Thorsten Heußer

4D respiratory motion-compensated image reconstruction of free-breathing radial MR data with very high undersampling.

To develop four‐dimensional (4D) respiratory time‐resolved MRI based on free‐breathing acquisition of radial MR data with very high undersampling.

Prior-based artifact correction (PBAC) in computed tomography.

PURPOSE Image quality in computed tomography (CT) often suffers from artifacts which may reduce the diagnostic value of the image. In many cases, these artifacts result from missing or corrupt regions in the projection data, e.g., in the case of metal, truncation, and limited angle artifacts. The authors propose a generalized correction method for different kinds of artifacts resulting from missing or corrupt data by making use of available prior knowledge to perform data completion. METHODS The proposed prior-based artifact correction (PBAC) method requires prior knowledge in form of a planning CT of the same patient or in form of a CT scan of a different patient showing the same body region. In both cases, the prior image is registered to the patient image using a deformable transformation. The registered prior is forward projected and data completion of the patient projections is performed using smooth sinogram inpainting. The obtained projection data are used to reconstruct the corrected image. RESULTS The authors investigate metal and truncation artifacts in patient data sets acquired with a clinical CT and limited angle artifacts in an anthropomorphic head phantom data set acquired with a gantry-based flat detector CT device. In all cases, the corrected images obtained by PBAC are nearly artifact-free. Compared to conventional correction methods, PBAC achieves better artifact suppression while preserving the patient-specific anatomy at the same time. Further, the authors show that prominent anatomical details in the prior image seem to have only minor impact on the correction result. CONCLUSIONS The results show that PBAC has the potential to effectively correct for metal, truncation, and limited angle artifacts if adequate prior data are available. Since the proposed method makes use of a generalized algorithm, PBAC may also be applicable to other artifacts resulting from missing or corrupt data.

Respiratory motion compensation for simultaneous PET/MR based on highly undersampled MR data

PURPOSE Positron emission tomography (PET) of the thorax region is impaired by respiratory patient motion. To account for motion, the authors propose a new method for PET/magnetic resonance (MR) respiratory motion compensation (MoCo), which uses highly undersampled MR data with acquisition times as short as 1 min/bed. METHODS The proposed PET/MR MoCo method (4D jMoCo PET) uses radial MR data to estimate the respiratory patient motion employing MR joint motion estimation and image reconstruction with temporal median filtering. Resulting motion vector fields are incorporated into the system matrix of the PET reconstruction. The proposed approach is evaluated for the thorax region utilizing a PET/MR simulation with 1 min MR acquisition time and simultaneous PET/MR measurements of six patients with MR acquisition times of 1 and 5 min and radial undersampling factors of 11.2 and 2.2, respectively. Reconstruction results are compared to 3D PET, 4D gated PET and a standard MoCo method (4D sMoCo PET), which performs iterative image reconstruction and motion estimation sequentially. Quantitative analysis comprises the parameters SUVmean, SUVmax, full width at half-maximum/lesion volume, contrast and signal-to-noise ratio. RESULTS For simulated PET data, our quantitative analysis shows that the proposed 4D jMoCo PET approach with temporal filtering achieves the best quantification accuracy of all tested reconstruction methods with a mean absolute deviation of 2.3% when compared to the ground truth. For measured PET patient data, the mean absolute deviation of 4D jMoCo PET using a 1 min MR acquisition for motion estimation is 2.1% relative to the 5 min MR acquisition. This demonstrates a robust behavior even in case of strong undersampling at MR acquisition times as short as 1 min. In contrast, 4D sMoCo PET shows considerable reduction of quantification accuracy for the 1 min MR acquisition time. Relative to 3D PET, the proposed 4D jMoCo PET approach with temporal filtering yields an average increase of SUVmean, SUVmax, and contrast of 29.9% and 13.8% for simulated and measured PET data, respectively. CONCLUSIONS Employing artifact-robust motion estimation enables PET/MR respiratory MoCo with MR acquisition times as short as 1 min/bed improving PET image quality and quantification accuracy.

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

BackgroundAccurate 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.ResultsAlthough 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.ConclusionsMLAA 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.

Investigation of the halo-artifact in 68Ga-PSMA-11-PET/MRI

Objectives Combined positron emission tomography (PET) and magnetic resonance imaging (MRI) targeting the prostate-specific membrane antigen (PSMA) with a 68Ga-labelled PSMA-analog (68Ga-PSMA-11) is discussed as a promising diagnostic method for patients with suspicion or history of prostate cancer. One potential drawback of this method are severe photopenic (halo-) artifacts surrounding the bladder and the kidneys in the scatter-corrected PET images, which have been reported to occur frequently in clinical practice. The goal of this work was to investigate the occurrence and impact of these artifacts and, secondly, to evaluate variants of the standard scatter correction method with regard to halo-artifact suppression. Methods Experiments using a dedicated pelvis phantom were conducted to investigate whether the halo-artifact is modality-, tracer-, and/or concentration-dependent. Furthermore, 31 patients with history of prostate cancer were selected from an ongoing 68Ga-PSMA-11-PET/MRI study. For each patient, PET raw data were reconstructed employing six different variants of PET scatter correction: absolute scatter scaling, relative scatter scaling, and relative scatter scaling combined with prompt gamma correction, each of which was combined with a maximum scatter fraction (MaxSF) of MaxSF = 75% or MaxSF = 40%. Evaluation of the reconstructed images with regard to halo-artifact suppression was performed both quantitatively using statistical analysis and qualitatively by two independent readers. Results The phantom experiments did not reveal any modality-dependency (PET/MRI vs. PET/CT) or tracer-dependency (68Ga vs. 18F-FDG). Patient- and phantom-based data indicated that halo-artifacts derive from high organ-to-background activity ratios (OBR) between bladder/kidneys and surrounding soft tissue, with a positive correlation between OBR and halo size. Comparing different variants of scatter correction, reducing the maximum scatter fraction from the default value MaxSF = 75% to MaxSF = 40% was found to efficiently suppress halo-artifacts in both phantom and patient data. In 1 of 31 patients, reducing the maximum scatter fraction provided new PET-based information changing the patient’s diagnosis. Conclusion Halo-artifacts are particularly observed for 68Ga-PSMA-11-PET/MRI due to 1) the biodistribution of the PSMA-11-tracer resulting in large OBRs for bladder and kidneys and 2) inaccurate scatter correction methods currently used in clinical routine, which tend to overestimate the scatter contribution. If not compensated for, 68Ga-PSMA-11 uptake pathologies may be masked by halo-artifacts leading to false-negative diagnoses. Reducing the maximum scatter fraction was found to efficiently suppress halo-artifacts.

Improved clinical workflow for simultaneous whole-body PET/MRI using high-resolution CAIPIRINHA-accelerated MR-based attenuation correction

PURPOSE To explore the value and reproducibility of a novel magnetic resonance based attenuation correction (MRAC) using a CAIPIRINHA-accelerated T1-weighted Dixon 3D-VIBE sequence for whole-body PET/MRI compared to the clinical standard. METHODS The PET raw data of 19 patients from clinical routine were reconstructed with standard MRAC (MRACstd) and the novel MRAC (MRACcaipi), a prototype CAIPIRINHA accelerated Dixon 3D-VIBE sequence, both acquired in 19 s/bed position. Volume of interests (VOIs) for liver, lung and all voxels of the total image stack were created to calculate standardized uptake values (SUVmean) followed by inter-method agreement (Passing-Bablok regression, Bland-Altman analysis). A voxel-wise SUV comparison per patient was performed for intra-individual correlation between MRACstd and MRACcaipi. Difference images (MRACstd-MRACcaipi) of attenuation maps and SUV images were calculated. The image quality of in/opposed-phase water and fat images obtained from MRACcaipi was assessed by two readers on a 5-point Likert-scale including intra-class coefficients for inter-reader agreement. RESULTS SUVmean correlations of VOIs demonstrated high linearity (0.95<Spearmans rho<1, p<0.0001, respectively), substantiated by voxel-wise SUV scatter-plots (1.79×108 pixels). Outliers could be explained by different physiological conditions between the scans such as different segmentation of air-containing tissue, lungs, kidneys, metal implants, diaphragm edge or small air bubbles in the gastrointestinal tracts that moved between MRAC acquisitions. Nasal sinuses and the trachea were better segmented in MRACcaipi. High-resolution T1w Dixon 3D VIBE images were acquired in all cases and could be used for PET/MRI fusion. MRACcaipi images were of high diagnostic quality (4.2±0.8) with 0.92-0.96 intra-class correlation. CONCLUSIONS The novel prototype MRACcaipi extends the value for attenuation correction by providing a high spatial resolution DIXON-based dataset suited for diagnostic assessment towards time-efficient whole-body PET/MRI.

Respiratory motion compensation for simultaneous PET/MR based on a 3D-2D registration of strongly undersampled radial MR data: a simulation study

We propose a new method for PET/MR respiratory motion compensation, which is based on a 3D-2D registration of strongly undersampled MR data and a) runs in parallel with the PET acquisition, b) can be interlaced with clinical MR sequences, and c) requires less than one minute of the total MR acquisition time per bed position. In our simulation study, we applied a 3D encoded radial stack-of-stars sampling scheme with 160 radial spokes per slice and an acquisition time of 38 s. Gated 4D MR images were reconstructed using a 4D iterative reconstruction algorithm. Based on these images, motion vector fields were estimated using our newly-developed 3D-2D registration framework. A 4D PET volume of a patient with eight hot lesions in the lungs and upper abdomen was simulated and MoCo 4D PET images were reconstructed based on the motion vector fields derived from MR. For evaluation, average SUVmean values of the artificial lesions were determined for a 3D, a gated 4D, a MoCo 4D and a reference (with ten-fold measurement time) gated 4D reconstruction. Compared to the reference, 3D reconstructions yielded an underestimation of SUVmean values due to motion blurring. In contrast, gated 4D reconstructions showed the highest variation of SUVmean due to low statistics. MoCo 4D reconstructions were only slightly affected by these two sources of uncertainty resulting in a significant visual and quantitative improvement in terms of SUVmean values. Whereas temporal resolution was comparable to the gated 4D images, signal-to-noise ratio and contrast-to-noise ratio were close to the 3D reconstructions.

Simultaneous reconstruction of attenuation and activity for non–TOF PET/MR using MR prior information

Accurate quantification of the activity distribution in positron emission tomography (PET) mandates attenuation correction (AC). Unlike in PET/CT, AC in PET/MR is, however, challenging, since information about the attenuation properties of the patient tissue distribution is not available directly. Standard MR-based AC (MRAC) does not account for the presence of bone and, thus, yields an underestimation of the activity distribution. We propose an algorithm to simultaneously reconstruct the activity and attenuation distribution using MR images as anatomical prior information for non time-of-flight PET/MR. The proposed algorithm is an extension of the existing maximum-likelihood reconstruction of attenuation and activity (MLAA). The MR images are used to obtain an initial attenuation map and to derive voxel-dependent expectations on the attenuation coefficients. These expectations are modeled using pre-defined attenuation values and Gaussian-like probability functions. An iterative reconstruction scheme incorporating the prior information on the attenuation coefficients is used to update attenuation and activity distribution in an alternating manner. The algorithm, called MR-MLAA, is evaluated for simulated 2D PET data for two patients with artificial lesions in the head region. The proposed algorithm helps recover bone attenuation information. However, for both patients, some misclassifications of air (considered as bone) and bone (considered as air or soft tissue) were observed. Nevertheless, PET quantification in lesions located close to bone tissue is greatly improved when using MR-MLAA. Errors in activity estimation are reduced to ranges of -9% to +1% whereas MRAC yields errors of -22% to -10%. In conclusion, MR-MLAA has the potential to improve quantification in hybrid PET/MR, especially in regions adjacent to dense bone tissue.

MLAA-based RF surface coil attenuation estimation in hybrid PET/MR imaging

Attenuation correction (AC) for both patient and hardware attenuation of the 511 keV annihilation photons is required for accurate PET quantification. In hybrid PET/MR imaging, AC for stationary hardware components such as patient table and MR head coil is performed using CT{derived attenuation templates. AC for flexible hardware components such as MR radiofrequency (RF) surface coils is more challenging. Registration{based approaches, aligning scaled CT{derived attenuation templates with the current patient position, have been proposed but are not used in clinical routine. Ignoring RF coil attenuation has been shown to result in regional activity underestimation values of up to 18 %. We propose to employ a modified version of the maximum{ likelihood reconstruction of attenuation and activity (MLAA) algorithm to obtain an estimate of the RF coil attenuation. Starting with an initial attenuation map not including the RF coil, the attenuation update of MLAA is applied outside the body outline only, allowing to estimate RF coil attenuation without changing the patient attenuation map. Hence, the proposed method is referred to as external MLAA (xMLAA). In this work, xMLAA for RF surface coil attenuation estimation is investigated using phantom and patient data acquired with a Siemens Biograph mMR. For the phantom data, average activity errors compared to the ground truth was reduced from -8:1% to +0:8% when using the proposed method. Patient data revealed an average activity underestimation of -6:1% for the abdominal region and -5:3% for the thoracic region when ignoring RF coil attenuation.

Five-dimensional respiratory and cardiac motion compensation for simultaneous PET/MR

We propose a new method for 5D motion-compensated PET reconstruction, which is based on radial MR data and which compensates for both respiratory and cardiac patient motion. The new method is evaluated for simultaneous 18F-FDG PET/MR acquisitions of four patients with a total acquisition time of 5min per bed position. PET/MR data are sorted into 20 overlapping respiratory phases and 12 overlapping cardiac phases. Respiratory and cardiac motion vector fields are estimated sequentially from MR data employing a novel algorithm, which alternates between MR image reconstruction and motion estimation. For 5D motion-compensated PET reconstruction, the resulting motion vector fields are incorporated into the system matrix. 5D motion-compensated PET images reveal less motion blurring than 3D motion average PET and considerably lower noise levels than 5D double-gated PET reconstructions. Evaluation of the myocardium of the four patients shows a quantitative improvement in terms of SUVmean and contrast when compared to the motion average.