Wendy Siman

Practical reconstruction protocol for quantitative 90Y bremsstrahlung SPECT/CT

PURPOSE To develop a practical background compensation (BC) technique to improve quantitative (90)Y-bremsstrahlung single-photon emission computed tomography (SPECT)/computed tomography (CT) using a commercially available imaging system. METHODS All images were acquired using medium-energy collimation in six energy windows (EWs), ranging from 70 to 410 keV. The EWs were determined based on the signal-to-background ratio in planar images of an acrylic phantom of different thicknesses (2-16 cm) positioned below a (90)Y source and set at different distances (15-35 cm) from a gamma camera. The authors adapted the widely used EW-based scatter-correction technique by modeling the BC as scaled images. The BC EW was determined empirically in SPECT/CT studies using an IEC phantom based on the sphere activity recovery and residual activity in the cold lung insert. The scaling factor was calculated from 20 clinical planar (90)Y images. Reconstruction parameters were optimized in the same SPECT images for improved image quantification and contrast. A count-to-activity calibration factor was calculated from 30 clinical (90)Y images. RESULTS The authors found that the most appropriate imaging EW range was 90-125 keV. BC was modeled as 0.53× images in the EW of 310-410 keV. The background-compensated clinical images had higher image contrast than uncompensated images. The maximum deviation of their SPECT calibration in clinical studies was lowest (<10%) for SPECT with attenuation correction (AC) and SPECT with AC + BC. Using the proposed SPECT-with-AC + BC reconstruction protocol, the authors found that the recovery coefficient of a 37-mm sphere (in a 10-mm volume of interest) increased from 39% to 90% and that the residual activity in the lung insert decreased from 44% to 14% over that of SPECT images with AC alone. CONCLUSIONS The proposed EW-based BC model was developed for (90)Y bremsstrahlung imaging. SPECT with AC + BC gave improved lesion detectability and activity quantification compared to SPECT with AC only. The proposed methodology can readily be used to tailor (90)Y SPECT/CT acquisition and reconstruction protocols with different SPECT/CT systems for quantification and improved image quality in clinical settings.

Effects of image noise, respiratory motion, and motion compensation on 3D activity quantification in count-limited PET images

The aims of this study were to evaluate the effects of noise, motion blur, and motion compensation using quiescent-period gating (QPG) on the activity concentration (AC) distribution-quantified using the cumulative AC volume histogram (ACVH)-in count-limited studies such as 90Y-PET/CT. An International Electrotechnical Commission phantom filled with low 18F activity was used to simulate clinical 90Y-PET images. PET data were acquired using a GE-D690 when the phantom was static and subject to 1-4 cm periodic 1D motion. The static data were down-sampled into shorter durations to determine the effect of noise on ACVH. Motion-degraded PET data were sorted into multiple gates to assess the effect of motion and QPG on ACVH. Errors in ACVH at AC90 (minimum AC that covers 90% of the volume of interest (VOI)), AC80, and ACmean (average AC in the VOI) were characterized as a function of noise and amplitude before and after QPG. Scan-time reduction increased the apparent non-uniformity of sphere doses and the dispersion of ACVH. These effects were more pronounced in smaller spheres. Noise-related errors in ACVH at AC20 to AC70 were smaller (<15%) compared to the errors between AC80 to AC90 (>15%). The accuracy of ACmean was largely independent of the total count. Motion decreased the observed AC and skewed the ACVH toward lower values; the severity of this effect depended on motion amplitude and tumor diameter. The errors in AC20 to AC80 for the 17 mm sphere were  -25% and  -55% for motion amplitudes of 2 cm and 4 cm, respectively. With QPG, the errors in AC20 to AC80 of the 17 mm sphere were reduced to  -15% for motion amplitudes  <4 cm. For spheres with motion amplitude to diameter ratio  >0.5, QPG was effective at reducing errors in ACVH despite increases in image non-uniformity due to increased noise. ACVH is believed to be more relevant than mean or maximum AC to calculate tumor control and normal tissue complication probability. However, caution needs to be exercised when using ACVH in post-therapy 90Y imaging because of its susceptibility to image degradation from both image noise and respiratory motion.

A revised monitor source method for practical deadtime count loss compensation in clinical planar and SPECT studies

The aim of the study is to verify the fundamental assumption in the monitor source method, i.e. uniform fractional count loss across the field of view (FOV), and to introduce a revised monitor source method for SPECT deadtime correction that minimally interferes with the clinical protocol. SPECT images of non-uniform phantoms (4GBq (99m)Tc) with and without monitor sources (2  ×  20MBq (99m)Tc) attached to each detector were acquired nine times over 48 h in the photopeak energy window and the scatter energy window. Fractional count loss uniformity across the FOV was evaluated by correlating count rates in different regions of interest on projection images at different deadtime loss levels. The correction factors were calculated as the ratios of monitor source count rates with and without the phantom. Such factors were applied to the phantom images acquired without the monitor sources. The counting efficiency (count rate per unit activity) of the camera was calculated as a function of activity in the FOV both prior to and after the deadtime count-loss correction. The deadtime correction effectiveness was assessed by the independence of the efficiency on the activity in the FOV. Methods to interpolate the projection deadtime loss, based on limited projections, were also investigated. The fractional deadtime count loss was uniform across the FOV (r > 0.99). After the deadtime correction, the efficiency was largely independent of the activity in the FOV. The median and maximum absolute errors after the deadtime count loss correction were ≤1% and ~2%, respectively. Measured deadtime loss from five views per detector can be used to estimate deadtime count loss with errors ≤1% for all SPECT projections. The revised monitor source method can effectively correct planar and SPECT deadtime loss. Sparse sampling of the projection deadtime loss allows the acquisition of high monitor source counts with minimal time added while preserving the entire useful FOV.

WE‐AB‐204‐01: Performance Characterization of Regularized‐Reconstruction Algorithm for 90Y PET/CT Images

Purpose: 9⁰Y PET/CT imaging and quantification have recently been suggested as an approach of treatment verification. However, due to low positron yield (32ppm), the 9⁰Y-PET/CT images are very noisy. Iterative reconstruction techniques that employ regularization, e.g. block sequential regularized expectation maximization (BSREM) algorithm (recently implemented on GE scanners – QClear™), has the potential to increase quantitative accuracy with lower noise penalty compared to OSEM. Our aim is to investigate the performance of RR algorithms in 9⁰Y PET/CT studies. Methods: A NEMA IEC phantom filled with 3GBq 9⁰YCl₂ (to simulate patient treatment) was imaged on GE-D690 for 1800s/bed. The sphere-to-background ratio of 7. The data were reconstructed using OSEM and BSREM with PSF modeling and TOF correction while varying the iterations (IT) from 1–6 with fixed 24subsets. For BSREM, the edge-preservation parameter (γ ) was 2 and the penalty-parameters (β) was varied 350–950. In all cases a post-reconstruction filter of 5.2mm (2pixel) transaxial and standard z-axis were used. Sphere average activity concentration (AC) and background standard deviation (SD) were then calculated from VOIs drawn in the spheres and background. Results: Increasing IT from 1to6, the %SD in OSEM increased from 30% to 80%, whereas %SD in BSREM images increased by <5% for all βs. BSREM with β=350 didn’t offer any improvement over OSEM (convergence of mean achieved at 2 IT, in this study). Increasing β from 350 to 950 reduced the AC accuracy of small spheres (<20mm) by 10% and noise from 40% to 20%, which resulted in CNR increase from 11 to 17. Conclusion: In count-limited studies such as 9⁰Y PET/CT, BSREM can be used to suppress image noise and increase CNR at the expense of a relatively small decrease of quantitative accuracy. The BSREM parameters need to be optimized for each study depending on the radionuclides and count densities. Research reported in this publication was supported by the National Cancer Institute of the National Institutes of Health under Award Number R01CA13898 and was also partly supported by General Electric.

SU‐E‐I‐20: Dead Time Count Loss Compensation in SPECT/CT: Projection Versus Global Correction

PURPOSE To compare projection-based versus global correction that compensate for deadtime count loss in SPECT/CT images. METHODS SPECT/CT images of an IEC phantom (2.3GBq 99mTc) with ∼10% deadtime loss containing the 37mm (uptake 3), 28 and 22mm (uptake 6) spheres were acquired using a 2 detector SPECT/CT system with 64 projections/detector and 15 s/projection. The deadtime, Ti and the true count rate, Ni at each projection, i was calculated using the monitor-source method. Deadtime corrected SPECT were reconstructed twice: (1) with projections that were individually-corrected for deadtime-losses; and (2) with original projections with losses and then correcting the reconstructed SPECT images using a scaling factor equal to the inverse of the average fractional loss for 5 projections/detector. For both cases, the SPECT images were reconstructed using OSEM with attenuation and scatter corrections. The two SPECT datasets were assessed by comparing line profiles in xyplane and z-axis, evaluating the count recoveries, and comparing ROI statistics. Higher deadtime losses (up to 50%) were also simulated to the individually corrected projections by multiplying each projection i by exp(-a*Ni*Ti), where a is a scalar. Additionally, deadtime corrections in phantoms with different geometries and deadtime losses were also explored. The same two correction methods were carried for all these data sets. RESULTS Averaging the deadtime losses in 5 projections/detector suffices to recover >99% of the loss counts in most clinical cases. The line profiles (xyplane and z-axis) and the statistics in the ROIs drawn in the SPECT images corrected using both methods showed agreement within the statistical noise. The count-loss recoveries in the two methods also agree within >99%. CONCLUSION The projection-based and the global correction yield visually indistinguishable SPECT images. The global correction based on sparse sampling of projections losses allows for accurate SPECT deadtime loss correction while keeping the study duration reasonable.

SU‐E‐I‐151: Performance Evaluation of a New Commercially Available Portable Pixelated Gamma Camera for 99mTc‐Scintimammography

Purpose: To characterize the imaging performance of a pixelated gamma camera (Ergo, Digirad) for 99mTc‐scintimammography. Methods: The 31×40cm2 Ergo detector consists of 6mm thick 3.31×3.24mm2 CsI(Tl) crystals coupled to siliconphotodiodes. The sensitivity and resolution was measured according to NEMA NU 1‐2007. Scintimammography performance was evaluated as hot tumordetection capabilities. We acquired images of different 99mTc‐spheres (inner diameters 3.95, 4.95, 6.23, 7.86, 9.89, 12.43mm) suspended in a 6.6cm thick 500mL 99mTc‐water bath. Images were acquired at tumor depths of 1.7 and 3.7mm with different sphere‐to‐background ratios (SBR: 5.0, 8.0, 10.1, 12.5, 18.8) for 10min acquisition using low‐energy collimation (LEHR). Acquisitions for 10, 5, 2.5, 1.25min were performed at SBR=5 where the 99mTc‐activity concentration (uCi/mL) in spheres/background was 34/6.8. The sphere‐CNR was estimated as: Sphere‐CNR = (SphereCounts_Max ‐ BackgroundCounts_Mean)/ BackgroundNoise. BackgroundNoise was the average standard deviation of 10 different 9‐pixel ROIs distributed across the image. BackgroundNoise was modeled as a power‐law function of BackgroundCounts_Mean and used to predict the sphere‐CNR at different activity levels and acquisition times. A preliminary visual assessment of sphere visibility was used to establish the threshold‐CNR for detection. Results: The sensitivity and resolution at 10cm using LEHR was measured to be 128cpm/uCi and 7.5mm. BackgroundNoise was found to vary as BackgroundCounts_Mean−0.67 suggesting a Poisson noise dominated imaging system. Threshold‐CNR of ∼8 corresponded to visible spheres. For SBR=5, depth=3.7cm, acquisition=10min, the measured sphere‐CNR for diameters 6.23, 7.86, 9.89, 12.43mm were 12.1, 15.9, 22.8, 33, respectively; that decreased to <3, 6.6, 10.1, 14.6 for acquisition=2.5min. The CNR predicted by the power‐law model for BackgroundNoise was in good agreement (differences of 9‐26%) with measured sphere‐CNR at lower acquisition times. Conclusions: The Ergo system is suitable for 99mTc‐ scintimammography with predictable performance at different imaging conditions. Small tumors (<1cm) could be visualized at a range of SBR under tested conditions.