Claes Ladefoged

Combined PET/MR imaging in neurology: MR-based attenuation correction implies a strong spatial bias when ignoring bone☆

AIM Combined PET/MR systems have now become available for clinical use. Given the lack of integrated standard transmission (TX) sources in these systems, attenuation and scatter correction (AC) must be performed using the available MR-images. Since bone tissue cannot easily be accounted for during MR-AC, PET quantification can be biased, in particular, in the vicinity of the skull. Here, we assess PET quantification in PET/MR imaging of patients using phantoms and patient data. MATERIALS AND METHODS Nineteen patients referred to our clinic for a PET/CT exam as part of the diagnostic evaluation of suspected dementia were included in our study. The patients were injected with 200MBq [(18)F]FDG and imaged with PET/CT and PET/MR in random sequence within 1h. Both, PET/CT and PET/MR were performed as single-bed acquisitions without contrast administration. PET/CT and PET/MR data were reconstructed following CT-based and MR-based AC, respectively. MR-AC was performed based on: (A) standard Dixon-Water-Fat segmentation (DWFS), (B) DWFS with co-registered and segmented CT bone values superimposed, and (C) with co-registered full CT-based attenuation image. All PET images were reconstructed using AW-OSEM, with neither resolution recovery nor time-of-flight option employed. PET/CT (D) or PET/MR (A-C) images were decay-corrected to the start time of the first examination. PET images following AC were evaluated visually and quantitatively using 10 homeomorphic regions of interest drawn on a transaxial T1w-MR image traversing the central basal ganglia. We report the relative difference (%) of the mean ROI values for (A)-(C) in reference to PET/CT (D). In a separate phantom experiment a 2L plastic bottle was layered with approximately 12mm of Gypsum plaster to mimic skull bone. The phantom was imaged on PET/CT only and standard MR-AC was performed by replacing hyperdense CT attenuation values corresponding to bone (plaster) with attenuation values of water. PET image reconstruction was performed with CT-AC (D) and CT-AC using the modified CT images corresponding to MR-AC using DWFS (A). RESULTS PET activity values in patients following MR-AC (A) showed a substantial radial dependency when compared to PET/CT. In all patients cortical PET activity was lower than the activity in the central region of the brain (10-15%). When adding bone attenuation values to standard MR-AC (B and C) the radial gradient of PET activity values was removed. Further evaluation of PET/MR activity following MR-AC (A) relative to MR-AC (C) using the full CT for attenuation correction showed an underestimation of 25% in the cortical regions and 5-10% in the central regions of the brain. Observations in patients were replicated by observations from the phantom study. CONCLUSION Our phantom and patient data demonstrate a spatially varying bias of the PET activity in PET/MR images of the brain when bone tissue is not accounted for during attenuation correction. This has immediate implications for PET/MR imaging of the brain. Therefore, refinements to existing MR-AC methods or alternative strategies need to be found prior to adopting PET/MR imaging of the brain in clinical routine and research.

Whole-body PET/MRI: The effect of bone attenuation during MR-based attenuation correction in oncology imaging

PURPOSE In combined PET/MRI standard PET attenuation correction (AC) is based on tissue segmentation following dedicated MR sequencing and, typically, bone tissue is not represented. We evaluate PET quantification in whole-body (WB)-PET/MRI following MR-AC without considering bone attenuation and then investigate different strategies to account for bone tissue in clinical PET/MR imaging. To this purpose, bone tissue representation was extracted from separate CT images, and different bone representations were simulated from hypothetically derived MR-based bone classifications. METHODS Twenty oncology patients referred for a PET/CT were injected with either [18F]-FDG or [18F]-NaF and imaged on PET/CT (Biograph TruePoint/mCT, Siemens) and PET/MRI (mMR, Siemens) following a standard single-injection, dual-imaging clinical WB-protocol. Routine MR-AC was based on in-/opposed-phase MR imaging (orgMR-AC). PET(/MRI) images were reconstructed (AW-OSEM, 3 iterations, 21 subsets, 4mm Gaussian) following routine MR-AC and MR-AC based on four modified attenuation maps. These modified attenuation maps were created for each patient by non-linear co-registration of the CT images to the orgMR-AC images, and adding CT bone mask values representing cortical bone: 1200HU (cortCT), spongiosa bone: 350HU (spongCT), average CT value (meanCT) and original CT values (orgCT). Relative difference images of the PET following AC using the modified attenuation maps were compared. SUVmean was calculated in anatomical reference regions and for PET-positive lesions. RESULTS The relative differences in SUVmean across patients following orgMR-AC and orgCT in soft tissue lesions and in bone lesions were similar (range: 0.0% to -22.5%), with an average underestimation of SUVmean of 7.2% and 10.0%, respectively when using orgMR-AC. In bone lesions, spongCT values were closest to orgCT (median bias of 1.3%, range: -9.0% to 13.5%) while the overestimation of SUVmean with respect to orgCT was highest for cortCT (40.8%, range: 1.5% to 110.8%). For soft tissue lesions the bias was highest using cortCT (13.4%, range: -2.3% to 17.3%) and lowest for spongCT (-2.2%, range: 0.0% to -13.7%). CONCLUSIONS In PET/MR imaging using standard MR-AC PET uptake values in soft lesions and bone lesions are underestimated by about 10%. In individual patients this bias can be as high as 22%, which is significant during clinical follow-up exams. If bone segmentation is available, then assigning a fixed attenuation value of spongious bone to all bone structures appears reasonable and results in only a minor bias of 5%, or less in uptake values of soft tissue and bone lesions.

Region specific optimization of continuous linear attenuation coefficients based on UTE (RESOLUTE): application to PET/MR brain imaging

The reconstruction of PET brain data in a PET/MR hybrid scanner is challenging in the absence of transmission sources, where MR images are used for MR-based attenuation correction (MR-AC). The main challenge of MR-AC is to separate bone and air, as neither have a signal in traditional MR images, and to assign the correct linear attenuation coefficient to bone. The ultra-short echo time (UTE) MR sequence was proposed as a basis for MR-AC as this sequence shows a small signal in bone. The purpose of this study was to develop a new clinically feasible MR-AC method with patient specific continuous-valued linear attenuation coefficients in bone that provides accurate reconstructed PET image data. A total of 164 [(18)F]FDG PET/MR patients were included in this study, of which 10 were used for training. MR-AC was based on either standard CT (reference), UTE or our method (RESOLUTE). The reconstructed PET images were evaluated in the whole brain, as well as regionally in the brain using a ROI-based analysis. Our method segments air, brain, cerebral spinal fluid, and soft tissue voxels on the unprocessed UTE TE images, and uses a mapping of R(*)2 values to CT Hounsfield Units (HU) to measure the density in bone voxels. The average error of our method in the brain was 0.1% and less than 1.2% in any region of the brain. On average 95% of the brain was within  ±10% of PETCT, compared to 72% when using UTE. The proposed method is clinically feasible, reducing both the global and local errors on the reconstructed PET images, as well as limiting the number and extent of the outliers.

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.

Impact of incorrect tissue classification in Dixon-based MR-AC: fat-water tissue inversion

BackgroundThe current MR-based attenuation correction (AC) used in combined PET/MR systems computes a Dixon attenuation map (MR-ACDixon) based on fat and water images derived from in- and opposed-phase MRI. We observed an occasional fat/water inversion in MR-ACDixon. The aim of our study was to estimate the prevalence of this phenomenon in a large patient cohort and assess the possible bias on PET data.MethodsPET/MRI was performed on a Siemens Biograph mMR (Siemens AG, Erlangen, Germany). We visually inspected attenuation maps of 283 brain or head/neck (H/N) patients, classified them as non-inverted or inverted, and calculated the fat/water tissue fraction. We selected ten FDG-PET brain patients with non-inverted attenuation maps for further analysis. Tissue inversion was simulated, and PET images were reconstructed using both original and inverted attenuation maps. The FDG-PET images of the ten brain patients were analyzed using 11 concentric annulus regions of 5 mm width placed over a central transaxial image plane traversing PETDixon.ResultsOut of the 283 patients, a fat/water inversion in 23 patients (8.1%) was observed. The average fraction of fat in the correct MR-ACDixon was 13% for brain and 17% for H/N patients. In the inverted cases, we found an average fat fraction of 56% for the brain patients and 41% for the H/N patients. The effect of the simulated tissue inversion in the brain studies was clearly seen on AC-PET images. The percent-difference image revealed a radial error where the largest difference was at the ventricles (30% ± 3%) and smallest at the cortical region (10% ± 2%).ConclusionsTissue inversion in Dixon MRI is well known and can occur when there is an error in the off-resonance correction method. Tissue inversion needs to be considered if, based on Dixon-AC, the construction of normal PET databases is performed or any quantitative physiological parameters are fitted. Visual inspection is needed if Dixon-AC is to be used in clinical routine.

Optimized MLAA for quantitative non-TOF PET/MR of the brain

For quantitative tracer distribution in positron emission tomography, attenuation correction is essential. In a hybrid PET/CT system the CT images serve as a basis for generation of the attenuation map, but in PET/MR, the MR images do not have a similarly simple relationship with the attenuation map. Hence attenuation correction in PET/MR systems is more challenging. Typically either of two MR sequences are used: the Dixon or the ultra-short time echo (UTE) techniques. However these sequences have some well-known limitations. In this study, a reconstruction technique based on a modified and optimized non-TOF MLAA is proposed for PET/MR brain imaging. The idea is to tune the parameters of the MLTR applying some information from an attenuation image computed from the UTE sequences and a T1w MR image. In this MLTR algorithm, an [Formula: see text] parameter is introduced and optimized in order to drive the algorithm to a final attenuation map most consistent with the emission data. Because the non-TOF MLAA is used, a technique to reduce the cross-talk effect is proposed. In this study, the proposed algorithm is compared to the common reconstruction methods such as OSEM using a CT attenuation map, considered as the reference, and OSEM using the Dixon and UTE attenuation maps. To show the robustness and the reproducibility of the proposed algorithm, a set of 204 [18F]FDG patients, 35 [11C]PiB patients and 1 [18F]FET patient are used. The results show that by choosing an optimized value of [Formula: see text] in MLTR, the proposed algorithm improves the results compared to the standard MR-based attenuation correction methods (i.e. OSEM using the Dixon or the UTE attenuation maps), and the cross-talk and the scale problem are limited.

Positron Emission Tomography/Magnetic Resonance Hybrid Scanner Imaging of Cerebral Blood Flow Using 15O-Water Positron Emission Tomography and Arterial Spin Labeling Magnetic Resonance Imaging in Newborn Piglets

Abnormality in cerebral blood flow (CBF) distribution can lead to hypoxic–ischemic cerebral damage in newborn infants. The aim of the study was to investigate minimally invasive approaches to measure CBF by comparing simultaneous 15O-water positron emission tomography (PET) and single TI pulsed arterial spin labeling (ASL) magnetic resonance imaging (MR) on a hybrid PET/MR in seven newborn piglets. Positron emission tomography was performed with IV injections of 20 MBq and 100 MBq 15O-water to confirm CBF reliability at low activity. Cerebral blood flow was quantified using a one-tissue-compartment-model using two input functions: an arterial input function (AIF) or an image-derived input function (IDIF). The mean global CBF (95% CI) PET-AIF, PET-IDIF, and ASL at baseline were 27 (23; 32), 34 (31; 37), and 27 (22; 32) mL/100 g per minute, respectively. At acetazolamide stimulus, PET-AIF, PET-IDIF, and ASL were 64 (55; 74), 76 (70; 83) and 79 (67; 92) mL/100 g per minute, respectively. At baseline, differences between PET-AIF, PET-IDIF, and ASL were 22% (P < 0.0001) and −0.7% (P = 0.9). At acetazolamide, differences between PET-AIF, PET-IDIF, and ASL were 19% (P = 0.001) and 24% (P = 0.0003). In conclusion, PET-IDIF overestimated CBF. Injected activity of 20 MBq 15O-water had acceptable concordance with 100 MBq, without compromising image quality. Single TI ASL was questionable for regional CBF measurements. Global ASL CBF and PET CBF were congruent during baseline but not during hyperperfusion.

Automatic correction of dental artifacts in PET/MRI

Abstract. A challenge when using current magnetic resonance (MR)-based attenuation correction in positron emission tomography/MR imaging (PET/MRI) is that the MRIs can have a signal void around the dental fillings that is segmented as artificial air-regions in the attenuation map. For artifacts connected to the background, we propose an extension to an existing active contour algorithm to delineate the outer contour using the nonattenuation corrected PET image and the original attenuation map. We propose a combination of two different methods for differentiating the artifacts within the body from the anatomical air-regions by first using a template of artifact regions, and second, representing the artifact regions with a combination of active shape models and k-nearest-neighbors. The accuracy of the combined method has been evaluated using 25 F18-fluorodeoxyglucose PET/MR patients. Results showed that the approach was able to correct an average of 97±3% of the artifact areas.

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.

PET/MR attenuation correction in brain imaging using a continuous bone signal derived from UTE

In the absence of transmission sources in combined clinical PET/MR systems, MR images are used for MR-based attenuation correction (MRAC). The main challenge in MR-AC is to separate the bone and air, as neither have a signal in the MR images. In the attenuation maps supplied by the vendor, a single value is assigned to bone using an ultra-short echo time (UTE) MR sequence. The purpose of this study was to develop a new multi-class segmentation-based MR-AC method, employing Continuous-Bone-using-R2* (MRAC_CBuR2*), and evaluate it on a large patient cohort. 53 [18F]-FDG PET/MR brain patients were included in this study. MRAC was based on an aligned CT (MRAC_CT, used as reference), standard MRAC_UTE and MRAC_CBuR2*. Our method segments the air, brain, CSF and soft tissue voxels on the UTE images, and uses a mapping of R2* values to HU to measure the density in bone voxels. Aligned anatomical masks are used to improve accuracy in noisy regions. Region-based analysis was performed using ICBM 2009a brain atlas with anatomical labels pre-defined. Using CBuR2*, 82% of the voxels in the brain are within ±5% of PET_CT, compared to 27% when using UTE. Using our method, there are clear improvements over UTE. The average error over the full brain is 0.8% (±1.7%), compared to -7.1% (±2.4%) in UTE. Of note, the maximum error in the cerebellum is -15% and 7% in UTE and CBuR2*, respectively. The proposed method uses the available UTE images to segment tissue classes, and uses the R2* map to measure a continuous bone signal. The improvement over the vendor provided UTE reduces both the global and local error on the reconstructed PET images.