Respiratory Bins Research Articles

Evaluation of respiratory and cardiac motion correction schemes in dual gated PET/CT cardiac imaging.

Cardiac imaging suffers from both respiratory and cardiac motion. One of the proposed solutions involves double gated acquisitions. Although such an approach may lead to both respiratory and cardiac motion compensation there are issues associated with (a) the combination of data from cardiac and respiratory motion bins, and (b) poor statistical quality images as a result of using only part of the acquired data. The main objective of this work was to evaluate different schemes of combining binned data in order to identify the best strategy to reconstruct motion free cardiac images from dual gated positron emission tomography (PET) acquisitions. A digital phantom study as well as seven human studies were used in this evaluation. PET data were acquired in list mode (LM). A real-time position management system and an electrocardiogram device were used to provide the respiratory and cardiac motion triggers registered within the LM file. Acquired data were subsequently binned considering four and six cardiac gates, or the diastole only in combination with eight respiratory amplitude gates. PET images were corrected for attenuation, but no randoms nor scatter corrections were included. Reconstructed images from each of the bins considered above were subsequently used in combination with an affine or an elastic registration algorithm to derive transformation parameters allowing the combination of all acquired data in a particular position in the cardiac and respiratory cycles. Images were assessed in terms of signal-to-noise ratio (SNR), contrast, image profile, coefficient-of-variation (COV), and relative difference of the recovered activity concentration. Regardless of the considered motion compensation strategy, the nonrigid motion model performed better than the affine model, leading to higher SNR and contrast combined with a lower COV. Nevertheless, when compensating for respiration only, no statistically significant differences were observed in the performance of the two motion models considered. Superior image SNR and contrast were seen using the affine respiratory motion model in combination with the diastole cardiac bin in comparison to the use of the whole cardiac cycle. In contrast, when simultaneously correcting for cardiac beating and respiration, the elastic respiratory motion model outperformed the affine model. In this context, four cardiac bins associated with eight respiratory amplitude bins seemed to be adequate. Considering the compensation of respiratory motion effects only, both affine and elastic based approaches led to an accurate resizing and positioning of the myocardium. The use of the diastolic phase combined with an affine model based respiratory motion correction may therefore be a simple approach leading to significant quality improvements in cardiac PET imaging. However, the best performance was obtained with the combined correction for both cardiac and respiratory movements considering all the dual-gated bins independently through the use of an elastic model based motion compensation.

TH‐E‐17A‐05: Optimizing Four Dimensional Cone Beam Computed Tomography Projection Allocation to Respiratory Bins

Purpose:Four dimensional cone beam computed tomography (4DCBCT) is an emerging image guidance strategy but it can suffer from poor image quality. To avoid repeating scans it is beneficial to make the best use of the imaging data obtained. For conventional 4DCBCT the location and size of respiratory bins is fixed and projections are allocated to the respiratory bin within which it falls. Strictly adhering to this rule is unnecessary and can compromise image quality. In this study we optimize the size and location of respiratory bins and allow projections to be sourced from adjacent phases of the respiratory cycle.Methods:A mathematical optimization framework using mixed integer quadratic programming has been developed that determines when to source projections from adjacent respiratory bins and optimizes the size and location of the bins. The method, which we will call projection sharing, runs in under 2 seconds of CPU time. Five 4DCBCT datasets of stage III‐IV lung cancer patients were used to test the algorithm. The standard deviation of the angular separation between projections (SD‐A) and the standard deviation in the volume of the reconstructed fiducial gold coil (SD‐V) were used as proxies to measure streaking artefacts and motion blur respectively.Results:The SD‐A using displacement binning and projection sharing was 30%–50% smaller than conventional phase based binning and 59%–76% smaller than conventional displacement binning indicating more uniformly spaced projections and fewer streaking artefacts. The SD‐V was 20–90% smaller when using projection sharing than using conventional phase based binning suggesting more uniform marker segmentation and less motion blur.Conclusion:Image quality was visibly and significantly improved with projection sharing. Projection sharing does not require any modifications to existing hardware and offers a more robust replacement to phase based binning, or, an option if phase based reconstruction is not of a suitable quality.This project is supported by an NHMRC Australia Fellowship and NHMRC project grant number 1034060

SU-D-17A-04: The Impact of Audiovisual Biofeedback On Image Quality During 4D Functional and Anatomic Imaging: Results of a Prospective Clinical Trial

Purpose: The ability of audiovisual (AV) biofeedback to improve breathing regularity has not previously been investigated for functional imaging studies. The purpose of this study was to investigate the impact of AV biofeedback on 4D-PET and 4D-CT image quality in a prospective clinical trial. We hypothesized that motion blurring in 4D-PET images and the number of artifacts in 4D-CT images are reduced using AV biofeedback. Methods: AV biofeedback is a real-time, interactive and personalized system designed to help a patient self-regulate his/her breathing using a patient-specific representative waveform and musical guides. In an IRB-approved prospective clinical trial, 4D-PET and 4D-CT images of 10 lung cancer patients were acquired with AV biofeedback (AV) and free breathing (FB). The 4D-PET images in 6 respiratory bins were analyzed for motion blurring by: (1) decrease of GTVPET and (2) increase of SUVmax in 4-DPET compared to 3D-PET. The 4D-CT images were analyzed for artifacts by: (1) comparing normalized cross correlation-based scores (NCCS); and (2) quantifying a visual assessment score (VAS). A two-tailed paired t-test was used to test the hypotheses. Results: The impact of AV biofeedback on 4D-PET and 4D-CT images varied widely between patients, suggesting inconsistent patient comprehension and capability. Overall, the 4D-PETmore » decrease of GTVPET was 2.0±3.0cm3 with AV and 2.3±3.9cm{sup 3} for FB (p=0.61). The 4D-PET increase of SUVmax was 1.6±1.0 with AV and 1.1±0.8 with FB (p=0.002). The 4D-CT NCCS were 0.65±0.27 with AV and 0.60±0.32 for FB (p=0.32). The 4D-CT VAS was 0.0±2.7 (p=ns). Conclusion: A 10-patient study demonstrated a statistically significant reduction of motion blurring of AV over FB for 1/2 functional 4D-PET imaging metrics. No difference between AV and FB was found for 2 anatomic 4D-CT imaging metrics. Future studies will focus on optimizing the human-computer interface and including patient training sessions for improved comprehension and capability. Supported by NIH/NCI R01 CA 093626, Stanford BioX Interdisciplinary Initiatives Program, NHMRC Australia Fellowship, and Kwanjeong Educational Foundation. GE Healthcare provided the Respiratory Gating Toolbox for 4D-PET image reconstruction. Stanford University owns US patent #E7955270 which is unlicensed to any commercial entity.« less

SU‐D‐18C‐01: A Novel 4D‐MRI Technology Based On K‐Space Retrospective Sorting

Purpose:Current 4D‐MRI techniques lack sufficient temporal/spatial resolution and consistent tumor contrast. To overcome these limitations, this study presents the development and initial evaluation of an entirely new framework of 4D‐MRI based on k‐space retrospective sorting.Methods:An important challenge of the proposed technique is to determine the number of repeated scans(NR) required to obtain sufficient k‐space data for 4D‐MRI. To do that, simulations using 29 cancer patients' respiratory profiles were performed to derive the relationship between data acquisition completeness(Cp) and NR, also relationship between NR(Cp=95%) and the following factors: total slice(NS), respiratory phase bin length(Lb), frame rate(fr), resolution(R) and image acquisition starting‐phase(P0). To evaluate our technique, a computer simulation study on a 4D digital human phantom (XCAT) were conducted with regular breathing (fr=0.5Hz; R=256×256). A 2D echo planer imaging(EPI) MRI sequence were assumed to acquire raw k‐space data, with respiratory signal and acquisition time for each k‐space data line recorded simultaneously. K‐space data was re‐sorted based on respiratory phases. To evaluate 4D‐MRI image quality, tumor trajectories were measured and compared with the input signal. Mean relative amplitude difference(D) and cross‐correlation coefficient(CC) are calculated. Finally, phase‐sharing sliding window technique was applied to investigate the feasibility of generating ultra‐fast 4D‐MRI.Result:Cp increased with NR(Cp=100*[1‐exp(‐0.19*NR)], when NS=30, Lb=100%/6). NR(Cp=95%) was inversely‐proportional to Lb (r=0.97), but independent of other factors. 4D‐MRI on XCAT demonstrated highly accurate motion information (D=0.67%, CC=0.996) with much less artifacts than those on image‐based sorting 4D‐MRI. Ultra‐fast 4D‐MRI with an apparent temporal resolution of 10 frames/second was reconstructed using the phase‐sharing sliding window technique.Conclusions:A novel 4D‐MRI technology based on k‐space sorting has been successfully developed and evaluated on the digital phantom. Framework established can be applied to a variety of MR sequences, showing great promises to develop the optimal 4D‐MRI technique for many radiation therapy applications.NIH (1R21CA165384‐01A1)

TH‐E‐17A‐09: High Quality and Artifact‐Free 4D Cone Beam CT and Its Application in Adaptive Treatment Planning

Purpose:To develop a high quality 4D cone beam CT (4DCBCT) method that is immune to patient/couch truncations and to investigate its application in adaptive replanning of lung XRT.Methods:In this study, IRB‐approved human subject CBCT data was acquired using a Varian on‐board imager with 1 minute rotation time. The acquired projection data was retrospectively sorted into 20 respiratory phase bins, from which 4DCBCT images with high SNR and high temporal resolution were generated using Prior Image Constrained Compressed Sensing (PICCS). Couch and patient truncations generate strong data inconsistency in the projection data and artifacts in the 4DCBCT image. They were addressed using an adaptive PICCS method. The artifact‐free PICCS‐4DCBCT images were used to generate adaptive treatment plans for the same patient at the 10th (day 21) and 30th (day 47) fractions. Dosimetric impacts with and without PICCS‐ 4DCBCT were evaluated by isodose distributions, DVHs, and other dosimetric factors.Results:The adaptive PICCS‐4DCBCT method improves image quality by removing residue truncation artifacts; measured universal image quality increased 37%. The isodose lines and DVHs with PICCS‐4DCBCT‐based adaptive replanning were significantly more conformal to PTV than without replanning due to changes in patient anatomy caused by progress of the treatment. The mean dose to PTV at the 10th fraction was 63.1Gy with replanning and 64.2Gy without replanning, where the prescribed dose was 60Gy, in 2Gy × 30 fractions. The mean dose to PTV at the 30th fraction was 61.6Gy with replanning and 64.9Gy without replanning. Lung V20 was 37.1%, 41.9% and 43.3% for original plan, 10th fraction plan and 30th fraction plan; with re‐planning, Lung V20 was 37.1%, 32%, 27.8%.Conclusion:4DCBCT imaging using adaptive PICCS is able to generate high quality, artifact‐free images that potentially can be used to create replanning for improving radiotherapy of the lung. K Niu, K Li, J Smilowitz: Nothing to Disclose.G Chen: General Electric Company Research funded, Siemens AG Research funded, Varian Medical Systems Research funded, Hologic Research funded.

MRI Investigation of the Linkage Between Respiratory Motion of the Heart and Markers on Patient's Abdomen and Chest: Implications for Respiratory Amplitude Binning List-Mode PET and SPECT Studies.

Respiratory motion of the heart impacts the diagnostic accuracy of myocardial-perfusion emission-imaging studies. Amplitude binning has come to be the method of choice for binning list-mode based acquisitions for correction of respiratory motion in PET and SPECT. In some subjects respiratory motion exhibits hysteretic behavior similar to damped non-linear cyclic systems. The detection and correction of hysteresis between the signals from surface movement of the patient's body used in binning and the motion of the heart within the chest remains an open area for investigation. This study reports our investigation in nine volunteers of the combined MRI tracking of the internal respiratory motion of the heart using Navigators with stereo-tracking of markers on the volunteer's chest and abdomen by a visual-tracking system (VTS). The respiratory motion signals from the internal organs and the external markers were evaluated for hysteretic behavior analyzing the temporal correspondence of the signals. In general, a strong, positive correlation between the external marker motion (AP direction) and the internal heart motion (SI direction) during respiration was observed. The average ± standard deviation in the Spearman's ranked correlation coefficient (ρ) over the nine volunteer studied was 0.92 ± 0.1 between the external abdomen marker and the internal heart, and 0.87 ± 0.2 between the external chest marker and the internal heart. However despite the good correlation on average for the nine volunteers, in three studies a poor correlation was observed due to hysteretic behavior between inspiration and expiration for either the chest marker and the internal motion of the heart, or the abdominal marker and the motion of the heart. In all cases we observed a good correlation of at least either the abdomen or the chest with the heart. Based on this result, we propose the use of marker motion from both the chest and abdomen regions when estimating the internal heart motion to detect and address hysteresis when binning list-mode emission data.

Respiratory motion guided four dimensional cone beam computed tomography: encompassing irregular breathing

Four dimensional cone beam computed tomography (4DCBCT) images suffer from angular under sampling and bunching of projections due to a lack of feedback between the respiratory signal and the acquisition system. To address this problem, respiratory motion guided 4DCBCT (RMG-4DCBCT) regulates the gantry velocity and projection time interval, in response to the patient’s respiratory signal, with the aim of acquiring evenly spaced projections in a number of phase or displacement bins during the respiratory cycle. Our previous study of RMG-4DCBCT was limited to sinusoidal breathing traces. Here we expand on that work to provide a practical algorithm for the case of real patient breathing data. We give a complete description of RMG-4DCBCT including full details on how to implement the algorithms to determine when to move the gantry and when to acquire projections in response to the patient’s respiratory signal. We simulate a realistic working RMG-4DCBCT system using 112 breathing traces from 24 lung cancer patients. Acquisition used phase-based binning and parameter settings typically used on commercial 4DCBCT systems (4 min acquisition time, 1200 projections across 10 respiratory bins), with the acceleration and velocity constraints of current generation linear accelerators. We quantified streaking artefacts and image noise for conventional and RMG-4DCBCT methods by reconstructing projection data selected from an oversampled set of Catphan phantom projections. RMG-4DCBCT allows us to optimally trade-off image quality, acquisition time and image dose. For example, for the same image quality and acquisition time as conventional 4DCBCT approximately half the imaging dose is needed. Alternatively, for the same imaging dose, the image quality as measured by the signal to noise ratio, is improved by 63% on average. C-arm cone beam computed tomography systems, with an acceleration up to 200°/s2, a velocity up to 100°/s and the acquisition of 80 projections per second, allow the image acquisition time to be reduced to below 60 s. We have made considerable progress towards realizing a system to reduce projection clustering in conventional 4DCBCT imaging and hence reduce the imaging dose to the patient.

WE-G-134-06: Image Quality in Thoracic 4D Cone-Beam CT: A Sensitivity Analysis of Respiratory Signal Source, Binning Method, and Reconstruction Algorithm

Purpose: Respiratory signal source, binning method, and reconstruction algorithm are three major factors affecting thoracic 4D cone-beam CT (4D-CBCT) image quality. Various studies have investigated each of them individually, but no sensitivity analysis to these factors has been performed. This study quantitatively compares the impacts of the three factors on thoracic 4D-CBCT image quality. Methods: A 4D-CBCT patient projection dataset acquired using audio-visual biofeedback with known degree of baseline shift in respiratory motion was reconstructed with the following factors: (i) respiratory signal source (via real-time position management or projection image based method), (ii) binning method (phase, displacement, or equal-projection-density (EPD) displacement binning), and (iii) reconstruction algorithm (Feldkamp-Davis-Kress (FDK), McKinnon-Bates (MKB), or adaptive-steepest-descent projection-onto-convex-sets (ASD-POCS)). The image quality was quantified using signal-to-noise ratio (SNR), contrast ratio (CR), and edge-response width (ERW) to assess noise, contrast, and sharpness, respectively. Results: Respiratory signal sources had no significant effect on any of the three metrics. Displacement binning was found to produce slightly more inconsistent SNR values owing to unevenly distributed angular views. The binning method otherwise had minimal effects on image quality. For the reconstruction algorithms, MKB resulted in a slightly higher SNR than FDK, while ASD-POCS improved SNR by a factor of three. Conversely, degradation in CR was observed with MKB and ASD-POCS. FDK and MKB produced very similar ERW, while slightly higher values were observed with ASD-POCS, indicating a small degree of blurriness. Conclusion: Respiratory signal sources and binning methods had a negligible impact on image quality, and did not introduce apparent motion artifacts. The MKB and ASD-POCS reconstruction algorithms reduced the noise and streaking but produced poorer image contrast. Of the reconstruction factors tested, reconstruction algorithms play the most important role in improving 4D-CBCT image quality and therefore represent the highest priority for further development. This project is supported by an NHMRC Australia Fellowship, NHMRC project grant 1034060, US NCI P01CA116602, an International Postgraduate Research Scholarships, and an Australian Postgraduate Award.

Advanced Respiratory Motion Compensation for Coronary MR Angiography

Despite technical advances, respiratory motion remains a major impediment in a substantial amount of patients undergoing coronary magnetic resonance angiography (CMRA). Traditionally, respiratory motion compensation has been performed with a one-dimensional respiratory navigator positioned on the right hemi-diaphragm, using a motion model to estimate and correct for the bulk respiratory motion of the heart. Recent technical advancements has allowed for direct respiratory motion estimation of the heart, with improved motion compensation performance. Some of these new methods, particularly using image-based navigators or respiratory binning, allow for more advanced motion correction which enables CMRA data acquisition throughout most or all of the respiratory cycle, thereby significantly reducing scan time. This review describes the three components typically involved in most motion compensation strategies for CMRA, including respiratory motion estimation, gating and correction, and how these processes can be utilized to perform advanced respiratory motion compensation.

Respiratory triggered 4D cone‐beam computed tomography: A novel method to reduce imaging dose

A novel method called respiratory triggered 4D cone-beam computed tomography (RT 4D CBCT) is described whereby imaging dose can be reduced without degrading image quality. RT 4D CBCT utilizes a respiratory signal to trigger projections such that only a single projection is assigned to a given respiratory bin for each breathing cycle. In contrast, commercial 4D CBCT does not actively use the respiratory signal to minimize image dose. To compare RT 4D CBCT with conventional 4D CBCT, 3600 CBCT projections of a thorax phantom were gathered and reconstructed to generate a ground truth CBCT dataset. Simulation pairs of conventional 4D CBCT acquisitions and RT 4D CBCT acquisitions were developed assuming a sinusoidal respiratory signal which governs the selection of projections from the pool of 3600 original projections. The RT 4D CBCT acquisition triggers a single projection when the respiratory signal enters a desired acquisition bin; the conventional acquisition does not use a respiratory trigger and projections are acquired at a constant frequency. Acquisition parameters studied were breathing period, acquisition time, and imager frequency. The performance of RT 4D CBCT using phase based and displacement based sorting was also studied. Image quality was quantified by calculating difference images of the test dataset from the ground truth dataset. Imaging dose was calculated by counting projections. Using phase based sorting RT 4D CBCT results in 47% less imaging dose on average compared to conventional 4D CBCT. Image quality differences were less than 4% at worst. Using displacement based sorting RT 4D CBCT results in 57% less imaging dose on average, than conventional 4D CBCT methods; however, image quality was 26% worse with RT 4D CBCT. Simulation studies have shown that RT 4D CBCT reduces imaging dose while maintaining comparable image quality for phase based 4D CBCT; image quality is degraded for displacement based RT 4D CBCT in its current implementation.

A comparison of phase, amplitude, and velocity binning for cone-beam computed tomographic projection-based motion reconstruction

PurposeWe previously developed a motion estimation technique based on direct cone-beam projection analysis. It is able to reconstruct the complete motion trajectory of a radio-opaque marker, including cycle-to-cycle variability, using respiratory binning of the projection images. This paper investigates the use of phase, amplitude, and amplitude-velocity binning in the context of projection-based cone-beam motion estimation (CBME). Methods and MaterialsWe simulated cone-beam computed tomographic scans of 160 tumor trajectories estimated by a CyberKnife Synchrony System (Accuray, Sunnyvale, CA), and reconstructed the complete trajectory with CBME using phase, amplitude, and amplitude-velocity binning of the projection data. Various numbers of respiratory bins, from 1 (no binning) to 100, were used for phase and amplitude binning, while 1 to 100 amplitude bins with 4 velocity bins were used for amplitude-velocity binning. From this large pool of data, we correlated the reconstruction accuracy with bin type, total number of bins, number of breathing cycles per bin, and the position of the bin within the breathing cycle. ResultsCBME predicted the true motion of the marker with a 3-dimensional (3D) mean root mean square (RMS) error of 0.24 mm for amplitude-velocity binning, 0.31 mm for amplitude binning, and 0.52 mm for phase binning. Reconstruction 3D RMS error increased to over 1 mm when less than 3 breathing cycles contributed to a bin. We found that reconstruction accuracy was optimized when about 20 bins were used. Accuracy also decreased in bins located around the inhale portion of the breath cycle, compared with the mid- and end-exhale positions. ConclusionsThis study provides a quantitative assessment of phase, amplitude, and amplitude-velocity binning for CBME. A joint binning approach should be used to give both the accuracy of amplitude binning, as well as the robustness of phase binning, in areas of limited motion sampling.

Optimizing 4D cone beam computed tomography acquisition by varying the gantry velocity and projection time interval

Four dimensional cone beam computed tomography (4DCBCT) is an emerging clinical image guidance strategy for tumour sites affected by respiratory motion. In current generation 4DCBCT techniques, both the gantry rotation speed and imaging frequency are constant and independent of the patient’s breathing which can lead to projection clustering. We present a mixed integer quadratic programming (MIQP) model for respiratory motion guided-4DCBCT (RMG-4DCBCT) which regulates the gantry velocity and projection time interval, in response to the patient’s respiratory signal, so that a full set of evenly spaced projections can be taken in a number of phase, or displacement, bins during the respiratory cycle. In each respiratory bin, an image can be reconstructed from the projections to give a 4D view of the patient’s anatomy so that the motion of the lungs, and tumour, can be observed during the breathing cycle. A solution to the full MIQP model in a practical amount of time, 10 s, is not possible with the leading commercial MIQP solvers, so a heuristic method is presented. Using parameter settings typically used on current generation 4DCBCT systems (4 min image acquisition, 1200 projections, 10 respiratory bins) and a sinusoidal breathing trace with a 4 s period, we show that the root mean square (RMS) of the angular separation between projections with displacement binning is 2.7° using existing constant gantry speed systems and 0.6° using RMG-4DCBCT. For phase based binning the RMS is 2.7° using constant gantry speed systems and 2.5° using RMG-4DCBCT. The optimization algorithm presented is a critical step on the path to developing a system for RMG-4DCBCT.

Whole‐heart coronary MRA with 100% respiratory gating efficiency: Self‐navigated three‐dimensional retrospective image‐based motion correction (TRIM)

To develop a three-dimensional retrospective image-based motion correction technique for whole-heart coronary MRA with self-navigation that eliminates both the need to setup a diaphragm navigator and gate the acquisition. The proposed technique uses one-dimensional self-navigation to track the superior-inferior translation of the heart, with which the acquired three-dimensional radial k-space data is segmented into different respiratory bins. Respiratory motion is then estimated in image space using an affine transform model and subsequently this information is used to perform efficient motion correction in k-space. The performance of the proposed technique on healthy volunteers is compared with the conventional navigator gating approach as well as data binning using diaphragm navigator. The proposed method is able to reduce the imaging time to 7.1±0.5 min from 13.9±2.6 min with conventional navigator gating. The scan setup time is reduced as well due to the elimination of the navigator. The proposed method yields excellent image quality comparable with either conventional navigator gating or the navigator binning approach. We have developed a new respiratory motion correction technique for coronary MRA that enables 1 mm(3) isotropic resolution and whole-heart coverage with 7 min of scan time. Further tests on patient population are needed to determine its clinical usage.

Role of respiratory-gated PET/CT for pancreatic tumors: A preliminary result

PurposeThe aim of this study is to ascertain role of respiratory-gated PET/CT for accurate diagnosis of pancreatic tumors. Materials and methodsPrior to clinical study, the phantom study was performed to evaluate the impact of respiratory motion on lesion quantification. Twenty-two patients (mean age 65 years) with pancreatic tumors were enrolled. Pathological diagnoses by surgical specimens consisted of pancreatic cancer (n=15) and benign intraductal papillary mucinous neoplasm (IPMN, n=7). Whole-body scan of non-respiratory-gated PET/CT was performed at first, and subsequent respiratory-gated PET/CT for one bed position was performed. All PET/CT studies were performed prior to surgery. The SUV max obtained by non-respiratory-gated PET/CT and respiratory-gated PET/CT, and percent difference in SUVmax (%SUVmax) were compared. ResultsThe profile curve of 5 respiratory bin image was most similar to that of static image. The third bin of 5 respiratory bin image showed highest FWHM (24.0mm) and FWTM (32.7mm). The mean SUVmax of pancreatic cancer was similar to that of benign IPMN on non-respiratory-gated PET/CT (p=0.05), whereas significant difference was found between two groups on respiratory-gated PET/CT (p=0.016). The mean %SUV of pancreatic cancer was greater than that of benign IPMN (p<0.0001). Identification of the primary tumor in pancreatic head (n=13, 59%) was improved by using respiratory-gated PET/CT because of minimal affection of physiological accumulation in duodenum. ConclusionRespiratory-gated PET/CT is a feasible technique for evaluation of pancreatic tumors and allows more accurate identification of pancreatic tumors compared with non-respiratory-gated PET/CT.

Four‐dimensional cone beam CT reconstruction and enhancement using a temporal nonlocal means method

Four-dimensional cone beam computed tomography (4D-CBCT) has been developed to provide respiratory phase-resolved volumetric imaging in image guided radiation therapy. Conventionally, it is reconstructed by first sorting the x-ray projections into multiple respiratory phase bins according to a breathing signal extracted either from the projection images or some external surrogates, and then reconstructing a 3D CBCT image in each phase bin independently using FDK algorithm. This method requires adequate number of projections for each phase, which can be achieved using a low gantry rotation or multiple gantry rotations. Inadequate number of projections in each phase bin results in low quality 4D-CBCT images with obvious streaking artifacts. 4D-CBCT images at different breathing phases share a lot of redundant information, because they represent the same anatomy captured at slightly different temporal points. Taking this redundancy along the temporal dimension into account can in principle facilitate the reconstruction in the situation of inadequate number of projection images. In this work, the authors propose two novel 4D-CBCT algorithms: an iterative reconstruction algorithm and an enhancement algorithm, utilizing a temporal nonlocal means (TNLM) method. The authors define a TNLM energy term for a given set of 4D-CBCT images. Minimization of this term favors those 4D-CBCT images such that any anatomical features at one spatial point at one phase can be found in a nearby spatial point at neighboring phases. 4D-CBCT reconstruction is achieved by minimizing a total energy containing a data fidelity term and the TNLM energy term. As for the image enhancement, 4D-CBCT images generated by the FDK algorithm are enhanced by minimizing the TNLM function while keeping the enhanced images close to the FDK results. A forward-backward splitting algorithm and a Gauss-Jacobi iteration method are employed to solve the problems. The algorithms implementation on GPU is designed to avoid redundant and uncoalesced memory access, in order to ensure a high computational efficiency. Our algorithms have been tested on a digital NURBS-based cardiac-torso phantom and a clinical patient case. The reconstruction algorithm and the enhancement algorithm generate visually similar 4D-CBCT images, both better than the FDK results. Quantitative evaluations indicate that, compared with the FDK results, our reconstruction method improves contrast-to-noise-ratio (CNR) by a factor of 2.56-3.13 and our enhancement method increases the CNR by 2.75-3.33 times. The enhancement method also removes over 80% of the streak artifacts from the FDK results. The total computation time is 509-683 s for the reconstruction algorithm and 524-540 s for the enhancement algorithm on an NVIDIA Tesla C1060 GPU card. By innovatively taking the temporal redundancy among 4D-CBCT images into consideration, the proposed algorithms can produce high quality 4D-CBCT images with much less streak artifacts than the FDK results, in the situation of inadequate number of projections.

The impact of audio-visual biofeedback on 4D PET images: Results of a phantom study

Irregular breathing causes motion blurring artifacts in 4D PET images. Audiovisual (AV) biofeedback has been demonstrated to improve breathing regularity. To investigate the hypothesis that, compared with free breathing, motion blurring artifacts are reduced with AV biofeedback, the authors performed the first experimental phantom-based quantification of the impact of AV biofeedback on 4D PET image quality. The authors acquired 4D PET dynamic phantom images with AV biofeedback and free breathing by moving a phantom programmed with AV biofeedback trained and free breathing respiratory traces of ten healthy subjects. The authors also acquired stationary phantom images for reference. The phantom was cylindrical with six hollow sphere targets (10, 13, 17, 22, 28, and 37 mm in diameter). The authors quantified motion blurring using the target diameter, Dice coefficient and recovery coefficient (RC) metrics to estimate the effect of motion. The average increase in target diameter for AV biofeedback was 0.6±1.6mm (4.7±13%), which was significantly (p<0.001) smaller than for free breathing 1.3±2.2mm (9.1±19%). The average Dice coefficient for AV biofeedback was 0.90±0.07, which was significantly (p<0.001) larger than for free breathing (0.88±0.10). The RCs for AV biofeedback were consistently higher than those for free breathing and comparable to those for stationary targets. However, for RCs the impact of target sizes was more dominant than that of motion. In addition, the authors observed large variations in the results with respect to target sizes, subject traces and respiratory bins due to partial volume effects and respiratory motion irregularity. The results indicate that AV biofeedback can significantly reduce motion blurring artifacts and may facilitate improved identification and localization of lung tumors in 4D PET images. The results justify proceeding with clinical studies to quantify the impact of AV biofeedback on 4D PET image quality and tumor detectability.

SU‐E‐J‐153: Tracking Respiratory Motion in CBCT Projection Images Using an Integrated Optical Flow (IOF) Method

Purpose: To introduce and evaluate a new method for automatically extracting respiratory phase information directly from CBCT or tomosynthesis projection data. Methods: In the proposed method, the Black and Anandan dense optical flow is computed in the longitudinal direction between a fixed region of interest (ROI) extracted from each projection image in a free‐breathing CBCT scan and its nearest chronological neighbor. The optical flow values are integrated over time to yield a respiratory signal curve. Free‐breathing CBCT projection data from several thoracic and abdominal subjects were used to the compare the integrated optical flow (IOF) method with the “ground truth” signals measured by manually tracking the motion of internal anatomy landmarks (e.g., the diaphragm). Finally, phase information from the proposed technique was used to reconstruct exhalation and inhalation tomosynthesis image sets, for comparison with free‐breathing tomosynthesis reconstructions of the same subjects.Results: The proposed integrated optical flow (IOF) method yielded respiratory motion curves whose phase information agreed well with measured data. However, the IOF amplitudes showed strong chronological trends, due to changing projection geometry. Furthermore, the IOF method sometimes required an adjustment of the ROI location part‐way through the scan due to the rotational motion. Phase‐based tomosynthesis reconstructions using only projections near the full‐inhale or full‐exhale phases (as determined via the automated IOF method) exhibited the expected trends, with internal anatomy and target tumor locations clearly distinguished by phase, and often more clearly visible than in the full free‐ breathing reconstructions, which contain far more motion blurring Conclusions: The proposed IOF method is an effective way to automatically sort free‐breathing CBCT projection data into respiratory phase bins for phase‐based 4D tomosynthesis or CBCT reconstruction. Future work will focus on automatic relocation of the ROI and de‐trending of the IOF measures using estimations from the free‐breathing CBCT or planning CT.

3D radial sampling and 3D affine transform-based respiratory motion correction technique for free-breathing whole-heart coronary MRA with 100% imaging efficiency

The navigator gating and slice tracking approach currently used for respiratory motion compensation during free-breathing coronary magnetic resonance angiography (MRA) has low imaging efficiency (typically 30-50%), resulting in long imaging times. In this work, a novel respiratory motion correction technique with 100% scan efficiency was developed for free-breathing whole-heart coronary MRA. The navigator signal was used as a reference respiratory signal to segment the data into six bins. 3D projection reconstruction k-space sampling was used for data acquisition and enabled reconstruction of low resolution images within each respiratory bin. The motion between bins was estimated by image registration with a 3D affine transform. The data from the different respiratory bins was retrospectively combined after motion correction to produce the final image. The proposed method was compared with a traditional navigator gating approach in nine healthy subjects. The proposed technique acquired whole-heart coronary MRA with 1.0 mm(3) isotropic spatial resolution in a scan time of 6.8 ± 0.9 min, compared with 16.2 ± 2.8 min for the navigator gating approach. The image quality scores, and length, diameter and sharpness of the right coronary artery (RCA), left anterior descending coronary artery (LAD), and left circumflex coronary artery (LCX) were similar for both approaches (P > 0.05 for all), but the proposed technique reduced scan time by a factor of 2.5.

SU‐EE‐A3‐03: Audiovisual Biofeedback Significantly Reduces Motion Blurring Artifacts in Four‐Dimensional (4D) PET Images

Purpose: To investigate the hypothesis that audiovisual biofeedback reduces motion blurring artifacts in 4D PET images. Method and Materials: 4D PET scans were acquired on a GE PET/CT scanner using audiovisual biofeedback guided and free breathing traces. A static image was used as the reference. The physical phantom consisted of six hollow spheres (NEMA ICE body phantom) with 10, 13, 17, 22, 28 and 37 mm in diameter as targets and a cylinder (Hoffman 3D brain phantom) as background. The sphere targets were filled with 18F‐FDG at a fixed target‐to‐background ratio (8:1) based on 10 mCi/70 kg. The phantom was placed on a 3D programmable motion platform which produced the breathing patterns of four subjects with and without audiovisual biofeedback. 4D PET images with five respiratory bins were reconstructed for each breathing pattern. The segmented volumes, dice coefficients, 1D profiles, and 2D profiles were determined for evaluation and compared for each respiratory bin. The breathing patterns were analyzed for correlation between irregularity of breathing and motion blurring.Results: Audiovisual biofeedback significantly reduced motion blurring by 16.5% (1D profile, p=0.004), 22.6% (2D profile, p=0.003), 34.5% (volume, p=0.009) and 6.5% (dice coefficient, p=0.004) on average for the small spheres (≤17 mm), and by 4.3% (p=0.008), 2.7% (p=0.104), 0.7% (p=0.446) and 5.0% (p=0.014), respectively, for the large spheres (≥20 mm). In general, 4D PET motion blurring was dependent on the magnitude and irregularity of motion. Conclusion: The first investigation of the effect of breathing training on 4D PET images has been performed. The results indicate that audiovisual biofeedback can significantly reduce motion blurring in 4D PET images and may facilitate improved identification and localization of small lung tumors. Conflict of Interest: Supported by NIH/NCI R01 93626

MO‐EE‐A3‐02: Inferring Nodal Volume and Primary Tumor Positions From Multiple Anatomical Surrogates Using 4D CT in Stage III Lung Cancer

Purpose: To investigate the feasibility of modeling primary tumor and nodal volume positions from anatomical surrogates in order to reduce the contouring burden of planning from 4D CTs in Stage III lung cancer. Method and Materials: To localize their centroid positions at each respiratory phase, we contoured nodal volumes and primary tumors in 16 Stage III lung cancer planning 10‐equal‐phase 4D CTs. We also localized a series of anatomical respiratory surrogates (carina, xyphoid, nipples, midsternal external marker) in each image. To explore the feasibility of our proposed method, we 1) characterized the correlations between target and surrogate 3D motion, 2) applied Ordinary Least‐Squares (OLS) and Partial Least‐Squares (PLS) to a random subset (3–8) of images to predict the target positions in the remaining images, 3) determined the best set of three respiratory phase bins to contour, and 4) used them to create 3‐phase models using either all anatomical surrogates or carina alone. Results: The surrogate best‐correlated to target motion was most often the carina but varied widely. Depending on the number of phases used to build the models, mean errors ranged from 1.0mm to 1.4mm and from 0.8mm to 1.0mm for OLS and PLS, respectively. When the 0%, 40%, and 70% respiration phases were used, 3‐phase models had mean(±standard deviation) errors of 0.8±0.5mm and 2.4±9.0mm for models based on all surrogates and carina alone, respectively. For target coordinates with motion&gt;5mm, the mean 3‐phase error was 1.3mm. Conclusion: Using only three contoured respiratory phases to train the models, the mean model error was on the order of CT resolution. Inferential modeling of the primary tumor and nodal volume positions may have the potential to decrease the time required to process 4D CT scans, thereby improving therapy by allowing for incorporation of patient‐specific margins in the planning process.