Pulmonary imaging using respiratory motion compensated simultaneous PET/MR

Impact of low injected activity on data driven respiratory gating for PET/CT imaging with continuous bed motion

Data driven respiratory gating (DDG) in positron emission tomography (PET) imaging extracts respiratory waveforms from the acquired PET data obviating the need for dedicated external devices. DDG performance, however, degrades with decreasing detected number of coincidence counts. In this paper, we assess the clinical impact of reducing injected activity on a new DDG algorithm designed for PET data acquired with continuous bed motion (CBM_DDG) by evaluating CBM_DDG waveforms, tumor quantification, and physician's perception of motion blur in resultant images. Forty patients were imaged on a Siemens mCT scanner in CBM mode. Reduced injected activity was simulated by generating list mode datasets with 50% and 25% of the original data (100%). CBM_DDG waveforms were compared to that of the original data over the range between the aortic arch and the center of the right kidney using the Pearson correlation coefficient (PCC). Tumor quantification was assessed by comparing the maximum standardized uptake value (SUVmax) and peak SUV (SUVpeak) of reconstructed images from the various list mode datasets using elastic motion deblurring (EMDB) reconstruction. Perceived motion blur was assessed by three radiologists of one lesion per patient on a continuous scale from no motion blur (0) to significant motion blur (3). The mean PCC of the 50% and 25% dataset waveforms was 0.74 ± 0.18 and 0.59 ± 0.25, respectively. In comparison to the 100% datasets, the mean SUVmax increased by 2.25% (p = 0.11) for the 50% datasets and by 3.91% (p = 0.16) for the 25% datasets, while SUVpeak changes were within ±0.25%. Radiologist evaluations of motion blur showed negligible changes with average values of 0.21, 0.3, and 0.28 for the 100%, 50%, and 25% datasets. Decreased injected activities degrades the resultant CBM_DDG respiratory waveforms; however this decrease has minimal impact on quantification and perceived image motion blur.

MR-assisted PET respiratory motion correction using deep-learning based short-scan motion fields

PURPOSE

We evaluated the impact of PET respiratory motion correction (MoCo) in a phantom and patients. Moreover, we proposed and examined a PET MoCo approach using motion vector fields (MVFs) from a deep-learning reconstructed short MRI scan.

METHODS

The evaluation of PET MoCo was performed in a respiratory motion phantom study with varying lesion sizes and tumor to background ratios (TBRs) using a static scan as the ground truth. MRI-based MVFs were derived from either 2000 spokes (MoCo₂₀₀₀ , 5-6 min acquisition time) using a Fourier transform reconstruction or 200 spokes (MoCo_P2P200 , 30-40 s acquisition time) using a deep-learning Phase2Phase (P2P) reconstruction and then incorporated into PET MoCo reconstruction. For six patients with hepatic lesions, the performance of PET MoCo was evaluated using quantitative metrics (SUV_max , SUV_peak , SUV_mean , lesion volume) and a blinded radiological review on lesion conspicuity.

RESULTS

MRI-assisted PET MoCo methods provided similar results to static scans across most lesions with varying TBRs in the phantom. Both MoCo₂₀₀₀ and MoCo_P2P200 PET images had significantly higher SUV_max , SUV_peak , SUV_mean and significantly lower lesion volume than non-motion-corrected (non-MoCo) PET images. There was no statistical difference between MoCo₂₀₀₀ and MoCo_P2P200 PET images for SUV_max , SUV_peak , SUV_mean or lesion volume. Both radiological reviewers found that MoCo₂₀₀₀ and MoCo_P2P200 PET significantly improved lesion conspicuity.

CONCLUSION

An MRI-assisted PET MoCo method was evaluated using the ground truth in a phantom study. In patients with hepatic lesions, PET MoCo images improved quantitative and qualitative metrics based on only 30-40 s of MRI motion modeling data.

Chest PET/MRI in Solid Cancers: Comparing the Diagnostic Performance of a Free-Breathing 3D-T1-GRE Stack-of-Stars Volume Interpolated Breath-Hold Examination (StarVIBE) Acquisition With That of a 3D-T1-GRE Volume Interpolated Breath-Hold Examination (VIBE) for Chest Staging During Whole-Body PET/MRI

BACKGROUND

Whole-body positron emission tomography/magnetic resonance imaging (WB-PET/MRI) is increasingly used in oncology. However, chest staging remains challenging.

PURPOSE

To compare the diagnostic performance of a free-breathing 3D-T1-GRE stack-of-stars volume interpolated breath-hold examination (StarVIBE) with that of a 3D-T1-GRE volume interpolated breath-hold examination (VIBE) during WB-PET/MRI for chest staging.

STUDY TYPE

Retrospective, cohort study.

POPULATION

One hundred and twenty-three patients were referred for initial staging of solid cancer, 46 of whom had pulmonary nodules and 14 had pulmonary metastasis.

FIELD STRENGTH/SEQUENCE

Free-breathing 3D-T1-GRE stack-of-stars (StarVIBE) and Cartesian 3D-T1-GRE VIBE at 3.0 T.

ASSESSMENT

Image quality was assessed using a 4-point scale and using the signal-to-noise ratio (SNR) of lung parenchyma and contrast-to-noise ratio (CNR) of pulmonary nodules. Diagnostic performances of both sequences were determined by three independent radiologists for detection of pulmonary nodules, lymph node involvement, and bone metastases using chest CT, pathology, and follow-up as reference standards.

STATISTICAL TESTS

Paired Student's t-test; chi-squared; Fisher's exact test. A P value <0.05 was considered statistically significant.

RESULTS

StarVIBE quality was judged as better in 34% of cases and at least equivalent to VIBE in 89% of cases, with significantly higher quality scores (4 [4-4] vs. 3 [3-4], respectively). SNR and CNR values were significantly higher with StarVIBE (8 ± 1.3 and 9.7 ± 4.6, respectively) than with VIBE (1.8 ± 0.2 and 5.5 ± 3.3, respectively). Compared to VIBE, StarVIBE showed significantly higher sensitivity (73% [95% CI 62-82] vs. 44% [95% CI 33-55], respectively) and specificity (95% [95% CI 88-99] vs. 67% [95% CI 56-77]) for pulmonary nodules detection and significantly higher sensitivity (100% [95% CI 89-100] vs. 67% [95% CI 48-82], respectively) for detection of lymph node involvement. Sensitivities for bone metastases detection were not significantly different (100% [95% CI 88-100] vs. 82% [95% CI 63-94], P = 0.054).

DATA CONCLUSION

Owing to improved SNR and CNR and spatial resolution, a free-breathing 3D stack-of-stars T1-GRE sequence improves chest staging in comparison with standard 3D-T1-GRE VIBE and may be integrated in WB-PET/MRI acquisitions for initial staging of solid cancer.

LEVEL OF EVIDENCE

3 TECHNICAL EFFICACY: Stage 2.

Synergistic motion compensation strategies for positron emission tomography when acquired simultaneously with magnetic resonance imaging

Subject motion in positron emission tomography (PET) is a key factor that degrades image resolution and quality, limiting its potential capabilities. Correcting for it is complicated due to the lack of sufficient measured PET data from each position. This poses a significant barrier in calculating the amount of motion occurring during a scan. Motion correction can be implemented at different stages of data processing either during or after image reconstruction, and once applied accurately can substantially improve image quality and information accuracy. With the development of integrated PET-MRI (magnetic resonance imaging) scanners, internal organ motion can be measured concurrently with both PET and MRI. In this review paper, we explore the synergistic use of PET and MRI data to correct for any motion that affects the PET images. Different types of motion that can occur during PET-MRI acquisitions are presented and the associated motion detection, estimation and correction methods are reviewed. Finally, some highlights from recent literature in selected human and animal imaging applications are presented and the importance of motion correction for accurate kinetic modelling in dynamic PET-MRI is emphasized. This article is part of the theme issue 'Synergistic tomographic image reconstruction: part 2'.

Additional Value of Integrated 18F-FDG PET/MRI for Evaluating Biliary Tract Cancer: Comparison with Contrast-Enhanced CT

Objective

To evaluate the value of ¹⁸F-fluorodeoxyglucose PET/MRI added to contrast-enhanced CT (CECT) in initial staging, assessment of resectability, and postoperative follow-up of biliary tract cancer.

Materials and Methods

This retrospective study included 100 patients (initial workup [n = 65] and postoperative follow-up [n = 35]) who had undergone PET/MRI and CECT for bile duct or gallbladder lesions between January 2013 and March 2020. Two radiologists independently reviewed the CECT imaging set and CECT plus PET/MRI set to determine the likelihood of malignancy, local and overall resectability, and distant metastasis in the initial workup group, and local recurrence and distant metastasis in the follow-up group. Diagnostic performances of the two imaging sets were compared using clinical-surgical-pathologic findings as standards of reference.

Results

The diagnostic performance of CECT significantly improved after the addition of PET/MRI for liver metastasis (area under the receiver operating characteristic curve [A_z]: 0.77 vs. 0.91 [p = 0.027] for reviewer 1; 0.76 vs. 0.92 [p = 0.021] for reviewer 2), lymph node metastasis (0.73 vs. 0.92 [p = 0.004]; 0.81 vs. 0.92 [p = 0.023]), and overall resectability (0.79 vs. 0.92 [p = 0.007]; 0.82 vs. 0.94 [p = 0.021]) in the initial workup group. In the follow-up group, the diagnostic performance of CECT plus PET/MRI was significantly higher than that of CECT imaging for local recurrence (0.81 vs. 1.00 [p = 0.029]; 0.82 vs. 0.94 [p = 0.045]).

Conclusion

PET/MRI may add value to CECT in patients with biliary tract cancer both in the initial workup for staging and determination of overall resectability and in follow-up for local recurrence.

A super-resolution framework for the reconstruction of T2-weighted (T2w) time-resolved (TR) 4DMRI using T1w TR-4DMRI as the guidance

PURPOSE

The purpose of this study was to develop T2-weighted (T2w) time-resolved (TR) four-dimensional magnetic resonance imaging (4DMRI) reconstruction technique with higher soft-tissue contrast for multiple breathing cycle motion assessment by building a super-resolution (SR) framework using the T1w TR-4DMRI reconstruction as guidance.

METHODS

The multi-breath T1w TR-4DMRI was reconstructed by deforming a high-resolution (HR: 2 × 2 × 2 mm³ ) volumetric breath-hold (BH, 20s) three-dimensional magnetic resonance imaging (3DMRI) image to a series of low-resolution (LR: 5 × 5 × 5 mm³ ) 3D cine images at a 2Hz frame rate in free-breathing (FB, 40 s) using an enhanced Demons algorithm, namely [T1^BH →FB] reconstruction. Within the same imaging session, respiratory-correlated (RC) T2w 4DMRI (2 × 2 × 2 mm³ ) was acquired based on an internal navigator to gain HR T2w (T2^HR ) in three states (full exhalation and mid and full inhalation) in ~5 min. Minor binning artifacts in the RC-4DMRI were automatically identified based on voxel intensity correlation (VIC) between consecutive slices as outliers (VIC < VIC^mean -σ) and corrected by deforming the artifact slices to interpolated slices from the adjacent slices iteratively until no outliers were identified. A T2^HR image with minimal deformation (<1 cm at the diaphragm) from the T1^BH image was selected for multi-modal B-Spline deformable image registration (DIR) to establish the T2^HR -T1^BH voxel correspondence. Two approaches to reconstruct T2w TR-4DMRI were investigated: (A) T2^HR →[T1^BH →FB]: to deform T2w HR to T1w BH only as T1w TR-4DMRI was reconstructed, and combine the two displacement vector fields (DVFs) to reconstruct T2w TR-4DMRI, and (B) [T2^HR ←T1^BH ]→FB: to deform T1w BH to T2w HR first and apply the deformed T1w BH to reconstruct T2w TR-4DMRI. The reconstruction times were similar, 8-12 min per volume. To validate the two methods, T2w- and T1w-mapped 4D XCAT digital phantoms were utilized with three synthetic spherical tumors (ϕ = 2.0, 3.0, and 4.0 cm) in the lower or mid lobes as the ground truth to evaluate the tumor location (the center of mass, COM), size (volume ratio, %V), and shape (Dice index). Six lung cancer patients were scanned under an IRB-approved protocol and the T2w TR-4DMRI images reconstructed from the two methods were compared based on the preservation of the three tumor characteristics. The local tumor-contained image quality was also characterized using the VIC and structure similarity (SSIM) indexes.

RESULTS

In the 4D digital phantom, excellent tumor alignment after T2^HR -T1^HR DIR is achieved: ∆COM = 0.8 ± 0.5 mm, %V = 1.06 ± 0.02, and Dice = 0.91 ± 0.03, in both deformation directions using the DIR-target image as the reference. In patients, binning artifacts are corrected with improved image quality: average VIC increases from 0.92 ± 0.03 to 0.95 ± 0.01. Both T2w TR-4DMRI reconstruction methods produce similar tumor alignment errors ∆COM = 2.9 ± 0.6 mm. However, method B ([T2^HR ←T1^BH ]→FB) produces superior results in preserving more T2w tumor features with a higher %V = 0.99 ± 0.03, Dice = 0.81 ± 0.06, VIC = 0.85 ± 0.06, and SSIM = 0.65 ± 0.10 in the T2w TR-4DMRI images.

CONCLUSIONS

This study has demonstrated the feasibility of T2w TR-4DMRI reconstruction with high soft-tissue contrast and adequately-preserved tumor position, size, and shape in multiple breathing cycles. The T2w-centric DIR (method B) produces a superior solution for the SR-based framework of T2w TR-4DMRI reconstruction with highly preserved tumor characteristics and local image features, which are useful for tumor delineation and motion management in radiation therapy.

Performing clinical 18F-FDG-PET/MRI of the mediastinum optimising a dedicated, patient-friendly protocol

OBJECTIVE

To construct a mediastinal-specific fluorine-18-fluorodeoxyglucose (F-FDG)-PET/MR protocol with high-quality MRI of minimal acquisition-time and comparable diagnostic value to F-FDG-PET/computed tomography (CT).

MATERIALS AND METHODS

Fifteen healthy participants received PET/MRI and 10 patients with mediastinal tumours (eight non-small-cell lung, two oesophageal cancer) received F-FDG-PET/MRI immediately after F-FDG-PET/CT. Sequences volume interpolated breath-hold examination (T1-VIBE) and Half-Fourier acquisition single-shot turbo spin echo (T2-HASTE) were optimised by varying the parameters: breath-hold (BH, end-expiration), fat suppression (spectral adiabatic inversion recovery), and ECG-triggering (ECG, end-diastole). Image quality (IQ) of each sequence-variation was qualitatively scored by medical experts and quantitatively assessed by calculating signal-to-noise ratios, contrast relative to muscle, standardized-uptake-value, and tumour-to-blood ratios. Patient comfort was evaluated on patients' experience. Diagnostic accuracy of F-FDG-PET/MRI was compared to F-FDG-PET/CT, in reference to histopathology/cytopathology.

RESULTS

ECG-triggered T1-VIBE images showed the highest signal-to-noise ratio (P < 0.01) and the largest contrast between mediastinal soft-tissues, regardless of BH or free-breathing acquisition. IQ of ECG-triggered T1-VIBE scans in BH were scored qualitatively highest with good reader agreement (κ = 0.62). IQ of T2-HASTE was not significantly affected by BH acquisition (P > 0.9). Qualitative IQ of T1-VIBE and T2-HASTE declined after spectral adiabatic inversion recovery fat-suppression. All patients could maintain BH at end-expiration and reported no discomfort. Diagnostic performance of F-FDG-PET/MR was not significantly different from F-FDG-PET/CT with comparable staging, standardized-uptake-values, and tumour-to-blood ratios. However, T-status was more often over-staged on F-FDG-PET/CT, while N-status was more frequently under-staged on F-FDG-PET/MR.

CONCLUSION

ECG-triggered T1-VIBE sequences acquired during short, multiple BHs are recommended for mediastinal imaging using F-FDG-PET/MR. With dedicated protocols, F-FDG-PET/MRI will be useful in thoracic oncology and aid in diagnostic evaluation and tailored treatment decision-making.

MR-based cardiac and respiratory motion correction of PET: application to static and dynamic cardiac 18F-FDG imaging

Motion of the myocardium deteriorates the quality and quantitative accuracy of cardiac PET images. We present a method for MR-based cardiac and respiratory motion correction of cardiac PET data and evaluate its impact on estimation of activity and kinetic parameters in human subjects. Three healthy subjects underwent simultaneous dynamic ¹⁸F-FDG PET and MRI on a hybrid PET/MR scanner. A cardiorespiratory motion field was determined for each subject using navigator, tagging and golden-angle radial MR acquisitions. Acquired coincidence events were binned into cardiac and respiratory phases using electrocardiogram and list mode-driven signals, respectively. Dynamic PET images were reconstructed with MR-based motion correction (MC) and without motion correction (NMC). Parametric images of ¹⁸F-FDG consumption rates (K_i) were estimated using Patlak's method for both MC and NMC images. MC alleviated motion artifacts in PET images, resulting in improved spatial resolution, improved recovery of activity in the myocardium wall and reduced spillover from the myocardium to the left ventricle cavity. Significantly higher myocardium contrast-to-noise ratio and lower apparent wall thickness were obtained in MC versus NMC images. Likewise, parametric images of K_i calculated with MC data had improved spatial resolution as compared to those obtained with NMC. Consistent with an increase in reconstructed activity concentration in the frames used during kinetic analyses, MC led to the estimation of higher K_i values almost everywhere in the myocardium, with up to 18% increase (mean across subjects) in the septum as compared to NMC. This study shows that MR-based motion correction of cardiac PET results in improved image quality that can benefit both static and dynamic studies.

Higher-order singular value decomposition-based lung parcellation for breathing motion management

Positron emission tomography (PET) imaging of the lungs is confounded by respiratory motion-induced blurring artifacts that degrade quantitative accuracy. Gating and motion-compensated image reconstruction are frequently used to correct these motion artifacts in PET. In the absence of voxel-by-voxel deformation measures, surrogate signals from external markers are used to track internal motion and generate gated PET images. The objective of our work is to develop a group-level parcellation framework for the lungs to guide the placement of markers depending on the location of the internal target region. We present a data-driven framework based on higher-order singular value decomposition (HOSVD) of deformation tensors that enables identification of synchronous areas inside the torso and on the skin surface. Four-dimensional (4-D) magnetic resonance (MR) imaging based on a specialized radial pulse sequence with a one-dimensional slice-projection navigator was used for motion capture under free-breathing conditions. The deformation tensors were computed by nonrigidly registering the gated MR images. Group-level motion signatures obtained via HOSVD were used to cluster the voxels both inside the volume and on the surface. To characterize the parcellation result, we computed correlation measures across the different regions of interest (ROIs). To assess the robustness of the parcellation technique, leave-one-out cross-validation was performed over the subject cohort, and the dependence of the result on varying numbers of gates and singular value thresholds was examined. Overall, the parcellation results were largely consistent across these test cases with Jaccard indices reflecting high degrees of overlap. Finally, a PET simulation study was performed which showed that, depending on the location of the lesion, the selection of a synchronous ROI may lead to noticeable gains in the recovery coefficient. Accurate quantitative interpretation of PET images is important for lung cancer management. Therefore, a guided motion monitoring approach is of utmost importance in the context of pulmonary PET imaging.

Magnetic Resonance-based Motion Correction for Quantitative PET in Simultaneous PET-MR Imaging

Motion degrades image quality and quantitation of PET images, and is an obstacle to quantitative PET imaging. Simultaneous PET-MR offers a tool that can be used for correcting the motion in PET images by using anatomic information from MR imaging acquired concurrently. Motion correction can be performed by transforming a set of reconstructed PET images into the same frame or by incorporating the transformation into the system model and reconstructing the motion-corrected image. Several phantom and patient studies have validated that MR-based motion correction strategies have great promise for quantitative PET imaging in simultaneous PET-MR.

Application of the 4-D XCAT Phantoms in Biomedical Imaging and Beyond

The four-dimensional (4-D) eXtended CArdiac-Torso (XCAT) series of phantoms was developed to provide accurate computerized models of the human anatomy and physiology. The XCAT series encompasses a vast population of phantoms of varying ages from newborn to adult, each including parameterized models for the cardiac and respiratory motions. With great flexibility in the XCAT's design, any number of body sizes, different anatomies, cardiac or respiratory motions or patterns, patient positions and orientations, and spatial resolutions can be simulated. As such, the XCAT phantoms are gaining a wide use in biomedical imaging research. There they can provide a virtual patient base from which to quantitatively evaluate and improve imaging instrumentation, data acquisition, techniques, and image reconstruction and processing methods which can lead to improved image quality and more accurate clinical diagnoses. The phantoms have also found great use in radiation dosimetry, radiation therapy, medical device design, and even the security and defense industry. This review paper highlights some specific areas in which the XCAT phantoms have found use within biomedical imaging and other fields. From these examples, we illustrate the increasingly important role that computerized phantoms and computer simulation are playing in the research community.

Impact of motion compensation and partial volume correction for 18F-NaF PET/CT imaging of coronary plaque

Recent studies have suggested that ¹⁸F-NaF-PET enables visualization and quantification of plaque micro-calcification in the coronary tree. However, PET imaging of plaque calcification in the coronary arteries is challenging because of the respiratory and cardiac motion as well as partial volume effects. The objective of this work is to implement an image reconstruction framework, which incorporates compensation for respiratory as well as cardiac motion (MoCo) and partial volume correction (PVC), for cardiac ¹⁸F-NaF PET imaging in PET/CT. We evaluated the effect of MoCo and PVC on the quantification of vulnerable plaques in the coronary arteries. Realistic simulations (Biograph TPTV, Biograph mCT) and phantom acquisitions (Biograph mCT) were used for these evaluations. Different uptake values in the calcified plaques were evaluated in the simulations, while three 'plaque-type' lesions of 36, 31 and 18 mm³ were included in the phantom experiments. After validation, the MoCo and PVC methods were applied in four pilot NaF-PET patient studies. In all cases, the MoCo-based image reconstruction was performed using the STIR software. The PVC was obtained from a local projection (LP) method, previously evaluated in preclinical and clinical PET. The results obtained show a significant increase of the measured lesion-to-background ratios (LBR) in the MoCo  +  PVC images. These ratios were further enhanced when using directly the tissue-activities from the LP method, making this approach more suitable for the quantitative evaluation of coronary plaques. When using the LP method on the MoCo images, LBR increased between 200% and 1119% in the simulated data, between 212% and 614% in the phantom experiments and between 46% and 373% in the plaques with positive uptake observed in the pilot patients. In conclusion, we have built and validated a STIR framework incorporating MoCo and PVC for ¹⁸F-NaF PET imaging of coronary plaques. First results indicate an improved quantification of plaque-type lesions.

Technical and instrumentational foundations of PET/MRI

This paper highlights the origins of combined positron emission tomography (PET) and magnetic resonance imaging (MRI) whole-body systems that were first introduced for applications in humans in 2010. This text first covers basic aspects of each imaging modality before describing the technical and methodological challenges of combining PET and MRI within a single system. After several years of development, combined and even fully-integrated PET/MRI systems have become available and made their way into the clinic. This multi-modality imaging system lends itself to the advanced exploration of diseases to support personalized medicine in a long run. To that extent, this paper provides an introduction to PET/MRI methodology and important technical solutions.

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 SUV_mean, SUV_max, 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 SUV_mean, SUV_max, 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.

Impact of motion and partial volume effects correction on PET myocardial perfusion imaging using simultaneous PET-MR

PET is an established modality for myocardial perfusion imaging (MPI) which enables quantification of absolute myocardial blood flow (MBF) using dynamic imaging and kinetic modeling. However, heart motion and partial volume effects (PVE) significantly limit the spatial resolution and quantitative accuracy of PET MPI. Simultaneous PET-MR offers a solution to the motion problem in PET by enabling MR-based motion correction of PET data. The aim of this study was to develop a motion and PVE correction methodology for PET MPI using simultaneous PET-MR, and to assess its impact on both static and dynamic PET MPI using 18F-Flurpiridaz, a novel 18F-labeled perfusion tracer. Two dynamic 18F-Flurpiridaz MPI scans were performed on healthy pigs using a PET-MR scanner. Cardiac motion was tracked using a dedicated tagged-MRI (tMR) sequence. Motion fields were estimated using non-rigid registration of tMR images and used to calculate motion-dependent attenuation maps. Motion correction of PET data was achieved by incorporating tMR-based motion fields and motion-dependent attenuation coefficients into image reconstruction. Dynamic and static PET datasets were created for each scan. Each dataset was reconstructed as (i) Ungated, (ii) Gated (end-diastolic phase), and (iii) Motion-Corrected (MoCo), each without and with point spread function (PSF) modeling for PVE correction. Myocardium-to-blood concentration ratios (MBR) and apparent wall thickness were calculated to assess image quality for static MPI. For dynamic MPI, segment- and voxel-wise MBF values were estimated by non-linear fitting of a 2-tissue compartment model to tissue time-activity-curves. MoCo and Gating respectively decreased mean apparent wall thickness by 15.1% and 14.4% and increased MBR by 20.3% and 13.6% compared to Ungated images (P  <  0.01). Combined motion and PSF correction (MoCo-PSF) yielded 30.9% (15.7%) lower wall thickness and 82.2% (20.5%) higher MBR compared to Ungated data reconstructed without (with) PSF modeling (P  <  0.01). For dynamic PET, mean MBF across all segments were comparable for MoCo (0.72  ±  0.21 ml/min/ml) and Gating (0.69  ±  0.18 ml/min/ml). Ungated data yielded significantly lower mean MBF (0.59  ±  0.16 ml/min/ml). Mean MBF for MoCo-PSF was 0.80  ±  0.22 ml/min/ml, which was 37.9% (25.0%) higher than that obtained from Ungated data without (with) PSF correction (P  <  0.01). The developed methodology holds promise to improve the image quality and sensitivity of PET MPI studies performed using PET-MR.

Innovations in Small-Animal PET/MR Imaging Instrumentation

Multimodal imaging has led to a more detailed exploration of different physiologic processes with integrated PET/MR imaging being the most recent entry. Although the clinical need is still questioned, it is well recognized that it represents one of the most active and promising fields of medical imaging research in terms of software and hardware. The hardware developments have moved from small detector components to high-performance PET inserts and new concepts in full systems. Conversely, the software focuses on the efficient performance of necessary corrections without the use of CT data. The most recent developments in both directions are reviewed.