BackgroundTo assess differences between four different voxel-based dosimetry methods (VBDM) for tumor, liver, and lung absorbed doses following 90Y microsphere selective internal radiation therapy (SIRT) based on 90Y bremsstrahlung SPECT/CT, a secondary objective was to estimate the sensitivity of liver and lung absorbed doses due to differences in organ segmentation near the liver-lung interface.MethodsInvestigated VBDM were Monte Carlo (MC), soft-tissue kernel with density correction (SKD), soft-tissue kernel (SK), and local deposition (LD). Seventeen SIRT cases were analyzed. Mean absorbed doses () were calculated for tumor, non-tumoral liver (NL), and right lung (RL). Simulations with various SPECT spatial resolutions (FHWMs) and multiple lung shunt fractions (LSs) estimated the accuracy of VBDM at the liver-lung interface. Sensitivity of patient RL and NL on segmentation near the interface was assessed by excluding portions near the interface.ResultsSKD, SK, and LD were within 5 % of MC for tumor and NL . LD and SKD overestimated RL compared to MC on average by 17 and 20 %, respectively; SK underestimated RL on average by −60 %. Simulations (20 mm FWHM, 20 % LS) showed that SKD, LD, and MC were within 10 % of the truth deep (>39 mm) in the lung; SK significantly underestimated the absorbed dose deep in the lung by approximately −70 %. All VBDM were within 10 % of truth deep (>12 mm) in the liver. Excluding 1, 2, and 3 cm of RL near the interface changed the resulting RL by −22, −38, and −48 %, respectively, for all VBDM. An average change of −7 % in the NL was realized when excluding 3 cm of NL from the interface. was realized when excluding 3 cm of NL from the interface.ConclusionsSKD, SK, and LD are equivalent to MC for tumor and NL . SK underestimates RL relative to MC whereas LD and SKD overestimate. RL is strongly influenced by the liver-lung interface.

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. C

Purpose: 90 Y-microsphere radioembolization or selective internal radiation therapy is increasingly being used as a treatment option for tumors that are not candidates for surgery and external beam radiation therapy. Recently, volumetric 90 Y-dosimetry techniques have been implemented to explore tumor dose-response on the basis of 3D 90 Y-activity distribution from PET imaging. Despite being a theranostic study, the optimization of quantitative 90 Y-PET image reconstruction still uses the mean activity concentration recovery coefficient (RC) as the objective function, which is more relevant to diagnostic and detection tasks than is to dosimetry. The aim of this study was to optimize 90 Y-PET image reconstruction by minimizing errors in volumetric dosimetry via the dose volume histogram (DVH). We propose a joint optimization of the number of equivalent iterations (the product of the iterations and subsets) and the postreconstruction filtration (FWHM) to improve the accuracy of voxel-level 90 Y dosimetry. Methods: A modified NEMA IEC phantom was used to emulate clinically relevant 90 Y-PET imaging conditions through various combinations of acquisition durations, activity concentrations, sphere-to-background ratios, and sphere diameters. PET data were acquired in list mode for 300 min in a single-bed position; we then rebinned the list mode PET data to 60, 45, 30, 15, and 5 min per bed, with 10 different realizations. Errors in the DVH were calculated as root mean square errors (RMSE) of the differences in the image-based DVH and the expected DVH. The new optimization approach was tested in a phantom study, and the results were compared with the more commonly used objective function of the mean activity concentration RC. Results: In a wide range of clinically relevant imaging conditions, using 36 equivalent iterations with a 5.2-mm filtration resulted in decreased systematic errors in volumetric 90 Y dosimetry, quantified as image-based DVH, in 90 Y-PET images reconstructed using the ordered subset expectation maximization (OSEM) iterative reconstruction algorithm with time of flight (TOF) and point spread function (PSF) modeling. Our proposed objective function of minimizing errors in DVH, which allows for joint optimization of 90 Y-PET iterations and filtration for volumetric quantification of the 90 Y dose, was shown to be superior to conventional RC-based optimization approaches for imagebased absorbed dose quantification. Conclusion: Our proposed objective function of minimizing errors in DVH, which allows for joint optimization of iterations and filtration to reduce errors in the PET-based volumetric quantification 90 Y dose, is relevant to dosimetry in therapy procedures. The proposed optimization method using DVH as the objective function could be applied to any imaging modality used to assess voxel-level quantitative information.

Purpose Quantify differences that exist between dosimetry models used for 90Y selective internal radiation therapy (SIRT). Methods and Materials Retrospectively, 37 tumors were delineated on 19 post-therapy quantitative 90Y SPECT/CT. Using matched volumes of interest (VOI), absorbed doses (AD) were reported using three dosimetry models: glass microsphere package insert standard model (SM), partition model (PM), and Monte Carlo (MC). Univariate linear regressions were performed to predict mean MC from SM and PM. Analysis was performed for two subsets: cases with a single tumor delineated (best case for PM); and cases with multiple tumors delineated (typical clinical scenario). Variability in PM from the ad hoc placement of a single spherical VOI to estimate the entire normal liver activity concentration for tumor (T) to non-tumoral liver (NL) ratios (TNR) was investigated. We interpreted the slope of the resulting regression as bias and the 95% prediction interval (95%PI) as uncertainty. MCNLsingle represents MC absorbed doses to the NL for the single tumor patient subset; other combinations of calculations follow a similar naming convention. Results SM was unable to predict MCTsingle or MCTmultiple (p>0.12, 95%PI>±177 Gy). However, SMsingle was able to predict (p<0.012) MCNLsingle , albeit with large uncertainties; SMsingle and SMmultiple yielded biases of 0.62 and 0.71, and 95%PI of ±40 and ±32 Gy, respectively. PMTsingle and PMTmultiple predicted (p<2E-6) MCTsingle and MCTmultiple with biases of 0.52 and 0.54, and 95%PI of ±38 and ±111 Gy, respectively. TNR variability in PMTsingle increased the 95%PI for predicting MCTsingle (bias=0.46 and 95%PI=±103 Gy). TNR variability in PMTmultiple modified the bias when predicting MCTmultiple (bias=0.32 and 95%PI=±110 Gy). Conclusions SM is unable to predict mean MC tumor absorbed dose. PM is statistically correlated with mean MC, but the resulting uncertainties in predicted MC are large. Large differences observed between dosimetry models for 90Y SIRT warrant caution when interpreting published SIRT absorbed doses. To reduce uncertainty, we suggest the entire NL VOI be used for TNR estimates when using PM.

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 Y-PET/CT. An International Electrotechnical Commission phantom filled with lowF activity was used to simulate clinical Y-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 AC (minimum AC that covers 90% of the volume of interest (VOI)), AC, and AC (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 AC to AC were smaller (<15%) compared to the errors between AC to AC (>15%). The accuracy of AC 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 AC to AC for the 17 mm sphere were  -25% and  -55% for motion amplitudes of 2 cm and 4 cm, respectively. With QPG, the errors in AC to AC 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 Y imaging because of its susceptibility to image degradation from both image noise and respiratory motion.

Herein, the authors describe detailed performance evaluation procedures of a new pixelated portable gamma camera system, which can also be applied to evaluate other pixelated gamma camera system. Spatial resolution assessment in near-field imaging condition offers a unique challenge where the measured FWHM is highly dependent on relative position between the capillary tube and the detector element. The evaluations of the Ergo gamma camera suggest suitable clinical imaging performance. This portable gamma camera has a high (LEAP) planar sensitivity, high energy and spatial resolutions that are comparable to other available gamma cameras, and it exhibits superior count rate performance that is linear up to tens of millions count per second. The Ergo imaging performance, however, can still be improved, for example, by optimizing collimator design for near field imaging.

Continuous-bed-motion (CBM) acquisition mode has been made commercially available in PET/CT scanners. CBM mode is designed for whole-body imaging, with a long scan length (multiple axial fields of view [aFOVs]) and short acquisition duration (2-3 min/aFOV). PET/CT has recently been used after Y-microsphere therapy to quantifyY activity distribution in the liver. Here we compared counting efficiencies along the bed-motion direction (-axis) between CBM and step-and-shoot (SS) acquisition modes for limited-view organ scans, such as Y PET/CT liver studies, that have short scan lengths (≤2 aFOVs) and long acquisition durations (10-30 min/aFOV). The counting efficiencies, that is, analytic sensitivities, in SS mode (single-aFOV and multiple-aFOV scans) and CBM mode were theoretically derived and experimentally validated using a cylindric Ge phantom. The sensitivities along the-axis were compared between the SS and CBM modes. The analytic and experimental count profiles were in good agreement, validating the analytic models. For fixed scan durations, the overall coincidence counting efficiency in CBM mode was lower (∼60%) than those in SS modes, and the maximum sensitivity in CBM mode was 50% or less of that in 1-aFOV SS mode and 100% or less of that in 2-aFOV SS mode. The ability of CBM mode to tailor-fit the PET/CT scan length and local scan duration is not realized in studies with a short scan length (≤30 cm) and long scan duration (20 min/aFOV for the scanner). SS acquisition mode is preferable to CBM mode for limited-view organ and count-starved scans, such as Y PET/CT liver scans, because of the higher counting efficiency of SS mode, which leads to better image quality and quantification precision.

Purpose: To develop and test the design of a new phantom, which is capable of producing experimental models of realistic activity distributions as observed in PET patients, for the evaluation of PET quantification accuracy and image segmentation algorithms. Methods: A phantom is constructed from thin plastic foils, less than 0.1 mm thick, which are cut along computer generated contours derived from the activity distribution of a large tumor in a patient PET scan. These sheets are used to displace activity inside a rectangular non‐uniform activity (NonU) cell (11.6 × 11.4 × 10.1 cm3), filled with a single activity solution of 18F‐ fluorodeoxyglucose (FDG), thus producing a non‐uniform activity distribution with variable activity gradients within a single PET slice or across multiple slices. The NonU cell is centered in a larger cylinder containing background activity. Corrections for omitted or deformed plastic sheets and for trapped air bubbles are applied to recover the known reference activity distribution. The phantom is tested in three different PET/CT scanners and the obtained images are compared to the known reference activity for different slices. Results: The resulting images retain the features of the selected region of interest of the original PET images of a patient tumor and agree well with the known activity distribution in the phantom. Differences between the known reference activity and the PET scan were found to be strongly dependent on registration and are less than 30% for more than 65% of the voxels for most of the tested slices. Conclusions: Using the NonU phantom to produce images of known activity distributions derived from clinically realistic activity configurations will aid in more accurate testing of PET quantification accuracy and in the development of image reconstruction, artifact correction and image segmentation algorithms. Improvements of the phantom design based on the test results are suggested.