Adaptation of the modified Bouc-Wen model to compensate for hysteresis in respiratory motion for the list-mode binning of cardiac SPECT and PET acquisitions: testing using MRI

Ultrasound-based sensors for respiratory motion assessment in multimodality PET imaging

Breathing motion can displace internal organs by up to several cm; as such, it is a primary factor limiting image quality in medical imaging. Motion can also complicate matters when trying to fuse images from different modalities, acquired at different locations and/or on different days. Currently available devices for monitoring breathing motion often do so indirectly, by detecting changes in the outline of the torso rather than the internal motion itself, and these devices are often fixed to floors, ceilings or walls, and thus cannot accompany patients from one location to another. We have developed small ultrasound-based sensors, referred to as 'organ configuration motion' (OCM) sensors, that attach to the skin and provide rich motion-sensitive information. In the present work we tested the ability of OCM sensors to enable respiratory gating during in vivo PET imaging. A motion phantom involving an FDG solution was assembled, and two cancer patients scheduled for a clinical PET/CT exam were recruited for this study. OCM signals were used to help reconstruct phantom and in vivo data into time series of motion-resolved images. As expected, the motion-resolved images captured the underlying motion. In Patient #1, a single large lesion proved to be mostly stationary through the breathing cycle. However, in Patient #2, several small lesions were mobile during breathing, and our proposed new approach captured their breathing-related displacements. In summary, a relatively inexpensive hardware solution was developed here for respiration monitoring. Because the proposed sensors attach to the skin, as opposed to walls or ceilings, they can accompany patients from one procedure to the next, potentially allowing data gathered in different places and at different times to be combined and compared in ways that account for breathing motion.

Clinical Evaluation of a Data-Driven Respiratory Gating Algorithm for Whole-Body PET with Continuous Bed Motion

Respiratory gating is the standard to prevent respiration effects from degrading image quality in PET. Data-driven gating (DDG) using signals derived from PET raw data is a promising alternative to gating approaches requiring additional hardware (e.g., pressure-sensitive belt gating [BG]). However, continuous-bed-motion (CBM) scans require dedicated DDG approaches for axially extended PET, compared with DDG for conventional step-and-shoot scans. In this study, a CBM-capable DDG algorithm was investigated in a clinical cohort and compared with BG using optimally gated (OG) and fully motion-corrected (elastic motion correction [EMOCO]) reconstructions. Methods: Fifty-six patients with suspected malignancies in the thorax or abdomen underwent whole-body ¹⁸F-FDG CBM PET/CT using DDG and BG. Correlation analyses were performed on both gating signals. Besides static reconstructions, OG and EMOCO reconstructions were used for BG and DDG. The metabolic volume, SUV_max, and SUV_mean of lesions were compared among the reconstructions. Additionally, the quality of lesion delineation in the different PET reconstructions was independently evaluated by 3 experts. Results: The global correlation coefficient between BG and DDG signals was 0.48 ± 0.11, peaking at 0.89 ± 0.07 when scanning the kidney and liver region. In total, 196 lesions were analyzed. SUV measurements were significantly higher in BG-OG, DDG-OG, BG-EMOCO, and DDG-EMOCO than in static images (P < 0.001; median SUV_max: static, 14.3 ± 13.4; BG-EMOCO, 19.8 ± 15.7; DDG-EMOCO, 20.5 ± 15.6; BG-OG, 19.6 ± 17.1; and DDG-OG, 18.9 ± 16.6). No significant differences between BG-OG and DDG-OG or between BG-EMOCO and DDG-EMOCO were found. Visual lesion delineation was significantly better in BG-EMOCO and DDG-EMOCO than in static reconstructions (P < 0.001); no significant difference was found when comparing BG and DDG for either EMOCO or OG reconstruction. Conclusion: DDG-based motion compensation of CBM PET acquisitions outperforms static reconstructions, delivering qualities comparable to BG approaches. The new algorithm may be a valuable alternative for CBM PET systems.

Recent advances in cardiac SPECT instrumentation and imaging methods

Cardiac SPECT continues to play a critical role in detecting and managing cardiovascular disease, in particularly coronary artery disease (CAD) (Jaarsma et al 2012 J. Am. Coll. Cardiol. 59 1719-28), (Agostini et al 2016 Eur. J. Nucl. Med. Mol. Imaging 43 2423-32). While conventional dual-head SPECT scanners using parallel-hole collimators and scintillation crystals with photomultiplier tubes are still the workhorse of cardiac SPECT, they have the limitations of low photon sensitivity (~130 count s^-1 MBq^-1), poor image resolution (~15 mm) (Imbert et al 2012 J. Nucl. Med. 53 1897-903), relatively long acquisition time, inefficient use of the detector, high radiation dose, etc. Recently our field observed an exciting growth of new developments of dedicated cardiac scanners and collimators, as well as novel imaging algorithms for quantitative cardiac SPECT. These developments have opened doors to new applications with potential clinical impact, including ultra-low-dose imaging, absolute quantification of myocardial blood flow (MBF) and coronary flow reserve (CFR), multi-radionuclide imaging, and improved image quality as a result of attenuation, scatter, motion, and partial volume corrections (PVCs). In this article, we review the recent advances in cardiac SPECT instrumentation and imaging methods. This review mainly focuses on the most recent developments published since 2012 and points to the future of cardiac SPECT from an imaging physics perspective.

Data-driven gating in PET: Influence of respiratory signal noise on motion resolution

PURPOSE

Data-driven gating (DDG) approaches for positron emission tomography (PET) are interesting alternatives to conventional hardware-based gating methods. In DDG, the measured PET data themselves are utilized to calculate a respiratory signal, that is, subsequently used for gating purposes. The success of gating is then highly dependent on the statistical quality of the PET data. In this study, we investigate how this quality determines signal noise and thus motion resolution in clinical PET scans using a center-of-mass-based (COM) DDG approach, specifically with regard to motion management of target structures in future radiotherapy planning applications.

METHODS

PET list mode datasets acquired in one bed position of 19 different radiotherapy patients undergoing pretreatment [¹⁸ F]FDG PET/CT or [¹⁸ F]FDG PET/MRI were included into this retrospective study. All scans were performed over a region with organs (myocardium, kidneys) or tumor lesions of high tracer uptake and under free breathing. Aside from the original list mode data, datasets with progressively decreasing PET statistics were generated. From these, COM DDG signals were derived for subsequent amplitude-based gating of the original list mode file. The apparent respiratory shift d from end-expiration to end-inspiration was determined from the gated images and expressed as a function of signal-to-noise ratio SNR of the determined gating signals. This relation was tested against additional 25 [¹⁸ F]FDG PET/MRI list mode datasets where high-precision MR navigator-like respiratory signals were available as reference signal for respiratory gating of PET data, and data from a dedicated thorax phantom scan.

RESULTS

All original 19 high-quality list mode datasets demonstrated the same behavior in terms of motion resolution when reducing the amount of list mode events for DDG signal generation. Ratios and directions of respiratory shifts between end-respiratory gates and the respective nongated image were constant over all statistic levels. Motion resolution d/d_max could be modeled as d/dmax=1-e-1.52(SNR-1)0.52, with d_max as the actual respiratory shift. Determining d_max from d and SNR in the 25 test datasets and the phantom scan demonstrated no significant differences to the MR navigator-derived shift values and the predefined shift, respectively.

CONCLUSIONS

The SNR can serve as a general metric to assess the success of COM-based DDG, even in different scanners and patients. The derived formula for motion resolution can be used to estimate the actual motion extent reasonably well in cases of limited PET raw data statistics. This may be of interest for individualized radiotherapy treatment planning procedures of target structures subjected to respiratory motion.

Correction of hysteretic respiratory motion in SPECT myocardial perfusion imaging: Simulation and patient studies

PURPOSE

Amplitude-based respiratory gating is known to capture the extent of respiratory motion (RM) accurately but results in residual motion in the presence of respiratory hysteresis. In our previous study, we proposed and developed a novel approach to account for respiratory hysteresis by applying the Bouc-Wen (BW) model of hysteresis to external surrogate signals of anterior/posterior motion of the abdomen and chest with respiration. In this work, using simulated and clinical SPECT myocardial perfusion imaging (MPI) studies, we investigate the effects of respiratory hysteresis and evaluate the benefit of correcting it using the proposed BW model in comparison with the abdomen signal typically employed clinically.

METHODS

The MRI navigator data acquired in free-breathing human volunteers were used in the specially modified 4D NCAT phantoms to allow simulating three types of respiratory patterns: monotonic, mild hysteresis, and strong hysteresis with normal myocardial uptake, and perfusion defects in the anterior, lateral, inferior, and septal locations of the mid-ventricular wall. Clinical scans were performed using a Tc-99m sestamibi MPI protocol while recording respiratory signals from thoracic and abdomen regions using a visual tracking system (VTS). The performance of the correction using the respiratory signals was assessed through polar map analysis in phantom and 10 clinical studies selected on the basis of having substantial RM.

RESULTS

In phantom studies, simulations illustrating normal myocardial uptake showed significant differences (P < 0.001) in the uniformity of the polar maps between the RM uncorrected and corrected. No significant differences were seen in the polar map uniformity across the RM corrections. Studies simulating perfusion defects showed significantly decreased errors (P < 0.001) in defect severity and extent for the RM corrected compared to the uncorrected. Only for the strong hysteretic pattern, there was a significant difference (P < 0.001) among the RM corrections. The errors in defect severity and extent for the RM correction using abdomen signal were significantly higher compared to that of the BW (severity = -4.0%, P < 0.001; extent = -65.4%, P < 0.01) and chest (severity = -4.1%, P < 0.001; extent = -52.5%, P < 0.01) signals. In clinical studies, the quantitative analysis of the polar maps demonstrated qualitative and quantitative but not statistically significant differences (P = 0.73) between the correction methods that used the BW signal and the abdominal signal.

CONCLUSIONS

This study shows that hysteresis in respiration affects the extent of residual motion left in the RM-binned data, which can impact wall uniformity and the visualization of defects. Thus, there appears to be the potential for improved accuracy in reconstruction in the presence of hysteretic RM with the BW model method providing a possible step in the direction of improvement.

Data-Driven Methods for the Determination of Anterior-Posterior Motion in PET

Physiological motion combined with elongated scanning times in PET leads to image degradation and quantification errors. Correction approaches usually require 1-D signals that can be obtained with hardware-based or data-driven methods. Most of the latter are optimized or limited to capture internal motion along the superior-inferior (S-I) direction. In this work we present methods for also extracting anterior-posterior (A-P) motion from PET data and propose a set of novel weighting mechanisms that can be used to emphasize certain lines-of-response (LORs) for an increased sensitivity and better signal-to-noise ratio (SNR). The proper functioning of the methods was verified in a phantom experiment. Further, their application to clinical [18^F]-FDG-PET data of 72 patients revealed that using the weighting mechanisms leads to signals with significantly higher spectral respiratory weights, i.e. signals with higher quality. Information about multi-dimensional motion is contained in PET data and can be derived with data-driven methods. Motion models or correction techniques such as respiratory gating might benefit from the proposed methods as they allow to describe the three-dimensional movements of PET-positive structures more precisely.

Impact of Data-driven Respiratory Gating in Clinical PET

Purpose To study the feasibility and impact of respiratory gating in positron emission tomographic (PET) imaging in a clinical trial comparing conventional hardware-based gating with a data-driven approach and to describe the distribution of determined parameters. Materials and Methods This prospective study was approved by the ethics committee of the University Hospital of Münster (AZ 2014-217-f-N). Seventy-four patients suspected of having abdominal or thoracic fluorine 18 fluorodeoxyglucose (FDG)-positive lesions underwent clinical whole-body FDG PET/computed tomographic (CT) examinations. Respiratory gating was performed by using a pressure-sensitive belt system (belt gating [BG]) and an automatic data-driven approach (data-driven gating [DDG]). PET images were analyzed for lesion uptake, metabolic volumes, respiratory shifts of lesions, and diagnostic image quality. Results Forty-eight patients had at least one lesion in the field of view, resulting in a total of 164 lesions analyzed (range of number of lesions per patient, one to 13). Both gating methods revealed respiratory shifts of lesions (4.4 mm ± 3.1 for BG vs 4.8 mm ± 3.6 for DDG, P = .76). Increase in uptake of the lesions compared with nongated values did not differ significantly between both methods (maximum standardized uptake value [SUVmax], +7% ± 13 for BG vs +8% ± 16 for DDG, P = .76). Similarly, gating significantly decreased metabolic lesion volumes with both methods (-6% ± 26 for BG vs -7% ± 21 for DDG, P = .44) compared with nongated reconstructions. Blinded reading revealed significant improvements in diagnostic image quality when using gating, without significant differences between the methods (DDG was judged to be inferior to BG in 22 cases, equal in 12 cases, and superior in 15 cases; P = .32). Conclusion Respiratory gating increases diagnostic image quality and uptake values and decreases metabolic volumes compared with nongated acquisitions. Data-driven approaches are clinically applicable alternatives to belt-based methods and might help establishing routine respiratory gating in clinical PET/CT. (©) RSNA, 2016 Online supplemental material is available for this article.