Respiratory Motion Correction Research Articles

Image Registration of 18F-FDG PET/CT Using the MotionFree Algorithm and CT Protocols through Phantom Study and Clinical Evaluation.

We evaluated the benefits of the MotionFree algorithm through phantom and patient studies. The various sizes of phantom and vacuum vials were linked to RPM moving with or without MotionFree application. A total of 600 patients were divided into six groups by breathing protocols and CT scanning time. Breathing protocols were applied as follows: (a) patients who underwent scanning without any breathing instructions; (b) patients who were instructed to hold their breath after expiration during CT scan; and (c) patients who were instructed to breathe naturally. The length of PET/CT misregistration was measured and we defined the misregistration when it exceeded 10 mm. In the phantom tests, the images produced by the MotionFree algorithm were observed to have excellent agreement with static images. There were significant differences in PET/CT misregistration according to CT scanning time and each breathing protocol. When applying the type (c) protocol, decreasing the CT scanning time significantly reduced the frequency and length of misregistrations (p < 0.05). The MotionFree application is able to correct respiratory motion artifacts and to accurately quantify lesions. The shorter time of CT scan can reduce the frequency, and the natural breathing protocol also decreases the lengths of misregistrations.

MR-guided motion-corrected PET image reconstruction for cardiac PET-MR.

Simultaneous PET-MR imaging has shown potential for the comprehensive assessment of myocardial health from a single examination. Furthermore, MR-derived respiratory motion information has been shown to improve PET image quality by incorporating this information into the PET image reconstruction. Separately, MR-based anatomically guided PET image reconstruction has been shown to perform effective denoising, but this has been so far demonstrated mainly in brain imaging. To date the combined benefits of motion compensation and anatomical guidance have not been demonstrated for myocardial PET-MR imaging. This work addresses this by proposing a single cardiac PET-MR image reconstruction framework which fully utilises MR-derived information to allow both motion compensation and anatomical guidance within the reconstruction. Methods: Fifteen patients underwent a 18F-FDG cardiac PET-MR scan with a previously introduced acquisition framework. The MR data processing and image reconstruction pipeline produces respiratory motion fields and a high-resolution respiratory motion-corrected MR image with good tissue contrast. This MR-derived information was then included in a respiratory motion-corrected, cardiac-gated, anatomically guided image reconstruction of the simultaneously acquired PET data. Reconstructions were evaluated by measuring myocardial contrast and noise and compared to images from several comparative intermediate methods using the components of the proposed framework separately. Results: Including respiratory motion correction, cardiac gating, and anatomical guidance significantly increased contrast. In particular, myocardium-to-blood pool contrast increased by 143% on average (p<0.0001) compared to conventional uncorrected, non-guided PET images. Furthermore, anatomical guidance significantly reduced image noise compared to non-guided image reconstruction by 16.1% (p<0.0001). Conclusion: The proposed framework for MR-derived motion compensation and anatomical guidance of cardiac PET data was shown to significantly improve image quality compared to alternative reconstruction methods. Each component of the reconstruction pipeline was shown to have a positive impact on the final image quality. These improvements have the potential to improve clinical interpretability and diagnosis based on cardiac PET-MR images.

Respiratory motion correction for enhanced quantification of hepatic lesions in simultaneous PET and DCE-MR imaging

Simultaneous positron-emission tomography (PET)-magnetic resonance (MR) imaging is a hybrid technique in oncological hepatic imaging combining soft-tissue and functional contrast of dynamic contrast enhanced MR (DCE-MR) with metabolic information from PET. In this context, respiratory motion represents a major challenge by introducing blurring, artifacts and misregistration in the liver. In this work, we propose a free-breathing 3D non-rigid respiratory motion correction framework for simultaneously acquired DCE-MR and PET data, which makes use of higher spatial resolution MR data to derive motion information used directly during image reconstruction to minimize image blurring and motion artifacts. The main aim was to increase contrast of hepatic metastases to improve their detection and characterization. DCE-MR data were acquired at 3T through a golden radial phase encoding scheme, enabling derivation of motion fields. These were used in the motion compensated image reconstruction of DCE-MR time-series (48 time-points, 6 s temporal resolution, 1.5 mm isotropic spatial resolution) and 3D PET activity map, which was subsequently interpolated to the DCE-MR resolution. The extended Tofts model was fitted to DCE-MR data, obtaining functional parametric maps related to perfusion such as the endothelial permeability (). Fifty-seven hepatic metastases were identified and analyzed. Quantitative evaluations of motion correction in PET images demonstrated average percentage increases of 16% ± 5% (mean ± SD) in Contrast (C), 18% ± 6% in SUVmean and 14% ± 2% in SUVmax, while DCE-MR and scored contrast-to-noise-ratio increases of 64% ± 3% and 90% ± 6%, respectively. Motion-corrected data visually showed improved image contrast of hepatic metastases and effectively reduced blurring and motion artefacts. Scatter plots of SUVmean versus suggested that the proposed framework improved differentiation of measurements. The presented motion correction framework for simultaneously acquired PET-DCE-MR data provides accurately aligned images with increased contrast of hepatic lesions allowing for improved detection and characterization.

Prospective data-driven respiratory gating of [68Ga]Ga-DOTATOC PET/CT

AimThe aim of this prospective study was to evaluate a data-driven gating software’s performance, in terms of identifying the respiratory signal, comparing [68Ga]Ga-DOTATOC and [18F]FDG examinations. In addition, for the [68Ga]Ga-DOTATOC examinations, tracer uptake quantitation and liver lesion detectability were assessed.MethodsTwenty-four patients with confirmed or suspected neuroendocrine tumours underwent whole-body [68Ga]Ga-DOTATOC PET/CT examinations. Prospective DDG was applied on all bed positions and respiratory motion correction was triggered automatically when the detected respiratory signal exceeded a certain threshold (R value ≥ 15), at which point the scan time for that bed position was doubled. These bed positions were reconstructed with quiescent period gating (QPG), retaining 50% of the total coincidences. A respiratory signal evaluation regarding the software’s efficacy in detecting respiratory motion for [68Ga]Ga-DOTATOC was conducted and compared to [18F]FDG data. Measurements of SUVmax, SUVmean, and tumour volume were performed on [68Ga]Ga-DOTATOC PET and compared between gated and non-gated images.ResultsThe threshold of R ≥ 15 was exceeded and gating triggered on mean 2.1 bed positions per examination for [68Ga]Ga-DOTATOC as compared to 1.4 for [18F]FDG. In total, 34 tumours were evaluated in a quantitative analysis. An increase of 25.3% and 28.1%, respectively, for SUVmax (P < 0.0001) and SUVmean (P < 0.0001), and decrease of 21.1% in tumour volume (P < 0.0001) was found when DDG was applied.ConclusionsHigh respiratory signal was exclusively detected in bed positions where respiratory motion was expected, indicating reliable performance of the DDG software on [68Ga]Ga-DOTATOC PET/CT. DDG yielded significantly higher SUVmax and SUVmean values and smaller tumour volumes, as compared to non-gated images.

Gastrointestinal 4D MRI with respiratory motion correction.

Gastrointestinal motion patterns such as peristalsis and segmental contractions can alter the shape and position of the stomach and intestines with respect to other irradiated organs during radiation therapy. Unfortunately, these deformations are concealed by conventional four-dimensional (4D)-MRI techniques, which were developed to visualize respiratory motion by binning acquired data into respiratory motion states without considering the phases of GI motion. We present a method to reconstruct breathing-compensated images showing the phases of periodic gastric motion and study the effect of this motion on regional anatomical structures. Sixty-seven DCE-MRI examinations were performed on patients undergoing MRI simulation for hepatocellular carcinoma using a golden-angle stack-of-stars sequence that collected 2000 radial spokes over 5min. The collected data were reconstructed using a method with integrated respiratory motion correction into a time series of 3D image volumes without visible breathing motion. From this series, a gastric motion signal was extracted by temporal filtering of time-intensity curves in the stomach. Using this motion signal, breathing-corrected back-projection images were sorted according to the gastric phase and reconstructed into 21 gastric motion state images showing the phases of gastric motion. Reconstructed image volumes showed gastric motion states clearly with no visible breathing motion or related artifacts. The mean frequency of the gastric motion signal was 3cycles/min with a standard deviation of 0.27cycles/min. Periodic gastrointestinal motion can be visualized without confounding respiratory motion using the presented GI 4D MRI technique. GI 4D MRIs may help define internal target volumes for treatment planning, aid in planning organ at risk volume definition, or support motion model development for gastrointestinal motion tracking algorithms for real-time MR-guided radiation therapy.

Clinical Evaluation of MR-Gated Respiratory Motion Correction in Simultaneous PET/MRI.

The recently available gated T1-weighted imaging with the Dixon technique enables the synchronized gating signal for both MR acquisition and PET reconstruction. Herein, we evaluated the clinical value of this MR-gated PET reconstruction in the thoracic-abdominal PET/MRI compared with non-MR-gated method. Twenty patients (28 hypermetabolic target lesions) underwent PET/MRI. Four types of PET images were reconstructed: non-MR-gating + gated attenuation correction (AC) (group A), MR-gating + gated AC (group B), non-MR-gating + breath-hold (BH) AC (group C), and MR-gating + BH AC (group D). A 4-point objective scale (from well match to obvious mismatch was scored from 3 to 0) was proposed to evaluate the mismatch. The detection rate and quantitative metrics were also evaluated. In the patient-based analysis, for groups A through D, the detection rates were 90%, 100%, 85%, and 90% as well as 95%, 100%, 85%, and 85%, assessed by readers 1 and 2, respectively, and significant difference of mismatch score was observed with the highest proportion of 3 points in group B (85%, 90%, 35%, and 40%, and 80%, 90%, 35%, and 20%, assessed by readers 1 and 2, respectively). The lesion-based analysis demonstrated significant differences in quantitative metrics for groups A through D (all P's < 0.05), with the highest quantitative metrics in group B (SUVmax: 7.49 ± 3.37, 8.45 ± 3.82, 6.90 ± 3.24, and 7.69 ± 3.50; SUVmean: 3.90 ± 1.60, 4.34 ± 1.84, 3.67 ± 1.61, and 4.03 ± 1.81; SUVpeak: 5.60 ± 2.50, 6.10 ± 2.80, 5.22 ± 2.40, and 5.65 ± 2.68; signal-to-noise ratio: 136.06 ± 90.58, 136.24 ± 81.63, 99.52 ± 53.16, and 107.57 ± 69.05). The MR-gated reconstruction using gated AC reduced the mismatch between MR and PET images and improved the thoracic-abdominal PET image quality in simultaneous PET/MRI systems.

Impact of PET data driven respiratory motion correction and BSREM reconstruction of 68Ga-DOTATATE PET/CT for differentiating neuroendocrine tumors (NET) and intrapancreatic accessory spleens (IPAS)

To evaluate whether quantitative PET parameters of motion-corrected 68Ga-DOTATATE PET/CT can differentiate between intrapancreatic accessory spleens (IPAS) and pancreatic neuroendocrine tumor (pNET). A total of 498 consecutive patients with neuroendocrine tumors (NET) who underwent 68Ga-DOTATATE PET/CT between March 2017 and July 2019 were retrospectively analyzed. Subjects with accessory spleens (n = 43, thereof 7 IPAS) and pNET (n = 9) were included, resulting in a total of 45 scans. PET images were reconstructed using ordered-subsets expectation maximization (OSEM) and a fully convergent iterative image reconstruction algorithm with β-values of 1000 (BSREM1000). A data-driven gating (DDG) technique (MOTIONFREE, GE Healthcare) was applied to extract respiratory triggers and use them for PET motion correction within both reconstructions. PET parameters among different samples were compared using non-parametric tests. Receiver operating characteristics (ROC) analyzed the ability of PET parameters to differentiate IPAS and pNETs. SUVmax was able to distinguish pNET from accessory spleens and IPAs in BSREM1000 reconstructions (p < 0.05). This result was more reliable using DDG-based motion correction (p < 0.003) and was achieved in both OSEM and BSREM1000 reconstructions. For differentiating accessory spleens and pNETs with specificity 100%, the ROC analysis yielded an AUC of 0.742 (sensitivity 56%)/0.765 (sensitivity 56%)/0.846 (sensitivity 62%)/0.840 (sensitivity 63%) for SUVmax 36.7/41.9/36.9/41.7 in OSEM/BSREM1000/OSEM + DDG/BSREM1000 + DDG, respectively. BSREM1000 + DDG can accurately differentiate pNET from accessory spleen. Both BSREM1000 and DDG lead to a significant SUV increase compared to OSEM and non-motion-corrected data.

A fast navigator (fastNAV) for prospective respiratory motion correction in first-pass myocardial perfusion imaging.

PurposeTo develop and evaluate a fast respiratory navigator (fastNAV) for cardiac MR perfusion imaging with subject‐specific prospective slice tracking.MethodsA fastNAV was developed for dynamic contrast‐enhanced cardiac MR perfusion imaging by combining spatially nonselective saturation with slice‐selective tip‐up and slice‐selective excitation pulses. The excitation slice was angulated from the tip‐up slice in the transverse plane to overlap only in the right hemidiaphragm for suppression of signal outside the right hemidiaphragm. A calibration scan was developed to enable the estimation of subject‐specific tracking factors. Perfusion imaging using subject‐specific fastNAV‐based slice tracking was then compared to a conventional sequence (ie, without slice tracking) in 10 patients under free‐breathing conditions. Respiratory motion in perfusion images was quantitatively assessed by measuring the average overlap of the left ventricle across images (avDice, 0:no overlap/1:perfect overlap) and the average displacement of the center of mass of the left ventricle (avCoM). Image quality was subjectively assessed using a 4‐point scoring system (1: poor, 4: excellent).ResultsThe fastNAV calibration was successfully performed in all subjects (average tracking factor of 0.46 ± 0.13, R = 0.94 ± 0.03). Prospective motion correction using fastNAV led to higher avDice (0.94 ± 0.02 vs. 0.90 ± 0.03, P < .001) and reduced avCoM (4.03 ± 0.84 vs. 5.22 ± 1.22, P < .001). There were no statistically significant differences between the 2 sequences in terms of image quality (both sequences: median = 3 and interquartile range = 3‐4, P = 1).ConclusionfastNAV enables fast and robust right hemidiaphragm motion tracking in a perfusion sequence. In combination with subject‐specific slice tracking, fastNAV reduces the effect of respiratory motion during free‐breathing cardiac MR perfusion imaging.

Clinical evaluation of three respiratory gating schemes for different respiratory patterns on cardiac SPECT.

Respiratory gating reduces respiratory blur in cardiac single photon emission computed tomography (SPECT). It can be implemented as three gating schemes: (a) equal amplitude-based gating (AG); (b) phase or time-based gating (TG); or (c) equal count-based gating (CG), that is, a variant of amplitude-based method. The goal of this study is to evaluate the effectiveness of these respiratory gating methods for patients with different respiratory patterns in myocardial perfusion SPECT. We reviewed 1274 anonymized patient respiratory traces obtained via the Vicon motion-tracking system during their 99m Tc-sestamibi SPECT scans and grouped them into four breathing categories: (a) regular respiration (RR); (b) periodic respiration (PR); (c) respiration with apnea (AR); and (d) unclassified respiration (UR). For each respiratory pattern, 15 patients were randomly selected and their list-mode data were rebinned using the three gating schemes. A preliminary reconstruction was performed for each gate with the heart region segmented and registered to a reference gate to estimate the respiratory motion. A final reconstruction incorporating respiratory motion correction was done to get a final image set. The estimated respiratory motion, the full-width-at-half-maxima (FWHM) measured across the image intensity profile of the left ventricle wall, as well as the normalized standard deviation measured in a uniform cuboid region of the thorax were analyzed. There are 47.1%, 24.3%, 13.5%, and 15.1% RR, PR, AR, and UR patients, respectively, among the 1274 patients in this study. The differences among the three gating schemes in RR were smaller than other respiratory patterns. The AG and CG methods showed statistically larger motion estimation than TG particularly in the AR and PR patterns. Noise of AG varied more in different gates, especially for AR and UR patterns. More than half of the patients reviewed exhibited nonregular breathing patterns. Amplitude-based gating, that is, AG and CG, is a preferred gating method for such patterns and is a robust respiratory gating implementation method given the respiratory pattern of the patients is unknown before data acquisition. Phase gating is also a feasible option for regular respiratory pattern.

Respiratory motion-compensated high-resolution 3D whole-heart T1\u03c1 mapping

BackgroundCardiovascular magnetic resonance (CMR) T1ρ mapping can be used to detect ischemic or non-ischemic cardiomyopathy without the need of exogenous contrast agents. Current 2D myocardial T1ρ mapping requires multiple breath-holds and provides limited coverage. Respiratory gating by diaphragmatic navigation has recently been exploited to enable free-breathing 3D T1ρ mapping, which, however, has low acquisition efficiency and may result in unpredictable and long scan times. This study aims to develop a fast respiratory motion-compensated 3D whole-heart myocardial T1ρ mapping technique with high spatial resolution and predictable scan time.MethodsThe proposed electrocardiogram (ECG)-triggered T1ρ mapping sequence is performed under free-breathing using an undersampled variable-density 3D Cartesian sampling with spiral-like order. Preparation pulses with different T1ρ spin-lock times are employed to acquire multiple T1ρ-weighted images. A saturation prepulse is played at the start of each heartbeat to reset the magnetization before T1ρ preparation. Image navigators are employed to enable beat-to-beat 2D translational respiratory motion correction of the heart for each T1ρ-weighted dataset, after which, 3D translational registration is performed to align all T1ρ-weighted volumes. Undersampled reconstruction is performed using a multi-contrast 3D patch-based low-rank algorithm. The accuracy of the proposed technique was tested in phantoms and in vivo in 11 healthy subjects in comparison with 2D T1ρ mapping. The feasibility of the proposed technique was further investigated in 3 patients with suspected cardiovascular disease. Breath-hold late-gadolinium enhanced (LGE) images were acquired in patients as reference for scar detection.ResultsPhantoms results revealed that the proposed technique provided accurate T1ρ values over a wide range of simulated heart rates in comparison to a 2D T1ρ mapping reference. Homogeneous 3D T1ρ maps were obtained for healthy subjects, with septal T1ρ of 58.0 ± 4.1 ms which was comparable to 2D breath-hold measurements (57.6 ± 4.7 ms, P = 0.83). Myocardial scar was detected in 1 of the 3 patients, and increased T1ρ values (87.4 ± 5.7 ms) were observed in the infarcted region.ConclusionsAn accelerated free-breathing 3D whole-heart T1ρ mapping technique was developed with high respiratory scan efficiency and near-isotropic spatial resolution (1.7 × 1.7 × 2 mm3) in a clinically feasible scan time of ~ 6 mins. Preliminary patient results suggest that the proposed technique may find applications in non-contrast myocardial tissue characterization.

Respiratory Motion Detection and Correction for MR Using the Pilot Tone

The aim of this study was to develop a method for tracking respiratory motion throughout full MR or PET/MR studies that requires only minimal additional hardware and no modifications to the sequences. Patient motion that is caused by respiration affects the quality of the signal of the individual radiofrequency receive coil elements. This effect can be detected as a modulation of a monofrequent signal that is emitted by a small portable transmitter placed inside the bore (Pilot Tone). The frequency is selected such that it is located outside of the frequency band of the actual MR readout experiment but well within the bandwidth of the radiofrequency receiver, that is, the oversampling area. Temporal variations of the detected signal indicate motion. After extraction of the signal from the raw data, principal component analysis was used to identify respiratory motion. The approach and potential applications during MR and PET/MR examinations that rely on a continuous respiratory signal were validated with an anthropomorphic, PET/MR-compatible motion phantom as well as in a volunteer study. Respiratory motion detection and correction were presented for MR and PET data in phantom and volunteer studies. The Pilot Tone successfully recovered the ground-truth respiratory signal provided by the phantom. The presented method provides reliable respiratory motion tracking during arbitrary imaging sequences throughout a full PET/MR study. All results can directly be transferred to MR-only applications as well.

Characterization of continuous bed motion effects on patient breathing and respiratory motion correction in PET/CT imaging.

Continuous bed motion (CBM) was recently introduced as an alternative to step‐and‐shoot (SS) mode for PET/CT data acquisition. In CBM, the patient is continuously advanced into the scanner at a preset speed, whereas in SS, the patient is imaged in overlapping bed positions. Previous investigations have shown that patients preferred CBM over SS for PET data acquisition. In this study, we investigated the effect of CBM versus SS on patient breathing and respiratory motion correction. One hundred patients referred for PET/CT were scanned using a Siemens mCT scanner. Patient respiratory waveforms were recorded using an Anzai system and analyzed using four methods: Methods 1 and 2 measured the coefficient of variation (COV) of the respiratory cycle duration (RCD) and amplitude (RCA). Method 3 measured the respiratory frequency signal prominence (RSP) and method 4 measured the width of the HDChest optimal gate (OG) window when using a 35% duty cycle. Waveform analysis was performed over the abdominothoracic region which exhibited the greatest respiratory motion and the results were compared between CBM and SS. Respiratory motion correction was assessed by comparing the ratios of SUVmax, SUVpeak, and CNR of focal FDG uptake, as well as Radiologists’ visual assessment of corresponding image quality of motion corrected and uncorrected images for both acquisition modes. The respiratory waveforms analysis showed that the RCD and RCA COV were 3.7% and 33.3% lower for CBM compared to SS, respectively, while the RSP and OG were 30.5% and 2.0% higher, respectively. Image analysis on the other hand showed that SUVmax, SUVpeak, and CNR were 8.5%, 4.5%, and 3.4% higher for SS compared to CBM, respectively, while the Radiologists’ visual comparison showed similar image quality between acquisition modes. However, none of the results showed statistically significant differences between SS and CBM, suggesting that motion correction is not impacted by acquisition mode.

Improving perfusion defect detection with respiratory motion correction in cardiac SPECT at standard and reduced doses

BackgroundIn cardiac SPECT perfusion imaging, respiratory motion can cause non-uniform blurring in the reconstructed myocardium. We investigate the potential benefit of respiratory correction with respiratory-binned acquisitions, both at standard dose and at reduced dose, for defect detection and for left ventricular (LV) wall resolution. MethodsWe applied two reconstruction methods for respiratory motion correction: post-reconstruction motion correction (PMC) and motion-compensated reconstruction (MCR), and compared with reconstruction without motion correction (Non-MC). We quantified the presence of perfusion defects in reconstructed images by using the total perfusion deficit (TPD) scores and conducted receiver-operating-characteristic (ROC) studies using TPD. We quantified the LV spatial resolution by using the FWHM of its cross-sectional intensity profile. ResultsThe values in the area-under-the-ROC-curve (AUC) achieved by MCR, PMC, and Non-MC at standard dose were 0.835, 0.830, and 0.798, respectively. Similar AUC improvements were also obtained by MCR and PMC over Non-MC at 50%, 25%, and 12.5% of full dose. Improvements in LV resolution were also observed with motion correction. ConclusionsRespiratory-binned acquisitions can improve perfusion-defect detection accuracy over traditional reconstruction both at standard dose and at reduced dose. Motion correction may contribute to achieving further dose reduction while maintaining the diagnostic accuracy of traditional acquisitions.

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 (Ki) 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 Ki 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 Ki 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.

Simultaneous respiratory motion correction and image reconstruction in 4D-multi pinhole small animal SPECT.

Respiratory motion in the chest region during single photon emission computed tomography (SPECT) is a major degrading factor that reduces the accuracy of image quantification. This effect is more notable when the tumor is very small, or the spatial resolution of the imaging system is less than the respiratory motion amplitude. Small animals imaging systems with sub-millimeter spatial resolution need more attention to the respiratory motion for quantitative studies. We developed a motion-embedded four-dimensional (4D)-multi pinhole SPECT (MPS) reconstruction algorithm for respiratory motion correction. This algorithm makes full use of projection statistics for reconstruction of every individual frame. The ROBY phantom with small tumors in liver was generated in eight different phases during one respiratory cycle. The MPS projections were modeled using a fast ray tracing method simulating an MPS acquisition. Individual frames were reconstructed and used for motion estimation. The Demons non-rigid registration algorithm was used to calculate deformation vector fields (DVFs) for simultaneous motion correction and image reconstruction. A motion-embedded 4D-MPS method was used to reconstruct images using all the projections and corresponding DVFs, simultaneously. The 4D-MPS reconstructed images were compared to the low-count single frame (LCSF) reconstructed image, the three-dimensional (3D)-MPS images reconstructed using individual frames, and post reconstruction registration (PRR) that aligns all individual phases to a reference frame using Demons-derived DVFs. The tumor volume relative error (TVE), tumor contrast relative error (TCE), and dice index (DI) for 2, 3, and 4mm liver were calculated and compared for different reconstruction methods. For the 4D-MPS reconstruction method, TVE was reduced and DI was higher compared to PRR, 3D-MPS, and LCSF. The extent of the improvement was higher for the small tumor size (i.e. 2mm). For the biggest tumor in contrast 3 (i.e. 4mm) TVE for 4D-MPS, PRR, 3D-MPS and, LCSF were 1.33%, 8%, 8%, and 14.67%, respectively. The results suggest that motion-embedded 4D-MPS method is an effective and practical way for respiratory motion correction. It reconstructs high quality gated frames while using all projection data to reconstruct each frame.

Respiratory motion correction for liver contrast-enhanced ultrasound by automatic selection of a reference image.

Respiratory motion correction is necessary for the quantitative analysis of liver contrast-enhanced ultrasound (CEUS) image sequences. Most respiratory motion correction methods are based on the dual mode of CEUS image sequences, including contrast and grayscale image sequences. Due to free-breathing motion, the acquired two-dimensional (2D) ultrasound cine might show the in-plane and out-of-plane motion of tumors. The registration of an entire 2D ultrasound contrast image sequence based on out-of-plane images is ineffective. For the respiratory motion correction of CEUS sequences, the reference image is usually considered the standard for the deletion of any out-of-plane images. Most methods used for the selection of the reference image are subjective in nature. Here, a quantitative selection method for an optimal reference image from CEUS image sequences in the B mode and contrast mode was explored. The original high-dimensional ultrasound grayscale image data were mapped into a two-dimensional space using Laplacian Eigenmaps (LE), and K-means clustering was adopted. The center image of the larger cluster with a near-peak contrast intensity was considered the optimal ultrasound reference image. In the ultrasound grayscale image sequence, the images with the maximum correlations to the reference image in the same time interval were selected as the corrected image sequence. The effectiveness of this proposed method was then validated on 18 CEUS cases of VX2 tumors in rabbit livers. Correction smoothed the time-intensity curves (TICs) extracted from the region of interest of the CEUS image sequences. Before correction, the average of the total mean structural similarity (TMSSIM) and the average of the mean correlation coefficient (MCC) from the image sequences were 0.45±0.11 and 0.67±0.16, respectively, and after correction, the average TMSSIM and MCC increased (P<0.001) by 31% to 0.59±0.11 and by 21% to 0.81±0.11, respectively. The average deviation value (DV) index of the TICs from the image sequences prior to correction was 92.16±18.12, and correction reduced the average to 31.71±7.31. The average TMSSIM and MCC values after correction using the mean frame of the reference image (MBMFRI) were clearly lower than those after correction using the proposed method (P<0.001). Moreover, the average DV after correction using the MBMFRI was obviously higher than that after correction using the proposed method (P<0.001). The breathing frequency of rabbits is notably faster than that of human beings, but the proposed correction method could reduce the effect of the respiratory motion in the CEUS image sequences. The reference image was selected quantitatively, which could improve the accuracy of the quantitative analysis of rabbit liver CEUS sequences using the reference image method based on the current standard of manual selection and the MBMFRI. Thiseasy-to-operatemethod can potentially be used in both animal studies and clinical applications.

PET/CT-guided biopsy with respiratory motion correction

Given the ability of positron emission tomography (PET) imaging to localize malignancies in heterogeneous tumors and tumors that lack an X-ray computed tomography (CT) correlate, combined PET/CT-guided biopsy may improve the diagnostic yield of biopsies. However, PET and CT images are naturally susceptible to problems due to respiratory motion, leading to imprecise tumor localization and shape distortion. To facilitate PET/CT-guided needle biopsy, we developed and investigated the feasibility of a workflow that allows to bring PET image guidance into interventional CT suite while accounting for respiratory motion. The performance of PET/CT respiratory motion correction using registered and summed phases method was evaluated through computer simulations using the mathematical 4D extended cardiac-torso phantom, with motion simulated from real respiratory traces. The performance of PET/CT-guided biopsy procedure was evaluated through operation on a physical anthropomorphic phantom. Vials containing radiolabeled 18F-fluorodeoxyglucose were placed within the physical phantom thorax as biopsy targets. We measured the average distance between target center and the simulated biopsy location among multiple trials to evaluate the biopsy localization accuracy. The computer simulation results showed that the RASP method generated PET images with a significantly reduced noise of 0.10 ± 0.01 standardized uptake value (SUV) as compared to an end-of-expiration image noise of 0.34 ± 0.04 SUV. The respiratory motion increased the apparent liver lesion size from 5.4 ± 1.1 to 35.3 ± 3.0cc. The RASP algorithm reduced this to 15.7 ± 3.7cc. The distances between the centroids for the static image lesion and two moving lesions in the liver and lung, when reconstructed with the RASP algorithm, were 0.83 ± 0.72mm and 0.42 ± 0.72mm. For the ungated imaging, these values increased to 3.48 ± 1.45mm and 2.5 ± 0.12mm, respectively. For the ungated imaging, this increased to 1.99 ± 1.72mm. In addition, the lesion activity estimation (e.g., SUV) was accurate and constant for images reconstructed using the RASP algorithm, whereas large activity bias and variations (± 50%) were observed for lesions in the ungated images. The physical phantom studies demonstrated a biopsy needle localization error of 2.9 ± 0.9mm from CT. Combined with the localization errors due to respiration for the PET images from simulations, the overall estimated lesion localization error would be 3.08mm for PET-guided biopsies images using RASP and 3.64mm when using ungated PET images. In other words, RASP reduced the localization error by approximately 0.6mm. The combined error analysis showed that replacing the standard end-of-expiration images with the proposed RASP method in PET/CT-guided biopsy workflow yields comparable lesion localization accuracy and reduced image noise. The RASP method can produce PET images with reduced noise, attenuation artifacts and respiratory motion, resulting in more accurate lesion localization. Testing the PET/CT-guided biopsy workflow using computer simulation and physical phantoms with respiratory motion, we demonstrated that guided biopsy procedure with the RASP method can benefit from improved PET image quality due to noise reduction, without compromising the accuracy of lesion localization.

Free-running simultaneous myocardial T1/T2 mapping and cine imaging with 3D whole-heart coverage and isotropic spatial resolution

PurposeTo develop a free-running framework for 3D isotropic simultaneous myocardial T1/T2 mapping and cine imaging. MethodsContinuous data acquisition with 3D golden angle radial trajectory is used in conjunction with T2 preparation of varying echo times and inversion recovery (IR) pulses to enable simultaneous myocardial T1/T2 mapping and cine imaging. Data acquisition is retrospectively synchronized with ECG signal, and 1D respiratory self-navigation signal is extracted from the k-space center of all radial spokes. Respiratory binning is performed based on the estimated respiratory signal, enabling estimation and correction of 3D translational respiratory motion. Using high-dimensionality patch-based undersampled reconstruction with dictionary-based low-rank inversion, whole-heart T1/T2 maps and cine images can be generated with 2 mm isotropic spatial resolution. The proposed technique was validated in a standardised phantom and ten healthy subjects in comparison to conventional 2D imaging techniques. ResultsPhantom T1 and T2 measurements demonstrated good agreement with 2D spin echo techniques. Septal T1 estimated with the proposed technique (1185.6 ± 49.8 ms) was longer than with a conventional breath-hold 2D IR-prepared sequence (1044.3 ± 26.7 ms), whereas T2 measurements (47.6 ± 2.5 ms) were lower than a breath-hold 2D gradient spin echo sequence (52.0 ± 1.8 ms). Precision of the proposed 3D mapping was higher than conventional 2D mapping techniques. Ejection fraction measured with the proposed 3D approach (63.8 ± 6.8%) agreed well with conventional breath-held multi-slice 2D cine (62.3 ± 6.4%). ConclusionsThe proposed technique provides co-registered 3D T1/T2 maps and cine images with isotropic spatial resolution from a single free-breathing scan, thereby providing a promising imaging tool for whole-heart myocardial tissue characterization and functional evaluation.

Event-by-event non-rigid data-driven PET respiratory motion correction methods: comparison of principal component analysis and centroid of distribution

Respiratory motion is a major cause of degradation of PET image quality. Respiratory gating and motion correction can be performed to reduce the effects of respiratory motion; these methods require motion information, typically obtained from external tracking systems. Various groups have studied data-driven (DD) motion estimation methods. Recently, a DD respiratory motion estimation method was established by calculating the centroid of distribution (COD) of listmode events, which was then used with event-by-event respiratory motion correction (EBE-MC) and showed results comparable to those with an external motion tracking device. The EBE-MC method only corrected for rigid motion, so that non-rigid components still contributed to motion-induced blurring. A non-rigid respiratory motion correction (NRMC) was later developed to overcome this problem, but was only evaluated using signals from an external monitor. Thus, it is desirable to further develop DD motion estimation to achieve the best respiratory motion correction results.We evaluated two DD respiratory motion detection methods, COD and principal component analysis (PCA), by comparing the extracted motion trace to that acquired by the Anzai system in dynamic studies with two tracers. PCA was chosen as a preliminary study indicated that it produced stable results than other DD methods. We then developed and performed DD-EBE-NRMC using either COD- or PCA-derived respiratory motion information. DD correction results were compared with Anzai-based results. For all tested studies, both COD and PCA showed a good-to-excellent match with Anzai signals, with PCA showing a higher correlation with Anzai signals. The DD-EBE-NRMC results showed that both COD and PCA provide comparable image quality improvement to the Anzai-based correction. Although COD showed a lower correlation with Anzai than PCA, COD-based NRMC results are comparable to those of PCA, both of which showed great reduction in motion-induced blurring.

Clinical impact of a new cone beam CT angiography respiratory motion artifact reduction algorithm during hepatic intra-arterial interventions.

To assess the impact of recently developed respiratory motion correction software on contrast-enhanced cone beam CT angiography (CBCT-a) for intraprocedural image guidance during intra-arterial liver-directed therapy. From 2015 to 2017, two groups of patients who underwent intra-arterial liver-directed therapy with (breathing, n = 30) or without (still, n = 30) significant respiratory motion artifacts were retrospectively included. All CBCT-a were processed with and without dedicated respiratory motion correction software. Four readers independently assessed the following in both reconstructions (motion correction ON and OFF): (1) overall image quality on a 0-to-5 point scale, and (2) presence of relevant peri-procedural information on tumor and vasculature (overall vessel geometry, visibility of extrahepatic vessels, target tumor conspicuity, visibility of tumor feeders). Motion correction increased the average image quality in the breathing group from 2.0 ± 0.9 to 2.9 ± 1.0 (p < 0.01). The visibility of vessel geometry, extrahepatic vessels, and tumor feeders was significantly improved for all readers, and tumor conspicuity was improved for three readers. The average image quality was not significantly different between reconstructions in the still group (motion correction ON and OFF), for any of the readers (4.0 ± 0.6 vs 4.2 ± 0.6; p = 0.12). There was no change in the visibility of vessel geometry, extrahepatic vessels, tumor feeders, or tumor conspicuity for the four readers using the respiratory motion correction software in this group. Using the dedicated respiratory motion correction software during intra-arterial liver-directed procedures increases the visualization of relevant peri-procedural information and image quality in CBCT-a corrupted by respiratory motion artifacts without affecting these elements in still CBCT-a. • The use of respiratory motion correction software could reduce the need for cone beam CT angiography acquisition retake. • Motion correction software significantly increases the visibility of vessel geometry, extrahepatic vessels, and tumor feeders, as well as tumor conspicuity in cone beam CT angiography corrupted by respiratory motion artifacts. • The use of respiratory motion correction software on cone beam CT angiography uncorrupted by respiratory motion artifact does not result in decreased image quality.