduction of metallic artifacts. The inclusion of TOF information significantly reduced artifacts due to simulated implants in the femoral head, sternum, and spine (P = 0.01, 0.01, and 0.03, respectively). It also improved image quality in these locations (P = 0.02, 0.01, and 0.01, respectively). The mean percentage error was -3.5% for TOF and -4.8% for non-TOF reconstructions, meaning that the inclusion of TOF information reduced the percentage error in SUV_max by 28.5% (P < 0.01). Conclusion: Qualitatively, there was a significant reduction of artifacts in the femoral head, sternum, and spine. There was also a significant qualitative improvement in image quality in these locations. Furthermore, our study indicated that simulated susceptibility artifacts related to metallic implants have a significant effect on small, moderately ¹⁸F-FDG-avid lesions near the implant site that possibly may go unnoticed without TOF information. On larger, highly ¹⁸F-FDG-avid lesions, the metallic implants had only a limited effect. The largest significant quantitative difference was found in artifacts of the sternum. There was only a weak inverse correlation between lesions affected by artifacts and distance from the implant.

An Expectation Maximization Method for Joint Estimation of Emission Activity Distribution and Photon Attenuation Map in PET

A maximum likelihood expectation maximization (MLEM) method is proposed for joint estimation of emission activity distribution and photon attenuation map from positron emission tomography (PET) emission data alone. The method is appealing since: (i) it guarantees monotonic likelihood increase to a local extremum, (ii) does not require arbitrary parameters, and (iii) guarantees the positivity of the estimated distributions. Moreover, we propose a discrete Poisson data acquisition model and numerical algorithm for: (i) efficient graphics processing unit (GPU) based formulation, and (ii) a closed form exact solution for the MLEM update equations, which is essential for accurate and robust estimation. Numerical experiments indicate that in the presence of noise, joint EMAA estimation converges to the true emission activity distribution with root mean square errors of 4% and 0.5% respectively in estimation of lung- and myocardial emission activity distributions for a computational XCAT thorax phantom.

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-AC_DIXON and MR-AC_UTE), five based on template/atlas information (MR-AC_SEGBONE (Koesters et al., 2016), MR-AC_ONTARIO (Anazodo et al., 2014), MR-AC_BOSTON (Izquierdo-Garcia et al., 2014), MR-AC_UCL (Burgos et al., 2014), and MR-AC_MAXPROB (Merida et al., 2015)), one based on simultaneous reconstruction of attenuation and emission (MR-AC_MLAA (Benoit et al., 2015)), and three based on image-segmentation (MR-AC_MUNICH (Cabello et al., 2015), MR-AC_CAR-RiDR (Juttukonda et al., 2015), and MR-AC_RESOLUTE (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-AC_DIXON (-11.3±3.5)%, MR-AC_UTE (-5.7±2.0)%, MR-AC_ONTARIO (-4.3±3.6)%, MR-AC_MUNICH (3.7±2.1)%, MR-AC_MLAA (-1.9±2.6)%, MR-AC_SEGBONE (-1.7±3.6)%, MR-AC_UCL (0.8±1.2)%, MR-AC_CAR-RiDR (-0.4±1.9)%, MR-AC_MAXPROB (-0.4±1.6)%, MR-AC_BOSTON (-0.3±1.8)%, and MR-AC_RESOLUTE (0.3±1.7)%, ordered by average bias. The overall best performing methods (MR-AC_BOSTON, MR-AC_MAXPROB, MR-AC_RESOLUTE and MR-AC_UCL, 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-AC_CAR-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.

Vision 20/20: Magnetic resonance imaging-guided attenuation correction in PET/MRI: Challenges, solutions, and opportunities

Attenuation correction is an essential component of the long chain of data correction techniques required to achieve the full potential of quantitative positron emission tomography (PET) imaging. The development of combined PET/magnetic resonance imaging (MRI) systems mandated the widespread interest in developing novel strategies for deriving accurate attenuation maps with the aim to improve the quantitative accuracy of these emerging hybrid imaging systems. The attenuation map in PET/MRI should ideally be derived from anatomical MR images; however, MRI intensities reflect proton density and relaxation time properties of biological tissues rather than their electron density and photon attenuation properties. Therefore, in contrast to PET/computed tomography, there is a lack of standardized global mapping between the intensities of MRI signal and linear attenuation coefficients at 511 keV. Moreover, in standard MRI sequences, bones and lung tissues do not produce measurable signals owing to their low proton density and short transverse relaxation times. MR images are also inevitably subject to artifacts that degrade their quality, thus compromising their applicability for the task of attenuation correction in PET/MRI. MRI-guided attenuation correction strategies can be classified in three broad categories: (i) segmentation-based approaches, (ii) atlas-registration and machine learning methods, and (iii) emission/transmission-based approaches. This paper summarizes past and current state-of-the-art developments and latest advances in PET/MRI attenuation correction. The advantages and drawbacks of each approach for addressing the challenges of MR-based attenuation correction are comprehensively described. The opportunities brought by both MRI and PET imaging modalities for deriving accurate attenuation maps and improving PET quantification will be elaborated. Future prospects and potential clinical applications of these techniques and their integration in commercial systems will also be discussed.

Individual refinement of attenuation correction maps for hybrid PET/MR based on multi-resolution regional learning

PET/MR is an emerging hybrid imaging modality. However, attenuation correction (AC) remains challenging for hybrid PET/MR in generating accurate PET images. Segmentation-based methods on special MR sequences are most widely recommended by vendors. However, their accuracy is usually not high. Individual refinement of available certified attenuation maps may be helpful for further clinical applications. In this study, we proposed a multi-resolution regional learning (MRRL) scheme to utilize the internal consistency of the patient data. The anatomical and AC MR sequences of the same subject were employed to guide the refinement of the provided AC maps. The developed algorithm was tested on 9 patients scanned consecutively with PET/MR and PET/CT (7 [¹⁸F]FDG and 2 [¹⁸F]FET). The preliminary results showed that MRRL can improve the accuracy of segmented attenuation maps and consequently the accuracy of PET reconstructions.

Comparison of Positron Emission Tomography Quantification Using Magnetic Resonance- and Computed Tomography-Based Attenuation Correction in Physiological Tissues and Lesions: A Whole-Body Positron Emission Tomography/Magnetic Resonance Study in 66 Patients

OBJECTIVE

Attenuation correction (AC) in fully integrated positron emission tomography (PET)/magnetic resonance (MR) systems plays a key role for the quantification of tracer uptake. The aim of this prospective study was to assess the accuracy of standardized uptake value (SUV) quantification using MR-based AC in direct comparison with computed tomography (CT)-based AC of the same PET data set on a large patient population.

MATERIALS AND METHODS

Sixty-six patients (22 female; mean [SD], 61 [11] years) were examined by means of combined PET/CT and PET/MR (11C-choline, 18F-FDG, or 68Ga-DOTATATE) subsequently. Positron emission tomography images from PET/MR examinations were corrected with MR-derived AC based on tissue segmentation (PET(MR)). The same PET data were corrected using CT-based attenuation maps (μ-maps) derived from PET/CT after nonrigid registration of the CT to the MR-based μ-map (PET(MRCT)). Positron emission tomography SUVs were quantified placing regions of interest or volumes of interest in 6 different body regions as well as PET-avid lesions, respectively.

RESULTS

The relative differences of quantitative PET values when using MR-based AC versus CT-based AC were varying depending on the organs and body regions assessed. In detail, the mean (SD) relative differences of PET SUVs were as follows: -7.8% (11.5%), blood pool; -3.6% (5.8%), spleen; -4.4% (5.6%)/-4.1% (6.2%), liver; -0.6% (5.0%), muscle; -1.3% (6.3%), fat; -40.0% (18.7%), bone; 1.6% (4.4%), liver lesions; -6.2% (6.8%), bone lesions; and -1.9% (6.2%), soft tissue lesions. In 10 liver lesions, distinct overestimations greater than 5% were found (up to 10%). In addition, overestimations were found in 2 bone lesions and 1 soft tissue lesion adjacent to the lung (up to 28.0%).

CONCLUSIONS

Results obtained using different PET tracers show that MR-based AC is accurate in most tissue types, with SUV deviations generally of less than 10%. In bone, however, underestimations can be pronounced, potentially leading to inaccurate SUV quantifications. In addition, SUV overestimations were found for some lesions close to lung borders. This has to be taken into account when comparing PET/CT- and PET/MR-derived SUVs.

Current image acquisition options in PET/MR

Whole-body PET/MR hybrid imaging combines excellent soft tissue contrast and various functional imaging parameters provided by MR with high sensitivity and quantification of radiotracer uptake provided by PET. Although clinical evaluation now is under way, PET/MR demands for new technologies and innovative solutions, currently subject to interdisciplinary research. Attenuation correction (AC) of human soft tissues and of hardware components has to be MR based to maintain quantification of PET imaging as CT attenuation information is missing. MR-based AC is inherently associated with the following challenges: patient tissues are segmented into only few tissue classes, providing discrete attenuation coefficients; bone is substituted as soft tissue in MR-based AC; the limited field of view in MRI leads to truncations in body imaging and, consequently, in MR-based AC; and correct segmentation of lung tissue may be hampered by breathing artifacts. Use of time of flight during PET image acquisition and reconstruction, however, may improve the accuracy of AC. This article provides a status of current image acquisition options in PET/MR hybrid imaging.

Initial PET performance evaluation of a preclinical insert for PET/MRI with digital SiPM technology

Hyperion-II(D) is a positron emission tomography (PET) insert which allows simultaneous operation in a clinical magnetic resonance imaging (MRI) scanner. To read out the scintillation light of the employed lutetium yttrium orthosilicate crystal arrays with a pitch of 1 mm and 12 mm in height, digital silicon photomultipliers (DPC 3200-22, Philips Digital Photon Counting) (DPC) are used. The basic PET performance in terms of energy resolution, coincidence resolution time (CRT) and sensitivity as a function of the operating parameters, such as the operating temperature, the applied overvoltage, activity and configuration parameters of the DPCs, has been evaluated at system level. The measured energy resolution did not show a large dependency on the selected parameters and is in the range of 12.4%-12.9% for low activity, degrading to  ∼13.6% at an activity of  ∼100 MBq. The CRT strongly depends on the selected trigger scheme (trig) of the DPCs, and we measured approximately 260 ps, 440 ps, 550 ps and 1300 ps for trig 1-4, respectively. The trues sensitivity for a NEMA NU 4 mouse-sized scatter phantom with a 70 mm long tube of activity was dependent on the operating parameters and was determined to be 0.4%-1.4% at low activity. The random fraction stayed below 5% at activity up to 100 MBq and the scatter fraction was evaluated as  ∼6% for an energy window of 411 keV-561 keV and  ∼16% for 250 keV-625 keV. Furthermore, we performed imaging experiments using a mouse-sized hot-rod phantom and a large rabbit-sized phantom. In 2D slices of the reconstructed mouse-sized hot-rod phantom (∅ = 28 mm), the rods were distinguishable from each other down to a rod size of 0.8 mm. There was no benefit from the better CRT of trig 1 over trig 3, where in the larger rabbit-sized phantom (∅ = 114 mm) we were able to show a clear improvement in image quality using the time-of-flight information. The findings will allow system architects-aiming at a similar detector design using DPCs-to make predictions about the design requirements and the performance that can be expected.

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

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 atlas-registration-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(-1), respectively, for the skull compared to reference CTAC mean value of 0.138cm(-1). 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 proposed atlas-AC method provided the most accurate attenuation maps, and thus the lowest quantification bias.

Attenuation correction in emission tomography using the emission data--A review

The problem of attenuation correction (AC) for quantitative positron emission tomography (PET) had been considered solved to a large extent after the commercial availability of devices combining PET with computed tomography (CT) in 2001; single photon emission computed tomography (SPECT) has seen a similar development. However, stimulated in particular by technical advances toward clinical systems combining PET and magnetic resonance imaging (MRI), research interest in alternative approaches for PET AC has grown substantially in the last years. In this comprehensive literature review, the authors first present theoretical results with relevance to simultaneous reconstruction of attenuation and activity. The authors then look back at the early history of this research area especially in PET; since this history is closely interwoven with that of similar approaches in SPECT, these will also be covered. We then review algorithmic advances in PET, including analytic and iterative algorithms. The analytic approaches are either based on the Helgason-Ludwig data consistency conditions of the Radon transform, or generalizations of John's partial differential equation; with respect to iterative methods, we discuss maximum likelihood reconstruction of attenuation and activity (MLAA), the maximum likelihood attenuation correction factors (MLACF) algorithm, and their offspring. The description of methods is followed by a structured account of applications for simultaneous reconstruction techniques: this discussion covers organ-specific applications, applications specific to PET/MRI, applications using supplemental transmission information, and motion-aware applications. After briefly summarizing SPECT applications, we consider recent developments using emission data other than unscattered photons. In summary, developments using time-of-flight (TOF) PET emission data for AC have shown promising advances and open a wide range of applications. These techniques may both remedy deficiencies of purely MRI-based AC approaches in PET/MRI and improve standalone PET imaging.

MR Imaging-Guided Attenuation Correction of PET Data in PET/MR Imaging

Attenuation correction (AC) is one of the most important challenges in the recently introduced combined PET/magnetic resonance (MR) scanners. PET/MR AC (MR-AC) approaches aim to develop methods that allow accurate estimation of the linear attenuation coefficients of the tissues and other components located in the PET field of view. MR-AC methods can be divided into 3 categories: segmentation, atlas, and PET based. This review provides a comprehensive list of the state-of-the-art MR-AC approaches and their pros and cons. The main sources of artifacts are presented. Finally, this review discusses the current status of MR-AC approaches for clinical applications.

Investigating the state-of-the-art in whole-body MR-based attenuation correction: an intra-individual, inter-system, inventory study on three clinical PET/MR systems

OBJECTIVE

We assess inter- and intra-subject variability of magnetic resonance (MR)-based attenuation maps (MRμMaps) of human subjects for state-of-the-art positron emission tomography (PET)/MR imaging systems.

MATERIALS AND METHODS

Four healthy male subjects underwent repeated MR imaging with a Siemens Biograph mMR, Philips Ingenuity TF and GE SIGNA PET/MR system using product-specific MR sequences and image processing algorithms for generating MRμMaps. Total lung volumes and mean attenuation values in nine thoracic reference regions were calculated. Linear regression was used for comparing lung volumes on MRμMaps. Intra- and inter-system variability was investigated using a mixed effects model.

RESULTS

Intra-system variability was seen for the lung volume of some subjects, (p = 0.29). Mean attenuation values across subjects were significantly different (p < 0.001) due to different segmentations of the trachea. Differences in the attenuation values caused noticeable intra-individual and inter-system differences that translated into a subsequent bias of the corrected PET activity values, as verified by independent simulations.

CONCLUSION

Significant differences of MRμMaps generated for the same subjects but different PET/MR systems resulted in differences in attenuation correction factors, particularly in the thorax. These differences currently limit the quantitative use of PET/MR in multi-center imaging studies.

Joint Estimation of Activity and Attenuation in Whole-Body TOF PET/MRI Using Constrained Gaussian Mixture Models

It has recently been shown that the attenuation map can be estimated from time-of-flight (TOF) PET emission data using joint maximum likelihood reconstruction of attenuation and activity (MLAA). In this work, we propose a novel MRI-guided MLAA algorithm for emission-based attenuation correction in whole-body PET/MR imaging. The algorithm imposes MR spatial and CT statistical constraints on the MLAA estimation of attenuation maps using a constrained Gaussian mixture model (GMM) and a Markov random field smoothness prior. Dixon water and fat MR images were segmented into outside air, lung, fat and soft-tissue classes and an MR low-intensity (unknown) class corresponding to air cavities, cortical bone and susceptibility artifacts. The attenuation coefficients over the unknown class were estimated using a mixture of four Gaussians, and those over the known tissue classes using unimodal Gaussians, parameterized over a patient population. To eliminate misclassification of spongy bones with surrounding tissues, and thus include them in the unknown class, we heuristically suppressed fat in water images and also used a co-registered bone probability map. The proposed MLAA-GMM algorithm was compared with the MLAA algorithms proposed by Rezaei and Salomon using simulation and clinical studies with two different tracer distributions. The results showed that our proposed algorithm outperforms its counterparts in suppressing the cross-talk and scaling problems of activity and attenuation and thus produces PET images of improved quantitative accuracy. It can be concluded that the proposed algorithm effectively exploits the MR information and can pave the way toward accurate emission-based attenuation correction in TOF PET/MRI.

PET performance and MRI compatibility evaluation of a digital, ToF-capable PET/MRI insert equipped with clinical scintillators

We evaluate the MR compatibility of the Hyperion-II(D) positron emission tomography (PET) insert, which allows simultaneous operation in a clinical magnetic resonance imaging (MRI) scanner. In contrast to previous investigations, this work aims at the evaluation of a clinical crystal configuration. An imaging-capable demonstrator with an axial field-of-view of 32 mm and a crystal-to-crystal spacing of 217.6 mm was equipped with LYSO scintillators with a pitch of 4 mm which were read out in a one-to-one coupling scheme by sensor tiles composed of digital silicon photomultipliers from Philips Digital Photon Counting (DPC 3200-22). The PET performance degradation (energy resolution and coincidence resolution time (CRT)) was evaluated during simultaneous operation of the MRI scanner. We used clinically motivated imaging sequences as well as synthetic gradient stress test sequences. Without activity of the MRI scanner, we measured for trigger scheme 1 (first photon trigger) an energy resolution of 11.4% and a CRT of 213 ps for a narrow energy (NE) window using five (22)Na point-like sources. When applying the synthetic gradient sequences, we found worst-case relative degradations of the energy resolution by 5.1% and of the CRT by 33.9%. After identifying the origin of the degradations and implementing a fix to the read-out hardware, the same evaluation revealed no degradation of the PET performance anymore even when the most demanding gradient stress tests were applied. The PET performance of the insert was initially evaluated using the point sources, a high-activity phantom and hot-rod phantoms in order to assess the spatial resolution. Trigger schemes 2-4 delivered an energy resolution of 11.4% as well and CRTs of 279 ps, 333 ps and 557 ps for the NE window, respectively. An isocenter sensitivity of 0.41% using the NE window and 0.71% with a wide energy window was measured. Using a hot-rod phantom, a spatial resolution in the order of 2 mm was demonstrated and the benefit of time-of-flight PET was shown with a larger rabbit-sized phantom. In conclusion, the Hyperion architecture is an interesting platform for clinically driven hybrid PET/MRI systems.

Emission-based estimation of lung attenuation coefficients for attenuation correction in time-of-flight PET/MR

In standard segmentation-based MRI-guided attenuation correction (MRAC) of PET data on hybrid PET/MRI systems, the inter/intra-patient variability of linear attenuation coefficients (LACs) is ignored owing to the assignment of a constant LAC to each tissue class. This can lead to PET quantification errors, especially in the lung regions. In this work, we aim to derive continuous and patient-specific lung LACs from time-of-flight (TOF) PET emission data using the maximum likelihood reconstruction of activity and attenuation (MLAA) algorithm. The MLAA algorithm was constrained for estimation of lung LACs only in the standard 4-class MR attenuation map using Gaussian lung tissue preference and Markov random field smoothness priors. MRAC maps were derived from segmentation of CT images of 19 TOF-PET/CT clinical studies into background air, lung, soft tissue and fat tissue classes, followed by assignment of predefined LACs of 0, 0.0224, 0.0864 and 0.0975 cm(-1), respectively. The lung LACs of the resulting attenuation maps were then estimated from emission data using the proposed MLAA algorithm. PET quantification accuracy of MRAC and MLAA methods was evaluated against the reference CT-based AC method in the lungs, lesions located in/near the lungs and neighbouring tissues. The results show that the proposed MLAA algorithm is capable of retrieving lung density gradients and compensate fairly for respiratory-phase mismatch between PET and corresponding attenuation maps. It was found that the mean of the estimated lung LACs generally follow the trend of the reference CT-based attenuation correction (CTAC) method. Quantitative analysis revealed that the MRAC method resulted in average relative errors of -5.2 ± 7.1% and -6.1 ± 6.7% in the lungs and lesions, respectively. These were reduced by the MLAA algorithm to -0.8 ± 6.3% and -3.3 ± 4.7%, respectively. In conclusion, we demonstrated the potential and capability of emission-based methods in deriving patient-specific lung LACs to improve the accuracy of attenuation correction in TOF PET/MR imaging, thus paving the way for their adaptation in the clinic.

Clinical Assessment of Emission- and Segmentation-Based MR-Guided Attenuation Correction in Whole-Body Time-of-Flight PET/MR Imaging

The joint maximum-likelihood reconstruction of activity and attenuation (MLAA) for emission-based attenuation correction has regained attention since the advent of time-of-flight PET/MR imaging. Recently, we improved the performance of the MLAA algorithm using an MR imaging-constrained gaussian mixture model (GMM). In this study, we compare the performance of our proposed algorithm with standard 4-class MR-based attenuation correction (MRAC) implemented on commercial systems.

METHODS

Five head and neck (18)F-FDG patients were scanned on PET/MR imaging and PET/CT scanners. Dixon fat and water MR images were registered to CT images. MRAC maps were derived by segmenting the MR images into 4 tissue classes and assigning predefined attenuation coefficients. For MLAA-GMM, MR images were segmented into known tissue classes, including fat, soft tissue, lung, background air, and an unknown MR low-intensity class encompassing cortical bones, air cavities, and metal artifacts. A coregistered bone probability map was also included in the unknown tissue class. Finally, the GMM prior was constrained over known tissue classes of attenuation maps using unimodal gaussians parameterized over a patient population.

RESULTS

The results showed that the MLAA-GMM algorithm outperformed the MRAC method by differentiating bones from air gaps and providing more accurate patient-specific attenuation coefficients of soft tissue and lungs. It was found that the MRAC and MLAA-GMM methods resulted in average standardized uptake value errors of -5.4% and -3.5% in the lungs, -7.4% and -5.0% in soft tissues/lesions, and -18.4% and -10.2% in bones, respectively.

CONCLUSION

The proposed MLAA algorithm is promising for accurate derivation of attenuation maps on time-of-flight PET/MR systems.

Impact of time-of-flight PET on quantification errors in MR imaging-based attenuation correction

Time-of-flight (TOF) PET/MR imaging is an emerging imaging technology with great capabilities offered by TOF to improve image quality and lesion detectability. We assessed, for the first time, the impact of TOF image reconstruction on PET quantification errors induced by MR imaging-based attenuation correction (MRAC) using simulation and clinical PET/CT studies.

METHODS

Standard 4-class attenuation maps were derived by segmentation of CT images of 27 patients undergoing PET/CT examinations into background air, lung, soft-tissue, and fat tissue classes, followed by the assignment of predefined attenuation coefficients to each class. For each patient, 4 PET images were reconstructed: non-TOF and TOF both corrected for attenuation using reference CT-based attenuation correction and the resulting 4-class MRAC maps. The relative errors between non-TOF and TOF MRAC reconstructions were compared with their reference CT-based attenuation correction reconstructions. The bias was locally and globally evaluated using volumes of interest (VOIs) defined on lesions and normal tissues and CT-derived tissue classes containing all voxels in a given tissue, respectively. The impact of TOF on reducing the errors induced by metal-susceptibility and respiratory-phase mismatch artifacts was also evaluated using clinical and simulation studies.

RESULTS

Our results show that TOF PET can remarkably reduce attenuation correction artifacts and quantification errors in the lungs and bone tissues. Using classwise analysis, it was found that the non-TOF MRAC method results in an error of -3.4% ± 11.5% in the lungs and -21.8% ± 2.9% in bones, whereas its TOF counterpart reduced the errors to -2.9% ± 7.1% and -15.3% ± 2.3%, respectively. The VOI-based analysis revealed that the non-TOF and TOF methods resulted in an average overestimation of 7.5% and 3.9% in or near lung lesions (n = 23) and underestimation of less than 5% for soft tissue and in or near bone lesions (n = 91). Simulation results showed that as TOF resolution improves, artifacts and quantification errors are substantially reduced.

CONCLUSION

TOF PET substantially reduces artifacts and improves significantly the quantitative accuracy of standard MRAC methods. Therefore, MRAC should be less of a concern on future TOF PET/MR scanners with improved timing resolution.

PET-MRI: a review of challenges and solutions in the development of integrated multimodality imaging

The integration of positron emission tomography (PET) and magnetic resonance imaging (MRI) has been an ongoing research topic for the last 20 years. This paper gives an overview of the different developments and the technical problems associated with combining PET and MRI in one system. After explaining the different detector concepts for integrating PET-MRI and minimising interference the limitations and advantages of different solutions for the detector and system are described for preclinical and clinical imaging systems. The different integrated PET-MRI systems are described in detail. Besides detector concepts and system integration the challenges and proposed solutions for attenuation correction and the potential for motion correction and resolution recovery are also discussed in this topical review.

Attenuation correction synthesis for hybrid PET-MR scanners: application to brain studies

Attenuation correction is an essential requirement for quantification of positron emission tomography (PET) data. In PET/CT acquisition systems, attenuation maps are derived from computed tomography (CT) images. However, in hybrid PET/MR scanners, magnetic resonance imaging (MRI) images do not directly provide a patient-specific attenuation map. The aim of the proposed work is to improve attenuation correction for PET/MR scanners by generating synthetic CTs and attenuation maps. The synthetic images are generated through a multi-atlas information propagation scheme, locally matching the MRI-derived patient's morphology to a database of MRI/CT pairs, using a local image similarity measure. Results show significant improvements in CT synthesis and PET reconstruction accuracy when compared to a segmentation method using an ultrashort-echo-time MRI sequence and to a simplified atlas-based method.

Quantitative simultaneous positron emission tomography and magnetic resonance imaging

Simultaneous positron emission tomography and magnetic resonance imaging (PET-MR) is an innovative and promising imaging modality that is generating substantial interest in the medical imaging community, while offering many challenges and opportunities. In this study, we investigated whether MR surface coils need to be accounted for in PET attenuation correction. Furthermore, we integrated motion correction, attenuation correction, and point spread function modeling into a single PET reconstruction framework. We applied our reconstruction framework to in vivo animal and patient PET-MR studies. We have demonstrated that our approach greatly improved PET image quality.

An SPM8-based approach for attenuation correction combining segmentation and nonrigid template formation: application to simultaneous PET/MR brain imaging

We present an approach for head MR-based attenuation correction (AC) based on the Statistical Parametric Mapping 8 (SPM8) software, which combines segmentation- and atlas-based features to provide a robust technique to generate attenuation maps (μ maps) from MR data in integrated PET/MR scanners.

METHODS

Coregistered anatomic MR and CT images of 15 glioblastoma subjects were used to generate the templates. The MR images from these subjects were first segmented into 6 tissue classes (gray matter, white matter, cerebrospinal fluid, bone, soft tissue, and air), which were then nonrigidly coregistered using a diffeomorphic approach. A similar procedure was used to coregister the anatomic MR data for a new subject to the template. Finally, the CT-like images obtained by applying the inverse transformations were converted to linear attenuation coefficients to be used for AC of PET data. The method was validated on 16 new subjects with brain tumors (n = 12) or mild cognitive impairment (n = 4) who underwent CT and PET/MR scans. The μ maps and corresponding reconstructed PET images were compared with those obtained using the gold standard CT-based approach and the Dixon-based method available on the Biograph mMR scanner. Relative change (RC) images were generated in each case, and voxel- and region-of-interest-based analyses were performed.

RESULTS

The leave-one-out cross-validation analysis of the data from the 15 atlas-generation subjects showed small errors in brain linear attenuation coefficients (RC, 1.38% ± 4.52%) compared with the gold standard. Similar results (RC, 1.86% ± 4.06%) were obtained from the analysis of the atlas-validation datasets. The voxel- and region-of-interest-based analysis of the corresponding reconstructed PET images revealed quantification errors of 3.87% ± 5.0% and 2.74% ± 2.28%, respectively. The Dixon-based method performed substantially worse (the mean RC values were 13.0% ± 10.25% and 9.38% ± 4.97%, respectively). Areas closer to the skull showed the largest improvement.

CONCLUSION

We have presented an SPM8-based approach for deriving the head μ map from MR data to be used for PET AC in integrated PET/MR scanners. Its implementation is straightforward and requires only the morphologic data acquired with a single MR sequence. The method is accurate and robust, combining the strengths of both segmentation- and atlas-based approaches while minimizing their drawbacks.

ML-reconstruction for TOF-PET with simultaneous estimation of the attenuation factors

In positron emission tomography (PET), attenuation correction is typically done based on information obtained from transmission tomography. Recent studies show that time-of-flight (TOF) PET emission data allow joint estimation of activity and attenuation images. Mathematical analysis revealed that the joint estimation problem is determined up to a scale factor. In this work, we propose a maximum likelihood reconstruction algorithm that jointly estimates the activity image together with the sinogram of the attenuation factors. The algorithm is evaluated with 2-D and 3-D simulations as well as clinical TOF-PET measurements of a patient scan and compared to reference reconstructions. The robustness of the algorithm to possible imperfect scanner calibration is demonstrated with reconstructions of the patient scan ignoring the varying detector sensitivities.

Comparison of MR-based attenuation correction and CT-based attenuation correction of whole-body PET/MR imaging

PURPOSE

The objective of this study was to evaluate the performance of the built-in MR-based attenuation correction (MRAC) included in the combined whole-body Ingenuity TF PET/MR scanner and compare it to the performance of CT-based attenuation correction (CTAC) as the gold standard.

METHODS

Included in the study were 26 patients who underwent clinical whole-body FDG PET/CT imaging and subsequently PET/MR imaging (mean delay 100 min). Patients were separated into two groups: the alpha group (14 patients) without MR coils during PET/MR imaging and the beta group (12 patients) with MR coils present (neurovascular, spine, cardiac and torso coils). All images were coregistered to the same space (PET/MR). The two PET images from PET/MR reconstructed using MRAC and CTAC were compared by voxel-based and region-based methods (with ten regions of interest, ROIs). Lesions were also compared by an experienced clinician.

RESULTS

Body mass index and lung density showed significant differences between the alpha and beta groups. Right and left lung densities were also significantly different within each group. The percentage differences in uptake values using MRAC in relation to those using CTAC were greater in the beta group than in the alpha group (alpha group -0.2 ± 33.6%, R(2) = 0.98, p < 0.001; beta group 10.31 ± 69.86%, R(2) = 0.97, p < 0.001).

CONCLUSION

In comparison to CTAC, MRAC led to underestimation of the PET values by less than 10% on average, although some ROIs and lesions did differ by more (including the spine, lung and heart). The beta group (imaged with coils present) showed increased overall PET quantification as well as increased variability compared to the alpha group (imaged without coils). PET data reconstructed with MRAC and CTAC showed some differences, mostly in relation to air pockets, metallic implants and attenuation differences in large bone areas (such as the pelvis and spine) due to the segmentation limitation of the MRAC method.

Investigating the use of nonattenuation corrected PET images for the attenuation correction of PET data

PURPOSE

The aim of this study is to investigate the feasibility of using the nonattenuated PET images (PET-NAC) as a means for the AC of PET data.

METHODS

A three-step iterative segmentation process is proposed. In step 1, a patient's body contour is segmented from the PET-NAC using an active contour algorithm. Voxels inside the contour are then assigned a value of 0.096 cm(-1) to represent the attenuation coefficient of soft tissue at 511 keV. This segmented attenuation map is then used to correct for attenuation the raw PET data and the resulting PET images are used as the input to Step 2 of the process. In step 2, the lung region is segmented using an optimal thresholding approach and the corresponding voxels are assigned a value of 0.024 cm(-1) representing the attenuation coefficients of lung tissue at 511 keV. The updated attenuation map is then used for a second time to correct for attenuation the raw PET data, and the resulting PET images are used as the input to step 3. The purpose of Step 3 is to delineate parts of the heart and liver in the lung contour using a region growing approach since these parts were unavoidably excluded in the lung contour in step 2. These parts are then corrected by using a value of 0.096 cm(-1) in the attenuation map. Finally the attenuation coefficients of the bed are included based on CT images to eliminate the impact of the couch on the accuracy of AC. The final attenuation map is then used to AC the raw PET data and generates the final PET image, which we name iterative AC PET (PET-IAC). To assess the proposed segmentation approach, a phantom and 14 patients (with a total of 55 lesions including bone) were scanned on a GE Discovery-RX PET∕CT scanner. PET-IAC images were generated using the proposed process and compared to those of CT-AC PET (PET-CTAC). Visual inspection, lesion SUV, and voxel by voxel histograms between PET-IAC and PET-CTAC for phantom and patient studies were performed to assess the accuracy of image quantification.

RESULTS

Visual inspection showed a small difference in lung parenchyma between the PET-IAC and PET-CTAC. Tumor SUV based on PET-IAC were on average different by 3%±9% (6%±7%) compared to the SUVs from the PET-CTAC in the phantom (patient) studies. For bone lesions only, the average difference was 3%±6%. The histogram comparing PET-CTAC and PET-IAC resulted in an average regression line of y=(1.08±0.07)x+(0.00007±0.0013), with R2=0.978±0.0057.

CONCLUSIONS

Preliminary results suggest that PET-NAC for the AC of PET images is feasible. Such an approach can potentially be used for dedicated PET or PET∕MR hybrid systems while minimizing scan time or potential image artifacts, respectively.

Transmission-less attenuation correction in time-of-flight PET: analysis of a discrete iterative algorithm

The maximum likelihood attenuation correction factors (MLACF) algorithm has been developed to calculate the maximum-likelihood estimate of the activity image and the attenuation sinogram in time-of-flight (TOF) positron emission tomography, using only emission data without prior information on the attenuation. We consider the case of a Poisson model of the data, in the absence of scatter or random background. In this case the maximization with respect to the attenuation factors can be achieved in a closed form and the MLACF algorithm works by updating the activity. Despite promising numerical results, the convergence of this algorithm has not been analysed. In this paper we derive the algorithm and demonstrate that the MLACF algorithm monotonically increases the likelihood, is asymptotically regular, and that the limit points of the iteration are stationary points of the likelihood. Because the problem is not convex, however, the limit points might be saddle points or local maxima. To obtain some empirical insight into the latter question, we present data obtained by applying MLACF to 2D simulated TOF data, using a large number of iterations and different initializations.

Improvement of attenuation correction in time-of-flight PET/MR imaging with a positron-emitting source

Quantitative PET imaging relies on accurate attenuation correction. Recently, there has been growing interest in combining state-of-the-art PET systems with MR imaging in a sequential or fully integrated setup. As CT becomes unavailable for these systems, an alternative approach to the CT-based reconstruction of attenuation coefficients (μ values) at 511 keV must be found. Deriving μ values directly from MR images is difficult because MR signals are related to the proton density and relaxation properties of tissue. Therefore, most research groups focus on segmentation or atlas registration techniques. Although studies have shown that these methods provide viable solutions in particular applications, some major drawbacks limit their use in whole-body PET/MR. Previously, we used an annulus-shaped PET transmission source inside the field of view of a PET scanner to measure attenuation coefficients at 511 keV. In this work, we describe the use of this method in studies of patients with the sequential time-of-flight (TOF) PET/MR scanner installed at the Icahn School of Medicine at Mount Sinai, New York, NY.

METHODS

Five human PET/MR and CT datasets were acquired. The transmission-based attenuation correction method was compared with conventional CT-based attenuation correction and the 3-segment, MR-based attenuation correction available on the TOF PET/MR imaging scanner.

RESULTS

The transmission-based method overcame most problems related to the MR-based technique, such as truncation artifacts of the arms, segmentation artifacts in the lungs, and imaging of cortical bone. Additionally, the TOF capabilities of the PET detectors allowed the simultaneous acquisition of transmission and emission data. Compared with the MR-based approach, the transmission-based method provided average improvements in PET quantification of 6.4%, 2.4%, and 18.7% in volumes of interest inside the lung, soft tissue, and bone tissue, respectively.

CONCLUSION

In conclusion, a transmission-based technique with an annulus-shaped transmission source will be more accurate than a conventional MR-based technique for measuring attenuation coefficients at 511 keV in future whole-body PET/MR studies.

Multi-wave and hybrid imaging techniques: a new direction for nondestructive testing and structural health monitoring

In this article, the state-of-the-art multi-wave and hybrid imaging techniques in the field of nondestructive evaluation and structural health monitoring were comprehensively reviewed. A new direction for assessment and health monitoring of various structures by capitalizing the advantages of those imaging methods was discussed. Although sharing similar system configurations, the imaging physics and principles of multi-wave phenomena and hybrid imaging methods are inherently different. After a brief introduction of nondestructive evaluation (NDE) , structure health monitoring (SHM) and their related challenges, several recent advances that have significantly extended imaging methods from laboratory development into practical applications were summarized, followed by conclusions and discussion on future directions.

Influence and compensation of truncation artifacts in MR-based attenuation correction in PET/MR

The goal of this article is to quantify the influence of truncation artifacts in the magnetic resonance (MR)-based attenuation map (MRMap) on reconstructed positron emission tomography (PET) image volumes and to propose a new method for minimizing this influence.

METHODS

PET data sets of 20 patients investigated in a Philips Ingenuity PET/MR were reconstructed with and without applying two different methods for truncation compensation (TC1 vendor-provided, TC2 newly developed). In this patient group, the extent of truncation artifacts and quality of the truncation compensation (TC) was assessed visually in the MRMaps. In three additional patients MRMaps generated by algorithm TC2 could be compared to the ground truth of transmission-based attenuation maps obtained with a Siemens ECAT HR(+) scanner. The influence of truncation on regional SUVs in lesions, other hot structures (bladder, kidney, myocardium) and the arms was assessed in suitable volume of interests (VOI).

RESULTS

Truncation compensated MRMaps exhibited residual artifacts in the arms in 16 patients for algorithm TC1 and to a lesser extent in eight patients for algorithm TC2. Compared to the transmission-based attenuation maps algorithm TC2 slightly overestimated the size of the truncated arms by 0.3 cm in the radial direction. Without truncation compensation, VOIs located in the trunk showed an average SUVmax underestimation of less than 5.4% relative to the results obtained with TC2. Inside the patients' arms underestimations up to 46.5% were found.

CONCLUSION

In the trunk, standardized uptake values (SUV) underestimations due to truncation artifacts in the MRMap are rather small. Inside the arms, severe SUV underestimations can occur. Therefore, reliable TC is mandatory and can be achieved by applying the newly developed algorithm TC2 which has yielded promising results so far. Implementation of the proposed method is straightforward and should be easily adaptable to other PET/MR systems.