SUV Measurements Research Articles

Quantitative brain [18F]FDG PET beyond normal blood glucose levels

Introduction SUV measurements from static brain [18F]FDG PET acquisitions are a commonly used tool in preclinical research, providing a simple alternative for kinetic modelling, which requires complex and time-consuming dynamic acquisitions. However, SUV can be severely affected by the animal handling and preconditioning protocols, primarily by those that may induce changes in blood glucose levels (BGL). Here, we aimed at developing and investigating the feasibility of SUV-based approaches for a wide range of BGL far beyond normal values, and consequently, to develop and validate a new model to generate standardized and reproducible SUV measurements for any BGL.Material and methods We performed dynamic and static brain [18F]FDG PET acquisitions in 52 male Sprague-Dawley rats sorted into control (n = 10), non-fasting (n = 14), insulin-induced hypoglycemia (n = 12) and glucagon-induced hyperglycemia (n = 16) groups. Brain [18F]FDG PET images were cropped, aligned and co-registered to a standard template to calculate whole-brain and regional SUV. Cerebral Metabolic Rate of Glucose (CMRglc) was also estimated from 2-Tissue Compartment Model (2TCM) and Patlak plot for validation purposes.Results Our results showed that BGL=100±6 mg/dL can be considered a reproducible reference value for normoglycemia. Furthermore, we successfully established a 2nd-degree polynomial model (C1=0.66E-4, C2=-0.0408 and C3=7.298) relying exclusively on BGL measures at pre-[18F]FDG injection time, that characterizes more precisely the relationship between SUV and BGL for a wide range of BGL values (from 10 to 338 mg/dL). We confirmed the ability of this model to generate corrected SUV estimations that are highly correlated to CMRglc estimations (R2= 0.54 2TCM CMRgluc and R2= 0.49 Patlak CMRgluc). Besides, slight regional differences in SUV were found in animals from extreme BGL groups, showing that [18F]FDG uptake is mostly directed toward central regions of the brain when BGLs are significantly decreased.Conclusion Our study successfully established a non-linear model that relies exclusively on pre-scan BGL measurements to characterize the relationship between [18F]FDG SUV and BGL. The extensive validation confirmed its ability to generate SUV-based surrogates of CMRglu along a wide range of BGL and it holds the potential to be adopted as a standard protocol by the preclinical neuroimaging community using brain [18F]FDG PET imaging.

The Additional Role of F18-FDG PET/CT in Characterizing MRI-Diagnosed Tumor Deposits in Locally Advanced Rectal Cancer.

Rationale: F18-FDG PET/CT may be helpful in baseline staging of patients with high-risk LARC presenting with vascular tumor deposits (TDs), in addition to standard pelvic MRI and CT staging. Methods: All patients with locally advanced rectal cancer that had TDs on their baseline MRI of the pelvis and had a baseline F18-FDG PET/CT between May 2016 and December 2020 were included in this retrospective study. TDs as well as lymph nodes identified on pelvic MRI were correlated to the corresponding nodular structures on a standard F18-FDG PET/CT, including measurements of nodular SUVmax and SUVmean. In addition, the effects of partial volume and spill-in on SUV measurements were studied. Results: A total number of 62 patients were included, in which 198 TDs were identified as well as 106 lymph nodes (both normal and metastatic). After ruling out partial volume effects and spill-in, 23 nodular structures remained that allowed for reliable measurement of SUVmax: 19 TDs and 4 LNs. The median SUVmax between TDs and LNs was not significantly different (p = 0.096): 4.6 (range 0.8 to 11.3) versus 2.8 (range 1.9 to 3.9). For the median SUVmean, there was a trend towards a significant difference (p = 0.08): 3.9 (range 0.7 to 7.8) versus 2.3 (range 1.5 to 3.4). Most nodular structures showing either an SUVmax or SUVmean ≥ 4 were characterized as TDs on MRI, while only two were characterized as LNs. Conclusions: SUV measurements may help in separating TDs from lymph node metastases or normal lymph nodes in patients with high-risk LARC.

Performance characteristics of the 5-ring GE Discovery MI PET/CT scanner using AAPM TG-126 report.

To report on the performance characteristics of the 5-ring GE Discovery MI PET/CT systems using the AAPM TG-126 report and compare these results to NEMA NU 2-2012 where applicable. TG-126 testing was performed on two GE 5-Rings Discovery MI scanners. Tests performed included spatial resolution, PET/CT image-registration accuracy, sensitivity, count rate performance, accuracy of corrections, image contrast, scatter/attenuation correction, and image uniformity. All acquired data were analyzed using scanner console or free software tools as described by TG-126 and the results were then compared to published NEMA NU 2-2012 values. Both scanners gave similar resolution results for TG-126 and NEMA NU 2-2012 and were within manufacturer specifications. Image-registration accuracy between PET and CT using our clinical protocol showed excellent results with values≤1mm. Sensitivity using TG-126 was 19.43cps/kBq while for NEMA the value was 20.73cps/kBq. The peak noise-equivalent counting rate was 2174 kcps at 63.1 kBq/mL and is not comparable to NEMA NU 2-2012 due to differences in phantoms and methods used to measure and calculate this parameter. The accuracy of corrections for count losses for TG-126 were expressed in SUV values and found to be within 10% of the expected SUV measurement of 1. Image contrast and scatter/attenuation correction using the TG-126 method gave acceptable results. Image uniformity assessment resulted in values within the recommended±5% limits. These results show that the 5-ring GE Discovery MI PET/CT scanner testing using TG-126 is reproducible and has similar results to NEMA NU 2-2012 tests where applicable. We hope these results start to form the basis to compare PET/CT systems using TG-126.

Optimization of SUV with Changing the Dose Amount in F18-FDG PET/CT of Pediatric Lymphoma Patients.

We aim to reveal an effect of residual activity leftover within the medical materials other than the empty syringe used for injection of the tracer on SUV measurements and consequently effect on possible treatment response assessment. Staging and follow-up of pediatric lymphoma patients mainly achieved by the help of PET/CT scans. It is crucial to make an optimal imaging technique for interpreting individual images and assessing treatment response. Standardized uptake value measurement is an important quantification parameter in PET/CT scanning of childhood lymphomas. Low dose of activity used in pediatric oncology patients makes them vulnerable to small changes of input values for subsequent metabolic parameters. Sixty-eight pediatric lymphoma patients below 50 kg were included into the study. SUVmax, SUVpeak values of the most metabolically active lesions, along with liver and mediastinum, were recorded. Metabolic parameters of the lesions/lymph nodes, mediastinum and liver parenchyma were compared before and after counts from medical materials other than empty syringe were taken into account. Wilcoxon signed-rank test was used for non-parametric paired sampled tests for the groups. There were statistically significant differences between the whole 6 above-mentioned groups confirming the importance of residual counts on metabolic parameters (p < 0.001). Our study demonstrated residual radioactivity in medical materials such as serum line tubes, i.v. catheters, three-way stopcock and also butterfly needles used during intravenous injection should also be included for optimum quantitative metabolic parameter values and to minimize its the adverse effect on treatment response evaluation, especially in borderline lesions.

Feasibility of Dedicated Breast Positron Emission Tomography Image Denoising Using a Residual Neural Network.

This study aimed to create a deep learning (DL)-based denoising model using a residual neural network (Res-Net) trained to reduce noise in ring-type dedicated breast positron emission tomography (dbPET) images acquired in about half the emission time, and to evaluate the feasibility and the effectiveness of the model in terms of its noise reduction performance and preservation of quantitative values compared to conventional post-image filtering techniques. Low-count (LC) and full-count (FC) PET images with acquisition durations of 3 and 7 minutes, respectively, were reconstructed. A Res-Net was trained to create a noise reduction model using fifteen patients' data. The inputs to the network were LC images and its outputs were denoised PET (LC + DL) images, which should resemble FC images. To evaluate the LC + DL images, Gaussian and non-local mean (NLM) filters were applied to the LC images (LC + Gaussian and LC + NLM, respectively). To create reference images, a Gaussian filter was applied to the FC images (FC + Gaussian). The usefulness of our denoising model was objectively and visually evaluated using test data set of thirteen patients. The coefficient of variation (CV) of background fibroglandular tissue or fat tissue were measured to evaluate the performance of the noise reduction. The SUVmax and SUVpeak of lesions were also measured. The agreement of the SUV measurements was evaluated by Bland-Altman plots. The CV of background fibroglandular tissue in the LC + DL images was significantly lower (9.102.76) than the CVs in the LC (13.60 3.66) and LC + Gaussian images (11.51 3.56). No significant difference was observed in both SUVmax and SUVpeak of lesions between LC + DL and reference images. For the visual assessment, the smoothness rating for the LC + DL images was significantly better than that for the other images except for the reference images. Our model reduced the noise in dbPET images acquired in about half the emission time while preserving quantitative values of lesions. This study demonstrates that machine learning is feasible and potentially performs better than conventional post-image filtering in dbPET denoising.

Detection of prostate cancer bone metastases with fast whole-body 99mTc-HMDP SPECT/CT using a general-purpose CZT system

BackgroundWe evaluated the effects of acquisition time, energy window width, and matrix size on the image quality, quantitation, and diagnostic performance of whole-body 99mTc-HMDP SPECT/CT in the primary metastasis staging of prostate cancer.MethodsThirty prostate cancer patients underwent 99mTc-HMDP SPECT/CT from the top of the head to the mid-thigh using a Discovery NM/CT 670 CZT system with list-mode acquisition, 50-min acquisition time, 15% energy window width, and 128 × 128 matrix size. The acquired list-mode data were resampled to produce data sets with shorter acquisition times of 41, 38, 32, 26, 20, and 16 min, narrower energy windows of 10, 8, 6, and 4%, and a larger matrix size of 256 × 256. Images were qualitatively evaluated by three experienced nuclear medicine physicians and quantitatively evaluated by noise, lesion contrast and SUV measurements. Diagnostic performance was evaluated from the readings of two experienced nuclear medicine physicians in terms of patient-, region-, and lesion-level sensitivity and specificity.ResultsThe originally acquired images had the best qualitative image quality and lowest noise. However, the acquisition time could be reduced to 38 min, the energy window narrowed to 8%, and the matrix size increased to 256 × 256 with still acceptable qualitative image quality. Lesion contrast and SUVs were not affected by changes in acquisition parameters. Acquisition time reduction had no effect on the diagnostic performance, as sensitivity, specificity, accuracy, and area under the receiver-operating characteristic curve were not significantly different between the 50-min and reduced acquisition time images. The average patient-level sensitivities of the two readers were 88, 92, 100, and 96% for the 50-, 32-, 26-, and 16-min images, respectively, and the corresponding specificities were 78, 84, 84, and 78%. The average region-level sensitivities of the two readers were 55, 58, 59, and 56% for the 50-, 32-, 26-, and 16-min images, respectively, and the corresponding specificities were 95, 98, 96, and 95%. The number of equivocal lesions tended to increase as the acquisition time decreased.ConclusionWhole-body 99mTc-HMDP SPECT/CT can be acquired using a general-purpose CZT system in less than 20 min without any loss in diagnostic performance in metastasis staging of high-risk prostate cancer patients.

Meta-Analysis of the Test-Retest Repeatability of [18F]-Fluorodeoxyglucose Standardized Uptake Values: Implications for Assessment of Tumor Response.

Currently, guidelines for PET with 18F-fluorodeoxyglucose (FDG-PET) interpretation for assessment of therapy response in oncology primarily involve visual evaluation of FDG-PET/CT scans. However, quantitative measurements of the metabolic activity in tumors may be even more useful in evaluating response to treatment. Guidelines based on such measurements, including the European Organization for Research and Treatment of Cancer Criteria and PET Response Criteria in Solid Tumors, have been proposed. However, more rigorous analysis of response criteria based on FDG-PET measurements is needed to adopt regular use in practice. Well-defined boundaries of repeatability and reproducibility of quantitative measurements to discriminate noise from true signal changes are a needed initial step. An extension of the meta-analysis from de Langen and colleagues (2012) of the test-retest repeatability of quantitative FDG-PET measurements, including mean, maximum, and peak standardized uptake values (SUVmax, SUVmean, and SUVpeak, respectively), was performed. Data from 11 studies in the literature were used to estimate the relationship between the variance in test-retest measurements with uptake level and various study-level, patient-level, and lesion-level characteristics. Test-retest repeatability of percentage fluctuations for all three types of SUV measurement (max, mean, and peak) improved with higher FDG uptake levels. Repeatability in all three SUV measurements varied for different lesion locations. Worse repeatability in SUVmean was also associated with higher tumor volumes. On the basis of these results, recommendations regarding SUV measurements for assessing minimal detectable changes based on repeatability and reproducibility are proposed. These should be applied to differentiate between response categories for a future set of FDG-PET-based criteria that assess clinically significant changes in tumor response.

Variations induced by body weight and background lesion normalization in standardized uptake value estimated by F18-FDG PET/CT

AimThis work aims to study the impact of different SUV variants in terms of mean and maximum measures as well as various normalization methods with respect to body weight, body mass index, body surface area, and lean body mass in patients with lymphoma.MethodsSixty-nine patients (34 male–35 female) were retrospectively selected. All patients had undergone F18-FDG PET/CT using the standard imaging protocol. In the first part of this study, SUVmean and SUVmax of patients’ lesions and three background sites including liver, aorta, and muscle were determined. Then, the normalization of lesion SUV to body weight and body background sites was performed. The ratio of lesion SUVmax to body background sites (muscle, aorta, and liver) SUVmax was determined in addition to the ratio of lesion SUVmean to body background sites SUVmean. The second part of the study included the calculations of the body mass index (BMI), body surface area (BSA), and lean body mass (LBM). The normalization of lesion, liver, aorta, and muscle SUV to BMI, BSA, and LBM was calculated and compared to each other.ResultsAfter performing the appropriate statistical calculations, the results showed that there is a significant difference in SUV measurements between the three background sites. Lesions normalized to the liver were significantly lower than those normalized to aorta and muscle and the results also showed a higher magnitude of lesions normalized to muscle in comparison to the aorta. The SUVmax and SUVmean normalized to different body weight indices showed the lowest variation with BSA and BMI while being increasingly higher with lean body mass using the two methods James and Janmahasatian, respectively, and then highest with body weight.ConclusionThe SUVmax and SUVmean showed lower variance in comparison to other background regions. Less variation was also remarkable in SUVmean normalized to BSA and Janma lean mass and also when SUVmax is normalized to James lean body mass. The SUVmax normalized to lean (i.e., James) as well as SUVmean normalized to lean (i.e., Janma) and BSA showed a significant independence with body weight.

Simulated Reduced-Count Whole-Body FDG PET: Evaluation in Children and Young Adults Imaged on a Digital PET Scanner.

BACKGROUND. Digital PET scanners with increased sensitivity may allow shorter scan acquisition times or reductions in administered radiopharmaceutical activities. OBJECTIVE. The purpose of this study was to evaluate in children and young adults the impact of shorter simulated acquisition times on the quality of whole-body FDG PET images obtained using a digital PET/CT system. METHODS. This retrospective study included 27 children and young adults (nine male and 18 female patients) who underwent clinically indicated whole-body FDG PET/CT examinations performed using a 25-cm axial FOV PET/CT system at 90 s per bed position (expressed hereafter as seconds per bed). Raw list-mode data were reprocessed to simulate acquisition times of 60, 55, 50, 45, 40, and 30 s/bed. Three radiologists independently reviewed reconstructed images and assigned Likert scores for lesion conspicuity, normal structure conspicuity, image quality, and image noise. A separate observer recorded the SUVmax, SUVmean, and SD of the SUV (SUVSD) for liver, thigh, and the most FDG-avid lesion. The SUVSD/SUVmean (the SUVSD divided by the SUVmean) was calculated as a surrogate of image noise. ANOVA, the Friedman test, and the Dunn test were used to compare qualitative measures (combining reader scores) and SUV measurements. RESULTS. The mean patient age was 10.8 ± 8.3 (SD) years, mean BMI was 18.7 ± 2.9, and mean administered FDG activity was 4.44 ± 0.37 MBq/kg (0.12 ± 0.01 mCi/kg). No qualitative measure showed a significant difference versus 90 s/bed for the simulated acquisition at 60 s/bed (all p > .05). Significant differences (all p < .05) versus 90 s/bed were observed for lesion conspicuity at at most 40 s/bed, conspicuity of normal structures and overall image quality at at most 45 s/bed, and image noise at at most 55 s/bed. SUVmean was not significantly different from 90 s/bed for any site for any reduced-count simulation (all p > .05). SUVSD/SUVmean and SUVmax showed gradual increases with decreasing acquisition times and were significantly different from 90 s/bed only for liver at 60 s/bed (for SUVmax: 1.00 ± 0.00 vs 1.05 ± 0.03, p = .02; for SUVSD/SUVmean: 0.09 ± 0.02 vs 0.11 ± 0.02, p = .04). CONCLUSION. Favorable findings for the simulated acquisition at 60 s/bed suggest that, in children and young adults who undergo imaging performed using a 25-cm FOV digital PET scanner, acquisition time or administered FDG activity may be decreased by approximately 33% from the clinical standard without significantly impacting image quality. CLINICAL IMPACT. A 25-cm axial FOV digital scanner may allow FDG PET/CT examinations to be performed with reduced radiation exposure or faster scan acquisition times.

Distinguishing Benign and Malignant Findings on [68 Ga]-FAPI PET/CT Based on Quantitative SUV Measurements

Aim/PurposeFibroblast activation protein (FAP) is overexpressed by cancer-associated fibroblasts. However, activated fibroblasts have been shown to play a significant role also in certain benign conditions such as wound healing or chronic inflammation. Therefore, the current study aimed to identify whether FAPI uptake might differ between malignant lesions and benign conditions.Material and MethodsWe retrospectively analyzed 155 patients with various cancer types who received [68 Ga]-FAPI-04/02-PET/CT between July 2017 and March 2020. SUVmax, SUVmean, and lesion-to-background ratios (LBR) of FAPI uptake were measured in benign processes compared to malignant lesions (primary and/or 2 exemplary metastases). In addition, receiver operating characteristic (ROC) curve analysis was conducted to compare the predictive capabilities of semiquantitative PET/CT parameters. Furthermore, the sensitivity, specificity, optimal cutoff value, and 95% confidence interval (CI) were determined for each parameter.ResultsBenign lesions exhibited significantly lower FAPI uptake compared to malignant lesions (mean SUVmax benign vs. malignant: 4.2 vs. 10.6; p < 0.001). In ROC analysis, cutoff values of these lesions (benign vs. malignant) were established based on SUVmax, SUVmean, and LBR. The SUVmax cutoff value for all lesions was 5.5 and the corresponding sensitivity, specificity, accuracy, and AUC were 78.8%, 85.1%, 82.0%, and 0.89%, respectively. ConclusionOur aim was to systematically analyze the pattern of FAPI uptake in benign and malignant processes. This investigation demonstrates that FAPI uptake might be useful to differentiate malignant and benign findings due to different patho-physiological origins.

Healthy Organs Uptake on Baseline 18F-FDG PET/CT as an Alternative to Total Metabolic Tumor Volume to Predict Event-Free Survival in Classical Hodgkin's Lymphoma.

PurposeHealthy organs uptake, including cerebellar and liver SUVs have been reported to be inversely correlated to total metabolic tumor volume (TMTV), a controversial predictor of event-free survival (EFS) in classical Hodgkin's Lymphoma (cHL). The objective of this study was to estimate TMTV by using healthy organs SUV measurements and assess the performance of this new index (UF, Uptake Formula) to predict EFS in cHL.MethodsPatients with cHL were retrospectively included. SUV values and TMTV derived from baseline 18F-FDG PET/CT were harmonized using ComBat algorithm across PET/CT systems. UF was estimated using ANOVA analysis. Optimal thresholds of TMTV and UF were calculated and tested using Cox models.Results163 patients were included. Optimal UF model of TMTV included age, lymphoma maximum SUVmax, hepatic SUVmean and cerebellar SUVmax (R2 14.0% - p < 0.001). UF > 236.8 was a significant predictor of EFS (HR: 2.458 [1.201–5.030], p = 0.01) and was not significantly different from TMTV > 271.0 (HR: 2.761 [1.183–5.140], p = 0.001). UF > 236.8 remained significant in a bivariate model including IPS score (p = 0.02) and determined two populations with different EFS (63.7 vs. 84.9%, p = 0.01).ConclusionThe Uptake Formula, a new index including healthy organ SUV values, shows similar performance to TMTV in predicting EFS in Hodgkin's Lymphoma. Validation cohorts will be needed to confirm this new prognostic parameter.

Comparison of PET/CT SUV metrics across different clinical software platforms

ObjectiveTo assess the agreement of SUV metrics across the different clinical PET reading software platforms available at our institution. MethodsPET/CT images were reviewed on four different FDA-approved software platforms: syngoMMWP VE36A and syngo.via VB30A (Siemens), Intellispace Portal 9.0 (Philips), and Encore 6.7 (MIM Software). A total of thirty SUV measurements were derived from ten 18F-FDG PET/CT oncology studies. A volume of interest (VOI) was drawn around the primary tumor to determine lesion SUVmax and a 3 cm diameter spherical VOI was placed in the right lobe of the liver to determine liver SUVmean and liver SUVmax. ResultsFor lesion SUVmax, statistically significant differences were found for syngoMMWP VE36A vs syngo.via VB30A (p = 0.002), syngoMMWP VE36A vs Intellispace Portal 9.0 (p = 0.002), and syngoMMWP VE36A vs Encore 6.7 (p = 0.001), respectively. For liver SUVmax, a statistically significant difference was found for syngoMMWP VE36A vs syngo.via VB30A (p = 0.033) only, whereas for liver SUVmean, no statistically significant differences were determined. A small systematic bias was found between syngoMMWP VE36A and all other platforms for lesion SUVmax. ConclusionSignificant differences and systematic biases were observed when measuring lesion SUVmax using different reader software systems. Although these differences may not be clinically significant, this bias could confound outcomes for quantitative, precision-research protocols. Hence, it is important for nuclear medicine departments to take SUV metric agreement into consideration, especially when transitioning to a new clinical platform.

A Guide to ComBat Harmonization of Imaging Biomarkers in Multicenter Studies.

The impact of PET image acquisition and reconstruction parameters on SUV measurements or radiomic feature values is widely documented. This scanner effect is detrimental to the design and validation of predictive or prognostic models and limits the use of large multicenter cohorts. To reduce the impact of this scanner effect, the ComBat method has been proposed and is now used in various contexts. The purpose of this article is to explain and illustrate the use of ComBat based on practical examples. We also give examples in which the ComBat assumptions are not met and, thus, in which ComBat should not be used.

Dynamic 18F-FDG PET imaging of liver lesions: evaluation of a two-tissue compartment model with dual blood input function

BackgroundDynamic PET with kinetic modeling was reported to be potentially helpful in the assessment of hepatic malignancy. In this study, a kinetic modeling analysis was performed on hepatocellular carcinoma (HCC) and intrahepatic cholangiocarcinoma (ICC) from dynamic FDG positron emission tomography/computer tomography (PET/CT) scans.MethodsA reversible two-tissue compartment model with dual blood input function, which takes into consideration the blood supply from both hepatic artery and portal vein, was used for accurate kinetic modeling of liver dynamic 18F-FDG PET imaging. The blood input functions were directly measured as the mean values over the VOIs on descending aorta and portal vein respectively. And the contribution of hepatic artery to the blood input function was optimization-derived in the process of model fitting. The kinetic model was evaluated using dynamic PET data acquired on 24 patients with identified hepatobiliary malignancy. 38 HCC or ICC identified lesions and 24 healthy liver regions were analyzed.ResultsResults showed significant differences in kinetic parameters {K}_{1}-{k}_{4}, blood supplying fraction {f}_{A}, and metabolic rate constant {K}_{i} between malignant lesions and healthy liver tissue. And significant differences were also observed in {K}_{1}, {k}_{3}, {f}_{A} and {K}_{i} between HCC and ICC lesions. Further investigations of the effect of SUV measurements on the derived kinetic parameters were conducted. And results showed comparable effectiveness of the kinetic modeling using either SUVmean or SUVmax measurements.ConclusionsDynamic 18F-FDG PET imaging with optimization-derived hepatic artery blood supply fraction dual-blood input function kinetic modeling can effectively distinguish malignant lesions from healthy liver tissue, as well as HCC and ICC lesions.

A retrospective study of SPECT/CT scans using SUV measurement of the normal lumbar vertebrae with Tc-99m methylene diphosphonate

<strong>Introduction:</strong> External Beam Radiation Therapy (EBRT), a type of whole breast radiation therapy, has been widely used in patients with early-stage breast cancer, however it is associated with longer treatment periods and higher toxicity.

Accuracy Assessment of SUV Measurements in SPECT/CT: APhantom Study.

Advances in iterative image reconstruction enable absolute quantification of SPECT/CT studies by incorporating compensations for collimator-detector response, attenuation, and scatter. This study aimed to assess the quantitative accuracy of SPECT/CT based on different levels of 99mTc activity (low/high) using different SUV metrics (SUVmean, SUVmax, SUV0.6 max, and SUV0.75 max [the average values that include pixels greater than 60% and 75% of the SUVmax in the volume of interest, respectively]). Methods: A Jaszczak phantom equipped with 6 fillable spheres was set up with low and high activity ratios of 1:4 and 1:10 (background-to-sphere) on background activities of 10 and 60 kBq/mL, respectively. The fixed-size volume of interest based on the diameter of each sphere was drawn on SPECT images using various metrics for SUV quantification purposes. Results: The convergence of activity concentration was dependent on the number of iterations and application of postfiltering. For the background-to-sphere ratio of 1:10 with a low background activity concentration, the SUVmean metric showed an underestimation of about 38% from the actual SUV, and SUVmax exhibited an overestimation of about 24% for the largest sphere diameter. Meanwhile, bias reductions of as much as -6% and -7% for SUV0.6 max and SUV0.75 max, respectively, were observed. SUVmax gave a more accurate reading than the others, although points that exceeded the actual value were detected. At 1:4 and 1:10 background activity of 10 kBq/mL, a low activity concentration attained a value close to the actual ratio. Use of 2 iterations and 10 subsets without postfiltering gave the most accurate values for reconstruction and the best image overall. Conclusion: SUVmax is the best metric in a high- or low-contrast-ratio phantom with at least 2 iterations, 10 subsets, and no postfiltering.

Artificial intelligence enables whole-body positron emission tomography scans with minimal radiation exposure.

To generate diagnostic 18F-FDG PET images of pediatric cancer patients from ultra-low-dose 18F-FDG PET input images, using a novel artificial intelligence (AI) algorithm. We used whole-body 18F-FDG-PET/MRI scans of 33 children and young adults with lymphoma (3-30years) to develop a convolutional neural network (CNN), which combines inputs from simulated 6.25% ultra-low-dose 18F-FDG PET scans and simultaneously acquired MRI scans to produce a standard-dose 18F-FDG PET scan. The image quality of ultra-low-dose PET scans, AI-augmented PET scans, and clinical standard PET scans was evaluated by traditional metrics in computer vision and by expert radiologists and nuclear medicine physicians, using Wilcoxon signed-rank tests and weighted kappa statistics. The peak signal-to-noise ratio and structural similarity index were significantly higher, and the normalized root-mean-square error was significantly lower on the AI-reconstructed PET images compared to simulated 6.25% dose images (p< 0.001). Compared to the ground-truth standard-dose PET, SUVmax values of tumors and reference tissues were significantly higher on the simulated 6.25% ultra-low-dose PET scans as a result of image noise. After the CNN augmentation, the SUVmax values were recovered to values similar to the standard-dose PET. Quantitative measures of the readers' diagnostic confidence demonstrated significantly higher agreement between standard clinical scans and AI-reconstructed PET scans (kappa = 0.942) than 6.25% dose scans (kappa = 0.650). Our CNN model could generate simulated clinical standard 18F-FDG PET images from ultra-low-dose inputs, while maintaining clinically relevant information in terms of diagnostic accuracy and quantitative SUV measurements.

The Effect of Various β Values on Image Quality and Semiquantitative Measurements in 68Ga-RM2 and 68Ga-PSMA-11 PET/MRI Images Reconstructed With a Block Sequential Regularized Expectation Maximization Algorithm.

To compare the block sequential regularized expectation maximization (BSREM) algorithm with the ordered subsets expectation maximization (OSEM) algorithm and to evaluate how different penalty factors (b values) influence image quality and SUV measurements. We analyzed data from 78 prostate cancer patients who underwent Ga-RM2 (n = 42) or Ga-prostate-specific membrane antigen (PSMA)-11 (n = 36) PET/MRI. The raw PET data were retrospectively reconstructed using both time-of-flight (TOF)-BSREM with b values of 250, 350, 500, 750, and 1000 and TOF-OSEM. Each reconstruction was reviewed independently by 3 nuclear medicine physicians and scored qualitatively using a Likert scale (1 = poor, 5 = excellent quality). SUV measurements were analyzed as well. Fifty-seven lesions were detected (21 on Ga-RM2 and 36 on Ga-PSMA-11 PET/MRI); SUVmax decreased with the increase of β values for both tracers. Background noise (SUVsd) decreased with increasing of β values for both tracers. The mean ± SD scores for Ga-RM2 PET images were 2.4 ± 0.5 for b = 250 reconstructions, 3.2 ± 0.6 for b = 350, 4 ± 0.6 for b = 500, 4.5 ± 0.5 for b = 750, 4.4 ± 0.7 for b = 1000, and 3.4 ± 0.6 for TOF-OSEM. The mean ± SD scores for Ga-PSMA-11 PET images were 3.2 ± 0.8 for b = 250 reconstructions, 4.1 ± 0.8 for b = 350, 4.7 ± 0.6 for b = 500, 4.8 ± 0.4 for b = 750, 4.7 ± 0.6 for b = 1000, and 3.8 ± 0.5 for TOF-OSEM. Time-of-flight-BSREM algorithm improves image quality. Different b values should be used for different Ga-labeled radiopharmaceuticals such as those targeting GRPR and PSMA receptors. Once selected, the same b value should be consistently used because SUVmax measurements differ with different b values.

Impact of different iterative metal artifact reduction (iMAR) algorithms on PET/CT attenuation correction after port implementation

PurposeTo evaluate the effect of various interactive metal artifact reduction (iMAR) algorithms on attenuation correction in the vicinity of port chambers in PET/CT. Material and methodsIn this prospective study, 30 oncological patients (12 female, 18 male, mean age 59.6 ± 10.5y) with implanted port chambers undergoing 18F-FDG PET/CT were included. CT images were reconstructed with standard weighted filtered back projection (WFBP) and three different iMAR algorithms (hip, dental filling (DF) and pacemaker (PM)). PET attenuation correction was performed with all four CT datasets. SUVmean, SUVmax and HU measurements were performed in fat and muscle tissue in the vicinity of the port chamber at the location of the strongest bright and dark band artifacts. Differences between HU and SUV values across all CT- and PET-images were investigated using a paired t-test. Bonferroni correction was used to prevent alpha-error accumulation (p < 0.008). ResultsIn comparison to WFBP (fat: 94.2 ± 53.9 HU, muscle: 197.6 ± 49.2 HU) all three iMAR algorithms led to a decrease of HU in bright band artifacts. iMAR-DF led to a decrease of 159.2 % (fat: -51.9 ± 58.5 HU, muscle: 94.5 ± 55.3 HU), iMAR-hip of 138.3 % (fat: -30.3 ± 58.5, muscle: 70.4 ± 28.8) and iMAR-PM of 122.3 % (fat: -21.2 ± 47.2 HU, muscle: 72.5 ± 25.1 HU; for all p < 0.008). There was no significant effect of iMAR on SUV measurements in comparison to WFBP. ConclusioniMAR leads to a significant change of HU values in artifacts caused by port catheter chambers in comparison to WFBP. However, no significant differences in attenuation correction and consecutive changes in SUV measurements can be observed.

Practical considerations for establishing dead-time corrections in quantitative SPECT imaging

Quantitative SPECT studies require specific information about the equipment being used. Particularly in the context of therapeutic studies, the effect of dead-time can be significant and must be quantified. We explored different techniques for measuring the dead-time constant and applying dead-time corrections to the data. Method: The dead-time constant was measured on four similar SPECT/CT systems by following the response of the system to a uniform phantom initially containing 17 GBq of Lu-177 over a period of 23 days. It was then calculated using the two-source method with 1 332 MBq of Tc-99 m. The dead-time constant found was used to correct SPECT/CT phantom images either applying the correction by projection or globally on the image. Results: Both methods of calculating the dead-time constant produced equivalent results. However, the dead-time constant varied by as much as 8% between machines of the same model and manufacturer. Correcting for dead-time by projection rather than globally produced slightly more precise results (0.94% error rather than 2.59% error). The benefit of this correction technique will be dependent on the level of asymmetry in the patient as well as the magnitude of the dead-time correction effect. Conclusion: quantification of the dead-time of a system can be performed quickly using the two-source method and any radioisotope. However, it is important to perform this measurement on every system being used. In vastly asymmetric images with high dead-time correction, correcting for dead-time by projection can be pertinent, increasing the precision of dosimetry calculations by several percent. However this additional gain may be within the error of SUV measurements for many clinical acquisitions.