BACKGROUND: Residual image noise is substantial in positron emission tomography (PET) and one of the factors limiting lesion detection, quantification, and overall image quality. Thus, improving noise reduction remains of considerable interest. This is especially true for respiratory-gated PET investigations. The only broadly used approach for noise reduction in PET imaging has been the application of low-pass filters, usually Gaussians, which however leads to loss of spatial resolution and increased partial volume effects affecting detectability of small lesions and quantitative data evaluation. The bilateral filter (BF) - a locally adaptive image filter - allows to reduce image noise while preserving well defined object edges but manual optimization of the filter parameters for a given PET scan can be tedious and time-consuming, hampering its clinical use. In this work we have investigated to what extent a suitable deep learning based approach can resolve this issue by training a suitable network with the target of reproducing the results of manually adjusted case-specific bilateral filtering.
METHODS: Altogether, 69 respiratory-gated clinical PET/CT scans with three different tracers ( [ 18 F ] FDG, [ 18 F ] L-DOPA, [ 68 Ga ] DOTATATE) were used for the present investigation. Prior to data processing, the gated data sets were split, resulting in a total of 552 single-gate image volumes. For each of these image volumes, four 3D ROIs were delineated: one ROI for image noise assessment and three ROIs for focal uptake (e.g. tumor lesions) measurements at different target/background contrast levels. An automated procedure was used to perform a brute force search of the two-dimensional BF parameter space for each data set to identify the \"optimal\" filter parameters to generate user-approved ground truth input data consisting of pairs of original and optimally BF filtered images. For reproducing the optimal BF filtering, we employed a modified 3D U-Net CNN incorporating residual learning principle. The network training and evaluation was performed using a 5-fold cross-validation scheme. The influence of filtering on lesion SUV quantification and image noise level was assessed by calculating absolute and fractional differences between the CNN, manual BF, or original (STD) data sets in the previously defined ROIs.
RESULTS: The automated procedure used for filter parameter determination chose adequate filter parameters for the majority of the data sets with only 19 patient data sets requiring manual tuning. Evaluation of the focal uptake ROIs revealed that CNN as well as BF based filtering essentially maintain the focal SUV max values of the unfiltered images with a low mean ± SD difference of δ SUV max CNN , STD = (-3.9 ± 5.2)% and δ SUV max BF , STD = (-4.4 ± 5.3)%. Regarding relative performance of CNN versus BF, both methods lead to very similar SUV max values in the vast majority of cases with an overall average difference of δ SUV max CNN , BF = (0.5 ± 4.8)%. Evaluation of the noise properties showed that CNN filtering mostly satisfactorily reproduces the noise level and characteristics of BF with δ Noise CNN , BF = (5.6 ± 10.5)%. No significant tracer dependent differences between CNN and BF were observed.
CONCLUSIONS: Our results show that a neural network based denoising can reproduce the results of a case by case optimized BF in a fully automated way. Apart from rare cases it led to images of practically identical quality regarding noise level, edge preservation, and signal recovery. We believe such a network might proof especially useful in the context of improved motion correction of respiratory-gated PET studies but could also help to establish BF-equivalent edge-preserving CNN filtering in clinical PET since it obviates time consuming manual BF parameter tuning.

BACKGROUND: Cardiac positron emission tomography (PET) can visualize and quantify the molecular and physiological pathways of cardiac function. However, cardiac and respiratory motion can introduce blurring that reduces PET image quality and quantitative accuracy. Dual cardiac- and respiratory-gated PET reconstruction can mitigate motion artifacts but increases noise as only a subset of data are used for each time frame of the cardiac cycle.
OBJECTIVE: The objective of this study is to create a zero-shot image denoising framework using a conditional generative adversarial networks (cGANs) for improving image quality and quantitative accuracy in non-gated and dual-gated cardiac PET images.
METHODS: Our study included retrospective list-mode data from 40 patients who underwent an 18F-fluorodeoxyglucose (18F-FDG) cardiac PET study. We initially trained and evaluated a 3D cGAN-known as Pix2Pix-on simulated non-gated low-count PET data paired with corresponding full-count target data, and then deployed the model on an unseen test set acquired on the same PET/CT system including both non-gated and dual-gated PET data.
RESULTS: Quantitative analysis demonstrated that the 3D Pix2Pix network architecture achieved significantly (p value<0.05) enhanced image quality and accuracy in both non-gated and gated cardiac PET images. At 5%, 10%, and 15% preserved count statistics, the model increased peak signal-to-noise ratio (PSNR) by 33.7%, 21.2%, and 15.5%, structural similarity index (SSIM) by 7.1%, 3.3%, and 2.2%, and reduced mean absolute error (MAE) by 61.4%, 54.3%, and 49.7%, respectively. When tested on dual-gated PET data, the model consistently reduced noise, irrespective of cardiac/respiratory motion phases, while maintaining image resolution and accuracy. Significant improvements were observed across all gates, including a 34.7% increase in PSNR, a 7.8% improvement in SSIM, and a 60.3% reduction in MAE.
CONCLUSIONS: The findings of this study indicate that dual-gated cardiac PET images, which often have post-reconstruction artifacts potentially affecting diagnostic performance, can be effectively improved using a generative pre-trained denoising network.

We have clinically implemented gated stereotactic body radiotherapy under abdominal compression using an Anzai laser-based gating device with visual guidance in combination with an Elekta linear accelerator. To ensure accuracy, we configured the gating window for each patient by correlating the respiratory curve from the laser sensor and the tumor positions from the 4D computed tomography (CT) images reconstructed with the aid of the respiratory curve. This allowed us to define a patient-specific gating window to keep the tumor displacement below 5 mm from the end-expiration, assuming the reproducibility of the tumor trajectories and the laser-based body surface measurements. Results are summarized as follows: 1) A patient-specific gating window internal target volume (ITV) with a prespecified maximum tumor displacement relative to the end-expiration was obtained by acquiring a 4D CT consisting of 20 phase CT sets and a respiratory curve from the Anzai system. 2) Respiratory hysteresis was managed by setting two different thresholds on the respiratory curve based on the predetermined maximum tumor displacement relative to end-expiration. 3) Abdominal compression increased gating window width, thereby presumably leading to faster gated-beam delivery. 4) Gamma index pass rates in sliding-window gated intensity-modulated radiotherapy (IMRT) were superior to those in gated volumetric modulated arc therapy (VMAT). 5) Intrafraction gated cone-beam computed tomography (CBCT) demonstrated that the tumor appeared to remain within the gating window ITV during the stereotactic gated sliding-window IMRT. In conclusion, we have successfully implemented gated stereotactic body radiotherapy at our clinic and achieved a favorable clinical validation result. More cases need to be evaluated to increase the validity.

We appreciate Chang JS.\'s interest in the article: \"Benefit of respiratory gating in the Danish Breast Cancer Group partial breast irradiation trial\". The author\'s response corroborates the statements and comments of Chang JS.

OBJECTIVE: Respiratory movement has an important impact on the radiotherapy for lung tumor. Respiratory gating technology is helpful to improve the accuracy of target delineation. This study investigated the value of prospective and retrospective respiratory gating simulations in target delineation and radiotherapy plan design for solitary pulmonary tumors (SPTs) in radiotherapy.
METHODS: The enrolled patients underwent CT simulation with three-dimensional (3D) CT non gating, prospective respiratory gating, and retrospective respiratory gating simulation. The target volumes were delineated on three sets of CT images, and radiotherapy plans were prepared accordingly. Tumor displacements and movement information obtained using the two respiratory gating approaches, as well as the target volumes and dosimetry parameters in the radiotherapy plan were compared.
RESULTS: No significant difference was observed in tumor displacement measured using the two gating methods (p > 0.05). However, the internal gross tumor volumes (IGTVs), internal target volumes (ITVs), and planning target volumes (PTVs) based on the retrospective respiratory gating simulation were larger than those obtained using prospective gating (group A: pIGTV = 0.041, pITV = 0.003, pPTV = 0.008; group B: pIGTV = 0.025, pITV = 0.039, pPTV = 0.004). The two-gating PTVs were both smaller than those delineated on 3D non gating images (p < 0.001). V5Gy, V10Gy, V20Gy, V30Gy, and mean lung dose in the two gated radiotherapy plans were lower than those in the 3D non gating plan (p < 0.001); however, no significant difference was observed between the two gating plans (p > 0.05).
CONCLUSIONS: The application of respiratory gating could reduce the target volume and the radiation dose that the normal lung tissue received. Compared to prospective respiratory gating, the retrospective gating provides more information about tumor movement in PTV.

Ultrahigh field magnetic resonance imaging (MRI) (≥ 7 T) has the potential to provide superior spatial resolution and unique image contrast. Apart from radiofrequency transmit inhomogeneities in the body at this field strength, imaging of the upper abdomen faces additional challenges associated with motion-induced ghosting artifacts. To address these challenges, the goal of this work was to develop a technique for high-resolution free-breathing upper abdominal MRI at 7 T with a large field of view. Free-breathing 3D gradient-recalled echo (GRE) water-excited radial stack-of-stars data were acquired in seven healthy volunteers (five males/two females, body mass index: 19.6-24.8 kg/m2) at 7 T using an eight-channel transceive array coil. Two volunteers were also examined at 3 T. In each volunteer, the liver and kidney regions were scanned in two separate acquisitions. To homogenize signal excitation, the time-interleaved acquisition of modes (TIAMO) method was used with personalized pairs of B1 shims, based on a 23-s Cartesian fast low angle shot (FLASH) acquisition. Utilizing free-induction decay navigator signals, respiratory-gated images were reconstructed at a spatial resolution of 0.8 × 0.8 × 1.0 mm3. Two experienced radiologists rated the image quality and the impact of B1 inhomogeneity and motion-related artifacts on multipoint scales. The images of all volunteers showcased effective water excitation and were accurately corrected for respiratory motion. The impact of B1 inhomogeneity on image quality was minimal, underscoring the efficacy of the multitransmit TIAMO shim. The high spatial resolution allowed excellent depiction of small structures such as the adrenal glands, the proximal ureter, the diaphragm, and small blood vessels, although some streaking artifacts persisted in liver image data. In direct comparisons with 3 T performed for two volunteers, 7-T acquisitions demonstrated increases in signal-to-noise ratio of 77% and 58%. Overall, this work demonstrates the feasibility of free-breathing MRI in the upper abdomen at submillimeter spatial resolution at a magnetic field strength of 7 T.

OBJECTIVE: To propose a straightforward and time-efficient quality assurance (QA) approach of beam time delay for respiratory-gated radiotherapy and validate the proposed method on typical respiratory gating systems, Catalyst™ and AlignRT™.
METHODS: The QA apparatus was composed of a motion platform and a Winston-Lutz cube phantom (WL3) embedded with metal balls. The apparatus was first scanned in CT-Sim and two types of QA plans specific for beam on and beam off time delay, respectively, were designed. Static reference images and motion testing images of the WL3 cube were acquired with EPID. By comparing the position differences of the embedded metal balls in the motion and reference images, beam time delays were determined. The proposed approach was validated on three linacs with either Catalyst™ or AlignRT™ respiratory gating systems. To investigate the impact of energy and dose rate on beam time delay, a range of QA plans with Eclipse (V15.7) were devised with varying energy and dose rates.
RESULTS: For all energies, the beam on time delays in AlignRT™ V6.3.226, AlignRT™ V7.1.1, and Catalyst™ were 92.13 ± $ \\pm $ 5.79 ms, 123.11 ± $ \\pm $ 6.44 ms, and 303.44 ± $ \\pm $ 4.28 ms, respectively. The beam off time delays in AlignRT™ V6.3.226, AlignRT™ V7.1.1, and Catalyst™ were 121.87 ± $ \\pm $ 1.34 ms, 119.33 ± $ \\pm $ 0.75 ms, and 97.69 ± $ \\pm $ 2.02 ms, respectively. Furthermore, the beam on delays decreased slightly as dose rates increased for all gating systems, whereas the beam off delays remained unaffected.
CONCLUSIONS: The validation results demonstrate the proposed QA approach of beam time delay for respiratory-gated radiotherapy was both reproducible and time-efficient to practice for institutions to customize accordingly.

Background. Thoracoabdominal MRI is limited by respiratory motion, especially in populations who cannot perform breath-holds. One approach for reducing motion blurring in radially-acquired MRI is respiratory gating. Straightforward \'hard-gating\' uses only data from a specified respiratory window and suffers from reduced SNR. Proposed \'soft-gating\' reconstructions may improve scan efficiency but reduce motion correction by incorporating data with nonzero weight acquired outside the specified window. However, previous studies report conflicting benefits, and importantly the choice of soft-gated weighting algorithm and effect on image quality has not previously been explored. The purpose of this study is to map how variable soft-gated weighting functions and parameters affect signal and motion blurring in respiratory-gated reconstructions of radial lung MRI, using neonates as a model population.Methods. Ten neonatal inpatients with respiratory abnormalities were imaged using a 1.5 T neonatal-sized scanner and 3D radial ultrashort echo-time (UTE) sequence. Images were reconstructed using ungated, hard-gated, and several soft-gating weighting algorithms (exponential, sigmoid, inverse, and linear weighting decay outside the period of interest), with %Nprojrepresenting the relative amount of data included. The apparent SNR (aSNR) and motion blurring (measured by the maximum derivative of image intensity at the diaphragm, MDD) were compared between reconstructions.Results. Soft-gating functions produced higher aSNR and lower MDD than hard-gated images using equivalent %Nproj, as expected. aSNR was not identical between different gating schemes for given %Nproj. While aSNR was approximately linear with %Nprojfor each algorithm, MDD performance diverged between functions as %Nprojdecreased. Algorithm performance was relatively consistent between subjects, except in images with high noise.Conclusion. The algorithm selection for soft-gating has a notable effect on image quality of respiratory-gated MRI; the timing of included data across the respiratory phase, and not simply the amount of data, plays an important role in aSNR. The specific soft-gating function and parameters should be considered for a given imaging application\'s requirements of signal and sharpness.

Free-breathing abdominal chemical exchange saturation transfer (CEST) has great potential for clinical application, but its technical implementation remains challenging. This study aimed to propose and evaluate a free-breathing abdominal CEST sequence. The proposed sequence employed respiratory gating (ResGat) to synchronize the data acquisition with respiratory motion and performed a water presaturation module before the CEST saturation to abolish the influence of respiration-induced repetition time variation. In vivo experiments were performed to compare different respiratory motion-control strategies and B0 offset correction methods, and to evaluate the effectiveness and necessity of the quasi-steady-state (QUASS) approach for correcting the influence of the water presaturation module on CEST signal. ResGat with a target expiratory phase of 0.5 resulted in a higher structural similarity index and a lower coefficient of variation on consecutively acquired CEST S0 images than breath-holding (BH) and respiratory triggering (all p < 0.05). B0 maps derived from the abdominal CEST dataset itself were more stable for B0 correction, compared with the separately acquired B0 maps by a dual-echo time scan and B0 maps derived from the water saturation shift referencing approach. Compared with BH, ResGat yielded more homogeneous magnetization transfer ratio asymmetry maps at 3.5 ppm (standard deviation: 3.96% vs. 3.19%, p = 0.036) and a lower mean squared difference between scan and rescan (27.52‱ vs. 16.82‱, p = 0.004). The QUASS approach could correct the water presaturation-induced CEST signal change, but its necessity for in vivo scanning needs further verification. The proposed free-breathing abdominal CEST sequence using ResGat had an acquisition efficiency of approximately four times that using BH. In conclusion, the proposed free-breathing abdominal CEST sequence using ResGat and water presaturation has a higher acquisition efficiency and image quality than abdominal CEST using BH.

Objective. Since pulse wave transit time (PWTT) shortens as pulmonary artery pressure (PAP) increases it was suggested as a potential non-invasive surrogate for PAP. The state of tidal lung filling is also known to affect PWTT independently of PAP. The aim of this retrospective analysis was to test whether respiratory gating improved the correlation coefficient between PWTT and PAP.Approach. In each one of five anesthetized and mechanically ventilated pigs two high-fidelity pressure catheters were placed, one directly behind the pulmonary valve, and the second one in a distal branch of the pulmonary artery. PAP was raised using the thromboxane A2 analogue U46619 and animals were ventilated in a pressure controlled mode (I:E ratio 1:2, respiratory rate 12/min, tidal volume of 6 ml kg-1). All signals were recorded using the multi-channel platform PowerLab®. The arrival of the pulse wave at each catheter tip was determined using a MATLAB-based modified hyperbolic tangent algorithm and PWTT calculated as the time interval between these arrivals.Main results. Correlation coefficient for PWTT and mean PAP wasr= 0.932 for thromboxane. This correlation coefficient increased considerably when heart beats either at end-inspiration (r= 0.978) or at end-expiration (r= 0.985) were selected (=respiratory gating).Significance. The estimation of mean PAP from PWTT improved significantly when taking the respiratory cycle into account. Respiratory gating is suggested to improve for the estimation of PAP by PWTT.