Evaluation of modified window-based scatter compensation in quantitative 177Lu-SPECT for a ring-configured CZT SPECT-CT

Evaluation of modified window-based scatter compensation in quantitative 177Lu-SPECT for a ring-configured CZT SPECT-CT | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Evaluation of modified window-based scatter compensation in quantitative 177Lu-SPECT for a ring-configured CZT SPECT-CT Irma Ceric Andelius, Anna Stenvall, Elias Nilsson, Erik Larsson, and 1 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8472942/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 4 You are reading this latest preprint version Abstract Background : The aim was to evaluate bias and precision for 177 Lu-activity-concentration estimation for window-based scatter compensation in a ring-configured CZT gamma camera. This paper extends a previous study by applying modified scatter compensation (MSC) methods. Whilst the original compensation addressed tailing in the 208 keV peak only, separating primary and scatter photons within the scatter window, the current adaption extents the concept to the 113 keV peak. In the modified version, the estimated primary signal in the scatter window can optionally also be added to measured projections to boost the signal-to-noise ratio (MSC + P). Methods : No additional measurements were acquired, and only previously collected listmode-data for a uniform cylindrical phantom, an image quality NEMA phantom and an anthropomorphic phantom were reframed to accommodate the updated window settings recommended for MSC and MSC + P. Reconstructions were performed using OS-EM with two to 30 iterations (10 subsets) with compensation for attenuation, scatter (DEW/TEW, MSC and MSC + P), distance-dependent spatial resolution, and penetration at 208 keV. Volume-of-interest following the physical sphere size were defined and activity-concentration estimates for each sphere, a liver region and for total activity in the phantoms were assessed in terms of bias and precision for short (10 min) and long timeframes (60 min). Results : Imaging at 208 keV generally result in similar bias and precision and total activity estimates for all scatter-compensation methods. For 113 keV, a slightly netter precision is obtained for MSC and MSC + P but at the cost of larger bias compared with TEW. The major difference is seen for total activity where the MSC and MSC + P manages to decrease bias considerably. The MSC + P yields a decrease in bias of about 10 percentage points when comparing short versus long time frames for activity concentration estimates at 113 keV. Conclusions : Despite the lack of broader improvement in bias and precision when using MSC and MSC + P the findings suggest potential value in more targeted applications. For instance, MSC and MSC + P improves preservation of total activity. Although the findings indicate that using MSC + P is not advisable for estimating high activity concentrations, it may positively influence the estimation of low activity concentrations. Quantitative SPECT CZT ring-configured SPECT lutetium-177 scatter compensation Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Figure 7 Figure 8 Figure 9 Figure 10 Background Quantitative single photon emission computed tomography (SPECT) is the cornerstone of image-based dosimetry in radionuclide therapy ( 1 ), with low bias and good precision of estimated activity concentrations being necessary for reliable and reproducible dosimetry. The introduction of clinical semi-conductor cadmium-zinc-telluride (CZT) ring-configured gamma-camera has led to an interest in using these systems also for quantitative tasks both for diagnostic ( e.g. , 99m Tc) and therapeutic ( e.g. , 177 Lu) radionuclides ( 2 ). The radionuclide 177 Lu emits two gamma photons useful for gamma-camera imagining at 113 keV and 208 keV. However, imaging of this radionuclide at CZT systems poses challenges as the systems are primarily designed for diagnostic tasks using 99m Tc, and collimator exchange is difficult for current designs. Thus, imaging at the higher energy suffers from penetration ( 2 , 3 ), whilst imaging at the lower energy suffers from a poor scatter-to-primary ratio. The poor scatter-to-primary ratio is a potential problem because of the charge-sharing phenomenon typical for pixelized CZT detectors ( 4 ). The charge-sharing phenomenon results in a tail of low-energy primary photons in the acquired signal, which makes window-based scatter compensation, such as the dual-energy window (DEW) and triple-energy windows (TEW) techniques, problematic. An underlying assumption of the standard DEW and TEW methods ( 5 , 6 ) is that the signal in the scatter windows consists of scattered photons only, and thus any contamination of primaries from the low-energy tail will result in erroneous scatter estimates and thus bias activity concentrations in the reconstructed image ( 7 , 8 ). Hence, the use of window-based scatter compensation for quantitative SPECT with CZT cameras requires consideration of such contamination. We demonstrated in a previous study that ring configured CZT-systems is a viable alternative to the dual headed Anger system for quantitative 177 Lu-SPECT ( 2 ). We further demonstrated that the ring-configured CZT system has a potential quantitative advantage compared with conventional Anger systems for imaging at 113 keV. However, we also noted substantial overestimation of total activity for imaging at this energy, which we suspected was related to imperfect scatter compensation. The present short communication extends our earlier investigation by evaluating a modified scatter-compensation (MSC) method that accounts for low energy tail of primary photons ( 9 ), enabled with the StarGuidePlus upgrade on the StarGuide™ (GE HealthCare, Haifa, Israel) system. Previous versions of the system implemented this method only for DEW scatter compensation at 208 keV, but the upgraded software also implements a TEW version applicable for imaging at 113 keV, which should reduce bias for this energy. The updated scatter-compensation module also allows for primary photons in scatter windows to be added back to the main window for the reconstruction (MSC + P), thereby potentially boosting the signal-to-noise ratio. We aim to assess the quantitative effect at 113 keV and 208 keV with respect to bias and precision for MSC, and MSC + P compared with the old scatter-compensation methods. Materials and methods The methodology applied here follows the approach described by Stenvall et al. ( 2 ), summarized here in brief. For a more comprehensive description, the reader is referred to the original publication. No additional phantom measurements were acquired in this study, only previously collected data for 177 Lu were utilized. Phantoms Phantoms described in Stenvall et al. ( 2 ) were utilized: A uniform cylindrical phantom (SUV phantom), an image quality NEMA phantom (NEMA IEC Body phantom) and an anthropomorphic phantom (LK-S Kyoto Liver/Kidney Phantom, Kyoto Kagaku Co., Ldt.). A new set of calibration factors was determined using the uniform cylindrical phantom for MSC and MSC + P. The NEMA phantom with six spheres was used to evaluate the quantitative performance of MSC and MSC + P for 177 Lu. The smallest sphere was replaced by a sphere with a volume of 113 ml and the spheres were positioned alternating between largest and smallest. The anthropomorphic phantom contained a liver insert with two spheres (Table 1 ). The sphere activity concentration and the tumour-to-liver ratio (set to 14) were based on the relationship determined from the pharmacokinetic model developed by Brolin et al. ( 10 ) 24 h post administration of [ 177 Lu]Lu-DOTA-TATE. Specifications for the phantoms are provided in Table 1 . Table 1 Specification of the phantoms prepared further described in by Stenvall et al. ( 2 ). Uniform phantom NEMA phantom Anthropomorphic phantom Diameter (mm)/Volume (mL) (fillable containers inner dimensions) -/5640 Sphere 1: 13/1.2 Sphere 2: 17/2.6 Sphere 3: 22/5.6 Sphere 4: 29/11.5 Sphere 5: 37/26.5 Sphere 6: 60/113.1 Sphere 1: 27/9.9 Sphere 2: 36/25.3 177 Lu activity concentration (MBq/ml) 0.098 1.8 Spheres: 1.93 (cold liver) 1.87 (warm liver) Liver: 0.13 SPECT reconstruction and calibration Previously collected listmode-data were reframed to adjust the energy window settings recommended for MSC and MSC + P (Table 2 ), and images were then reconstructed for the 113 keV and 208 keV peak separately ( 2 ). Reconstructions were performed with OS-EM with 2, 5, 10, 20 and 30 iterations (10 subsets) with a voxel size of 2.46x2.46x2.46 mm 3 using compensation for attenuation, distant-dependent resolution, scatter (MSC and MSC + P, as specified in Table 2 ), and compensation for penetration for the 208 keV peak. All reconstructions were performed on the Smart Console version 1.0 (GE Healthcare, Haifa, Israel). Reconstructed images from Stenvall et al. ( 2 ) were used for comparison. These were reconstructed with the same settings with respect to attenuation and resolution recovery but differed in energy windows and the scatter compensation. The images for 113 keV was reconstructed with TEW scatter compensation (with no account for the primary tail) and the images for 208 keV was reconstructed with DEW scatter compensation but accounting for the primary tail (a setting that could not be disabled). These two methods will be referred to the names used in Stenvall et al. ( 2 ), i.e. , TEW and DEW. The calibration factor was determined by placing a large cylindrical volume of interest (VOI, radius 7 cm and depth 20 cm) in the centre of the reconstructed image. For a thorough description the reader is referred to Stenvall et al ( 2 ). Scatter compensation Scatter compensation was employed by acquiring multiple energy windows (primary window (PW), low window (LW), high window (HW)). The MSC assumes that all energy windows contain primary and scattered photons, which thus forms linear equation system with the different contributions as unknowns. By solving this equation system, scatter and primary contributions can be estimated for each window. The scatter estimates are added to the forward projection in the iterative reconstruction ( 9 ). MSC + P includes adding tail photons to the primary window. By taking the sum of all three windows and estimating the scatter the remaining counts will be primaries ( 9 ). Details about the energy window settings are presented in Table 2 . Table 2 Energy window settings. PW: peak window, LW: low window, HW: high window Type Window centre/keV Window width/% DEW and TEW Emission (113 PW) 113.0 ± 10 Scatter (113 LW) 96.6 -4.6/+4.4 Scatter (113 HW) 129.4 -3.3/+3.7 Emission (208 PW) 208 ± 6 Scatter (208 LW) 185 ± 5 MSC and MSC + P Emission (113 PW) 113.0 ± 8 Scatter (113 LW) 93.5 ± 11 Scatter (113 HW) 133 ± 8 Emission (208 PW) 208 ± 6 Scatter (208 LW) 182.7 ± 7 Evaluation Spherical VOIs were defined by identifying the sphere centre-of-mass in SPECT images and including the voxels closest to the centre-point until the physical sphere volume was reached. For the anthropomorphic phantom with warm background, a 10 ml spherical VOI was also defined in the liver background. The same set of VOIs were used for all reconstructions. The bias was characterised by the mean relative error of the activity concentration over timeframes $$\:{\epsilon\:}_{i}=\frac{{\stackrel{-}{C}}_{i}}{{C}_{\text{r}\text{e}\text{f}}}-1,$$ 1 where \(\:{\stackrel{-}{C}}_{i}\) is the mean known activity concentration for sphere i , and \(\:{C}_{ref}\) is the calculated activity concentration at the start of image acquisition. The coefficient of variation (CV) was computed, as a measure of precision, according to $$\:CV=\frac{{s}_{i}}{{\stackrel{-}{C}}_{i}},$$ 2 where \(\:{s}_{i}\) is the standard deviation in the calculated activity concentration for sphere i over the six timeframes. Results NEMA phantom Examples of reconstructed images for 113 keV and 208 keV are presented in Fig. 1. The 208 keV images reconstructed with DEW, MSC and MSC + P appear similar, whilst the 113 keV images differ depending on scatter compensation method. The TEW and MSC images have a better contrast than the MSC + P image where a low-signal background is introduced between the spheres. Profiles through the two largest spheres and the non-radioactive background reconstructed with 10 iterations and 10 subsets are presented in Fig. 2. The profiles show signal outside of the spheres for all scatter compensation methods. For the 208 keV peak with DEW a slightly increased signal outside the spheres was observed whereas for MSC and MSC + P there is no apparent difference. For the 113 keV peak, a difference is seen when comparing TEW with MSC and MSC + P. Plots of mean relative error versus CV for different reconstructions are shown in Fig. 3 and numerical data at 30 iterations are presented in Table 3 . There is a tendency of lower CV for increasing sphere size. For the 208 keV peak for DEW, MSC and MSC + P the mean relative errors and CV result in similar values. For the 113 keV peak, mean relative error is larger, but CV is notably reduced when using MSC and MSC + P compared to the TEW. Mean relative errors in estimated total activity as a function of number of iterations are shown in Fig. 4. For both the 113 keV and the 208 keV images, the total activity is stabilized after a few iterations for all scatter compensation methods (TEW/DEW, MSC and MSC + P). When using TEW for the 113 keV peak, the results demonstrate a systematic overestimation of about 20% whereas the remaining methods results in mean error within 10%. Table 3 Mean relative error ± CV for estimated activity concentration in the NEMA and anthropomorphic phantom at 30 iterations. The NEMA spheres are denoted N1-N6 and the spheres in the anthropomorphic phantom are denoted A1-A2 (C for cold background, W for warm background and LB for liver background). Data for DEW and TEW are from Stenvall et al. ( 2 ) and are included for comparison. 113 keV 208 keV Sphere Volume /ml TEW/% MSC/% MSC + P/% DEW/% MSC/% MSC + P/% N1 1.2 \(\:-48\pm\:11\) \(\:-57.9\pm\:8.9\) \(\:-67.9\pm\:7.5\) \(\:-64\pm\:16\) \(\:-69\pm\:15\) \(\:-72\pm\:19\) N2 2.6 \(\:-29.9\pm\:3.7\) \(\:-47.5\pm\:5.0\) \(\:-56.4\pm\:6.3\) \(\:-45.1\pm\:5.3\) \(\:-45.1\pm\:3.8\) \(\:-46.9\pm\:4.4\) N3 5.6 \(\:-20.9\pm\:3.7\) \(\:-38.9\pm\:3.6\) \(\:-49.1\pm\:3.4\) \(\:-40.1\pm\:3.2\) \(\:-38.9\pm\:3.2\) \(\:-39.7\pm\:3.7\) N4 11.5 \(\:-12.4\pm\:2.4\) \(\:-30.1\pm\:2.7\) \(\:-41.6\pm\:2.3\) \(\:-31.8\pm\:1.7\) \(\:-29.1\pm\:1.7\) \(\:-29.3\pm\:1.5\) N5 26.5 \(\:-17.4\pm\:1.6\) \(\:-30.5\pm\:0.9\) \(\:-38.4\pm\:0.8\) \(\:-33.5\pm\:1.5\) \(\:-31.3\pm\:0.7\) \(\:-30.0\pm\:0.7\) N6 113.1 \(\:-7.1\pm\:0.8\) \(\:-15.4\pm\:0.6\) \(\:-21.5\pm\:0.2\) \(\:-26.1\pm\:0.6\) \(\:-24.8\pm\:0.6\) \(\:-23.4\pm\:0.7\) A1 C 9.9 \(\:-20.5\pm\:1.8\) \(\:-37.5\pm\:2.0\) \(\:-48.3\pm\:1.5\) \(\:-38.3\pm\:3.2\) \(\:-36.8\pm\:3.1\) \(\:-36.5\pm\:1.8\) A1 W 9.9 \(\:-23.1\pm\:5.7\) \(\:-35.5\pm\:5.6\) \(\:-43.8\pm\:4.0\) \(\:-39.7\pm\:1.6\) \(\:-39.2\pm\:1.7\) \(\:-39.5\pm\:1.0\) A2 C 25.3 \(\:-11.7\pm\:1.9\) \(\:-28.2\pm\:\text{2,1}\) \(\:-39.2\pm\:1.6\) \(\:-31.6\pm\:0.5\) \(\:-29.3\pm\:0.7\) \(\:-29.2\pm\:0.7\) A2 W 25.3 \(\:-16.3\pm\:2.6\) \(\:-27.1\pm\:1.1\) \(\:-34.3\pm\:1.5\) \(\:-32.5\pm\:2.2\) \(\:-30.7\pm\:2.3\) \(\:-29.4\pm\:1.6\) LB 10 \(\:-7.9\pm\:19.1\) \(\:-9.7\pm\:14.1\) \(\:-5.0\pm\:7.3\) \(\:-3.1\pm\:6.0\) \(\:2.7\pm\:6.7\) \(\:8.9\pm\:7.1\) Anthropomorphic phantom Examples of reconstructed images of the anthropomorphic phantom with radioactive and non-radioactive background are presented in Fig. 5 and Fig. 6. For 113 keV with warm background reconstructed with MSC and MSC + P, the background appears more uniform compared with TEW. The modified scatter compensation methods reduce residual signal outside the liver. There are clear streaks in the axial direction visible for images at 208 keV, particularly for the images with non-radioactive background. Mean relative error and CV for the two spheres are presented in Fig. 7 and numerical data in presented in Table 3 . For the 208 keV peak with warm background mean relative error and CV are consistent for DEW, MSC and MSC + P. For the 113 keV peak a slightly lower CV is obtained for the larger sphere (25 ml), however the TEW yields the lowest mean relative error. For the 208 keV peak with non-radioactive background, DEW, MSC and MSC + P perform similarly in relation to mean relative error and CV with a slight decrease in CV for MSC + P. The 113 keV peak demonstrates no major difference in CV for TEW, MSC and MSC + P. Mean relative errors for the largest sphere with TEW results in a value of -12%, whereas for the MSC the mean relative error is -25% and MSC + P is -30%. Figure 8 shows mean relative error and standard deviation (SD) as a function of number of iterations for a 10 ml spherical VOI placed in the warm background. For the 208 keV peak, DEW and MSC show similar mean relative errors for 30 iterations whilst MSC + P results in a larger mean relative error. However, the SD was improved for DEW compared to MSC and MSC + P. For the 113 keV peak TEW and MSC shows similar mean relative error with improved SD for MSC. MSC + P result in improved mean relative error and SD. Estimated total activity for extended acquisition time Figure 10 shows the mean relative error and standard deviation for each sphere reconstructed with 10 min time frame (black circles) compared to the relative error for reconstructed data using full-time data (bars) for the NEMA and anthropomorphic phantom with cold and warm background. For NEMA phantom for the 113 keV peak MSC, there is no noticeable difference in relative error when comparing short versus long acquisition time. However, for the MSC + P a larger difference is observed, where the relative error is reduced by 10 percentage points for the long timeframe compared to the short timeframe. The same observation can be made for the anthropomorphic phantom with cold and warm background, where a decrease in mean relative error of approximately 10 percentage points is obtained. For the 208 keV images the difference is a few percentage points when comparing short versus long times. Discussion In our previous study ( 2 ), we demonstrated better activity concentration mean relative errors for imaging at 113 keV with TEW compared with 208 keV with DEW (also shown in Fig. 3 and Fig. 7 in the current paper), but that this lower bias in concentration was accompanied by a gross over-estimation of total activity in the phantom (also shown in Fig. 4 and Fig. 9 in the current paper). The trend that activity concentrations demonstrate lower bias for 113 keV than 208 keV persist also for the modified scatter-compensation methods, but the difference is smaller. In general, the modified methods (MSC and MSC + P) for 113 keV are associated with a higher bias but a slightly better precision for activity-concentration estimates than the TEW method. The most striking difference, however, is the substantially better estimation of total activity with the modified methods. In Stenvall et al . ( 2 ), we judged the low underestimation of activity concentration for 113 keV as genuinely better property rather than merely being an indirect result of overestimation of total activity. This was based on that we were able to reduce bias in total activity by increasing the total acquisition time while keeping the low bias for concentration estimates. The results in the current study to some extent contradict that conclusion, as the modified scatter-compensation methods, which are theoretically more sound than standard TEW and are quite successful in reducing the total-activity error but leads to worse activity-concentration estimates. Estimates for the 208 keV energy windows are relatively unaffected by the introduction of MSC compared with the older DEW implementation. This is the result of that the old DEW method already accounted for the tail effect (a setting that could not be disabled in the reconstruction software), and thus the main difference between DEW and MSC for 208 keV is the use of different energy-window settings, following updated recommendations from the system manufacturer. The similarity between estimates from these two methods is confirmatory in that the exact window settings are not the main issue with respect to accuracy of activity-concentration estimates. On the whole, the 208 keV window appears inferior to the 113 keV window for estimation of activity concentration, possibly due to the issue of penetration at this energy ( 11 ), which is also visible in, e.g. , Fig. 6, despite the employment of explicit penetration compensation in the reconstruction. The rationale behind the MSC + P method is to utilize the primary signal in the scatter windows to boost the signal-to-noise ratio. However, as the acquired signal in these scatter windows have a poor scatter-to-primary ratio, the extra primary signal will be uncertain and thus risk increasing systematic errors. The trend observed for activity-concentration estimates in Fig. 3 and Fig. 7 is also larger mean-relative errors for MSC + P compared with MSC, although at the gain of a slightly lower CV. This could potentially also explain the low-signal background seen centrally for the NEMA phantom when employing MSC + P at 113 keV in Fig. 1. Accordingly, there appears to be little reason to employ the MSC + P method for estimation of activity-concentration in high-concentration regions. Conversely, Fig. 8 indicates a potential advantage of MSC + P compared with MSC and TEW for estimation of the liver background activity concentration, where this method achieves substantially better repeatability over timeframes than other methods with no major difference in systematic error. These results are also in line with the images presented in Fig. 5, where the MSC + P images appear less noisy than other methods for 113 keV. Thus, the use of MSC + P may have a role to play for estimation of lower activity concentrations thanks to its ability to reduce random errors. Much research around imaging of 177 Lu on ring-configured CZT gamma-cameras has focused on the ability to shorten acquisition times ( 12 ). In Stenvall et al . ( 2 ), we argued that such reduction should be carried out cautiously and that similar opportunities to reduce acquisition times are already available on standard gamma-cameras based on Anger logic. The better preservation of total activity for 10-minute acquisitions for the modified scatter-compensation methods, to some extent, relieves the problems indicated for short acquisition times. However, the MSC + P method demonstrates better activity-concentration estimates when the full acquisition time of 1 h is used compared with the shorter ones. Thus, there still appears to be a risk of introducing bias if the acquisition time is aggressively reduced. One major limitation of the current study is its reliance on the camera manufacturer’s software for reconstruction and hence also for implementation of scatter-compensation methods. Thus, we do not have full insight into the implementation details of the modified scatter-compensation methods, which also limits the scope of the conclusions that can be drawn from experiments. This is in line with, what we believe, is a general problem for the literature on SPECT for ring-configured CZT system, where it has proven difficult to separate the effects of detector material, camera geometry, and software. For the moment, we can only make statements that are specific to the StarGuide system (including software), and the generalizability to other systems is uncertain and requires further research. Another aspect to consider for the future is the study of model-based scatter compensation for ring-configured SPECT systems. Window-based methods have indeed been proven useful for estimating scatter, but tend to deteriorate the signal-to-noise ratio and suffer from an inherent conflict between noise and bias with respect to window width ( 13 ). In light of the extra complexity of modified scatter-compensation methods appropriate for pixelized CZT detectors compared with the original DEW and TEW methods, taking the step to a model-based approach could be proven advantageous, at least for quantitative tasks. Conclusions Modified scatter compensation methods that account for the low-energy primary tail improve the preservation of total activity for quantitative 177 Lu SPECT using ring-configured CZT SPECT systems compared with original window-based scatter compensation. The improvement in activity-concentration accuracy is modest, and even slightly worse for 113 keV in high-activity regions. Using the estimated primary signal in scatter windows to increase the signal-to-noise ratio is not advisable for the estimation of high activity concentrations but may have a role for the estimation of low activity-concentrations. Abbreviations CV coefficient of variation CZT cadmium zinc telluride DEW dual energy window HW high window LW low window MSC modified scatter correction MSC+P modified scatter correction + primaries PW primary window SD standard deviation SPECT single photon emission computed tomography TEW triple energy window Declarations Ethical approval and consent to participate: Not applicable Consent for publication : Not applicable Availability of data and materials : Data are available upon reasonable request to the corresponding author Competing interests : The authors declare no competing interests. Funding : The authors acknowledge financial support from the Mrs Berta Kamprad foundation (FBKS-2025-21-689, FBKS-2024-7-583) and the Swedish Cancer Society (243785Pj01H). Authors’ contributions : ICA: Planning of the study, data analysis, and manuscript writing AS: Planning of the study and manuscript writing, EN: Planning of the study and manuscript writing EL: Planning of the study and manuscript writing JG: Planning of the study, data analysis, and manuscript writing. All authors read and approved the final manuscript. References Dewaraja YK, Frey EC, Sgouros G, Brill AB, Roberson P, Zanzonico PB, et al. MIRD pamphlet No. 23: quantitative SPECT for patient-specific 3-dimensional dosimetry in internal radionuclide therapy. J Nucl Med. 2012;53(8):1310–25. doi: 10.2967/jnumed.111.100123 Stenvall A, Ceric Andelius I, Nilsson E, Lindvall A, Larsson E, Gustafsson J. 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J Nucl Med. 1994;35(1):143–51. doi: Cite Share Download PDF Status: Under Review Version 1 posted Reviewers agreed at journal 15 Jan, 2026 Reviewers invited by journal 13 Jan, 2026 Editor assigned by journal 30 Dec, 2025 First submitted to journal 29 Dec, 2025 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-8472942","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":574230007,"identity":"16f330ee-cfbb-4e57-bc8f-a9c28c385554","order_by":0,"name":"Irma Ceric 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14:43:11","extension":"html","order_by":24,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":92281,"visible":true,"origin":"","legend":"","description":"","filename":"earlyproof.html","url":"https://assets-eu.researchsquare.com/files/rs-8472942/v1/f62678c57918cdacea896c5f.html"},{"id":100599668,"identity":"db7f2abf-c9f8-4829-9833-332b496475c9","added_by":"auto","created_at":"2026-01-19 14:44:39","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":141918,"visible":true,"origin":"","legend":"\u003cp\u003eTransversal slice of the NEMA phantom reconstructed with 10 iterations (10 subsets).The dashed line in the image for DEW/TEW at 113 keV indicates the location of the profile in figure 2. Images for DEW and TEW are for data from Stenvall et al. (2)and are included for comparison.\u003c/p\u003e","description":"","filename":"image1.png","url":"https://assets-eu.researchsquare.com/files/rs-8472942/v1/eb487f97a6d240bb2e7a60c3.png"},{"id":100599606,"identity":"f46f4e68-d896-4bb4-81f3-15e24fc6220f","added_by":"auto","created_at":"2026-01-19 14:44:12","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":72792,"visible":true,"origin":"","legend":"\u003cp\u003eProfiles trough sphere 5 (26.5 ml) and sphere 6 (113 ml) plotted on a logarithmic scale reconstructed with 10 iterations. The dashed line indicates the true activity concentration. Data for DEW and TEW are from Stenvall et al. (2)and are included for comparison.\u003c/p\u003e","description":"","filename":"image2.png","url":"https://assets-eu.researchsquare.com/files/rs-8472942/v1/5ede58b7ef2e86cc543d4b13.png"},{"id":100599875,"identity":"4c1397b6-88be-42fd-be5b-473a41f4a326","added_by":"auto","created_at":"2026-01-19 14:45:26","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":80615,"visible":true,"origin":"","legend":"\u003cp\u003eCoefficient of variation versus mean relative error for NEMA phantom where each symbol represents a specific number of iterations (2, 5, 10, 20, 30 (10 subsets)). Note that the ordinate is individual for each subplot. Data for DEW and TEW are from Stenvall et al. (2)and are included for comparison.\u003c/p\u003e","description":"","filename":"image3.png","url":"https://assets-eu.researchsquare.com/files/rs-8472942/v1/83af00a5a2697858610ba97c.png"},{"id":100599440,"identity":"e8d6e4de-3f59-48b9-87d4-66a2559cb2ea","added_by":"auto","created_at":"2026-01-19 14:43:18","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":68870,"visible":true,"origin":"","legend":"\u003cp\u003eMean relative error in estimated total activity in the NEMA phantom for the 113 keV peak for TEW, MSC and MSC+P and for the 208 keV peak for DEW, MSC and MSC+P as a function of number of iterations (2, 5, 10, 20, 30 (10 subsets)). Data for DEW and TEW are from Stenvall et al. (2) and are included for comparison.\u003c/p\u003e","description":"","filename":"image4.png","url":"https://assets-eu.researchsquare.com/files/rs-8472942/v1/7c75efe58d52afc5fc0b94d2.png"},{"id":100599593,"identity":"d74a14f3-c401-4e14-bcb6-55a7f23a847a","added_by":"auto","created_at":"2026-01-19 14:44:08","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":166493,"visible":true,"origin":"","legend":"\u003cp\u003eSagittal slice for the anthropomorphic phantom with warm background reconstructed with 10 iterations (10 subsets). Top row shows images reconstructed with 113 keV (top left: TEW peak, middle: MSC, top right: MSC+P) and bottom row shows images reconstructed with 208 keV (top left: DEW, middle: MSC, top right: MSC+P). Images for DEW and TEW are for data from Stenvall et al. (2) and are included for comparison.\u003c/p\u003e","description":"","filename":"image5.png","url":"https://assets-eu.researchsquare.com/files/rs-8472942/v1/6e9e91d9cdc2fcfd30045895.png"},{"id":100599601,"identity":"d632d041-fe65-4994-ba68-0197d3475fa6","added_by":"auto","created_at":"2026-01-19 14:44:10","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":93706,"visible":true,"origin":"","legend":"\u003cp\u003eSagittal slice for the anthropomorphic phantom with cold background reconstructed with 10 iterations (10 subsets). Top row shows images reconstructed with 113 keV (top left: DEW, middle: MSC, top right: MSC+P) peak and bottom row shows images reconstructed with 208 keV (top left: TEW, middle: MSC, top right: MSC+P). Images for DEW and TEW are for data from Stenvall et al. (2) and are included for comparison.\u003c/p\u003e","description":"","filename":"image6.png","url":"https://assets-eu.researchsquare.com/files/rs-8472942/v1/a82d11e63f3d98e104e552ae.png"},{"id":100599590,"identity":"43336aa6-ce50-4845-b697-9784a239720d","added_by":"auto","created_at":"2026-01-19 14:44:07","extension":"png","order_by":7,"title":"Figure 7","display":"","copyAsset":false,"role":"figure","size":108393,"visible":true,"origin":"","legend":"\u003cp\u003eCoefficient of variation versus mean relative error for the anthropomorphicphantom where each symbol represents a specific number of iterations. Top row shows measurements performed with warm background and bottom row shows measurements performed with cold background. Note that the ordinate is individual for each subplot. Data for DEW and TEW are from Stenvall et al. (2)and are included for comparison.\u003c/p\u003e","description":"","filename":"image7.png","url":"https://assets-eu.researchsquare.com/files/rs-8472942/v1/35a4e18508d55b705c7df6e7.png"},{"id":100599541,"identity":"1c9c00a5-50a9-4cd7-8db1-a3634c3d1728","added_by":"auto","created_at":"2026-01-19 14:43:51","extension":"png","order_by":8,"title":"Figure 8","display":"","copyAsset":false,"role":"figure","size":111446,"visible":true,"origin":"","legend":"\u003cp\u003eThe mean relative error with standard deviations as a function of number of iterations for a 10 ml VOI in the liver compartment of the warm anthropomorphic phantom.\u003c/p\u003e","description":"","filename":"image8.png","url":"https://assets-eu.researchsquare.com/files/rs-8472942/v1/44364bc93169d2a0a1477ffa.png"},{"id":100599803,"identity":"90eecdcb-234f-4caf-a3ec-0618351b89c5","added_by":"auto","created_at":"2026-01-19 14:45:04","extension":"png","order_by":9,"title":"Figure 9","display":"","copyAsset":false,"role":"figure","size":68326,"visible":true,"origin":"","legend":"\u003cp\u003eMean relative error of total activity in the anthropomorphic phantom as a function of number of iterations. Data for DEW and TEW are from Stenvall et al. (2) and are included for comparison.\u003c/p\u003e","description":"","filename":"image9.png","url":"https://assets-eu.researchsquare.com/files/rs-8472942/v1/d7c71e8f1e9d60db7e460001.png"},{"id":100599619,"identity":"24e02cde-39fc-4a59-a2de-85eaeb78b41a","added_by":"auto","created_at":"2026-01-19 14:44:20","extension":"png","order_by":10,"title":"Figure 10","display":"","copyAsset":false,"role":"figure","size":86799,"visible":true,"origin":"","legend":"\u003cp\u003eMean relative error and standard deviations in NEMA spheres for total activity in 10-minutes time frames (black circles) and relative error for full-time data (bars) (top row). Corresponding estimations for the spheres in the anthropomorphic warm and cold background in the middle and lower row, respectively. Data for DEW and TEW are from Stenvall et al. (2) and are included for comparison.\u003c/p\u003e","description":"","filename":"image10.png","url":"https://assets-eu.researchsquare.com/files/rs-8472942/v1/af4248fd3c02003580775a17.png"},{"id":100797972,"identity":"f9f90ef3-fc47-48e4-8a16-6974e6be5ae3","added_by":"auto","created_at":"2026-01-21 13:52:02","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1502513,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8472942/v1/c66e862e-3e21-4703-991c-f94d43e8423f.pdf"}],"financialInterests":"","formattedTitle":"Evaluation of modified window-based scatter compensation in quantitative 177Lu-SPECT for a ring-configured CZT SPECT-CT","fulltext":[{"header":"Background","content":"\u003cp\u003eQuantitative single photon emission computed tomography (SPECT) is the cornerstone of image-based dosimetry in radionuclide therapy (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e), with low bias and good precision of estimated activity concentrations being necessary for reliable and reproducible dosimetry. The introduction of clinical semi-conductor cadmium-zinc-telluride (CZT) ring-configured gamma-camera has led to an interest in using these systems also for quantitative tasks both for diagnostic (\u003cem\u003ee.g.\u003c/em\u003e, \u003csup\u003e99m\u003c/sup\u003eTc) and therapeutic (\u003cem\u003ee.g.\u003c/em\u003e, \u003csup\u003e177\u003c/sup\u003eLu) radionuclides (\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThe radionuclide \u003csup\u003e177\u003c/sup\u003eLu emits two gamma photons useful for gamma-camera imagining at 113 keV and 208 keV. However, imaging of this radionuclide at CZT systems poses challenges as the systems are primarily designed for diagnostic tasks using \u003csup\u003e99m\u003c/sup\u003eTc, and collimator exchange is difficult for current designs. Thus, imaging at the higher energy suffers from penetration (\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e, \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e), whilst imaging at the lower energy suffers from a poor scatter-to-primary ratio. The poor scatter-to-primary ratio is a potential problem because of the charge-sharing phenomenon typical for pixelized CZT detectors (\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThe charge-sharing phenomenon results in a tail of low-energy primary photons in the acquired signal, which makes window-based scatter compensation, such as the dual-energy window (DEW) and triple-energy windows (TEW) techniques, problematic. An underlying assumption of the standard DEW and TEW methods (\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e, \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e) is that the signal in the scatter windows consists of scattered photons only, and thus any contamination of primaries from the low-energy tail will result in erroneous scatter estimates and thus bias activity concentrations in the reconstructed image (\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e, \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e). Hence, the use of window-based scatter compensation for quantitative SPECT with CZT cameras requires consideration of such contamination.\u003c/p\u003e \u003cp\u003eWe demonstrated in a previous study that ring configured CZT-systems is a viable alternative to the dual headed Anger system for quantitative \u003csup\u003e177\u003c/sup\u003eLu-SPECT (\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e). We further demonstrated that the ring-configured CZT system has a potential quantitative advantage compared with conventional Anger systems for imaging at 113 keV. However, we also noted substantial overestimation of total activity for imaging at this energy, which we suspected was related to imperfect scatter compensation. The present short communication extends our earlier investigation by evaluating a modified scatter-compensation (MSC) method that accounts for low energy tail of primary photons (\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e9\u003c/span\u003e), enabled with the StarGuidePlus upgrade on the StarGuide\u0026trade; (GE HealthCare, Haifa, Israel) system. Previous versions of the system implemented this method only for DEW scatter compensation at 208 keV, but the upgraded software also implements a TEW version applicable for imaging at 113 keV, which should reduce bias for this energy. The updated scatter-compensation module also allows for primary photons in scatter windows to be added back to the main window for the reconstruction (MSC\u0026thinsp;+\u0026thinsp;P), thereby potentially boosting the signal-to-noise ratio. We aim to assess the quantitative effect at 113 keV and 208 keV with respect to bias and precision for MSC, and MSC\u0026thinsp;+\u0026thinsp;P compared with the old scatter-compensation methods.\u003c/p\u003e"},{"header":"Materials and methods","content":"\u003cp\u003eThe methodology applied here follows the approach described by Stenvall et al. (\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e), summarized here in brief. For a more comprehensive description, the reader is referred to the original publication. No additional phantom measurements were acquired in this study, only previously collected data for \u003csup\u003e177\u003c/sup\u003eLu were utilized.\u003c/p\u003e \u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003ePhantoms\u003c/h2\u003e \u003cp\u003ePhantoms described in Stenvall et al. (\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e) were utilized: A uniform cylindrical phantom (SUV phantom), an image quality NEMA phantom (NEMA IEC Body phantom) and an anthropomorphic phantom (LK-S Kyoto Liver/Kidney Phantom, Kyoto Kagaku Co., Ldt.). A new set of calibration factors was determined using the uniform cylindrical phantom for MSC and MSC\u0026thinsp;+\u0026thinsp;P. The NEMA phantom with six spheres was used to evaluate the quantitative performance of MSC and MSC\u0026thinsp;+\u0026thinsp;P for \u003csup\u003e177\u003c/sup\u003eLu. The smallest sphere was replaced by a sphere with a volume of 113 ml and the spheres were positioned alternating between largest and smallest. The anthropomorphic phantom contained a liver insert with two spheres (Table \u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). The sphere activity concentration and the tumour-to-liver ratio (set to 14) were based on the relationship determined from the pharmacokinetic model developed by Brolin et al. (\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e10\u003c/span\u003e) 24 h post administration of [\u003csup\u003e177\u003c/sup\u003eLu]Lu-DOTA-TATE. Specifications for the phantoms are provided in Table \u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eSpecification of the phantoms prepared further described in by Stenvall et al. (\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e).\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eUniform phantom\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNEMA phantom\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eAnthropomorphic phantom\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDiameter (mm)/Volume (mL) (fillable containers inner dimensions)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-/5640\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eSphere 1: 13/1.2\u003c/p\u003e \u003cp\u003eSphere 2: 17/2.6\u003c/p\u003e \u003cp\u003eSphere 3: 22/5.6\u003c/p\u003e \u003cp\u003eSphere 4: 29/11.5\u003c/p\u003e \u003cp\u003eSphere 5: 37/26.5\u003c/p\u003e \u003cp\u003eSphere 6: 60/113.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eSphere 1: 27/9.9\u003c/p\u003e \u003cp\u003eSphere 2: 36/25.3\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003csup\u003e177\u003c/sup\u003eLu activity concentration (MBq/ml)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.098\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eSpheres: 1.93 (cold liver)\u003c/p\u003e \u003cp\u003e1.87 (warm liver)\u003c/p\u003e \u003cp\u003eLiver: 0.13\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eSPECT reconstruction and calibration\u003c/h3\u003e\n\u003cp\u003ePreviously collected listmode-data were reframed to adjust the energy window settings recommended for MSC and MSC\u0026thinsp;+\u0026thinsp;P (Table \u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e), and images were then reconstructed for the 113 keV and 208 keV peak separately (\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e). Reconstructions were performed with OS-EM with 2, 5, 10, 20 and 30 iterations (10 subsets) with a voxel size of 2.46x2.46x2.46 mm\u003csup\u003e3\u003c/sup\u003e using compensation for attenuation, distant-dependent resolution, scatter (MSC and MSC\u0026thinsp;+\u0026thinsp;P, as specified in Table \u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e), and compensation for penetration for the 208 keV peak. All reconstructions were performed on the Smart Console version 1.0 (GE Healthcare, Haifa, Israel). Reconstructed images from Stenvall et al. (\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e) were used for comparison. These were reconstructed with the same settings with respect to attenuation and resolution recovery but differed in energy windows and the scatter compensation. The images for 113 keV was reconstructed with TEW scatter compensation (with no account for the primary tail) and the images for 208 keV was reconstructed with DEW scatter compensation but accounting for the primary tail (a setting that could not be disabled). These two methods will be referred to the names used in Stenvall et al. (\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e), \u003cem\u003ei.e.\u003c/em\u003e, TEW and DEW.\u003c/p\u003e \u003cp\u003eThe calibration factor was determined by placing a large cylindrical volume of interest (VOI, radius 7 cm and depth 20 cm) in the centre of the reconstructed image. For a thorough description the reader is referred to Stenvall et al (\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e).\u003c/p\u003e\n\u003ch3\u003eScatter compensation\u003c/h3\u003e\n\u003cp\u003eScatter compensation was employed by acquiring multiple energy windows (primary window (PW), low window (LW), high window (HW)). The MSC assumes that all energy windows contain primary and scattered photons, which thus forms linear equation system with the different contributions as unknowns. By solving this equation system, scatter and primary contributions can be estimated for each window. The scatter estimates are added to the forward projection in the iterative reconstruction (\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e9\u003c/span\u003e). MSC\u0026thinsp;+\u0026thinsp;P includes adding tail photons to the primary window. By taking the sum of all three windows and estimating the scatter the remaining counts will be primaries (\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e9\u003c/span\u003e). Details about the energy window settings are presented in Table \u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eEnergy window settings. PW: peak window, LW: low window, HW: high window\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"3\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eType\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eWindow centre/keV\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eWindow width/%\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c3\" namest=\"c1\"\u003e \u003cp\u003eDEW and TEW\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEmission (113 PW)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e113.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u0026plusmn;\u0026thinsp;10\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eScatter (113 LW)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e96.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-4.6/+4.4\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eScatter (113 HW)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e129.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-3.3/+3.7\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEmission (208 PW)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e208\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u0026plusmn;\u0026thinsp;6\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eScatter (208 LW)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e185\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u0026plusmn;\u0026thinsp;5\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c3\" namest=\"c1\"\u003e \u003cp\u003eMSC and MSC\u0026thinsp;+\u0026thinsp;P\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEmission (113 PW)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e113.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u0026plusmn;\u0026thinsp;8\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eScatter (113 LW)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e93.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u0026plusmn;\u0026thinsp;11\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eScatter (113 HW)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e133\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u0026plusmn;\u0026thinsp;8\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEmission (208 PW)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e208\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u0026plusmn;\u0026thinsp;6\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eScatter (208 LW)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e182.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u0026plusmn;\u0026thinsp;7\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e\n\u003ch3\u003eEvaluation\u003c/h3\u003e\n\u003cp\u003eSpherical VOIs were defined by identifying the sphere centre-of-mass in SPECT images and including the voxels closest to the centre-point until the physical sphere volume was reached. For the anthropomorphic phantom with warm background, a 10 ml spherical VOI was also defined in the liver background. The same set of VOIs were used for all reconstructions. The bias was characterised by the mean relative error of the activity concentration over timeframes\u003cdiv id=\"Equ1\" class=\"Equation\"\u003e\u003cdiv format=\"TEX\" class=\"mathdisplay\" id=\"FileID_Equ1\" name=\"EquationSource\"\u003e\n$$\\:{\\epsilon\\:}_{i}=\\frac{{\\stackrel{-}{C}}_{i}}{{C}_{\\text{r}\\text{e}\\text{f}}}-1,$$\u003c/div\u003e\u003cdiv class=\"EquationNumber\"\u003e1\u003c/div\u003e\u003c/div\u003e\u003c/p\u003e \u003cp\u003ewhere \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{\\stackrel{-}{C}}_{i}\\)\u003c/span\u003e\u003c/span\u003e is the mean known activity concentration for sphere \u003cem\u003ei\u003c/em\u003e, and \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{C}_{ref}\\)\u003c/span\u003e\u003c/span\u003e is the calculated activity concentration at the start of image acquisition. The coefficient of variation (CV) was computed, as a measure of precision, according to\u003cdiv id=\"Equ2\" class=\"Equation\"\u003e\u003cdiv format=\"TEX\" class=\"mathdisplay\" id=\"FileID_Equ2\" name=\"EquationSource\"\u003e\n$$\\:CV=\\frac{{s}_{i}}{{\\stackrel{-}{C}}_{i}},$$\u003c/div\u003e\u003cdiv class=\"EquationNumber\"\u003e2\u003c/div\u003e\u003c/div\u003e\u003c/p\u003e \u003cp\u003ewhere \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{s}_{i}\\)\u003c/span\u003e\u003c/span\u003e is the standard deviation in the calculated activity concentration for sphere \u003cem\u003ei\u003c/em\u003e over the six timeframes.\u003c/p\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eNEMA phantom\u003c/h2\u003e \u003cp\u003eExamples of reconstructed images for 113 keV and 208 keV are presented in Fig.\u0026nbsp;1. The 208 keV images reconstructed with DEW, MSC and MSC\u0026thinsp;+\u0026thinsp;P appear similar, whilst the 113 keV images differ depending on scatter compensation method. The TEW and MSC images have a better contrast than the MSC\u0026thinsp;+\u0026thinsp;P image where a low-signal background is introduced between the spheres. Profiles through the two largest spheres and the non-radioactive background reconstructed with 10 iterations and 10 subsets are presented in Fig.\u0026nbsp;2. The profiles show signal outside of the spheres for all scatter compensation methods. For the 208 keV peak with DEW a slightly increased signal outside the spheres was observed whereas for MSC and MSC\u0026thinsp;+\u0026thinsp;P there is no apparent difference. For the 113 keV peak, a difference is seen when comparing TEW with MSC and MSC\u0026thinsp;+\u0026thinsp;P.\u003c/p\u003e \u003cp\u003ePlots of mean relative error versus CV for different reconstructions are shown in Fig.\u0026nbsp;3 and numerical data at 30 iterations are presented in Table \u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e. There is a tendency of lower CV for increasing sphere size. For the 208 keV peak for DEW, MSC and MSC\u0026thinsp;+\u0026thinsp;P the mean relative errors and CV result in similar values. For the 113 keV peak, mean relative error is larger, but CV is notably reduced when using MSC and MSC\u0026thinsp;+\u0026thinsp;P compared to the TEW.\u003c/p\u003e \u003cp\u003eMean relative errors in estimated total activity as a function of number of iterations are shown in Fig.\u0026nbsp;4. For both the 113 keV and the 208 keV images, the total activity is stabilized after a few iterations for all scatter compensation methods (TEW/DEW, MSC and MSC\u0026thinsp;+\u0026thinsp;P). When using TEW for the 113 keV peak, the results demonstrate a systematic overestimation of about 20% whereas the remaining methods results in mean error within 10%.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eMean relative error\u0026thinsp;\u0026plusmn;\u0026thinsp;CV for estimated activity concentration in the NEMA and anthropomorphic phantom at 30 iterations. The NEMA spheres are denoted N1-N6 and the spheres in the anthropomorphic phantom are denoted A1-A2 (C for cold background, W for warm background and LB for liver background). Data for DEW and TEW are from Stenvall et al. (\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e) and are included for comparison.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"8\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c5\" namest=\"c3\"\u003e \u003cp\u003e113 keV\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c8\" namest=\"c6\"\u003e \u003cp\u003e208 keV\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSphere\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eVolume\u003c/p\u003e \u003cp\u003e/ml\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eTEW/%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eMSC/%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eMSC\u0026thinsp;+\u0026thinsp;P/%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eDEW/%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eMSC/%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eMSC\u0026thinsp;+\u0026thinsp;P/%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eN1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:-48\\pm\\:11\\)\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:-57.9\\pm\\:8.9\\)\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:-67.9\\pm\\:7.5\\)\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:-64\\pm\\:16\\)\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:-69\\pm\\:15\\)\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:-72\\pm\\:19\\)\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eN2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:-29.9\\pm\\:3.7\\)\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:-47.5\\pm\\:5.0\\)\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:-56.4\\pm\\:6.3\\)\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:-45.1\\pm\\:5.3\\)\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:-45.1\\pm\\:3.8\\)\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:-46.9\\pm\\:4.4\\)\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eN3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:-20.9\\pm\\:3.7\\)\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:-38.9\\pm\\:3.6\\)\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:-49.1\\pm\\:3.4\\)\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:-40.1\\pm\\:3.2\\)\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:-38.9\\pm\\:3.2\\)\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:-39.7\\pm\\:3.7\\)\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eN4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e11.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:-12.4\\pm\\:2.4\\)\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:-30.1\\pm\\:2.7\\)\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:-41.6\\pm\\:2.3\\)\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:-31.8\\pm\\:1.7\\)\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:-29.1\\pm\\:1.7\\)\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:-29.3\\pm\\:1.5\\)\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eN5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e26.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:-17.4\\pm\\:1.6\\)\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:-30.5\\pm\\:0.9\\)\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:-38.4\\pm\\:0.8\\)\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:-33.5\\pm\\:1.5\\)\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:-31.3\\pm\\:0.7\\)\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:-30.0\\pm\\:0.7\\)\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eN6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e113.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:-7.1\\pm\\:0.8\\)\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:-15.4\\pm\\:0.6\\)\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:-21.5\\pm\\:0.2\\)\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:-26.1\\pm\\:0.6\\)\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:-24.8\\pm\\:0.6\\)\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:-23.4\\pm\\:0.7\\)\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eA1 C\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e9.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:-20.5\\pm\\:1.8\\)\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:-37.5\\pm\\:2.0\\)\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:-48.3\\pm\\:1.5\\)\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:-38.3\\pm\\:3.2\\)\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:-36.8\\pm\\:3.1\\)\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:-36.5\\pm\\:1.8\\)\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eA1 W\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e9.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:-23.1\\pm\\:5.7\\)\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:-35.5\\pm\\:5.6\\)\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:-43.8\\pm\\:4.0\\)\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:-39.7\\pm\\:1.6\\)\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:-39.2\\pm\\:1.7\\)\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:-39.5\\pm\\:1.0\\)\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eA2 C\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e25.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:-11.7\\pm\\:1.9\\)\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:-28.2\\pm\\:\\text{2,1}\\)\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:-39.2\\pm\\:1.6\\)\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:-31.6\\pm\\:0.5\\)\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:-29.3\\pm\\:0.7\\)\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:-29.2\\pm\\:0.7\\)\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eA2 W\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e25.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:-16.3\\pm\\:2.6\\)\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:-27.1\\pm\\:1.1\\)\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:-34.3\\pm\\:1.5\\)\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:-32.5\\pm\\:2.2\\)\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:-30.7\\pm\\:2.3\\)\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:-29.4\\pm\\:1.6\\)\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLB\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:-7.9\\pm\\:19.1\\)\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:-9.7\\pm\\:14.1\\)\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:-5.0\\pm\\:7.3\\)\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:-3.1\\pm\\:6.0\\)\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:2.7\\pm\\:6.7\\)\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:8.9\\pm\\:7.1\\)\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eAnthropomorphic phantom\u003c/h3\u003e\n\u003cp\u003eExamples of reconstructed images of the anthropomorphic phantom with radioactive and non-radioactive background are presented in Fig.\u0026nbsp;5 and Fig.\u0026nbsp;6. For 113 keV with warm background reconstructed with MSC and MSC\u0026thinsp;+\u0026thinsp;P, the background appears more uniform compared with TEW. The modified scatter compensation methods reduce residual signal outside the liver. There are clear streaks in the axial direction visible for images at 208 keV, particularly for the images with non-radioactive background.\u003c/p\u003e \u003cp\u003eMean relative error and CV for the two spheres are presented in Fig.\u0026nbsp;7 and numerical data in presented in Table \u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e. For the 208 keV peak with warm background mean relative error and CV are consistent for DEW, MSC and MSC\u0026thinsp;+\u0026thinsp;P. For the 113 keV peak a slightly lower CV is obtained for the larger sphere (25 ml), however the TEW yields the lowest mean relative error. For the 208 keV peak with non-radioactive background, DEW, MSC and MSC\u0026thinsp;+\u0026thinsp;P perform similarly in relation to mean relative error and CV with a slight decrease in CV for MSC\u0026thinsp;+\u0026thinsp;P. The 113 keV peak demonstrates no major difference in CV for TEW, MSC and MSC\u0026thinsp;+\u0026thinsp;P. Mean relative errors for the largest sphere with TEW results in a value of -12%, whereas for the MSC the mean relative error is -25% and MSC\u0026thinsp;+\u0026thinsp;P is -30%. Figure\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e8\u003c/span\u003e shows mean relative error and standard deviation (SD) as a function of number of iterations for a 10 ml spherical VOI placed in the warm background. For the 208 keV peak, DEW and MSC show similar mean relative errors for 30 iterations whilst MSC\u0026thinsp;+\u0026thinsp;P results in a larger mean relative error. However, the SD was improved for DEW compared to MSC and MSC\u0026thinsp;+\u0026thinsp;P. For the 113 keV peak TEW and MSC shows similar mean relative error with improved SD for MSC. MSC\u0026thinsp;+\u0026thinsp;P result in improved mean relative error and SD.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e\n\u003ch3\u003eEstimated total activity for extended acquisition time\u003c/h3\u003e\n\u003cp\u003eFigure \u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e10\u003c/span\u003e shows the mean relative error and standard deviation for each sphere reconstructed with 10 min time frame (black circles) compared to the relative error for reconstructed data using full-time data (bars) for the NEMA and anthropomorphic phantom with cold and warm background. For NEMA phantom for the 113 keV peak MSC, there is no noticeable difference in relative error when comparing short versus long acquisition time. However, for the MSC\u0026thinsp;+\u0026thinsp;P a larger difference is observed, where the relative error is reduced by 10 percentage points for the long timeframe compared to the short timeframe. The same observation can be made for the anthropomorphic phantom with cold and warm background, where a decrease in mean relative error of approximately 10 percentage points is obtained. For the 208 keV images the difference is a few percentage points when comparing short versus long times.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eIn our previous study (\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e), we demonstrated better activity concentration mean relative errors for imaging at 113 keV with TEW compared with 208 keV with DEW (also shown in Fig.\u0026nbsp;3 and Fig.\u0026nbsp;7 in the current paper), but that this lower bias in concentration was accompanied by a gross over-estimation of total activity in the phantom (also shown in Fig.\u0026nbsp;4 and Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e9\u003c/span\u003e in the current paper). The trend that activity concentrations demonstrate lower bias for 113 keV than 208 keV persist also for the modified scatter-compensation methods, but the difference is smaller. In general, the modified methods (MSC and MSC\u0026thinsp;+\u0026thinsp;P) for 113 keV are associated with a higher bias but a slightly better precision for activity-concentration estimates than the TEW method. The most striking difference, however, is the substantially better estimation of total activity with the modified methods. In Stenvall \u003cem\u003eet al\u003c/em\u003e. (\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e), we judged the low underestimation of activity concentration for 113 keV as genuinely better property rather than merely being an indirect result of overestimation of total activity. This was based on that we were able to reduce bias in total activity by increasing the total acquisition time while keeping the low bias for concentration estimates. The results in the current study to some extent contradict that conclusion, as the modified scatter-compensation methods, which are theoretically more sound than standard TEW and are quite successful in reducing the total-activity error but leads to worse activity-concentration estimates.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eEstimates for the 208 keV energy windows are relatively unaffected by the introduction of MSC compared with the older DEW implementation. This is the result of that the old DEW method already accounted for the tail effect (a setting that could not be disabled in the reconstruction software), and thus the main difference between DEW and MSC for 208 keV is the use of different energy-window settings, following updated recommendations from the system manufacturer. The similarity between estimates from these two methods is confirmatory in that the exact window settings are not the main issue with respect to accuracy of activity-concentration estimates. On the whole, the 208 keV window appears inferior to the 113 keV window for estimation of activity concentration, possibly due to the issue of penetration at this energy (\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e11\u003c/span\u003e), which is also visible in, \u003cem\u003ee.g.\u003c/em\u003e, Fig.\u0026nbsp;6, despite the employment of explicit penetration compensation in the reconstruction.\u003c/p\u003e \u003cp\u003eThe rationale behind the MSC\u0026thinsp;+\u0026thinsp;P method is to utilize the primary signal in the scatter windows to boost the signal-to-noise ratio. However, as the acquired signal in these scatter windows have a poor scatter-to-primary ratio, the extra primary signal will be uncertain and thus risk increasing systematic errors. The trend observed for activity-concentration estimates in Fig.\u0026nbsp;3 and Fig.\u0026nbsp;7 is also larger mean-relative errors for MSC\u0026thinsp;+\u0026thinsp;P compared with MSC, although at the gain of a slightly lower CV. This could potentially also explain the low-signal background seen centrally for the NEMA phantom when employing MSC\u0026thinsp;+\u0026thinsp;P at 113 keV in Fig.\u0026nbsp;1. Accordingly, there appears to be little reason to employ the MSC\u0026thinsp;+\u0026thinsp;P method for estimation of activity-concentration in high-concentration regions. Conversely, Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e8\u003c/span\u003e indicates a potential advantage of MSC\u0026thinsp;+\u0026thinsp;P compared with MSC and TEW for estimation of the liver background activity concentration, where this method achieves substantially better repeatability over timeframes than other methods with no major difference in systematic error. These results are also in line with the images presented in Fig.\u0026nbsp;5, where the MSC\u0026thinsp;+\u0026thinsp;P images appear less noisy than other methods for 113 keV. Thus, the use of MSC\u0026thinsp;+\u0026thinsp;P may have a role to play for estimation of lower activity concentrations thanks to its ability to reduce random errors.\u003c/p\u003e \u003cp\u003eMuch research around imaging of \u003csup\u003e177\u003c/sup\u003eLu on ring-configured CZT gamma-cameras has focused on the ability to shorten acquisition times (\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e12\u003c/span\u003e). In Stenvall \u003cem\u003eet al\u003c/em\u003e. (\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e), we argued that such reduction should be carried out cautiously and that similar opportunities to reduce acquisition times are already available on standard gamma-cameras based on Anger logic. The better preservation of total activity for 10-minute acquisitions for the modified scatter-compensation methods, to some extent, relieves the problems indicated for short acquisition times. However, the MSC\u0026thinsp;+\u0026thinsp;P method demonstrates better activity-concentration estimates when the full acquisition time of 1 h is used compared with the shorter ones. Thus, there still appears to be a risk of introducing bias if the acquisition time is aggressively reduced.\u003c/p\u003e \u003cp\u003eOne major limitation of the current study is its reliance on the camera manufacturer\u0026rsquo;s software for reconstruction and hence also for implementation of scatter-compensation methods. Thus, we do not have full insight into the implementation details of the modified scatter-compensation methods, which also limits the scope of the conclusions that can be drawn from experiments. This is in line with, what we believe, is a general problem for the literature on SPECT for ring-configured CZT system, where it has proven difficult to separate the effects of detector material, camera geometry, and software. For the moment, we can only make statements that are specific to the StarGuide system (including software), and the generalizability to other systems is uncertain and requires further research.\u003c/p\u003e \u003cp\u003eAnother aspect to consider for the future is the study of model-based scatter compensation for ring-configured SPECT systems. Window-based methods have indeed been proven useful for estimating scatter, but tend to deteriorate the signal-to-noise ratio and suffer from an inherent conflict between noise and bias with respect to window width (\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e13\u003c/span\u003e). In light of the extra complexity of modified scatter-compensation methods appropriate for pixelized CZT detectors compared with the original DEW and TEW methods, taking the step to a model-based approach could be proven advantageous, at least for quantitative tasks.\u003c/p\u003e"},{"header":"Conclusions","content":"\u003cp\u003eModified scatter compensation methods that account for the low-energy primary tail improve the preservation of total activity for quantitative \u003csup\u003e177\u003c/sup\u003eLu SPECT using ring-configured CZT SPECT systems compared with original window-based scatter compensation. The improvement in activity-concentration accuracy is modest, and even slightly worse for 113 keV in high-activity regions. Using the estimated primary signal in scatter windows to increase the signal-to-noise ratio is not advisable for the estimation of high activity concentrations but may have a role for the estimation of low activity-concentrations.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cp\u003eCV coefficient of variation\u003c/p\u003e\n\u003cp\u003eCZT cadmium zinc telluride\u003c/p\u003e\n\u003cp\u003eDEW dual energy window\u003c/p\u003e\n\u003cp\u003eHW high window\u003c/p\u003e\n\u003cp\u003eLW low window\u003c/p\u003e\n\u003cp\u003eMSC modified scatter correction \u003c/p\u003e\n\u003cp\u003eMSC+P modified scatter correction + primaries\u003c/p\u003e\n\u003cp\u003ePW primary window\u003c/p\u003e\n\u003cp\u003eSD standard deviation\u003c/p\u003e\n\u003cp\u003eSPECT single photon emission computed tomography \u003c/p\u003e\n\u003cp\u003eTEW triple energy window\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthical approval and consent to participate:\u003c/strong\u003e Not applicable\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e: Not applicable\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and materials\u003c/strong\u003e: Data are available upon reasonable request to the corresponding author\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e: The authors declare no competing interests.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e: The authors acknowledge financial support from the Mrs Berta Kamprad foundation (FBKS-2025-21-689, FBKS-2024-7-583) and the Swedish Cancer Society (243785Pj01H).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors\u0026rsquo; contributions\u003c/strong\u003e: ICA: Planning of the study, data analysis, and manuscript writing AS: Planning of the study and manuscript writing, EN: Planning of the study and manuscript writing EL: Planning of the study and manuscript writing JG: Planning of the study, data analysis, and manuscript writing. All authors read and approved the final manuscript.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eDewaraja YK, Frey EC, Sgouros G, Brill AB, Roberson P, Zanzonico PB, et al. MIRD pamphlet No. 23: quantitative SPECT for patient-specific 3-dimensional dosimetry in internal radionuclide therapy. J Nucl Med. 2012;53(8):1310\u0026ndash;25. doi: 10.2967/jnumed.111.100123\u003c/li\u003e\n\u003cli\u003eStenvall A, Ceric Andelius I, Nilsson E, Lindvall A, Larsson E, Gustafsson J. Bias and precision of SPECT-based (177)Lu activity-concentration estimation using a ring-configured solid-state versus a dual-headed anger system. EJNMMI Phys. 2024;11(1):91. doi: 10.1186/s40658-024-00693-5\u003c/li\u003e\n\u003cli\u003eKennedy JA, Lugassi R, Gill R, Keidar Z. Digital Solid-State SPECT/CT Quantitation of Absolute (177)Lu Radiotracer Concentration: In Vivo and In Vitro Validation. J Nucl Med. 2020;61(9):1381\u0026ndash;7. doi: 10.2967/jnumed.119.239277\u003c/li\u003e\n\u003cli\u003eRoth D, Larsson E, Sundl\u0026ouml;v A, Sj\u0026ouml;green Gleisner K. Characterisation of a hand-held CZT-based gamma camera for (177)Lu imaging. EJNMMI Phys. 2020;7(1):46. doi: 10.1186/s40658-020-00313-y\u003c/li\u003e\n\u003cli\u003eJaszczak RJ, Greer KL, Floyd CE, Jr., Harris CC, Coleman RE. Improved SPECT quantification using compensation for scattered photons. J Nucl Med. 1984;25(8):893\u0026ndash;900. doi: \u003c/li\u003e\n\u003cli\u003eOgawa K, Harata Y, Ichihara T, Kubo A, Hashimoto S. A practical method for position-dependent Compton-scatter correction in single photon emission CT. IEEE Trans Med Imaging. 1991;10(3):408\u0026ndash;12. doi: 10.1109/42.97591\u003c/li\u003e\n\u003cli\u003ePourmoghaddas A, Vanderwerf K, Ruddy TD, Glenn Wells R. Scatter correction improves concordance in SPECT MPI with a dedicated cardiac SPECT solid-state camera. J Nucl Cardiol. 2015;22(2):334\u0026ndash;43. doi: 10.1007/s12350-014-0008-0\u003c/li\u003e\n\u003cli\u003eMann SD, Tornai MP. Initial Evaluation of a Modified Dual-Energy Window Scatter Correction Method for CZT-based Gamma Cameras for Breast SPECT. Proc Spie. 2015;9413. doi: Artn 94132x 10.1117/12.2082195\u003c/li\u003e\n\u003cli\u003eWilk M, inventor; GE Precision Healthcare LLC, assignee. Methods and systems for scatter and tailing correction. US 2024/0371053 A1. 2024.\u003c/li\u003e\n\u003cli\u003eBrolin G, Gustafsson J, Ljungberg M, Sj\u0026ouml;green Gleisner K. Pharmacokinetic digital phantoms for accuracy assessment of image-based dosimetry in (177)Lu-DOTATATE peptide receptor radionuclide therapy. Phys Med Biol. 2015;60(15):6131\u0026ndash;49. doi: 10.1088/0031-9155/60/15/6131\u003c/li\u003e\n\u003cli\u003eDanieli R, Stella M, Leube J, Tran-Gia J, Marin C, Uribe CF, et al. Quantitative (177)Lu SPECT/CT imaging for personalized dosimetry using a ring-shaped CZT-based camera. EJNMMI Phys. 2023;10(1):64. doi: 10.1186/s40658-023-00586-z\u003c/li\u003e\n\u003cli\u003eSong H, Ferri V, Duan H, Aparici CM, Davidzon G, Franc BL, et al. SPECT at the speed of PET: a feasibility study of CZT-based whole-body SPECT/CT in the post (177)Lu-DOTATATE and (177)Lu-PSMA617 setting. Eur J Nucl Med Mol Imaging. 2023;50(8):2250\u0026ndash;7. doi: 10.1007/s00259-023-06176-6\u003c/li\u003e\n\u003cli\u003eLjungberg M, King MA, Hademenos GJ, Strand SE. Comparison of four scatter correction methods using Monte Carlo simulated source distributions. J Nucl Med. 1994;35(1):143\u0026ndash;51. doi: \u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":true,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"ejnmmi-physics","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"ejph","sideBox":"Learn more about [EJNMMI Physics](http://ejnmmiphys.springeropen.com)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/ejph/default.aspx","title":"EJNMMI Physics","twitterHandle":"@officialEANM","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"BMC/SO AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Quantitative SPECT, CZT, ring-configured SPECT, lutetium-177, scatter compensation","lastPublishedDoi":"10.21203/rs.3.rs-8472942/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8472942/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eBackground\u003c/strong\u003e: The aim was to evaluate bias and precision for \u003csup\u003e177\u003c/sup\u003eLu-activity-concentration estimation for window-based scatter compensation in a ring-configured CZT gamma camera. This paper extends a previous study by applying modified scatter compensation (MSC) methods. Whilst the original compensation addressed tailing in the 208 keV peak only, separating primary and scatter photons within the scatter window, the current adaption extents the concept to the 113 keV peak. In the modified version, the estimated primary signal in the scatter window can optionally also be added to measured projections to boost the signal-to-noise ratio (MSC + P).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMethods\u003c/strong\u003e: No additional measurements were acquired, and only previously collected listmode-data for a uniform cylindrical phantom, an image quality NEMA phantom and an anthropomorphic phantom were reframed to accommodate the updated window settings recommended for MSC and MSC + P. Reconstructions were performed using OS-EM with two to 30 iterations (10 subsets) with compensation for attenuation, scatter (DEW/TEW, MSC and MSC + P), distance-dependent spatial resolution, and penetration at 208 keV. Volume-of-interest following the physical sphere size were defined and activity-concentration estimates for each sphere, a liver region and for total activity in the phantoms were assessed in terms of bias and precision for short (10 min) and long timeframes (60 min).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults\u003c/strong\u003e: Imaging at 208 keV generally result in similar bias and precision and total activity estimates for all scatter-compensation methods. For 113 keV, a slightly netter precision is obtained for MSC and MSC + P but at the cost of larger bias compared with TEW. The major difference is seen for total activity where the MSC and MSC + P manages to decrease bias considerably. The MSC + P yields a decrease in bias of about 10 percentage points when comparing short versus long time frames for activity concentration estimates at 113 keV.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusions\u003c/strong\u003e: Despite the lack of broader improvement in bias and precision when using MSC and MSC + P the findings suggest potential value in more targeted applications. For instance, MSC and MSC + P improves preservation of total activity. Although the findings indicate that using MSC + P is not advisable for estimating high activity concentrations, it may positively influence the estimation of low activity concentrations.\u003c/p\u003e","manuscriptTitle":"Evaluation of modified window-based scatter compensation in quantitative 177Lu-SPECT for a ring-configured CZT SPECT-CT","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-01-19 13:35:22","doi":"10.21203/rs.3.rs-8472942/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"reviewerAgreed","content":"","date":"2026-01-15T13:06:29+00:00","index":0,"fulltext":""},{"type":"reviewersInvited","content":"","date":"2026-01-14T02:35:59+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-12-31T00:06:19+00:00","index":"","fulltext":""},{"type":"submitted","content":"EJNMMI Physics","date":"2025-12-29T07:19:18+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"ejnmmi-physics","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"ejph","sideBox":"Learn more about [EJNMMI Physics](http://ejnmmiphys.springeropen.com)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/ejph/default.aspx","title":"EJNMMI Physics","twitterHandle":"@officialEANM","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"BMC/SO AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"4e5d8157-dfd8-4b1b-bd69-a443c9e21021","owner":[],"postedDate":"January 19th, 2026","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2026-05-04T15:02:30+00:00","versionOfRecord":[],"versionCreatedAt":"2026-01-19 13:35:22","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-8472942","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-8472942","identity":"rs-8472942","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}