Ordered Subset Expectation Maximization Research Articles

Evaluation and reduction of respiratory motion artifacts in small animal SPECT with GATE

The degradation of image quality caused by respiration is a major impediment to accurate lesion detection in single photon emission computed tomography (SPECT) imaging. This study was performed to evaluate the effects of lung motion on image quantification. A small animal SPECT system with NaI(Tl) was modeled in the Geant4 application for tomographic emission (GATE) simulation for a lung lesion using a 4D mouse whole-body phantom. SPECT images were obtained using 120 projection views acquired from 0o to 360o with a 3o step. Slices were reconstructed using ordered subsets expectation maximization (OS-EM) without attenuation correction with five iterations and four subsets. Image quality was compared between the static mode without respiratory motion, and dynamic mode with respiratory motion in terms of spatial resolution was measured by the full width at half maximum (FWHM), signal-to-noise ratio (SNR), and contrast-to-noise ratio (CNR). The FWHM of the non-gated image and the respiratory gated image were also compared. Spatial resolution improved as activity increased and lesion diameter decreased in the static and dynamic modes. The SNR and CNR increased significantly as lesion activity increased and lesion diameter decreased. Our results show that respiratory motion leads to reduced contrast and quantitative accuracy and that image quantification depends on both the amplitude and the pattern of the respiratory motion. We verified that respiratory motion can have a major effect on the accuracy of measurement of lung lesions and that respiratory gating can reduce activity smearing on SPECT images.

Reproducibility Between Brain Uptake Ratio Using Anatomic Standardization and Patlak-Plot Methods.

The Patlak-plot and conventional methods of determining brain uptake ratio (BUR) have some problems with reproducibility. We formulated a method of determining BUR using anatomic standardization (BUR-AS) in a statistical parametric mapping algorithm to improve reproducibility. The objective of this study was to demonstrate the inter- and intraoperator reproducibility of mean cerebral blood flow as determined using BUR-AS in comparison to the conventional-BUR (BUR-C) and Patlak-plot methods. The images of 30 patients who underwent brain perfusion SPECT were retrospectively used in this study. The images were reconstructed using ordered-subset expectation maximization and processed using an automatic quantitative analysis for cerebral blood flow of ECD tool. The mean SPECT count was calculated from axial basal ganglia slices of the normal side (slices 31-40) drawn using a 3-dimensional stereotactic region-of-interest template after anatomic standardization. The mean cerebral blood flow was calculated from the mean SPECT count. Reproducibility was evaluated using coefficient of variation and Bland-Altman plotting. For both inter- and intraoperator reproducibility, the BUR-AS method had the lowest coefficient of variation and smallest error range about the Bland-Altman plot. Mean CBF obtained using the BUR-AS method had the highest reproducibility. Compared with the Patlak-plot and BUR-C methods, the BUR-AS method provides greater inter- and intraoperator reproducibility of cerebral blood flow measurement.

Local validation of the use of Evolution for Bone for bone SPECT imaging.

In order to locally validate the technique, a retrospective review of a cohort of randomly selected single-photon emission computed tomography (SPECT) bone scans reconstructed with ordered subsets expectation maximization (OSEM) and Evolution for Bone was undertaken. Thirty consecutive bone SPECT patient data sets (17 spine, nine pelvis, and four spine and pelvis) were chosen. Poisson resampling was used to simulate reduced count data at 50, 75, and 100% of the original number of counts. Evolution for Bone applied resolution recovery to the reduced count images. All images were compared with the original OSEM images, currently used as the standard for clinical use. A qualitative blinded assessment was made by two independent observers, who assessed for noise, contrast, and resolution. Both radiologists saw an improvement in resolution (P = 0.776), noise (P = 0.007), and image quality with all data sets, compared with images processed purely with OSEM and viewed in Volumetrix. However, they completely disagreed on contrast, as the two radiologists scored contrast differently; however, the results are understandable. Images with 50, 75, and 100% of the original counts viewed using Evolution for Bone have improved image quality compared with images processed purely with OSEM and viewed in Volumetrix. Evolution for Bone therefore has great potential in departments for reducing either patient doses, waiting lists, or both.

Evaluation and reduction of respiratory motion artifacts in small animal SPECT with GATE

The degradation of image quality caused by respiration is a major impediment to accurate lesion detection in single photon emission computed tomography (SPECT) imaging. This study was performed to evaluate the effects of lung motion on image quantification. A small animal SPECT system with NaI(Tl) was modeled in the Geant4 application for tomographic emission (GATE) simulation for a lung lesion using a 4D mouse whole-body phantom. SPECT images were obtained using 120 projection views acquired from 0̂ to 360̂ with a 3̂ step. Slices were reconstructed using ordered subsets expectation maximization (OS-EM) without attenuation correction with five iterations and four subsets. Image quality was compared between the static mode without respiratory motion, and dynamic mode with respiratory motion in terms of spatial resolution was measured by the full width at half maximum (FWHM), signal-to-noise ratio (SNR), and contrast-to-noise ratio (CNR). The FWHM of the non-gated image and the respiratory gated image were also compared. Spatial resolution improved as activity increased and lesion diameter decreased in the static and dynamic modes. The SNR and CNR increased significantly as lesion activity increased and lesion diameter decreased. Our results show that respiratory motion leads to reduced contrast and quantitative accuracy and that image quantification depends on both the amplitude and the pattern of the respiratory motion. We verified that respiratory motion can have a major effect on the accuracy of measurement of lung lesions and that respiratory gating can reduce activity smearing on SPECT images.

Effect of 18F-FDG uptake time on lesion detectability in PET imaging of early stage breast cancer.

Prior reports have suggested that delayed 18F-fluorodeoxyglucose positron emission tomography (FDG-PET) oncology imaging can improve the contrast-to-noise ratio (CNR) for known lesions. Our goal was to estimate realistic bounds for lesion detectability for static measurements within 1 to 4 hours between FDG injection and image acquisition. Tumor and normal tissue kinetic model parameters were estimated from dynamic PET studies of patients with early-stage breast cancer. These parameters were used to generate time-activity curves (TACs) for up to 4 hours, for which we assumed both nonreversible and reversible models with different rates of FDG dephosphorylation (k4). For each pair of tumor and normal tissue TACs, 600 PET sinogram realizations were generated, and images were reconstructed using the ordered subsets expectation maximization reconstruction algorithm. Test statistics for each tumor and normal tissue region of interest were output from the computer model observers and evaluated using a receiver operating characteristic analysis, with the calculated area under the curve (AUC) providing a measure of lesion detectability. For the nonreversible model (k4 = 0), the AUC increased in 11 of 23 (48%) patients for 1 to 2 hours after the current standard postradiotracer injection imaging window of 1 hour. This improvement was driven by increased tumor/normal tissue contrast before the impact of increased noise that resulted from radiotracer decay began to dominate the imaging signal. As k4 was increased from 0 to 0.01 min−1, the time of maximum detectability shifted earlier, due to decreasing FDG concentration in the tumor lowering the CNR. These results imply that delayed PET imaging may reveal inconspicuous lesions that otherwise would have gone undetected.

The impact of reconstruction algorithms and time of flight information on PET/CT image quality.

BackgroundThe aim of the study was to explore the influence of various time-of-flight (TOF) and non-TOF reconstruction algorithms on positron emission tomography/computer tomography (PET/CT) image quality.Materials and methods.Measurements were performed with a triple line source phantom, consisting of capillaries with internal diameter of ∼ 1 mm and standard Jaszczak phantom. Each of the data sets was reconstructed using analytical filtered back projection (FBP) algorithm, iterative ordered subsets expectation maximization (OSEM) algorithm (4 iterations, 24 subsets) and iterative True-X algorithm incorporating a specific point spread function (PSF) correction (4 iterations, 21 subsets). Baseline OSEM (2 iterations, 8 subsets) was included for comparison. Procedures were undertaken following the National Electrical Manufacturers Association (NEMA) NU-2-2001 protocol.ResultsMeasurement of spatial resolution in full width at half maximum (FWHM) was 5.2 mm, 4.5 mm and 2.9 mm for FBP, OSEM and True-X; and 5.1 mm, 4.5 mm and 2.9 mm for FBP+TOF, OSEM+TOF and True-X+TOF respectively. Assessment of reconstructed Jaszczak images at different concentration ratios showed that incorporation of TOF information improves cold contrast, while hot contrast only slightly, however the most prominent improvement could be seen in background variability - noise reduction.ConclusionsOn the basis of the results of investigation we concluded, that incorporation of TOF information in reconstruction algorithm mostly affects reduction of the background variability (levels of noise in the image), while the improvement of spatial resolution due to incorporation of TOF information is negligible. Comparison of traditional and modern reconstruction algorithms showed that analytical FBP yields comparable results in some parameter measurements, such as cold contrast and relative count error. Iterative methods show highest levels of hot contrast, when TOF and PSF corrections were applied simultaneously.

Reliability and advantages of using non-uniform Chang's attenuation correction method using a CT-based attenuation coefficient map in (99m)Tc-GSA SPECT/CT hepatic imaging.

BackgroundGenerally, attenuation correction is made by incorporating a linear attenuation coefficient, which is based on the attenuation coefficient map (mu-map) created from a computed tomography scan, into the ordered subsets-expectation maximization reconstruction method in non-uniform domains. A non-uniform Chang’s attenuation correction method that uses the mu-map created from a computed tomography image that was made after reconstruction has been performed is currently available. The purpose of this study was to determine the usefulness of the non-uniform Chang’s attenuation correction method in 99mTc-galactosyl human serum albumin diethylenetriamine pentaacetic acid single photon emission computed tomography/computed tomography imaging.MethodsSingle photon emission computed tomography/computed tomography imaging was performed in phantoms with 99mTc water solutions and in a clinical study of 20 donors in living liver tissue transplantation. Attenuation correction was then performed in the reconstructed single photon emission computed tomography images with the non-uniform Chang’s method and ordered subsets-expectation maximization attenuation correction methods with triple energy window scatter correction. Root mean square error values were used for assessment of the image uniformity, and we evaluated the absolute radioactivity in liver parts in the phantoms and those in the donors who had a normal liver function.ResultsThe values of root mean square error on the non-uniform Chang’s attenuation correction images were lower than those on ordered subsets-expectation maximization attenuation correction images for both the phantoms and the 20 donors. The difference between the true and estimated radioactivity in the non-uniform Chang’s attenuation correction method was smaller than that in the ordered subsets-expectation maximization attenuation correction methods in the phantom study.ConclusionsThe non-uniform Chang’s attenuation correction is considered to be superior to the ordered subsets-expectation maximization attenuation correction in the assessment of absolute liver radioactivity and liver image uniformity on 99mTc-galactosyl human serum albumin diethylenetriamine pentaacetic acid single photon emission computed tomography/computed tomography imaging.

Effects of Regularisation Priors and Anatomical Partial Volume Correction on Dynamic PET Data

Dynamic PET provides temporal information about the tracer uptake. However, each PET frame has usually low statistics, resulting in noisy images. Furthermore, PET images suffer from partial volume effects. The goal of this study is to understand the effects of prior regularisation on dynamic PET data and subsequent anatomical partial volume correction. The Median Root Prior (MRP) regularisation method was used in this work during reconstruction. The quantification and noise in image-domain and time-domain (time-activity curves) as well as the impact on parametric images is assessed and compared with Ordinary Poisson Ordered Subset Expectation Maximisation (OP-OSEM) reconstruction with and without Gaussian filter. This study shows the improvement in PET images and time-activity curves (TAC) in terms of noise as well as in the parametric images when using prior regularisation in dynamic PET data. Anatomical partial volume correction improves the TAC and consequently, parametric images. Therefore, the use of MRP with anatomical partial volume correction is of interest for dynamic PET studies.

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

PurposePoint-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.MethodsNEMA 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.ResultsFor 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.ConclusionThese 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.Electronic supplementary materialThe online version of this article (doi:10.1007/s00259-015-3128-0) contains supplementary material, which is available to authorized users.

Estimation of Tumor Volumes by 11C-MeAIB and 18F-FDG PET in an Orthotopic Glioblastoma Rat Model.

Brain tumor volume assessment is a major challenge. Molecular imaging using PET may be a promising option because it reflects the biologically active cells. We compared the agreement between PET- and histology-derived tumor volumes in an orthotopic glioblastoma rat model with a noninfiltrating (U87MG) and an infiltrating (T87) tumor phenotype using 2 different radiotracers, 2 different image reconstruction algorithms, parametric imaging, and 2 different image segmentation techniques. Rats with U87MG- and T87-derived glioblastomas were continuously scanned with PET for 1 h starting immediately after the injection of 11C-methylaminoisobutyric acid (11C-MeAIB). One hour later, 18F-FDG was injected, followed by a 3-h dynamic PET scan. Images were reconstructed using 2-dimensional ordered-subsets expectation maximization and 3-dimensional maximum a posteriori probability (MAP3D) algorithms. In addition, a parametric image, encompassing the entire tumor kinetics in a single image, was calculated on the basis of the 11C-MeAIB images. All reconstructed images were segmented by fixed thresholding of maximum voxel intensity (VImax) and mean background intensity. The agreement between PET- and histology-derived tumor volumes and intra- and interobserver agreement of the PET-derived volumes were evaluated using Bland-Altman plots. By PET, the mean U87MG tumor volume was 35.0 mm3 using 18F-FDG and 34.1 mm3 with 11C-MeAIB, compared with 33.7 mm3 by histology. Corresponding T87 tumor volumes were 122.1 mm3 using 18F-FDG, 118.3 mm3 with 11C-MeAIB, and 125.4 mm3 by histology. None of these volumes were significantly different. The best agreement between PET- and histology-derived U87MG tumor volumes was achieved with 11C-MeAIB, MAP3D reconstruction, and fixed thresholding of VImax. The intra- and interobserver agreement was high using this method. For T87 tumors, the best agreement between PET- and histology-derived volumes was obtained using 18F-FDG, MAP3D reconstruction, and fixed thresholding of mean background intensity. The agreement using 11C-MeAIB, parametric imaging, and fixed thresholding of VImax was slightly inferior, but the intra- and interobserver agreement was clearly superior. Estimation of tumor volume by PET of noninfiltrating brain tumors was accurate and reproducible. In contrast, tumor volume estimation by PET of infiltrating brain tumors was difficult and hard to reproduce. On the basis of our results, PET evaluation of highly infiltrating brain tumors should be further developed.

Validation of semi-quantitative methods for DAT SPECT: influence of anatomical variability and partial volume effect

The aim of this work was to evaluate the influence of anatomical variability between subjects and of the partial volume effect (PVE) on the standardized Specific Uptake Ratio (SUR) in [123I]FP-bib SPECT studies. To this end, magnetic resonance (MR) images of 23 subjects with differences in the striatal volume of up to 44% were segmented and used to generate a database of 138 Monte Carlo simulated SPECT studies. Data included normal uptakes and pathological cases. Studies were reconstructed by filtered back projection (FBP) and the ordered-subset expectation-maximization algorithm. Quantification was carried out by applying a reference method based on regions of interest (ROIs) derived from the MR images and ROIs derived from the Automated Anatomical Labelling map. Our results showed that, regardless of anatomical variability, the relationship between calculated and true SUR values for caudate and putamen could be described by a multiple linear model which took into account the spill-over phenomenon caused by PVE ( for caudate and ≥0.980 for putamen) and also by a simple linear model (R2 ≥ 0.952 for caudate and ≥0.973 for putamen). Calculated values were standardized by inverting both linear systems. Differences between standardized and true values showed that, although the multiple linear model was the best approach in terms of variability ( ≥ 11.79 for caudate and ≤7.36 for putamen), standardization based on a simple linear model was also suitable ( ≥ 12.44 for caudate and ≤12.57 for putamen).

Performance evaluation of a 90°-rotating dual-head small animal PET system

Dual-head PET system suffers from poor resolution in the dimension perpendicular to the detector heads and vastly increased computations required by the accurate estimation of the system response matrix (SRM). The problem of poor x-axis resolution is caused by missing data owing to the intrinsic geometry flaws of the dual-head PET, which leads to high SRM similarity between the adjacent voxels along the x-axis. To compensate for this problem, our dual-head PET system prototype incorporates a -rotating mechanism. In addition, the cubic field of view (FOV) and cubic voxels are adopted to achieve a better geometrical symmetry, which avoids the re-estimation of SRM after rotation. The spatial resolution, sensitivity, noise equivalent count rate, scatter fraction and pileup fraction under different head separation distances were evaluated by a series of simulations, and the results were compared with those of the non-rotation system. The SRM was estimated using the Monte Carlo method and the three-dimensional images were reconstructed using the ordered subsets expectation maximization algorithm. Experimental results reveal a significantly improved x-axis resolution via the proposed rotation mechanism. Our system can achieve x-axis spatial resolution of 0.79 mm, 0.74 mm and 0.72 mm at the center of FOV under the head separation distance of 5 cm, 10 cm and 15 cm, respectively.

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.

Phantom and Clinical Evaluation of the Bayesian Penalized Likelihood Reconstruction Algorithm Q.Clear on an LYSO PET/CT System.

Q.Clear, a Bayesian penalized-likelihood reconstruction algorithm for PET, was recently introduced by GE Healthcare on their PET scanners to improve clinical image quality and quantification. In this work, we determined the optimum penalization factor (beta) for clinical use of Q.Clear and compared Q.Clear with standard PET reconstructions. A National Electrical Manufacturers Association image-quality phantom was scanned on a time-of-flight PET/CT scanner and reconstructed using ordered-subset expectation maximization (OSEM), OSEM with point-spread function (PSF) modeling, and the Q.Clear algorithm (which also includes PSF modeling). Q.Clear was investigated for β (B) values of 100-1,000. Contrast recovery (CR) and background variability (BV) were measured from 3 repeated scans, reconstructed with the different algorithms. Fifteen oncology body (18)F-FDG PET/CT scans were reconstructed using OSEM, OSEM PSF, and Q.Clear using B values of 200, 300, 400, and 500. These were visually analyzed by 2 scorers and scored by rank against a panel of parameters (overall image quality; background liver, mediastinum, and marrow image quality; noise level; and lesion detectability). As β is increased, the CR and BV decreases; Q.Clear generally gives a higher CR and lower BV than OSEM. For the smallest sphere reconstructed with Q.Clear B400, CR is 28.4% and BV 4.2%, with corresponding values for OSEM of 24.7% and 5.0%. For the largest hot sphere, Q.Clear B400 yields a CR of 75.2% and a BV of 3.8%, with corresponding values for OSEM of 64.4% and 4.0%. Scorer 1 and 2 ranked B400 as the preferred reconstruction in 13 of 15 (87%) and 10 of 15 (73%) cases. The least preferred reconstruction was OSEM PSF in all cases. In most cases, lesion detectability was highest ranked for B200, in 9 of 15 (67%) and 10 of 15 (73%), with OSEM PSF ranked lowest. Poor lesion detectability on OSEM PSF was seen in cases of mildly (18)F-FDG-avid mediastinal nodes in lung cancer and small liver metastases due to background noise. Conversely, OSEM PSF was ranked second highest for lesion detectability in most pulmonary nodule evaluation cases. The combined scores confirmed B400 to be the preferred reconstruction. Our phantom measurement results demonstrate improved CR and reduced BV when using Q.Clear instead of OSEM. A β value of 400 is recommended for oncology body PET/CT using Q.Clear.

The assessment of time-of-flight on image quality and quantification with reduced administered activity and scan times in 18F-FDG PET.

The last decade has seen considerable technological innovations in PET detectors with the availability, among other advances, of time-of-flight (TOF). TOF has been shown to increase the signal-to-noise ratio (SNR), which should allow for a reduction in acquired counts while maintaining image quality. Fifty-eight patients referred for routine F-flurodeoxyglucose ((18)F-FDG) oncology PET studies were included in this study. Patients with weight below or above 100 kg were prescribed 350 or 400 MBq of (18)F-FDG, respectively. Listmode data were acquired for 2.5 min per bed position and reconstructed with ordered-subset expectation maximization (OSEM) reconstruction. TOF reconstruction was performed on reduced-count data, with two levels of reduction (-20 and -40% for patients <100 kg and -16 and -30% for patients >100 kg) achieved by clipping the listmode data. Liver SNR, mediastinum mean standardized uptake value (SUV(mean)), and lesion maximum standardized uptake value (SUV(max)) were measured in all images. All images were visually assessed as adequate or suboptimal. No significant difference was seen in mediastinum SUV(mean) or lesion SUV(max) when comparing reduced-count TOF with full-count OSEM images. Compared with the original OSEM images, liver SNR was higher for TOF images using the more conservative -20% reduction of counts (P < 0.001, Wilcoxon's signed-rank test), whereas no significant statistical difference was seen with -40% reductions. Incorporation of TOF allows for a reduction in acquired counts; this method has been implemented at our institution, with administered activity reduced for all patients to 280 MBq and a reduction in scan times for all but the largest patients. This has significantly reduced the patient radiation dose and improved scanner flexibility and throughput.

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

PurposeIterative 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. MethodsA 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. ResultsForty-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). ConclusionsThis 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.

High-resolution brain SPECT imaging by combination of parallel and tilted detector heads.

To improve the spatial resolution of brain single-photon emission computed tomography (SPECT), we propose a new brain SPECT system in which the detector heads are tilted towards the rotation axis so that they are closer to the brain. In addition, parallel detector heads are used to obtain the complete projection data set. We evaluated this parallel and tilted detector head system (PT-SPECT) in simulations. In the simulation study, the tilt angle of the detector heads relative to the axis was 45°. The distance from the collimator surface of the parallel detector heads to the axis was 130 mm. The distance from the collimator surface of the tilted detector heads to the origin on the axis was 110 mm. A CdTe semiconductor panel with a 1.4 mm detector pitch and a parallel-hole collimator were employed in both types of detector head. A line source phantom, cold-rod brain-shaped phantom, and cerebral blood flow phantom were evaluated. The projection data were generated by forward-projection of the phantom images using physics models, and Poisson noise at clinical levels was applied to the projection data. The ordered-subsets expectation maximization algorithm with physics models was used. We also evaluated conventional SPECT using four parallel detector heads for the sake of comparison. The evaluation of the line source phantom showed that the transaxial FWHM in the central slice for conventional SPECT ranged from 6.1 to 8.5 mm, while that for PT-SPECT ranged from 5.3 to 6.9 mm. The cold-rod brain-shaped phantom image showed that conventional SPECT could visualize up to 8-mm-diameter rods. By contrast, PT-SPECT could visualize up to 6-mm-diameter rods in upper slices of a cerebrum. The cerebral blood flow phantom image showed that the PT-SPECT system provided higher resolution at the thalamus and caudate nucleus as well as at the longitudinal fissure of the cerebrum compared with conventional SPECT. PT-SPECT provides improved image resolution at not only upper but also at central slices of the cerebrum.

(90)Y -PET imaging: Exploring limitations and accuracy under conditions of low counts and high random fraction.

(90)Y -positron emission tomography (PET) imaging is becoming a recognized modality for postinfusion quantitative assessment following radioembolization therapy. However, the extremely low counts and high random fraction associated with (90)Y -PET may significantly impair both qualitative and quantitative results. The aim of this work was to study image quality and noise level in relation to the quantification and bias performance of two types of Siemens PET scanners when imaging (90)Y and to compare experimental results with clinical data from two types of commercially available (90)Y microspheres. Data were acquired on both Siemens Biograph TruePoint [non-time-of-flight (TOF)] and Biograph microcomputed tomography (mCT) (TOF) PET/CT scanners. The study was conducted in three phases. The first aimed to assess quantification and bias for different reconstruction methods according to random fraction and number of true counts in the scan. The NEMA 1994 PET phantom was filled with water with one cylindrical insert left empty (air) and the other filled with a solution of (90)Y . The phantom was scanned for 60 min in the PET/CT scanner every one or two days. The second phase used the NEMA 2001 PET phantom to derive noise and image quality metrics. The spheres and the background were filled with a (90)Y solution in an 8:1 contrast ratio and four 30 min acquisitions were performed over a one week period. Finally, 32 patient data (8 treated with Therasphere(®) and 24 with SIR-Spheres(®)) were retrospectively reconstructed and activity in the whole field of view and the liver was compared to theoretical injected activity. The contribution of both bremsstrahlung and LSO trues was found to be negligible, allowing data to be decay corrected to obtain correct quantification. In general, the recovered activity for all reconstruction methods was stable over the range studied, with a small bias appearing at extremely high random fraction and low counts for iterative algorithms. Point spread function (PSF) correction and TOF reconstruction in general reduce background variability and noise and increase recovered concentration. Results for patient data indicated a good correlation between the expected and PET reconstructed activities. A linear relationship between the expected and the measured activities in the organ of interest was observed for all reconstruction method used: a linearity coefficient of 0.89 ± 0.05 for the Biograph mCT and 0.81 ± 0.05 for the Biograph TruePoint. Due to the low counts and high random fraction, accurate image quantification of (90)Y during selective internal radionuclide therapy is affected by random coincidence estimation, scatter correction, and any positivity constraint of the algorithm. Nevertheless, phantom and patient studies showed that the impact of number of true and random coincidences on quantitative results was found to be limited as long as ordinary Poisson ordered subsets expectation maximization reconstruction algorithms with random smoothing are used. Adding PSF correction and TOF information to the reconstruction greatly improves the image quality in terms of bias, variability, noise reduction, and detectability. On the patient studies, the total activity in the field of view is in general accurately measured by Biograph mCT and slightly overestimated by the Biograph TruePoint.

Investigating the limits of PET/CT imaging at very low true count rates and high random fractions in ion-beam therapy monitoring.

External beam radiotherapy with protons and heavier ions enables a tighter conformation of the applied dose to arbitrarily shaped tumor volumes with respect to photons, but is more sensitive to uncertainties in the radiotherapeutic treatment chain. Consequently, an independent verification of the applied treatment is highly desirable. For this purpose, the irradiation-induced β(+)-emitter distribution within the patient is detected shortly after irradiation by a commercial full-ring positron emission tomography/x-ray computed tomography (PET/CT) scanner installed next to the treatment rooms at the Heidelberg Ion-Beam Therapy Center (HIT). A major challenge to this approach is posed by the small number of detected coincidences. This contribution aims at characterizing the performance of the used PET/CT device and identifying the best-performing reconstruction algorithm under the particular statistical conditions of PET-based treatment monitoring. Moreover, this study addresses the impact of radiation background from the intrinsically radioactive lutetium-oxyorthosilicate (LSO)-based detectors at low counts. The authors have acquired 30 subsequent PET scans of a cylindrical phantom emulating a patientlike activity pattern and spanning the entire patient counting regime in terms of true coincidences and random fractions (RFs). Accuracy and precision of activity quantification, image noise, and geometrical fidelity of the scanner have been investigated for various reconstruction algorithms and settings in order to identify a practical, well-suited reconstruction scheme for PET-based treatment verification. Truncated listmode data have been utilized for separating the effects of small true count numbers and high RFs on the reconstructed images. A corresponding simulation study enabled extending the results to an even wider range of counting statistics and to additionally investigate the impact of scatter coincidences. Eventually, the recommended reconstruction scheme has been applied to exemplary postirradiation patient data-sets. Among the investigated reconstruction options, the overall best results in terms of image noise, activity quantification, and accurate geometrical recovery were achieved using the ordered subset expectation maximization reconstruction algorithm with time-of-flight (TOF) and point-spread function (PSF) information. For this algorithm, reasonably accurate (better than 5%) and precise (uncertainty of the mean activity below 10%) imaging can be provided down to 80,000 true coincidences at 96% RF. Image noise and geometrical fidelity are generally improved for fewer iterations. The main limitation for PET-based treatment monitoring has been identified in the small number of true coincidences, rather than the high intrinsic random background. Application of the optimized reconstruction scheme to patient data-sets results in a 25% - 50% reduced image noise at a comparable activity quantification accuracy and an improved geometrical performance with respect to the formerly used reconstruction scheme at HIT, adopted from nuclear medicine applications. Under the poor statistical conditions in PET-based treatment monitoring, improved results can be achieved by considering PSF and TOF information during image reconstruction and by applying less iterations than in conventional nuclear medicine imaging. Geometrical fidelity and image noise are mainly limited by the low number of true coincidences, not the high LSO-related random background. The retrieved results might also impact other emerging PET applications at low counting statistics.

SU‐E‐T‐02: 90Y Microspheres Dosimetry Calculation with Voxel‐S‐Value Method: A Simple Use in the Clinic

Purpose:To present a simple and feasible method of voxel‐S‐value (VSV) dosimetry calculation for daily clinical use in radioembolization (RE) with 90Y microspheres. Dose distributions are obtained and visualized over CT images.Methods:Spatial dose distributions and dose in liver and tumor are calculated for RE patients treated with Sirtex Medical miscrospheres at our center. Data obtained from the previous simulation of treatment were the basis for calculations: Tc‐99m maggregated albumin SPECT‐CT study in a gammacamera (Infinia, General Electric Healthcare.). Attenuation correction and ordered‐subsets expectation maximization (OSEM) algorithm were applied.For VSV calculations, both SPECT and CT were exported from the gammacamera workstation and registered with the radiotherapy treatment planning system (Eclipse, Varian Medical systems). Convolution of activity matrix and local dose deposition kernel (S values) was implemented with an in‐house developed software based on Python code. The kernel was downloaded from www.medphys.it. Final dose distribution was evaluated with the free software Dicompyler.Results:Liver mean dose is consistent with Partition method calculations (accepted as a good standard). Tumor dose has not been evaluated due to the high dependence on its contouring. Small lesion size, hot spots in health tissue and blurred limits can affect a lot the dose distribution in tumors. Extra work includes: export and import of images and other dicom files, create and calculate a dummy plan of external radiotherapy, convolution calculation and evaluation of the dose distribution with dicompyler. Total time spent is less than 2 hours.Conclusion:VSV calculations do not require any extra appointment or any uncomfortable process for patient. The total process is short enough to carry it out the same day of simulation and to contribute to prescription decisions prior to treatment. Three‐dimensional dose knowledge provides much more information than other methods of dose calculation usually applied in the clinic.