3D PET Image Research Articles

High-resolution, quantitative 3D PET image reconstruction for the Siemens hybrid 3T MR/BrainPET scanner using the PET reconstruction software toolkit (PRESTO).

The Siemens 3T MR-BrainPET scanner allows us to simultaneously acquire high-resolution MR and PET images thus giving a strong asset for studies of the human brain. Meanwhile, the system is routinely used for MR-PET studies with a variety of radiotracers, e.g. 18F-FDG, 18F-FET, 11C-Raclopride, 11C-Flumazenil, 15O-Water. Based on the vendors’ sinogram-based reconstruction, quantitative dynamic images are obtained. However, this reconstruction uses compressed data in terms of span (axial) and mash (transaxial). Avoiding such data reduction strategies is desirable to improve the image quality. In this context, the PET Reconstruction Software Toolkit (PRESTO) provides better image quality in terms of resolution and noise at the expense of increased computational effort. For the first time, an accurate quantification with PRESTO has been achieved by integrating all mandatory data corrections. All data corrections are calculated for LORs individually and passed to the OP-OSEM implementation of PRESTO. The corrections comprise: component-based normalisation, template-based attenuation correction, variance-reduced random correction, scatter correction based on Single Scatter Simulation, dead time/pile up correction, decay correction and system calibration. In this way, the reconstructed images provide calibrated time-activity (TA) values (Bq/cc). Comparisons between TA curves (TAC) from the sinogram-based reconstruction and PRESTO show reproducible values within a few percent for all available tracers. Exemplarily, Figure ​Figure11 compares the brain tumor dynamics for a scan with FET. No significant deviations are observed in the TACs. However, the better SNR becomes evident for PRESTO (Figure ​(Figure2).2). Consequently, the hybrid 3T MR-BrainPET has emerged as an excellent tool for a wide spectrum of PET studies of the human brain due to the continuous improvements, which have successfully addressed the issues of quantification, optimising image quality and workflow. Figure 1 Comparison of TAC of a dynamic FET human brain tumor measurement. Figure 2 Image quality of a FET brain tumor measurement; PRESTO (top) vendors’ reconstruction (bottom).

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-C-9A-06: The Impact of CT Image Used for Attenuation Correction in 4D-PET

Purpose: To evaluate the appropriateness of using 3D non-gated CT image for attenuation correction (AC) in a 4D-PET (gated PET) imaging protocol used in radiotherapy treatment planning simulation. Methods: The 4D-PET imaging protocol in a Siemens PET/CT simulator (Biograph mCT, Siemens Medical Solutions, Hoffman Estates, IL) was evaluated. CIRS Dynamic Thorax Phantom (CIRS Inc., Norfolk, VA) with a moving glass sphere (8 mL) in the middle of its thorax portion was used in the experiments. The glass was filled with 18F-FDG and was in a longitudinal motion derived from a real patient breathing pattern. Varian RPM system (Varian Medical Systems, Palo Alto, CA) was used for respiratory gating. Both phase-gating and amplitude-gating methods were tested. The clinical imaging protocol was modified to use three different CT images for AC in 4D-PET reconstruction: first is to use a single-phase CT image to mimic actual clinical protocol (single-CT-PET); second is to use the average intensity projection CT (AveIP-CT) derived from 4D-CT scanning (AveIP-CT-PET); third is to use 4D-CT image to do the phase-matched AC (phase-matching- PET). Maximum SUV (SUVmax) and volume of the moving target (glass sphere) with threshold of 40% SUVmax were calculated for comparison between 4D-PET images derived with different AC methods. Results: The SUVmax varied 7.3%±6.9% over the breathing cycle in single-CT-PET, compared to 2.5%±2.8% in AveIP-CT-PET and 1.3%±1.2% in phasematching PET. The SUVmax in single-CT-PET differed by up to 15% from those in phase-matching-PET. The target volumes measured from single- CT-PET images also presented variations up to 10% among different phases of 4D PET in both phase-gating and amplitude-gating experiments. Conclusion: Attenuation correction using non-gated CT in 4D-PET imaging is not optimal process for quantitative analysis. Clinical 4D-PET imaging protocols should consider phase-matched 4D-CT image if available to achieve better accuracy.

TU-F-12A-05: Sensitivity of Textural Features to 3D Vs. 4D FDG-PET/CT Imaging in NSCLC Patients

Purpose: Neighborhood Gray-level difference matrices (NGLDM) based texture parameters extracted from conventional (3D) 18F-FDG PET scans in patients with NSCLC have been previously shown to associate with response to chemoradiation and poorer patient outcome. However, the change in these parameters when utilizing respiratory-correlated (4D) FDG-PET scans has not yet been characterized for NSCLC. The Objectives: of this study was to assess the extent to which NGLDM-based texture parameters on 4D PET images vary with reference to values derived from 3D scans in NSCLC. Methods: Eight patients with newly diagnosed NSCLC treated with concomitant chemoradiotherapy were included in this study. 4D PET scans were reconstructed with OSEM-IR in 5 respiratory phase-binned images and corresponding CT data of each phase were employed for attenuation correction. NGLDM-based texture features, consisting of coarseness, contrast, busyness, complexity and strength, were evaluated for gross tumor volumes defined on 3D/4D PET scans by radiation oncologists. Variation of the obtained texture parameters over the respiratory cycle were examined with respect to values extracted from 3D scans. Results: Differences between texture parameters derived from 4D scans at different respiratory phases and those extracted from 3D scans ranged from −30% to 13% for coarseness, −12% to 40% for contrast, −5%more » to 50% for busyness, −7% to 38% for complexity, and −43% to 20% for strength. Furthermore, no evident correlations were observed between respiratory phase and 4D scan texture parameters. Conclusion: Results of the current study showed that NGLDM-based texture parameters varied considerably based on choice of 3D PET and 4D PET reconstruction of NSCLC patient images, indicating that standardized image acquisition and analysis protocols need to be established for clinical studies, especially multicenter clinical trials, intending to validate prognostic values of texture features for NSCLC.« less

Optimized Bayes variational regularization prior for 3D PET images

A new prior for variational Maximum a Posteriori regularization is proposed to be used in a 3D One-Step-Late (OSL) reconstruction algorithm accounting also for the Point Spread Function (PSF) of the PET system.The new regularization prior strongly smoothes background regions, while preserving transitions. A detectability index is proposed to optimize the prior.The new algorithm has been compared with different reconstruction algorithms such as 3D-OSEM+PSF, 3D-OSEM+PSF+post-filtering and 3D-OSL with a Gauss-Total Variation (GTV) prior.The proposed regularization allows controlling noise, while maintaining good signal recovery; compared to the other algorithms it demonstrates a very good compromise between an improved quantitation and good image quality.

128: 4D dose calculations and 4D PET image reconstruction using deformable tetrahedral models of moving organs

Purpose: Respiratory-induced organ motion is a technical challenge to nuclear imaging and to particle therapy dose calculations for lung cancer treatment in particular. Internal organ tissue displacements and deformations induced by breathing need to be taken into account when calculating Monte Carlo dose distributions or when performing tomographic reconstructions for PET imaging. Current techniques based on Deformable Image Registration (DIR) cannot fully take into account complex internal deformations of the lungs nor the fact that respiratory motion is not reproducible. This study proposes a method to calculate dose distribution and to reconstruct PET activities over adaptive tetrahedral meshes which deform with time. As an illustration, biomechanical modeling based on Finite Element Analysis (FEA) was used for motion field computation.

Efficient fully 3D list-mode TOF PET image reconstruction using a factorized system matrix with an image domain resolution model

A factorized system matrix utilizing an image domain resolution model is attractive in fully 3D time-of-flight PET image reconstruction using list-mode data. In this paper, we study a factored model based on sparse matrix factorization that is comprised primarily of a simplified geometrical projection matrix and an image blurring matrix. Beside the commonly-used Siddon’s ray-tracer, we propose another more simplified geometrical projector based on the Bresenham’s ray-tracer which further reduces the computational cost. We discuss in general how to obtain an image blurring matrix associated with a geometrical projector, and provide theoretical analysis that can be used to inspect the efficiency in model factorization. In simulation studies, we investigate the performance of the proposed sparse factorization model in terms of spatial resolution, noise properties and computational cost. The quantitative results reveal that the factorization model can be as efficient as a non-factored model, while its computational cost can be much lower. In addition we conduct Monte Carlo simulations to identify the conditions under which the image resolution model can become more efficient in terms of image contrast recovery. We verify our observations using the provided theoretical analysis. The result offers a general guide to achieve the optimal reconstruction performance based on a sparse factorization model with an image domain resolution model.

A volume of intersection approach for on-the-fly system matrix calculation in 3D PET image reconstruction

The aim of this study is the evaluation of on-the-fly volume of intersection computation for system’s geometry modelling in 3D PET image reconstruction. For this purpose we propose a simple geometrical model in which the cubic image voxels on the given Cartesian grid are approximated with spheres and the rectangular tubes of response (ToRs) are approximated with cylinders. The model was integrated into a fully 3D list-mode PET reconstruction for performance evaluation. In our model the volume of intersection between a voxel and the ToR is only a function of the impact parameter (the distance between voxel centre to ToR axis) but is independent of the relative orientation of voxel and ToR. This substantially reduces the computational complexity of the system matrix calculation. Based on phantom measurements it was determined that adjusting the diameters of the spherical voxel size and the ToR in such a way that the actual voxel and ToR volumes are conserved leads to the best compromise between high spatial resolution, low noise, and suppression of Gibbs artefacts in the reconstructed images. Phantom as well as clinical datasets from two different PET systems (Siemens ECAT HR+ and Philips Ingenuity-TF PET/MR) were processed using the developed and the respective vendor-provided (line of intersection related) reconstruction algorithms. A comparison of the reconstructed images demonstrated very good performance of the new approach. The evaluation showed the respective vendor-provided reconstruction algorithms to possess 34–41% lower resolution compared to the developed one while exhibiting comparable noise levels. Contrary to explicit point spread function modelling our model has a simple straight-forward implementation and it should be easy to integrate into existing reconstruction software, making it competitive to other existing resolution recovery techniques.

Motion-specific internal target volumes for FDG-avid mediastinal and hilar lymph nodes

Background and purposeTo quantify the benefit of motion-specific internal target volumes for FDG-avid mediastinal and hilar lymph nodes generated using 4D-PET, vs. conventional internal target volumes generated using non-respiratory gated PET and 4D-CT scans. Materials and methodsFive patients with FDG-avid tumors metastatic to 11 hilar or mediastinal lymph nodes were imaged with respiratory-correlated FDG-PET (4D-PET) and 4D-CT. FDG-avid nodes were contoured by a radiation oncologist in two ways. Standard-of-care volumes were contoured using conventional un-gated PET, 4D-CT, and breath-hold CT. A second, motion-specific, set of volumes were contoured using 4D-PET.Contours based on 4D-PET corresponded directly to an internal target volume (ITV4D), whereas contours based on un-gated PET were expanded by a series of exploratory isotropic margins (from 5 to 13mm) based on literature recommendations on lymph node motion to form internal target volumes (ITV3D). ResultsA 13mm expansion of the un-gated PET nodal volume was needed to cover the ITV4D for 10 of 11 nodes studied. The ITV3D based on a 13mm expansion included on average 45cm3 of tissue that was not included in the ITV4D. ConclusionsMotion-specific lymph-node internal target volumes generated from 4D-PET imaging could be used to improve accuracy and/or reduce normal-tissue irradiation compared to the standard-of-care un-gated PET based internal target volumes.

SU-E-J-203: Texture Analysis of 3D and 4D PET/CT Images of Lung Cancer

Purpose: Texture/feature analysis of PET/CT images has great potential for predicting/monitoring tumor/normal tissue response to therapy, quantifying tumor spatiotemporal heterogeneity and radiosensitivity, and as indicators for adaptive therapy schemes. The objective of this study was to define a baseline and determine candidate texture/feature parameters. To this end, we performed image analysis on three dimensional (3D) and four dimensional (4D) PET/CT images of non‐small cell lung cancer patients. The ultimate goal is the development of radiomics tools for application in radiotherapy. Methods: All 4D‐PET data were reconstructed in 10 bins using the corresponding phases in 4D‐CT for attenuation correction. Co‐occurrence matrices of the tumor volumes were generated based on 3D and 4D PET images for 8 lung cancer patients. The texture parameters that were extracted from the original images or the co‐occurrence matrices included: entropy, local homogeneity, contrast, energy, V10‐V90, V80, V70, V40, I10‐I90, I30, Coefficient Variation, SD, Mean Intensity, Maximum Intensity, Minimum Intensity, and number of voxels. Texture comparisons between 3D and 4D PET and CT images and between various phases of 4D scans were performed. Results: A weak dependency of all the tested texture parameters on respiration phase was found for the 4D‐PET data for all patients, while large differences in some textures were found between the 3D‐PET or CT and one of the phases of the corresponding 4D data set, with larger percentage differences for the CT images. The differences for PET varied from 25% to 900%. Conclusion: Motion due to breathing altered statistical information obtained from intensity distributions from PET images, consequently 4D‐PET features were significantly different than 3D‐PET features. Texture parameters show minimal dependency on phase. PET images from one of the phases of a 4D‐PET with its corresponding 4D‐CT for attenuation correction are useful for texture analysis.

TU‐E‐141‐09: Impact of Attenuation Correction Mode On 4D PET/CT for Target Definition in Lung Cancer Patients

Purpose: The impact of attenuation correction on respiratory‐gated (4D) PET/CT images to define lung cancer targets, relative to 4D maximum intensity projection (MIP) or 3D static images, is poorly understood. Changes from 3DPET to 4DPET SUV metrics and target volumes were characterized in patients as a function of PET acquisition and CT attenuation correction (CTAC). Methods: Lung cancer patients underwent PET/CT list‐mode examinations spanning 3 bed positions. Static and respiratory phase‐gated sinograms were unlisted to generate 3DPET and 4DPET images. Emission data were attenuation‐corrected with phase‐averaged (4DAVG) or phase‐matched (4DMATCH) 4DCT and reconstructed with OSEM (2 iterations, 28 subsets, 5 mm post‐filter) on 2.0×2.0×3.3 mm3 voxel grids. PET target volumes were defined in MIM™5.6.3 using a gradient search method. Differences in SUVmax, SUVmean, SUVpeak, and defined volumes were compared between 3D, 4D MIP, and individual 4D phases by pairwise sign‐rank tests. 4DAVG and 4DMATCH CTAC‐PET image metrics were compared between respiratory phases using multi‐group non‐parametric ANOVA. Results: For 13 FDG‐PET avid lesions, SUVmax, SUVmean and SUVpeak were significantly higher in 4DMIP and 4D phase‐gated images relative to 3D images (9–11%, p<0.03). 4DMIP volumes were larger than 3D and 4D phase volumes (6–14%, p<0.01). 4DMATCH SUVmax was higher than 4DAVG SUVmax near end‐expiration phase and lower around peak‐inspiration phase (p=0.001). 4DMATCH SUVmean exceeded 4DAVG SUVmean at end‐expiration (p=0.02), while SUVpeak trended similarly but was insufficiently powered (p=0.06). 4D phase volumes were not significantly different between attenuation correction methods (p>0.37). Conclusion: 4DPET provides improved image quantification over 3DPET. 4DPET quantification near end‐expiration appears superior with phase‐matched CTAC, but may be less reliable during phase‐gates with residual motion and phase‐sorting CT artifacts. Optimization of CTAC from patient‐specific respiratory patterns may improve robustness of 4D PET/CT for lung cancer target definition and dose painting.

Deformation effect on SUVmax changes in thoracic tumors using 4-D PET/CT scan.

Respiratory motion blurs the standardized uptake value (SUV) and leads to a further signal reduction and changes in the SUV maxima. 4D PET can provide accurate tumor localization as a function of the respiratory phase in PET/CT imaging. We investigated thoracic tumor motion by respiratory 4D CT and assessed its deformation effect on the SUV changes in 4D PET imaging using clinical patient data. Twelve radiation oncology patients with thoracic cancer, including five lung cancer patients and seven esophageal cancer patients, were recruited to the present study. The 4D CT and PET image sets were acquired and reconstructed for 10 respiratory phases across the whole respiratory cycle. The optical flow method was applied to the 4D CT data to calculate the maximum displacements of the tumor motion in respiration. Our results show that increased tumor motion has a significant degree of association with the SUVmax loss for lung cancer. The results also show that the SUVmax loss has a higher correlation with tumors located at lower lobe of lung or at lower regions of esophagus.

Generation of 4-Dimensional CT Images Based on 4-Dimensional PET–Derived Motion Fields

Respiratory motion can potentially reduce accuracy in anatomic and functional image fusion from multimodality systems. It can blur the uptake of small lesions and lead to significant activity underestimation. Solutions presented to date include respiration-synchronized anatomic and functional acquisitions. To increase the signal-to-noise ratio of the synchronized PET images, methods using nonrigid transformations during the reconstruction process have been proposed. In most of these methods, 4-dimensional (4D) CT images were used to derive the required deformation matrices. However, variations between acquired 4D PET and corresponding CT image series due to differences in respiratory conditions during PET and CT acquisitions have been reported. In addition, the radiation dose burden resulting from a 4D CT acquisition may not be justifiable for every patient. In this paper, we present a method for the generation of dynamic CT images from the combination of one reference CT image and deformation matrices obtained from the elastic registration of 4D PET images not corrected for attenuation. On the one hand, our approach eliminates the need for the acquisition of dynamic CT. On the other hand, it also ensures a good match between CT and PET images, allowing accurate attenuation correction to be performed for respiration-synchronized PET acquisitions. The proposed method was first validated on Monte Carlo-simulated datasets, and then on patient datasets (n = 4) by comparing generated 4D CT images with the corresponding acquired original CT images. Different levels of PET image statistical quality were considered in order to investigate the impact of image noise in the derivation of the 4D CT series. Our results suggest that clinically relevant PET acquisition times can be used for the implementation of such an approach, making this an even more attractive solution considering the absence of the extra dose given by a standard 4D CT acquisition. Finally, this approach may be applicable to other multimodality devices such as PET/MR.

The retrospective binning method improves the consistency of phase binning in respiratory-gated PET/CT

This study assesses the accuracy of prospective phase-gated PET/CT data binning and presents a retrospective data binning method that improves image quality and consistency. Respiratory signals from 17 patients who underwent 4D PET/CT were analysed to evaluate the reproducibility of temporal triggers used for the standard phase-based gating method. Breathing signals were reprocessed to implement retrospective PET data binning. The mean and standard deviation of time lags between automatic triggers provided by the Real-time Position Management (RPM, Varian) gating device and inhalation peaks derived from respiratory curves were computed for each patient. The total number of respiratory cycles available for 4D PET/CT according to the binning mode (prospective versus retrospective) was compared. The maximum standardized uptake value (SUVmax), biological tumour volume (BTV) and tumour trajectory measures were determined from the PET/CT images of five patients. Compared to retrospective binning (RB), prospective gating approach led to (i) a significant loss in breathing cycles (15%) and (ii) the inconsistency of data binning due to temporal dispersion of triggers (average 396 ms). Consequently, tumour characterization could be impacted. In retrospective mode, SUVmax was up to 27% higher, where no significant difference appeared in BTV. In addition, prospective mode gave an inconsistent spatial location of the tumour throughout the bins. Improved consistency with breathing patterns and greater motion amplitude of the tumour centroid were observed with retrospective mode. The detection of the tumour motion and trajectory was improved also for small temporal dispersion of triggers. This study shows that the binning mode could have a significant impact on 4D PET images. The consistency of triggers with breathing signals should be checked before clinical use of gated PET/CT images, and our RB method improves 4D PET/CT image quantification.

Analysis of Serial FDG 4DPET Images Acquired During Radiation Therapy in Advanced Lung Cancer Patients

Analysis of Serial FDG 4DPET Images Acquired During Radiation Therapy in Advanced Lung Cancer Patients

Poster - Thur Eve - 20: Serial FDG 4DPET imaging during radiotherapy in advanced lung cancer patients.

The availability of respiratory synchronized PET (4DPET) imaging has enabled more accurate analysis of metabolic response since motion blur is minimized. We present our preliminary analysis of serial FDG 4DPET images acquired at weeks 0, 2, 4, and 7 during radiotherapy of seven stage II-III NSCLC patients. The tumor and nodal PTV of the week 0 images restrained a 4DPET image thresholding algorithm to automatically contour SUV levels ranging from 20 to 80% of the maximum SUV, creating an intensity volume histogram (IVH) for each week. These contours allowed analysis of PET volumes and standard PET metrics such as SUVmax and SUVmean . We found a trend for decreasing SUVmax and SUVmean over a treatment course in both the tumor and nodal regions. On average, the SUVmax within the tumor decreased by 17±13% (1 SD) after 2 weeks, 30±13% after 4 weeks, and 39±19% after 7 weeks of radiotherapy. Decreasing volume trends were also observed in the 20 to 80% max SUV autocontours, ranging from 26±29% to 50±40% respectively, over 7 weeks of treatment. Only one patient demonstrated an increase in FDG uptake within the tumor volume between week 0 and week 2 of treatment, and was also the only patient to recur locally at 3 months following treatment. Changes in tumor metabolism over the course of advanced NSCLC radiotherapy are quantifiable with serial FDG 4DPET imaging. Preliminary analysis suggests that variations in these trends could be useful in identifying non-responding patients that may require an alternative radiotherapeutic approach.

Fourier-wavelet restoration in PET/CT brain studies

Our goal is to improve brain PET imaging through the application of a novel, hybrid Fourier-wavelet (WFT) restoration technique. The major limitation of PET studies is a relatively poor resolution in comparison with MRI and CT imaging and there is a need for improved PET imaging. A GE DLS PET/CT 16 slice system was used to acquire the studies. In order to create restoration filters the point source study was performed. The 6-fillable spheres and 3D Hoffman brain phantom studies were acquired and used to test and optimize the restoration approach. The patient data used in the study were acquired in a 3D PET mode, using the standard clinical protocol. Here, we have implemented Fourier-wavelet regularized restoration. In the Fourier domain, the inverse of modulation transfer function was multiplied by a Butterworth low-pass filter, order n=6 and cut-off frequency f=0.35cycles/pixel. In addition, wavelet (Daubechies, order 2) noise suppression was applied by “hard threshold”. Hot spheres and 3D Hoffman brain studies showed that the restoration process not only improves resolution and contrast but also improves quantification in 3D PET/CT imaging. The average contrast increase was 19% and the quantification improved in the range 8−20% depending on sphere size. In the restored images, there was no significant increase in noise when compared with the original images. The clinical studies followed brain phantom findings, i.e., the restored images had better contrast and resolution properties, when compared with the original images. The results of the study demonstrate that the quality and quantification of 3D brain 18F FDG PET images can be significantly improved by Fourier-wavelet (WFT) restoration filtering.

SU-E-J-169: 4D-PET for Abdominal Tumor Target Volume Generation.

To examine the impact of 4D-PET on target volume delineation of upper-abdominal tumors, versus conventional un-gated PET. Four patients with upper-abdominal tumors underwent respiratory-correlated FDG PET/CT scanning (4D-PET) as part of a continuing IRB-approved research protocol. Internal target volumes of FDG-avid tumors were contoured on the 4D-PET and conventional un-gated PET by a radiation oncologist who is a specialist in gastro-intestinal tumors. To create the 4D-PET ITV, the end-inhale and end-exhale 4D-PET phases were used. The relative volumes and volumetric overlaps of the 4D and un-gated target volumes were examined. Additionally, 4D-PET was used to measure the motion of the tumors. Of the four patients who were imaged, one showed minimal motion (〈 3 mm in any direction) and one showed minimal FDG avidity; these were removed from further analysis. Of the two tumors which showed significant motion and FDG uptake, 4D-PET volumes were 28% and 21% larger than un-gated PET volumes. The un-gated PET volumes were almost entirely contained within the 4D-PET volumes (95% and 93% for the two tumors). Tumors appeared to deform as well as translate with breathing, although this could be due to varying intra-gate motion rather than actual physiological deformation. The superior-inferior borders of the tumors exhibited the most motion, with displacements of 5.6 mm and 6.4 mm. 4D-PET can be used to estimate the motion of FDG-avid upper-abdominal tumors. Use of 4D-PET increases the size of target volumes compared to un-gated PET in a subset of upper-abdominal cancer patients. Direct measurement of tumor motion and deformation by 4D-PET imaging could allow the use of patient-specific margins rather than population-based margins, potentially leading to increased target coverage and reduced normal tissue irradiation.

WE-G-213CD-02: 4D-PET Maximum Intensity Projections Improve Accuracy of Mobile Tumor Volume Delineation.

To examine the efficacy and accuracy of respiratory-gated positron emission tomography (4D-PET) maximum intensity projections (MIPs) in segmenting mobile tumor internal target volumes (ITVs) through a phantom study. An acrylic phantom was used for PET list-mode acquisition, consisting of 11C-filled spheres affixed inside a cylinder containing an 18-fluorodeoxyglucose solution. The phantom was attached to a robotic arm that underwent 1D motion based on clinically-derived patient breathing trajectories. An amplitude-based gating was performed on sequential list-mode sub-files of varying signal-to-background ratios, and PET-MIPs were generated from the gated images. ITVs were segmented by first denoising and deblurring images using a custom post-processing module and then applying an absolute SUV threshold. ITV accuracy was assessed using the volume recovery fraction (VRF) - the ratio of measured ITV to true volume occupied by the moving phantom spheres - which was used to compare PET-MIP, ungated PET, and static sphere images. In addition, the effects of tumor trajectories, number of gating windows, and margin additions were investigated. VRFs of ITVs generated from PET-MIPs were consistently higher than those from ungated PET. They also demonstrated a closer agreement to VRFs of static spheres (up to 99% similarity vs. 72% for ungated PET), suggesting that tumor motion had very little effect on the accuracy of PET-MIP measurements. Trajectories with higher amplitude and baseline drift decreased VRF by up to 14% for both PET-MIP and ungated PET. Increasing the number of gating windows (up to eight windows) resulted in higher VRFs for PET-MIPs without producing excessive image noise. PET-MIPs required a smaller margin addition than ungated PET to achieve a better overlap with the ground truth ITV. Compared to ungated PET, PET-MIPs are not significantly affected by tumor motion. 4D-PET imaging is a promising and viable methodology to better delineate mobile tumor volumes.

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.