Application and evaluation of a measured spatially variant system model for PET image reconstruction

Classification and evaluation strategies of auto-segmentation approaches for PET: Report of AAPM task group No. 211

PURPOSE

The purpose of this educational report is to provide an overview of the present state-of-the-art PET auto-segmentation (PET-AS) algorithms and their respective validation, with an emphasis on providing the user with help in understanding the challenges and pitfalls associated with selecting and implementing a PET-AS algorithm for a particular application.

APPROACH

A brief description of the different types of PET-AS algorithms is provided using a classification based on method complexity and type. The advantages and the limitations of the current PET-AS algorithms are highlighted based on current publications and existing comparison studies. A review of the available image datasets and contour evaluation metrics in terms of their applicability for establishing a standardized evaluation of PET-AS algorithms is provided. The performance requirements for the algorithms and their dependence on the application, the radiotracer used and the evaluation criteria are described and discussed. Finally, a procedure for algorithm acceptance and implementation, as well as the complementary role of manual and auto-segmentation are addressed.

FINDINGS

A large number of PET-AS algorithms have been developed within the last 20 years. Many of the proposed algorithms are based on either fixed or adaptively selected thresholds. More recently, numerous papers have proposed the use of more advanced image analysis paradigms to perform semi-automated delineation of the PET images. However, the level of algorithm validation is variable and for most published algorithms is either insufficient or inconsistent which prevents recommending a single algorithm. This is compounded by the fact that realistic image configurations with low signal-to-noise ratios (SNR) and heterogeneous tracer distributions have rarely been used. Large variations in the evaluation methods used in the literature point to the need for a standardized evaluation protocol.

CONCLUSIONS

Available comparison studies suggest that PET-AS algorithms relying on advanced image analysis paradigms provide generally more accurate segmentation than approaches based on PET activity thresholds, particularly for realistic configurations. However, this may not be the case for simple shape lesions in situations with a narrower range of parameters, where simpler methods may also perform well. Recent algorithms which employ some type of consensus or automatic selection between several PET-AS methods have potential to overcome the limitations of the individual methods when appropriately trained. In either case, accuracy evaluation is required for each different PET scanner and scanning and image reconstruction protocol. For the simpler, less robust approaches, adaptation to scanning conditions, tumor type, and tumor location by optimization of parameters is necessary. The results from the method evaluation stage can be used to estimate the contouring uncertainty. All PET-AS contours should be critically verified by a physician. A standard test, i.e., a benchmark dedicated to evaluating both existing and future PET-AS algorithms needs to be designed, to aid clinicians in evaluating and selecting PET-AS algorithms and to establish performance limits for their acceptance for clinical use. The initial steps toward designing and building such a standard are undertaken by the task group members.

Harmonizing standardized uptake value recovery between two PET/CT systems from different manufacturers when using resolution modelling and time-of-flight

PET iterative reconstruction algorithms with resolution modelling (RM) can be used to improve spatial resolution in the images. However, RM has a significant impact on quantification, which raises issues for harmonization across multicentre networks or collaborations. This investigation compared quantification from two modern time-of-flight (TOF) PET/CT systems from different manufacturers with RM with the intention to harmonize recovery. Images of a National Electrical Manufacturers Association image quality phantom with a sphere-to-background concentration ratio of 4 : 1 were acquired on a GE Discovery 710 and a Siemens Biograph mCT and reconstructed with RM and TOF. Voxel dimensions and image noise (background coefficient of variation) were matched. One to five iterations were used with 2 and 4 mm Gaussian filters. Mean and maximum contrast recovery (CR) were measured for the 10, 13, 17 and 22 mm hot phantom spheres. Notable differences in CR for images reconstructed with matched reconstruction parameters were observed between the scanners. A set of parameters was found that reduced differences in CR between scanners. Using these parameters, relative differences for the Biograph compared with the Discovery were -8.1, -3.7, +7 and +0.7% for mean CR and -23.1, -6.9, +9.1 and +0.9% for maximum CR in the 10, 13, 17 and 22 mm spheres, respectively. This study has used a technique of harmonizing standardized uptake value recovery on PET/CT systems from different vendors with advanced reconstructions including TOF and RM using phantom data. Considerable quantitative differences may occur in images, which highlights the need to apply methods such as those used in this work for multicentre studies.

High-resolution dynamic imaging and quantitative analysis of lung cancer xenografts in nude mice using clinical PET/CT

Considering the general application of dedicated small-animal positron emission tomography/computed tomography is limited, an acceptable alternative in many situations might be clinical PET/CT. To estimate the feasibility of using clinical PET/CT with [F-18]-fluoro-2-deoxy-D-glucose for high-resolution dynamic imaging and quantitative analysis of cancer xenografts in nude mice. Dynamic clinical PET/CT scans were performed on xenografts for 60 min after injection with [F-18]-fluoro-2-deoxy-D-glucose. Scans were reconstructed with or without SharpIR method in two phases. And mice were sacrificed to extracting major organs and tumors, using ex vivo γ-counting as a reference. Strikingly, we observed that the image quality and the correlation between the all quantitive data from clinical PET/CT and the ex vivo counting was better with the SharpIR reconstructions than without. Our data demonstrate that clinical PET/CT scanner with SharpIR reconstruction is a valuable tool for imaging small animals in preclinical cancer research, offering dynamic imaging parameters, good image quality and accurate data quatification.

Hybrid ZTE/Dixon MR-based attenuation correction for quantitative uptake estimation of pelvic lesions in PET/MRI

PURPOSE

This study introduces a new hybrid ZTE/Dixon MR-based attenuation correction (MRAC) method including bone density estimation for PET/MRI and quantifies the effects of bone attenuation on metastatic lesion uptake in the pelvis.

METHODS

Six patients with pelvic lesions were scanned using fluorodeoxyglucose (18F-FDG) in an integrated time-of-flight (TOF) PET/MRI system. For PET attenuation correction, MR imaging consisted of two-point Dixon and zero echo-time (ZTE) pulse sequences. A continuous-value fat and water pseudoCT was generated from a two-point Dixon MRI. Bone was segmented from the ZTE images and converted to Hounsfield units (HU) using a continuous two-segment piecewise linear model based on ZTE MRI intensity. The HU values were converted to linear attenuation coefficients (LAC) using a bilinear model. The bone voxels of the Dixon-based pseudoCT were replaced by the ZTE-derived bone to produce the hybrid ZTE/Dixon pseudoCT. The three different AC maps (Dixon, hybrid ZTE/Dixon, CTAC) were used to reconstruct PET images using a TOF-ordered subset expectation maximization algorithm with a point-spread function model. Metastatic lesions were separated into two classes, bone lesions and soft tissue lesions, and analyzed. The MRAC methods were compared using a root-mean-squared error (RMSE), where the registered CTAC was taken as ground truth.

RESULTS

The RMSE of the maximum standardized uptake values (SUV_max ) is 11.02% and 7.79% for bone (N = 6) and soft tissue lesions (N = 8), respectively, using Dixon MRAC. The RMSE of SUVmax for these lesions is significantly reduced to 3.28% and 3.94% when using the new hybrid ZTE/Dixon MRAC. Additionally, the RMSE for PET SUVs across the entire pelvis and all patients are 8.76% and 4.18%, for the Dixon and hybrid ZTE/Dixon MRAC methods, respectively.

CONCLUSION

A hybrid ZTE/Dixon MRAC method was developed and applied to pelvic regions in an integrated TOF PET/MRI, demonstrating improved MRAC. This new method included bone density estimation, through which PET quantification is improved.

NEMA NU 2-2012 performance studies for the SiPM-based ToF-PET component of the GE SIGNA PET/MR system

PURPOSE

The GE SIGNA PET/MR is a new whole body integrated time-of-flight (ToF)-PET/MR scanner from GE Healthcare. The system is capable of simultaneous PET and MR image acquisition with sub-400 ps coincidence time resolution. Simultaneous PET/MR holds great potential as a method of interrogating molecular, functional, and anatomical parameters in clinical disease in one study. Despite the complementary imaging capabilities of PET and MRI, their respective hardware tends to be incompatible due to mutual interference. In this work, the GE SIGNA PET/MR is evaluated in terms of PET performance and the potential effects of interference from MRI operation.

METHODS

The NEMA NU 2-2012 protocol was followed to measure PET performance parameters including spatial resolution, noise equivalent count rate, sensitivity, accuracy, and image quality. Each of these tests was performed both with the MR subsystem idle and with continuous MR pulsing for the duration of the PET data acquisition. Most measurements were repeated at three separate test sites where the system is installed.

RESULTS

The scanner has achieved an average of 4.4, 4.1, and 5.3 mm full width at half maximum radial, tangential, and axial spatial resolutions, respectively, at 1 cm from the transaxial FOV center. The peak noise equivalent count rate (NECR) of 218 kcps and a scatter fraction of 43.6% are reached at an activity concentration of 17.8 kBq/ml. Sensitivity at the center position is 23.3 cps/kBq. The maximum relative slice count rate error below peak NECR was 3.3%, and the residual error from attenuation and scatter corrections was 3.6%. Continuous MR pulsing had either no effect or a minor effect on each measurement.

CONCLUSIONS

Performance measurements of the ToF-PET whole body GE SIGNA PET/MR system indicate that it is a promising new simultaneous imaging platform.

Clinical evaluation of TOF versus non-TOF on PET artifacts in simultaneous PET/MR: a dual centre experience

PURPOSE

Our objective was to determine clinically the value of time-of-flight (TOF) information in reducing PET artifacts and improving PET image quality and accuracy in simultaneous TOF PET/MR scanning.

METHODS

A total 65 patients who underwent a comparative scan in a simultaneous TOF PET/MR scanner were included. TOF and non-TOF PET images were reconstructed, clinically examined, compared and scored. PET imaging artifacts were categorized as large or small implant-related artifacts, as dental implant-related artifacts, and as implant-unrelated artifacts. Differences in image quality, especially those related to (implant) artifacts, were assessed using a scale ranging from 0 (no artifact) to 4 (severe artifact).

RESULTS

A total of 87 image artifacts were found and evaluated. Four patients had large and eight patients small implant-related artifacts, 27 patients had dental implants/fillings, and 48 patients had implant-unrelated artifacts. The average score was 1.14 ± 0.82 for non-TOF PET images and 0.53 ± 0.66 for TOF images (p < 0.01) indicating that artifacts were less noticeable when TOF information was included.

CONCLUSION

Our study indicates that PET image artifacts are significantly mitigated with integration of TOF information in simultaneous PET/MR. The impact is predominantly seen in patients with significant artifacts due to metal implants.

Hybrid Pixel-Waveform (HPWF) Enabled CdTe Detectors for Small Animal Gamma-Ray Imaging Applications

This paper presents the design and preliminary evaluation of small-pixel CdTe gamma ray detectors equipped with a hybrid pixel-waveform (HPWF) readout system for gamma ray imaging applications with additional discussion on CZT due to its similarity. The HPWF readout system utilizes a pixelated anode readout circuitry which is designed to only provide the pixel address. This readout circuitry works in coincidence with a high-speed digitizer to sample the cathode waveform which provides the energy, timing, and depth-of-interaction (DOI) information. This work focuses on the developed and experimentally evaluated prototype HPWF-CdTe detectors with a custom CMOS pixel-ASIC to readout small anode pixels of 350 μm in size, and a discrete waveform sampling circuitry to digitize the signal waveform induced on the large cathode. The intrinsic timing, energy, and spatial resolution were experimentally evaluated in this paper in conjunction with methods for depth of interaction (DOI) partitioning of the CdTe crystal. While the experimental studies discussed in this paper are primarily for evaluating HPWF detectors for small animal PET imaging, these detectors could find their applications for ultrahigh-resolution SPECT and other imaging modalities.

A Subband-Specific Deconvolution Model for MTF Improvement in CT

The purpose of this research is to achieve uniform spatial resolution in CT (computed tomography) images without hardware modification. The main idea of this study is to consider geometry optics model, which can provide the approximate blurring PSF (point spread function) kernel, which varies according to the distance from X-ray tube to each pixel. The FOV (field of view) was divided into several band regions based on the distance from X-ray source, and each region was deconvolved with different deconvolution kernels. Though more precise calculation for the PSF for deconvolution is possible as the number of subbands increases, we set the number of subbands to 11. 11 subband settings seem to be a balancing point to reduce noise boost, while MTF (modulation transfer function) increase still remains. As the results show, subband-wise deconvolution makes image resolution (in terms of MTF) relatively uniform across the FOV. The results show that spatial resolution in CT images can be uniform across the FOV without using additional equipment. The beauty of this method is that it can be applied to any CT system as long as we know the specific system parameters and determine the appropriate PSF for deconvolution maps of the system. The proposed algorithm shows promising result in improving spatial resolution uniformity while avoiding the excessive noise boost.

Evaluation of lesion detectability in positron emission tomography when using a convergent penalized likelihood image reconstruction method

We have previously developed a convergent penalized likelihood (PL) image reconstruction algorithm using the relative difference prior (RDP) and showed that it achieves more accurate lesion quantitation compared to ordered subsets expectation maximization (OSEM). We evaluated the detectability of low-contrast liver and lung lesions using the PL-RDP algorithm compared to OSEM. We performed a two-alternative forced choice study using a channelized Hotelling observer model that was previously validated against human observers. Lesion detectability showed a stronger dependence on lesion size for PL-RDP than OSEM. Lesion detectability was improved using time-of-flight (TOF) reconstruction, with greater benefit for the liver compared to the lung and with increasing benefit for decreasing lesion size and contrast. PL detectability was statistically significantly higher than OSEM for 20 mm liver lesions when contrast was [Formula: see text] ([Formula: see text]), and TOF PL detectability was statistically significantly higher than TOF OSEM for 15 and 20 mm liver lesions with contrast [Formula: see text] and [Formula: see text], respectively. For all other cases, there was no statistically significant difference between PL and OSEM ([Formula: see text]). For the range of studied lesion properties, lesion detectability using PL-RDP was equivalent or improved compared to using OSEM.

Evaluation of spatial dependence of point spread function-based PET reconstruction using a traceable point-like 22Na source

Background

The point spread function (PSF) of positron emission tomography (PET) depends on the position across the field of view (FOV). Reconstruction based on PSF improves spatial resolution and quantitative accuracy. The present study aimed to quantify the effects of PSF correction as a function of the position of a traceable point-like ²²Na source over the FOV on two PET scanners with a different detector design.

Methods

We used Discovery 600 and Discovery 710 (GE Healthcare) PET scanners and traceable point-like ²²Na sources (<1 MBq) with a spherical absorber design that assures uniform angular distribution of the emitted annihilation photons. The source was moved in three directions at intervals of 1 cm from the center towards the peripheral FOV using a three-dimensional (3D)-positioning robot, and data were acquired over a period of 2 min per point. The PET data were reconstructed by filtered back projection (FBP), the ordered subset expectation maximization (OSEM), OSEM + PSF, and OSEM + PSF + time-of-flight (TOF). Full width at half maximum (FWHM) was determined according to the NEMA method, and total counts in regions of interest (ROI) for each reconstruction were quantified.

Results

The radial FWHM of FBP and OSEM increased towards the peripheral FOV, whereas PSF-based reconstruction recovered the FWHM at all points in the FOV of both scanners. The radial FWHM for PSF was 30–50 % lower than that of OSEM at the center of the FOV. The accuracy of PSF correction was independent of detector design. Quantitative values were stable across the FOV in all reconstruction methods. The effect of TOF on spatial resolution and quantitation accuracy was less noticeable.

Conclusions

The traceable ²²Na point-like source allowed the evaluation of spatial resolution and quantitative accuracy across the FOV using different reconstruction methods and scanners. PSF-based reconstruction reduces dependence of the spatial resolution on the position. The quantitative accuracy over the entire FOV of the PET system is good, regardless of the reconstruction methods, although it depends slightly on the position.

Image-based Modeling of PSF Deformation with Application to Limited Angle PET Data

The point-spread-functions (PSFs) of reconstructed images can be deformed due to detector effects such as resolution blurring and parallax error, data acquisition geometry such as insufficient sampling or limited angular coverage in dual-panel PET systems, or reconstruction imperfections/simplifications. PSF deformation decreases quantitative accuracy and its spatial variation lowers consistency of lesion uptake measurement across the imaging field-of-view (FOV). This can be a significant problem with dual panel PET systems even when using TOF data and image reconstruction models of the detector and data acquisition process. To correct for the spatially variant reconstructed PSF distortions we propose to use an image-based resolution model (IRM) that includes such image PSF deformation effects. Originally the IRM was mostly used for approximating data resolution effects of standard PET systems with full angular coverage in a computationally efficient way, but recently it was also used to mitigate effects of simplified geometric projectors. Our work goes beyond this by including into the IRM reconstruction imperfections caused by combination of the limited angle, parallax errors, and any other (residual) deformation effects and testing it for challenging dual panel data with strongly asymmetric and variable PSF deformations. We applied and tested these concepts using simulated data based on our design for a dedicated breast imaging geometry (B-PET) consisting of dual-panel, time-of-flight (TOF) detectors. We compared two image-based resolution models; i) a simple spatially invariant approximation to PSF deformation, which captures only the general PSF shape through an elongated 3D Gaussian function, and ii) a spatially variant model using a Gaussian mixture model (GMM) to more accurately capture the asymmetric PSF shape in images reconstructed from data acquired with the B-PET scanner geometry. Results demonstrate that while both IRMs decrease the overall uptake bias in the reconstructed image, the second one with the spatially variant and accurate PSF shape model is also able to ameliorate the spatially variant deformation effects to provide consistent uptake results independent of the lesion location within the FOV.

Design Features and Mutual Compatibility Studies of the Time-of-Flight PET Capable GE SIGNA PET/MR System

A recent entry into the rapidly evolving field of integrated PET/MR scanners is presented in this paper: a whole body hybrid PET/MR system (SIGNA PET/MR, GE Healthcare) capable of simultaneous acquisition of both time-of-flight (TOF) PET and high resolution MR data. The PET ring was integrated into an existing 3T MR system resulting in a (patient) bore opening of 60 cm diameter, with a 25 cm axial FOV. PET performance was evaluated both on the standalone PET ring and on the same detector integrated into the MR system, to assess the level of mutual interference between both subsystems. In both configurations we obtained detector performance data. PET detector performance was not significantly affected by integration into the MR system. The global energy resolution was within 2% (10.3% versus 10.5%), and the system coincidence time resolution showed a maximum change of < 3% (385 ps versus 394 ps) when measured outside MR and during simultaneous PET/MRI acquisitions, respectively. To evaluate PET image quality and resolution, the NEMA IQ phantom was acquired with MR idle and with MR active. Impact of PET on MR IQ was assessed by comparing SNR with PET acquisition on and off. B0 and B1 homogeneities were acquired before and after the integration of the PET ring inside the magnet. In vivo brain and whole body head-to-thighs data were acquired to demonstrate clinical image quality.

Dynamic Imaging of Individual Remyelination Profiles in Multiple Sclerosis

Background

Quantitative in vivo imaging of myelin loss and repair in patients with multiple sclerosis (MS) is essential to understand the pathogenesis of the disease and to evaluate promyelinating therapies. Selectively binding myelin in the central nervous system white matter, Pittsburgh compound B ([¹¹C]PiB) can be used as a positron emission tomography (PET) tracer to explore myelin dynamics in MS.

Methods

Patients with active relapsing‐remitting MS (n = 20) and healthy controls (n = 8) were included in a longitudinal trial combining PET with [¹¹C]PiB and magnetic resonance imaging. Voxel‐wise maps of [¹¹C]PiB distribution volume ratio, reflecting myelin content, were derived. Three dynamic indices were calculated for each patient: the global index of myelin content change; the index of demyelination; and the index of remyelination.

Results

At baseline, there was a progressive reduction in [¹¹C]PiB binding from the normal‐appearing white matter to MS lesions, reflecting a decline in myelin content. White matter lesions were characterized by a centripetal decrease in the tracer binding at the voxel level. During follow‐up, high between‐patient variability was found for all indices of myelin content change. Dynamic remyelination was inversely correlated with clinical disability (p = 0.006 and beta‐coefficient = –0.67 with the Expanded Disability Status Scale; p = 0.003 and beta‐coefficient = –0.68 with the MS Severity Scale), whereas no significant clinical correlation was found for the demyelination index.

Interpretation

[¹¹C]PiB PET allows quantification of myelin dynamics in MS and enables stratification of patients depending on their individual remyelination potential, which significantly correlates with clinical disability. This technique should be considered to assess novel promyelinating drugs. Ann Neurol 2016;79:726–738

[Accuracy of Resolution Recovery in PSF-based Fully-3D PET Image Reconstruction: Simulation and Phantom Study in Multicenter Trial]

PURPOSE

Recently, the quality of positron emission tomography (PET) images has rapidly improved using resolution recovery algorithm with point spread function (PSF). The aim of this study was to investigate the accuracy of the resolution recovery algorithm using three different PET systems.

METHODS

Three PET scanner models, the GE Discovery 600 M (D600M), SIEMENS Biograph mCT (mCT), and SHIMADZU SET-3000GCT/X (3000GCT) were used in this study. The radial dependences of spatial resolution (full width at half maximum: FWHM) were obtained by point source measurements (0.9 mmφ). All PET data were acquired in three-dimensional (3D) mode and reconstructed using the filtered back projection (FBP) , 3D-ordered subsets expectation maximization (3D-OSEM or dynamic row-action maximum likelihood algorithm) , and 3D-OSEM+PSF (PSF) algorithms. Two indicators, aspect ratio (ASR) and resolution recovery ratio (RRR), were calculated from measured FWHMs and compared among the three PET scanners.

RESULTS

In D600 and 3000GCT, distortions of the radial direction were slightly increased at circumference of field of view (FOV). On the other hand, random distortions were occurred in both radial and tangential direction in mCT. ASRs calculated from 3D-OSEM images at circumference of FOV were 2.06, 1.22, and 2.04 on D600M, mCT, and 3000GCT, respectively. ASR improved with PSF in all PET scanners. On the other hand, RRR with PSF were calculated 57.6%, 61.4%, and 31.6%, respectively.

CONCLUSION

Our results suggest that the spatial resolutions of PET images could be improved with PSF algorithm in all PET systems; however, effect of PSF was different depending on PET systems. Furthermore, PSF algorithm could not completely improve spatial resolutions in circumference of FOV.

On the assessment of spatial resolution of PET systems with iterative image reconstruction

Spatial resolution is an important metric for performance characterization in PET systems. Measuring spatial resolution is straightforward with a linear reconstruction algorithm, such as filtered backprojection, and can be performed by reconstructing a point source scan and calculating the full-width-at-half-maximum (FWHM) along the principal directions. With the widespread adoption of iterative reconstruction methods, it is desirable to quantify the spatial resolution using an iterative reconstruction algorithm. However, the task can be difficult because the reconstruction algorithms are nonlinear and the non-negativity constraint can artificially enhance the apparent spatial resolution if a point source image is reconstructed without any background. Thus, it was recommended that a background should be added to the point source data before reconstruction for resolution measurement. However, there has been no detailed study on the effect of the point source contrast on the measured spatial resolution. Here we use point source scans from a preclinical PET scanner to investigate the relationship between measured spatial resolution and the point source contrast. We also evaluate whether the reconstruction of an isolated point source is predictive of the ability of the system to resolve two adjacent point sources. Our results indicate that when the point source contrast is below a certain threshold, the measured FWHM remains stable. Once the contrast is above the threshold, the measured FWHM monotonically decreases with increasing point source contrast. In addition, the measured FWHM also monotonically decreases with iteration number for maximum likelihood estimate. Therefore, when measuring system resolution with an iterative reconstruction algorithm, we recommend using a low-contrast point source and a fixed number of iterations.

Novel penalised likelihood reconstruction of PET in the assessment of histologically verified small pulmonary nodules

OBJECTIVES

Investigate the effect of a novel Bayesian penalised likelihood (BPL) reconstruction algorithm on analysis of pulmonary nodules examined with 18F-FDG PET/CT, and to determine its effect on small, sub-10-mm nodules.

METHODS

18F-FDG PET/CTs performed for nodule evaluation in 104 patients (121 nodules) were retrospectively reconstructed using the new algorithm, and compared to time-of-flight ordered subset expectation maximisation (OSEM) reconstruction. Nodule and background parameters were analysed semi-quantitatively and visually.

RESULTS

BPL compared to OSEM resulted in statistically significant increases in nodule SUVmax (mean 5.3 to 8.1, p < 0.00001), signal-to-background (mean 3.6 to 5.3, p < 0.00001) and signal-to-noise (mean 24 to 41, p < 0.00001). Mean percentage increase in SUVmax (%ΔSUVmax) was significantly higher in nodules ≤10 mm (n = 31, mean 73%) compared to >10 mm (n = 90, mean 42 %) (p = 0.025). Increase in signal-to-noise was higher in nodules ≤10 mm (224%, mean 12 to 27) compared to >10 mm (165%, mean 28 to 46). When applying optimum SUVmax thresholds for detecting malignancy, the sensitivity and accuracy increased using BPL, with the greatest improvements in nodules ≤10 mm.

CONCLUSION

BPL results in a significant increase in signal-to-background and signal-to-noise compared to OSEM. When semi-quantitative analyses to diagnose malignancy are applied, higher SUVmax thresholds may be warranted owing to the SUVmax increase compared to OSEM.

KEY POINTS

• Novel Bayesian penalised likelihood PET reconstruction was applied for lung nodule evaluation. • This was compared to current standard of care OSEM reconstruction. • The novel reconstruction generated significant increases in lung nodule signal-to-background and signal-to-noise. • These increases were highest in small, sub-10-mm pulmonary nodules. • Higher SUV max thresholds may be warranted when using semi-quantitative analyses to diagnose malignancy.

The edge artifact in the point-spread function-based PET reconstruction at different sphere-to-background ratios of radioactivity

OBJECTIVE

The aim of this study was to quantitatively evaluate the edge artifacts in PET images reconstructed using the point-spread function (PSF) algorithm at different sphere-to-background ratios of radioactivity (SBRs).

METHODS

We used a NEMA IEC body phantom consisting of six spheres with 37, 28, 22, 17, 13 and 10 mm in inner diameter. The background was filled with (18)F solution with a radioactivity concentration of 2.65 kBq/mL. We prepared three sets of phantoms with SBRs of 16, 8, 4 and 2. The PET data were acquired for 20 min using a Biograph mCT scanner. The images were reconstructed with the baseline ordered subsets expectation maximization (OSEM) algorithm, and with the OSEM + PSF correction model (PSF). For the image reconstruction, the number of iterations ranged from one to 10. The phantom PET image analyses were performed by a visual assessment of the PET images and profiles, a contrast recovery coefficient (CRC), which is the ratio of SBR in the images to the true SBR, and the percent change in the maximum count between the OSEM and PSF images (Δ % counts).

RESULTS

In the PSF images, the spheres with a diameter of 17 mm or larger were surrounded by a dense edge in comparison with the OSEM images. In the spheres with a diameter of 22 mm or smaller, an overshoot appeared in the center of the spheres as a sharp peak in the PSF images in low SBR. These edge artifacts were clearly observed in relation to the increase of the SBR. The overestimation of the CRC was observed in 13 mm spheres in the PSF images. In the spheres with a diameter of 17 mm or smaller, the Δ % counts increased with an increasing SBR. The Δ % counts increased to 91 % in the 10-mm sphere at the SBR of 16.

CONCLUSIONS

The edge artifacts in the PET images reconstructed using the PSF algorithm increased with an increasing SBR. In the small spheres, the edge artifact was observed as a sharp peak at the center of spheres and could result in overestimation.

Pitfalls and Artifacts in the Use of PET/CT in Oncology Imaging

Accurate reporting of combined PET/CT imaging requires a thorough understanding of the normal and variant physiological distribution of tracers as well as common incidental findings and technical artifacts. We describe these pitfalls and artifacts, what action may help to mitigate them in clinical practice, and what further action may be appropriate. This review presents these in a region-based approach, in order to closely mimic clinical practice, and focuses on technical artifacts followed by a description of two commonly used oncologic tracers: FDG and choline.

Does a novel penalized likelihood reconstruction of 18F-FDG PET-CT improve signal-to-background in colorectal liver metastases?

PURPOSE

Iterative reconstruction algorithms are widely used to reconstruct positron emission tomography computerised tomography (PET/CT) data. Lesion detection in the liver by 18F-fluorodeoxyglucose PET/CT (18F-FDG-PET/CT) is hindered by 18F-FDG uptake in background liver parenchyma. The aim of this study was to compare semi-quantitative parameters of histologically-proven colorectal liver metastases detected by 18F-FDG-PET/CT using data based on a Bayesian penalised likelihood (BPL) reconstruction, with data based on a conventional time-of-flight (ToF) ordered subsets expectation maximisation (OSEM) reconstruction.

METHODS

A BPL reconstruction algorithm was used to retrospectively reconstruct sinogram PET data. This data was compared with OSEM reconstructions. A volume of interest was placed within normal background liver parenchyma. Lesions were segmented using automated thresholding. Lesion maximum standardised uptake value (SUVmax), standard deviation of background liver parenchyma SUV, signal-to-background ratio (SBR), and signal-to-noise ratio (SNR) were collated. Data was analysed using paired Student's t-tests and the Pearson correlation.

RESULTS

Forty-two liver metastases from twenty-four patients were included in the analysis. The average lesion SUVmax increased from 8.8 to 11.6 (p<0.001) after application of the BPL algorithm, with no significant difference in background noise. SBR increased from 4.0 to 4.9 (p<0.001) and SNR increased from 10.6 to 13.1 (p<0.001) using BPL. There was a statistically significant negative correlation between lesion size and the percentage increase in lesion SUVmax (p=0.03).

CONCLUSIONS

This BPL reconstruction algorithm improved SNR and SBR for colorectal liver metastases detected by 18F-FDG-PET/CT, increasing the lesion SUVmax without increasing background liver SUV or image noise. This may improve the detection of FDG-avid focal liver lesions and the diagnostic performance of clinical 18F-FDG-PET/CT in this setting, with the largest impact for small foci.

Plant-PET Scans: In Vivo Mapping of Xylem and Phloem Functioning

Medical imaging techniques are rapidly expanding in the field of plant sciences. Positron emission tomography (PET) is advancing as a powerful functional imaging technique to decipher in vivo the function of xylem water flow (with (15)O or (18)F), phloem sugar flow (with (11)C or (18)F), and the importance of their strong coupling. However, much remains to be learned about how water flow and sugar distribution are coordinated in intact plants, both under present and future climate regimes. We propose to use PET analysis of plants (plant-PET) to visualize and generate these missing data about integrated xylem and phloem transport. These insights are crucial to understanding how a given environment will affect plant physiological processes and growth.

[Harmonization of Standardized Uptake Value among Different Generation PET/ CT Cameras Based on a Phantom Experiment -Utility of SUV(peak)]

Standardized uptake value (SUV) has been widely used as a semi-quantitative metric of uptake in FDGPET/ CT for diagnosis of malignant tumors and evaluation of tumor therapies. However, the SUV depends on various factors including PET/CT scanner specifications and reconstruction parameters. The purpose of this study is to harmonize the SUV among two PET/CT models of different generation: two units of Discovery ST Elite Performance(DSTEP) and Discovery 690 (D690) PET/CT scanners. The NEMA body phantom filled with 18F solution was scanned for 30 minutes in list-mode. The D690 PET images were reconstructed with OSEM, OSEM+TOF, and OSEM+PSF. Gaussian post-filters of 4-9 mm FWHM were applied to find the parameters that provides harmonized SUV. We determined the SUV-harmonized parameter for each reconstruction algorithm. Then, the 10 PET images simulating clinical scan conditions were respectively generated to evaluate the bias and variability of SUV(max) and SUV(peak). The SUV(max) strongly depended not only on spatial resolution but also on image noise. On the other hand, the SUV(peak) was a robust metric to image noise level. TOF improved the variability of SUV(max) and SUV(peak). Thus, we were able to harmonize the spatial resolution using SUV(peak) based on the phantom study. Because SUV(max) was also strongly affected by image noise, sufficient count statistics is essential for SUV(max) harmonization. We recommended that TOF reconstruction and SUV(peak) metric should be used to harmonize SUV.

Multimodal Partial-Volume Correction: Application to 18F-Fluoride PET/CT Bone Metastases Studies

(18)F-fluoride PET/CT offers the opportunity for accurate skeletal metastasis staging, compared with conventional imaging methods. (18)F-fluoride is a bone-specific tracer whose uptake depends on osteoblastic activity. Because of the resulting increase in bone mineralization and sclerosis, the osteoblastic process can also be detected morphologically in CT images. Although CT is characterized by high resolution, the potential of PET is limited by its lower spatial resolution and the resulting partial-volume effect. In this context, the synergy between PET and CT presents an opportunity to resolve this limitation using a novel multimodal approach called synergistic functional-structural resolution recovery (SFS-RR). Its performance is benchmarked against current resolution recovery technology using the point-spread function (PSF) of the scanner in the reconstruction procedure.

METHODS

The SFS-RR technique takes advantage of the multiresolution property of the wavelet transform applied to both functional and structural images to create a high-resolution PET image that exploits the structural information of CT. Although the method was originally conceived for PET/MR imaging of brain data, an ad hoc version for whole-body PET/CT is proposed here. Three phantom experiments and 2 datasets of metastatic bone (18)F-fluoride PET/CT images from primary prostate and breast cancer were used to test the algorithm performances. The SFS-RR images were compared with the manufacturer's PSF-based reconstruction using the standardized uptake value (SUV) and the metabolic volume as metrics for quantification.

RESULTS

When compared with standard PET images, the phantom experiments showed a bias reduction of 14% in activity and 1.3 cm(3) in volume estimates for PSF images and up to 20% and 2.5 cm(3) for the SFS-RR images. The SFS-RR images were characterized by a higher recovery coefficient (up to 60%) whereas noise levels remained comparable to those of standard PET. The clinical data showed an increase in the SUV estimates for SFS-RR images up to 34% for peak SUV and 50% for maximum SUV and mean SUV. Images were also characterized by sharper lesion contours and better lesion detectability.

CONCLUSION

The proposed methodology generates PET images with improved quantitative and qualitative properties. Compared with standard methods, SFS-RR provides superior lesion segmentation and quantification, which may result in more accurate tumor characterization.

Harmonizing FDG PET quantification while maintaining optimal lesion detection: prospective multicentre validation in 517 oncology patients

PURPOSE

Point-spread function (PSF) or PSF + time-of-flight (TOF) reconstruction may improve lesion detection in oncologic PET, but can alter quantitation resulting in variable standardized uptake values (SUVs) between different PET systems. This study aims to validate a proprietary software tool (EQ.PET) to harmonize SUVs across different PET systems independent of the reconstruction algorithm used.

METHODS

NEMA NU2 phantom data were used to calculate the appropriate filter for each PSF or PSF+TOF reconstruction from three different PET systems, in order to obtain EANM compliant recovery coefficients. PET data from 517 oncology patients were reconstructed with a PSF or PSF+TOF reconstruction for optimal tumour detection and an ordered subset expectation maximization (OSEM3D) reconstruction known to fulfil EANM guidelines. Post-reconstruction, the proprietary filter was applied to the PSF or PSF+TOF data (PSFEQ or PSF+TOFEQ). SUVs for PSF or PSF+TOF and PSFEQ or PSF+TOFEQ were compared to SUVs for the OSEM3D reconstruction. The impact of potential confounders on the EQ.PET methodology including lesion and patient characteristics was studied, as was the adherence to imaging guidelines.

RESULTS

For the 1380 tumour lesions studied, Bland-Altman analysis showed a mean ratio between PSF or PSF+TOF and OSEM3D of 1.46 (95%CI: 0.86-2.06) and 1.23 (95%CI: 0.95-1.51) for SUVmax and SUVpeak, respectively. Application of the proprietary filter improved these ratios to 1.02 (95%CI: 0.88-1.16) and 1.04 (95%CI: 0.92-1.17) for SUVmax and SUVpeak, respectively. The influence of the different confounding factors studied (lesion size, location, radial offset and patient's BMI) was less than 5%. Adherence to the European Association of Nuclear Medicine (EANM) guidelines for tumour imaging was good.

CONCLUSION

These data indicate that it is not necessary to sacrifice the superior lesion detection and image quality achieved by newer reconstruction techniques in the quest for harmonizing quantitative comparability between PET systems.

Quantitative comparison of OSEM and penalized likelihood image reconstruction using relative difference penalties for clinical PET

Ordered subset expectation maximization (OSEM) is the most widely used algorithm for clinical PET image reconstruction. OSEM is usually stopped early and post-filtered to control image noise and does not necessarily achieve optimal quantitation accuracy. As an alternative to OSEM, we have recently implemented a penalized likelihood (PL) image reconstruction algorithm for clinical PET using the relative difference penalty with the aim of improving quantitation accuracy without compromising visual image quality. Preliminary clinical studies have demonstrated visual image quality including lesion conspicuity in images reconstructed by the PL algorithm is better than or at least as good as that in OSEM images. In this paper we evaluate lesion quantitation accuracy of the PL algorithm with the relative difference penalty compared to OSEM by using various data sets including phantom data acquired with an anthropomorphic torso phantom, an extended oval phantom and the NEMA image quality phantom; clinical data; and hybrid clinical data generated by adding simulated lesion data to clinical data. We focus on mean standardized uptake values and compare them for PL and OSEM using both time-of-flight (TOF) and non-TOF data. The results demonstrate improvements of PL in lesion quantitation accuracy compared to OSEM with a particular improvement in cold background regions such as lungs.

Clinical validation of high-resolution image reconstruction algorithms in brain 18F-FDG-PET: effect of incorporating Gaussian filter, point spread function, and time-of-flight

OBJECTIVES

Accurate estimation of radiopharmaceutical uptake in the brain is difficult because of count statistics, low spatial resolution, and smoothing filter. The aim of this study was to assess the counting rate performance of PET scanners and the image quality with different combinations of high-resolution image reconstruction algorithms in brain F-2-fluorodeoxy-D-glucose (F-FDG)-PET.

MATERIALS AND METHODS

Using 23 patient studies, we analyzed the coincidence rates of true and random, random fraction, and the noise equivalent counts per axial length (NECpatient) in brain and liver bed positions. The reconstruction algorithms were combined with baseline ordered subsets expectation maximization, Gaussian filter (GF), point spread function (PSF), and time-of-flight (TOF). The image quality of the brain cortex was quantitatively evaluated with respect to spatial resolution, contrast, and signal-to-noise ratio (SNR).

RESULTS

The true coincidence rate in the brain was higher by 1.86 times and the random coincidence rate was lower by 0.61 times compared with that in the liver. In the brain, random fraction was lower and NECpatient was higher than that of the liver. Although GF improved the SNR, spatial resolution and contrast were reduced by 12 and 11%, respectively (P<0.01). PSF improved spatial resolution and SNR by 11 and 53%, respectively (P<0.01), and TOF improved SNR by ∼23% (P<0.01).

CONCLUSION

We have demonstrated that a high-resolution image reconstruction algorithm for brain F-FDG-PET is promising without the use of a GF because of high true coincidence counts and that combined with PSF and TOF is optimal for obtaining a better SNR of the image.

Evaluation of image reconstruction algorithms encompassing Time-Of-Flight and Point Spread Function modelling for quantitative cardiac PET: phantom studies

BACKGROUND

To perform kinetic modelling quantification, PET dynamic data must be acquired in short frames, where different critical conditions are met. The accuracy of reconstructed images influences quantification. The added value of Time-Of-Flight (TOF) and Point Spread Function (PSF) in cardiac image reconstruction was assessed.

METHODS

A static phantom was used to simulate two extreme conditions: (i) the bolus passage and (ii) the steady uptake. Various count statistics and independent noise realisations were considered. A moving phantom filled with two different radionuclides was used to simulate: (i) a great range of contrasts and (ii) the cardio/respiratory motion. Analytical and iterative reconstruction (IR) algorithms also encompassing TOF and PSF modelling were evaluated.

RESULTS

Both analytic and IR algorithms provided good results in all the evaluated conditions. The amount of bias introduced by IR was found to be limited. TOF allowed faster convergence and lower noise levels. PSF achieved near full myocardial activity recovery in static conditions. Motion degraded performances, but the addition of both TOF and PSF maintained the best overall behaviour.

CONCLUSIONS

IR accounting for TOF and PSF can be recommended for the quantification of dynamic cardiac PET studies as they improve the results compared to analytic and standard IR.

Experimental evaluation and basis function optimization of the spatially variant image-space PSF on the Ingenuity PET/MR scanner

PURPOSE

The Ingenuity time-of-flight (TF) PET/MR is a recently developed hybrid scanner combining the molecular imaging capabilities of PET with the excellent soft tissue contrast of MRI. It is becoming common practice to characterize the system's point spread function (PSF) and understand its variation under spatial transformations to guide clinical studies and potentially use it within resolution recovery image reconstruction algorithms. Furthermore, due to the system's utilization of overlapping and spherical symmetric Kaiser-Bessel basis functions during image reconstruction, its image space PSF and reconstructed spatial resolution could be affected by the selection of the basis function parameters. Hence, a detailed investigation into the multidimensional basis function parameter space is needed to evaluate the impact of these parameters on spatial resolution.

METHODS

Using an array of 12 × 7 printed point sources, along with a custom made phantom, and with the MR magnet on, the system's spatially variant image-based PSF was characterized in detail. Moreover, basis function parameters were systematically varied during reconstruction (list-mode TF OSEM) to evaluate their impact on the reconstructed resolution and the image space PSF. Following the spatial resolution optimization, phantom, and clinical studies were subsequently reconstructed using representative basis function parameters.

RESULTS

Based on the analysis and under standard basis function parameters, the axial and tangential components of the PSF were found to be almost invariant under spatial transformations (~4 mm) while the radial component varied modestly from 4 to 6.7 mm. Using a systematic investigation into the basis function parameter space, the spatial resolution was found to degrade for basis functions with a large radius and small shape parameter. However, it was found that optimizing the spatial resolution in the reconstructed PET images, while having a good basis function superposition and keeping the image representation error to a minimum, is feasible, with the parameter combination range depending upon the scanner's intrinsic resolution characteristics.

CONCLUSIONS

Using the printed point source array as a MR compatible methodology for experimentally measuring the scanner's PSF, the system's spatially variant resolution properties were successfully evaluated in image space. Overall the PET subsystem exhibits excellent resolution characteristics mainly due to the fact that the raw data are not under-sampled/rebinned, enabling the spatial resolution to be dictated by the scanner's intrinsic resolution and the image reconstruction parameters. Due to the impact of these parameters on the resolution properties of the reconstructed images, the image space PSF varies both under spatial transformations and due to basis function parameter selection. Nonetheless, for a range of basis function parameters, the image space PSF remains unaffected, with the range depending on the scanner's intrinsic resolution properties.

Applications of the line-of-response probability density function resolution model in PET list mode reconstruction

Resolution degradation in PET image reconstruction can be caused by inaccurate modeling of the physical factors in the acquisition process. Resolution modeling (RM) is a common technique that takes into account the resolution degrading factors in the system matrix. Our previous work has introduced a probability density function (PDF) method of deriving the resolution kernels from Monte Carlo simulation and parameterizing the LORs to reduce the number of kernels needed for image reconstruction. In addition, LOR-PDF allows different PDFs to be applied to LORs from different crystal layer pairs of the HRRT. In this study, a thorough test was performed with this new model (LOR-PDF) applied to two PET scanners-the HRRT and Focus-220. A more uniform resolution distribution was observed in point source reconstructions by replacing the spatially-invariant kernels with the spatially-variant LOR-PDF. Specifically, from the center to the edge of radial field of view (FOV) of the HRRT, the measured in-plane FWHMs of point sources in a warm background varied slightly from 1.7 mm to 1.9 mm in LOR-PDF reconstructions. In Minihot and contrast phantom reconstructions, LOR-PDF resulted in up to 9% higher contrast at any given noise level than image-space resolution model. LOR-PDF also has the advantage in performing crystal-layer-dependent resolution modeling. The contrast improvement by using LOR-PDF was verified statistically by replicate reconstructions. In addition, [(11)C]AFM rats imaged on the HRRT and [(11)C]PHNO rats imaged on the Focus-220 were utilized to demonstrated the advantage of the new model. Higher contrast between high-uptake regions of only a few millimeter diameter and the background was observed in LOR-PDF reconstruction than in other methods.

Impact of respiratory motion correction and spatial resolution on lesion detection in PET: a simulation study based on real MR dynamic data

The aim of this study is to investigate the impact of respiratory motion correction and spatial resolution on lesion detectability in PET as a function of lesion size and tracer uptake. Real respiratory signals describing different breathing types are combined with a motion model formed from real dynamic MR data to simulate multiple dynamic PET datasets acquired from a continuously moving subject. Lung and liver lesions were simulated with diameters ranging from 6 to 12 mm and lesion to background ratio ranging from 3:1 to 6:1. Projection data for 6 and 3 mm PET scanner resolution were generated using analytic simulations and reconstructed without and with motion correction. Motion correction was achieved using motion compensated image reconstruction. The detectability performance was quantified by a receiver operating characteristic (ROC) analysis obtained using a channelized Hotelling observer and the area under the ROC curve (AUC) was calculated as the figure of merit. The results indicate that respiratory motion limits the detectability of lung and liver lesions, depending on the variation of the breathing cycle length and amplitude. Patients with large quiescent periods had a greater AUC than patients with regular breathing cycles and patients with long-term variability in respiratory cycle or higher motion amplitude. In addition, small (less than 10 mm diameter) or low contrast (3:1) lesions showed the greatest improvement in AUC as a result of applying motion correction. In particular, after applying motion correction the AUC is improved by up to 42% with current PET resolution (i.e. 6 mm) and up to 51% for higher PET resolution (i.e. 3 mm). Finally, the benefit of increasing the scanner resolution is small unless motion correction is applied. This investigation indicates high impact of respiratory motion correction on lesion detectability in PET and highlights the importance of motion correction in order to benefit from the increased resolution of future PET scanners.

Performance evaluation of the Trans-PET® BioCaliburn® LH system: a large FOV small-animal PET system

The Trans-PET(®) BioCaliburn(®) LH is a commercial positron emission tomography (PET) system for animal imaging. The system offers a large transaxial field-of-view (FOV) of 13.0 cm to allow imaging of multiple rodents or larger animals. This paper evaluates and reports the performance characteristics of this system.

METHODS

in this paper, the system was evaluated for its spatial resolutions, sensitivity, scatter fraction, count rate performance and image quality in accordance with the National Electrical Manufacturers Association (NEMA) NU-4 2008 specification with modifications. Phantoms and animals not specified in the NEMA specification were also scanned to provide further demonstration of its imaging capability.

RESULTS

the spatial resolution is 1.0 mm at the center. When using a 350-650 keV energy window and a 5 ns coincidence time window, the sensitivity at the center is 2.04%. The noise equivalent count-rate curve reaches a peak value of 62 kcps at 28 MBq for the mouse-sized phantom and a peak value of 25 kcps at 31 MBq for the rat-sized phantom. The scatter fractions are 8.4% and 17.7% for the mouse- and rat-sized phantoms, respectively. The uniformity and recovery coefficients measured by using the NEMA image-quality phantom both indicate good imaging performance, even though the reconstruction algorithm provided by the vendor does not implement all desired corrections. The Derenzo-phantom images show that the system can resolve 1.0 mm diameter rods. Animal studies demonstrate the capabilities of the system in dynamic imaging and to image multiple rodents.

CONCLUSION

the Trans-PET(®) BioCaliburn(®) LH system offers high spatial resolution, a large transaixal FOV and adequate sensitivity. It produces animal images of good quality and supports dynamic imaging. The system is an attractive imaging technology for preclinical research.

Impact of point spread function modelling and time of flight on FDG uptake measurements in lung lesions using alternative filtering strategies

BACKGROUND

The use of maximum standardised uptake value (SUVmax) is commonplace in oncology positron emission tomography (PET). Point spread function (PSF) modelling and time-of-flight (TOF) reconstructions have a significant impact on SUVmax, presenting a challenge for centres with defined protocols for lesion classification based on SUVmax thresholds. This has perhaps led to the slow adoption of these reconstructions. This work evaluated the impact of PSF and/or TOF reconstructions on SUVmax, SUVpeak and total lesion glycolysis (TLG) under two different schemes of post-filtering.

METHODS

Post-filters to match voxel variance or SUVmax were determined using a NEMA NU-2 phantom. Images from 68 consecutive lung cancer patients were reconstructed with the standard iterative algorithm along with TOF; PSF modelling - Siemens HD·PET (HD); and combined PSF modelling and TOF - Siemens ultraHD·PET (UHD) with the two post-filter sets. SUVmax, SUVpeak, TLG and signal-to-noise ratio of tumour relative to liver (SNR(T-L)) were measured in 74 lesions for each reconstruction. Relative differences in uptake measures were calculated, and the clinical impact of any changes was assessed using published guidelines and local practice.

RESULTS

When matching voxel variance, SUVmax increased substantially (mean increase +32% and +49% for HD and UHD, respectively), potentially impacting outcome in the majority of patients. Increases in SUVpeak were less notable (mean increase +17% and +23% for HD and UHD, respectively). Increases with TOF alone were far less for both measures. Mean changes to TLG were <10% for all algorithms for either set of post-filters. SNR(T-L) were greater than ordered subset expectation maximisation (OSEM) in all reconstructions using both post-filtering sets.

CONCLUSIONS

Matching image voxel variance with PSF and/or TOF reconstructions, particularly with PSF modelling and in small lesions, resulted in considerable increases in SUVmax, inhibiting the use of defined protocols for lesion classification based on SUVmax. However, reduced partial volume effects may increase lesion detectability. Matching SUVmax in phantoms translated well to patient studies for PSF reconstruction but less well with TOF, where a small positive bias was observed in patient images. Matching SUVmax significantly reduced voxel variance and potential variability of uptake measures. Finally, TLG may be less sensitive to reconstruction methods compared with either SUVmax or SUVpeak.

Relative role of motion and PSF compensation in whole-body oncologic PET-MR imaging

PURPOSE

Respiratory motion and partial-volume effects are the two main sources of image degradation in whole-body PET imaging. Simultaneous PET-MR allows measurement of respiratory motion using MRI while collecting PET events. Improved PET images may be obtained by modeling respiratory motion and point spread function (PSF) within the PET iterative reconstruction process. In this study, the authors assessed the relative impact of PSF modeling and MR-based respiratory motion correction in phantoms and patient studies using a whole-body PET-MR scanner.

METHODS

An asymmetric exponential PSF model accounting for radially varying and axial detector blurring effects was obtained from point source acquisitions performed in the PET-MR scanner. A dedicated MRI acquisition protocol using single-slice steady state free-precession MR acquisitions interleaved with pencil-beam navigator echoes was developed to track respiratory motion during PET-MR studies. An iterative ordinary Poisson fully 3D OSEM PET reconstruction algorithm modeling all the physical effects of the acquisition (attenuation, scatters, random events, detectors efficiencies, PSF), as well as MR-based nonrigid respiratory deformations of tissues (in both emission and attenuation maps) was developed. Phantom and(18)F-FDG PET-MR patient studies were performed to evaluate the proposed quantitative PET-MR methods.

RESULTS

The phantom experiment results showed that PSF modeling significantly improved contrast recovery while limiting noise propagation in the reconstruction process. In patients with soft-tissue static lesions, PSF modeling improved lesion contrast by 19.7%-109%, enhancing the detectability and assessment of small tumor foci. In a patient study with small moving hepatic lesions, the proposed reconstruction technique improved lesion contrast by 54.4%-98.1% and reduced apparent lesion size by 21.8%-34.2%. Improvements were particularly important for the smallest lesion undergoing large motion at the lung-liver interface. Heterogeneous tumor structures delineation was substantially improved. Enhancements offered by PSF modeling were more important when correcting for motion at the same time.

CONCLUSIONS

The results suggest that the proposed quantitative PET-MR methods can significantly enhance the performance of tumor diagnosis and staging as compared to conventional methods. This approach may enable utilization of the full potential of the scanner in oncologic studies of both the lower abdomen, with moving lesions, as well as other parts of the body unaffected by motion.

Surface-based partial-volume correction for high-resolution PET

Tissue radioactivity concentrations, measured with positron emission tomography (PET) are subject to partial volume effects (PVE) due to the limited spatial resolution of the scanner. Last generation high-resolution PET cameras with a full width at half maximum (FWHM) of 2-4mm are less prone to PVEs than previous generations. Corrections for PVEs are still necessary, especially when studying small brain stem nuclei or small variations in cortical neuroreceptor concentrations which may be related to cytoarchitectonic differences. Although several partial-volume correction (PVC) algorithms exist, these are frequently based on a priori assumptions about tracer distribution or only yield corrected values of regional activity concentrations without providing PVE corrected images. We developed a new iterative deconvolution algorithm (idSURF) for PVC of PET images that aims to overcome these limitations by using two innovative techniques: 1) the incorporation of anatomic information from a cortical gray matter surface representation, extracted from magnetic resonance imaging (MRI) and 2) the use of anatomically constrained filtering to attenuate noise. PVE corrected images were generated with idSURF implemented into a non-interactive processing pipeline. idSURF was validated using simulated and clinical PET data sets and compared to a frequently used standard PVC method (Geometric Transfer Matrix: GTM). The results on simulated data sets show that idSURF consistently recovers accurate radiotracer concentrations within 1-5% of true values. Both radiotracer concentrations and non-displaceable binding potential (BPnd) values derived from clinical PET data sets with idSURF were highly correlated with those obtained with the standard PVC method (R(2) = 0.99, error = 0%-3.2%). These results suggest that idSURF is a valid and potentially clinically useful PVC method for automatic processing of large numbers of PET data sets.

Iterative reconstruction using a Monte Carlo based system transfer matrix for dedicated breast positron emission tomography

To maximize sensitivity, it is desirable that ring Positron Emission Tomography (PET) systems dedicated for imaging the breast have a small bore. Unfortunately, due to parallax error this causes substantial degradation in spatial resolution for objects near the periphery of the breast. In this work, a framework for computing and incorporating an accurate system matrix into iterative reconstruction is presented in an effort to reduce spatial resolution degradation towards the periphery of the breast. The GATE Monte Carlo Simulation software was utilized to accurately model the system matrix for a breast PET system. A strategy for increasing the count statistics in the system matrix computation and for reducing the system element storage space was used by calculating only a subset of matrix elements and then estimating the rest of the elements by using the geometric symmetry of the cylindrical scanner. To implement this strategy, polar voxel basis functions were used to represent the object, resulting in a block-circulant system matrix. Simulation studies using a breast PET scanner model with ring geometry demonstrated improved contrast at 45% reduced noise level and 1.5 to 3 times resolution performance improvement when compared to MLEM reconstruction using a simple line-integral model. The GATE based system matrix reconstruction technique promises to improve resolution and noise performance and reduce image distortion at FOV periphery compared to line-integral based system matrix reconstruction.

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.