Patlak Method Research Articles

Measurement variability of blood-brain barrier permeability using dynamic contrast-enhanced magnetic resonance imaging.

Dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) is used to quantify the blood-brain barrier (BBB) permeability-surface area product. Serial measurements can indicate changes in BBB health, of interest to the study of normal physiology, neurological disease, and the effect of therapeutics. We performed a scan-rescan study to inform both sample size calculation for future studies and an appropriate reference change value for patient care. The final dataset included 28 healthy individuals (mean age 53.0 years, 82% female) scanned twice with mean interval 9.9 weeks. DCE-MRI was performed at 3T using a 3D gradient echo sequence with whole brain coverage, T1 mapping using variable flip angles, and a 16-min dynamic sequence with a 3.2-s time resolution. Segmentation of white and grey matter (WM/GM) was performed using a 3D magnetization-prepared gradient echo image. The influx constant Ki was calculated using the Patlak method. The primary outcome was the within-subject coefficient of variation (CV) of Ki in both WM and GM. Ki values followed biological expectations in relation to known GM/WM differences in cerebral blood volume (CBV) and consequently vascular surface area. Subject-derived arterial input functions showed marked within-subject variability which were significantly reduced by using a venous input function (CV of area under the curve 46 vs. 12%, p < 0.001). Use of the venous input function significantly improved the CV of Ki in both WM (30 vs. 59%, p < 0.001) and GM (21 vs. 53%, p < 0.001). Further improvement was obtained using motion correction, scaling the venous input function by the artery, and using the median rather than the mean of individual voxel data. The final method gave CV of 27% and 17% in WM and GM, respectively. No further improvement was obtained by replacing the subject-derived input function by one standard population input function. CV of Ki was shown to be highly sensitive to dynamic sequence duration, with shorter measurement periods giving marked deterioration especially in WM. In conclusion, measurement variability of 3D brain DCE-MRI is sensitive to analysis method and a large precision improvement is obtained using a venous input function.

Comparative benefits of Ki and SUV images in lesion detection during PET/CT imaging

BackgroundClinical application of the tracer net influx rate (Ki) imaging in PET/CT remains limited, due to a lack of evidence demonstrating the superiority of Ki images in lesion detection, and guidelines on when to utilize Ki images. This study aims to compare the benefits of Ki and standardized uptake value (SUV) images in lesion detection during PET/CT imaging. By analyzing the performance of both techniques in identifying tumor lesions, the study seeks to provide guidance for the clinical application of Ki images.ResultsThis retrospective study included 134 patients with 244 pathologically confirmed lesions (200 malignant and 44 benign). Patients with a histopathological diagnosis received a weight-based 18F-FDG injection and underwent 60-min total-body PET/CT dynamic imaging. SUV images were reconstructed using data collected from the last 10 min of the scans. Ki images were generated using the Patlak methods with data from minutes 12–60. The background SUVmax, SUVmean, SUVSD, Kimax, Kimean, and KiSD values were recorded. The signal-to-noise ratios of the SUV (SUVSNR) and Ki (KiSNR) images were calculated. The lesion detection rate and sensitivity of the SUV and Ki images were evaluated. The lesion-detection rates were 97.7% (214/219) and 99.5% (218/219) for the SUV and Ki images, respectively (p = .22). Five false-negative lesions on the SUV images were true-positive on the Ki images (3 hepatic malignancies and 2 metastatic lymph nodes). The sensitivity (94.0% vs. 96.0%, p = .22), specificity (41.9% vs. 41.9%, p > .99), accuracy (84.4% vs. 86.1%, p = .61), positive predictive value (87.9% vs. 88.1%, p = .94), negative predictive value (60.0% vs. 69.2%, p = .47), and the area under the curve [0.68 (95% confidence interval, 0.61–0.73) vs. 0.69 (95% confidence interval, 0.62–0.74)] were similar in the SUV and Ki images (all p ≥ .10).ConclusionKi images exhibit benefits in lesion detection compared to SUV images, particularly in organs with high background such as liver. The enhanced contrast provided by Ki imaging is recommended to clinically improve detection rates in such cases.

Cerebral and myocardial kinetics of [11C]acetoacetate and [11C]β-hydroxybutyrate: A comparative crossover study in healthy rats

BackgroundKetone metabolism has been studied using positron emission tomography (PET) with the radiotracers [11C]acetoacetate and [11C]β-hydroxybutyrate. However, whether these two radiotracers actually yield equivalent estimates of cerebral and myocardial ketone metabolism has not yet been investigated. This study aimed to investigate and compare the kinetics of both tracers in the brain and heart of healthy rats under varying levels of circulating ketones at baseline and after a single-dose exogenous ketone ester (KE) supplement. MethodsSix healthy Sprague-Dawley rats each underwent two scans with each tracer: one following oral KE administration and one with a placebo. Cerebral kinetic parameters (Ki, VT, and cerebral metabolic rate (CMR)) were obtained using the Patlak method, whereas myocardial kinetic parameters (K1, k2, and VT) were derived using a 1-tissue compartment model. Parameters were compared through mixed-effects, correlation, and Bland-Altman analyses. ResultsGlobal CMR increased 3–4-fold in the KE group versus placebo, with strong positive correlations between CMR and plasma ketone levels for both tracers. Correlations between [11C]acetoacetate and [11C]β-hydroxybutyrate were moderate and non-significant for relative cerebral uptake expressed as Ki (ρ = 0.40) and for VT (ρ = 0.38) but strongly positive for absolute uptake, CMR (r = 0.84), with a non-significant mean bias of −0.03. In contrast, myocardial kinetics showed only non-significant weak to moderate correlations between the radiotracers (K1 (r = 0.04), k2 (r = −0.27), and VT (ρ = 0.43)), with no systematic biases. Conclusion[11C]acetoacetate and [11C]β-hydroxybutyrate can be used interchangeably for measuring global CMR in healthy rats but differ in certain cerebral and myocardial kinetics. Whether these findings are generalizable to pathological conditions warrants further studies to explore the kinetics of these tracers in disease models.

Optimization and impact of sensitivity mode on abbreviated scan protocols with population-based input function for parametric imaging of [18F]-FDG for a long axial FOV PET scanner

BackgroundThe long axial field of view, combined with the high sensitivity of the Biograph Vision Quadra PET/CT scanner enables the precise deviation of an image derived input function (IDIF) required for parametric imaging. Traditionally, this requires an hour-long dynamic PET scan for [18F]-FDG, which can be significantly reduced by using a population-based input function (PBIF). In this study, we expand these examinations and include the scanner’s ultra-high sensitivity (UHS) mode in comparison to the high sensitivity (HS) mode and evaluate the potential for further shortening of the scan time.MethodsPatlak Ki and DV estimates were determined by the indirect and direct Patlak methods using dynamic [18F]-FDG data of 6 oncological patients with 26 lesions (0–65 min p.i.). Both sensitivity modes for different number/duration of PET data frames were compared, together with the potential of using abbreviated scan durations of 20, 15 and 10 min by using a PBIF. The differences in parametric images and tumour-to-background ratio (TBR) due to the shorter scans using the PBIF method and between the sensitivity modes were assessed.ResultsA difference of 3.4 ± 7.0% (Ki) and 1.2 ± 2.6% (DV) was found between both sensitivity modes using indirect Patlak and the full IDIF (0–65 min). For the abbreviated protocols and indirect Patlak, the UHS mode resulted in a lower bias and higher precision, e.g., 45–65 min p.i. 3.8 ± 4.4% (UHS) and 6.4 ± 8.9% (HS), allowing shorter scan protocols, e.g. 50–65 min p.i. 4.4 ± 11.2% (UHS) instead of 7.3 ± 20.0% (HS). The variation of Ki and DV estimates for both Patlak methods was comparable, e.g., UHS mode 3.8 ± 4.4% and 2.7 ± 3.4% (Ki) and 14.4 ± 2.7% and 18.1 ± 7.5% (DV) for indirect and direct Patlak, respectively. Only a minor impact of the number of Patlak frames was observed for both sensitivity modes and Patlak methods. The TBR obtained with direct Patlak and PBIF was not affected by the sensitivity mode, was higher than that derived from the SUV image (6.2 ± 3.1) and degraded from 20.2 ± 12.0 (20 min) to 10.6 ± 5.4 (15 min). Ki and DV estimate images showed good agreement (UHS mode, RC: 6.9 ± 2.3% (Ki), 0.1 ± 3.1% (DV), peak signal-to-noise ratio (PSNR): 64.5 ± 3.3 dB (Ki), 61.2 ± 10.6 dB (DV)) even for abbreviated scan protocols of 50–65 min p.i.ConclusionsBoth sensitivity modes provide comparable results for the full 65 min dynamic scans and abbreviated scans using the direct Patlak reconstruction method, with good Ki and DV estimates for 15 min short scans. For the indirect Patlak approach the UHS mode improved the Ki estimates for the abbreviated scans.

Blood‐brain barrier disruption measured by dynamic contrast‐enhanced MRI in Alzheimer’s disease

AbstractBackgroundAlzheimer’s disease (AD) is characterized by the accumulation of amyloid beta (Aβ) plaques in the brain. Blood‐brain barrier (BBB) dysfunction has been associated with AD. Aβ‐plaques have been found to disrupt the BBB, leading to increased permeability and invasion of immune cells into the CNS and triggering an inflammatory response, and contributing to neurodegeneration. In this study, we investigated BBB disruption in Alzheimer’s disease and its associations with amyloid deposition and clinical severity, and cognitive decline.MethodIn this cross‐sectional study, n = 16 AD patients were included. AD patients were defined as amyloid positive by CSF amyloid‐β42/amyloid‐β40 ratio &lt; 5,5% and a Mini‐Mental‐State Examination (MMSE) score &lt; 27. Dynamic contrast‐enhanced magnetic resonance imaging (DCE MRI), a non‐invasive imaging technique that uses intravenously injected gadolinium to quantify the permeability of the BBB has been acquired. DCE‐MRI quantification was quantified using the Patlak method. To analyse the regional degree of BBB disruption the AAL atlas was warped onto the Patlak maps and the median of each ROI was calculated. The cortical amyloid deposition has been quantified using 18F]flutemetamol β‐amyloid‐PET and cognitive performance was assessed using the Alzheimer’s Disease neuropsychological battery (CERAD‐NB). Associations were tested using linear regression models adjusted for age and sex in SPSS.ResultThe highest Ktrans values were measured in the orbitofrontal cortex (mean: 1,6×10−3 min−1). BBB dysfunction in median Ktrans values in the bilateral temporal lobe and particularly the right hippocampus were associated with decreases in the CSF amyloid‐β ratio. Furthermore, BBB dysfunction was negatively associated with cognitive decline measured by the CERAD‐NB. BBB dysfunction overlapped with amyloid PET accumulation in the parietal and temporal brain regions.ConclusionDCE MRI shows spatially localized BBB dysfunction in AD. The BBB dysfunction seems to be more severe in regions of the brain that are affected by Aβ plaques. This could support the idea that Aβ plaque contributes to BBB dysfunction in AD. BBB dysfunction also tends to be pronounced in patients with more severe cognitive impairment, suggesting that it may play a role in the progression of AD.

RF12 | PSUN106 Quantifying Liver and Brain Levels of 11β-hydroxysteroid Dehydrogenase Type 1 in Obesity Using Positron Emission Tomography Imaging

Abstract Objectives Cortisol is known to promote adipocyte differentiation and maturation, and prolonged exposure to excess cortisol contributes to the development of obesity and metabolic dysregulation. The intracellular 11β-hydroxysteroid dehydrogenase type 1 (11β-HSD1) enzyme catalyzes the conversion of inactive cortisone to active cortisol. Recently, we demonstrated reduced brain 11β-HSD1 levels in vivo with increasing body mass index (BMI), using positron emission tomography (PET) radioligands [11C]- and [18F]AS2471907(1). PET imaging can simultaneously quantify uptake in multiple organs (e.g., liver/brain). [18F]AS2471907 has high uptake and specific binding in the brain and liver(2). Liver and brain 11β-HSD1 measured by PET imaging may help elucidate the roles of cortisol activation in the setting of metabolic dysregulation. Thus, we performed PET imaging studies to examine 11β-HSD1 levels in the liver and brain. Methods Nine individuals (5F/4M) with a range of BMIs (22.6-34.4 kg/m2) underwent a 90 min PET/CT acquisition with arterial plasma sampling after injection of [18F]AS2471907. Regions-of-interest (ROI) for the liver were manually drawn on a summed PET image (60-90 min). Seventeen brain ROIs were selected from the anatomical automatic labeling (AAL) template and applied to the dynamic PET images to generate time-activity-curves (TACs). Brain volume of distribution (VT, mL/cm3), the target tissue to plasma ratio of radioligand at equilibrium, was estimated for each ROI using the multilinear analysis-1 method with plasma input function. Mean whole-brain VT values were calculated by averaging all ROIs. Given the appearance of irreversible kinetics in the liver, Ki (min-1), the rate of irreversible tracer uptake, was calculated using the Patlak method. Results Qualitative brain and liver uptake was assessed by examining a summed PET image (SUV 60-90min). The parent fraction in plasma was 88±1% at 90 min, indicating negligible plasma radiolabeled-metabolites contributing the measured signal in the liver. Kinetic modeling estimates demonstrated decreasing whole brain VT with increasing BMI (R2=0.53), similar to our previously published study examining only brain in a larger cohort(1). Patlak methods provided good estimates of Ki. In an opposite manner from the brain, correlations seen in the liver using Ki were positively correlated with BMI (R2=0.57). Conclusions These preliminary studies suggest obesity is associated with increased 11β-HSD1 levels in the liver but decreased 11β-HSD1 levels in the brain. Clinically, liver specific 11β-HSD1 inhibitors may prove beneficial in treating metabolic sequalae of obesity such non-alcoholic fatty liver disease (NAFLD) by inhibiting activity of higher 11β-HSD1 levels. Further studies in NAFLD and obesity are necessary to determine appropriate populations that would benefit from 11β-HSD1 inhibitors and longitudinal in vivo PET imaging to help inform development of future therapeutics.

MO814: Sucroferric Oxyhydroxide versus Calcium Carbonate in the Treatment Bone Metabolism in Patients with Ckd3–5 Evaluated by 18F-NA Fluoride PET/CT and Biomarkers: A Randomized Crossover Study

Abstract BACKGROUND AND AIMS Non-invasive methods for assessing bone metabolism have been lacking in chronic kidney disease (CKD), and the effects of different treatments on bone metabolism are mostly unknown. However, fluorine-18 labeled sodium fluoride (18F-NaF) PET/CT scanning can assess bone turnover as skeletal plasma clearance of tracer (Ki) and bone volume/tissue volume (BV/TV) in CKD. In a randomized crossover study, we aimed to compare the 8-week treatment effects of a non-calcium-based phosphate binder, sucroferric oxyhydroxide (SO), with 8 weeks of treatment with a calcium-based phosphate binder, calcium carbonate (CC), on bone turnover and BV/TV. METHOD Whole body 18F-NaF PET/CT scans were performed at the end of the CC and SO treatment periods in each participant. Ki was determined by the single-point Patlak method with semi-population input functions. A recently established CKD-MDB population residual curve was applied. Estimation of BV/TV was made by CT-derived Hounsfield units (HU) in specified volumes of interest. Paired t-tests were used or non-parametric tests (Wilcoxon signed-ranks test) when data were not normally distributed. Statistical analyses were performed using SPSS 20. RESULTS Ki assessed by the 18F-NaF scan was not significantly different at the lumbar spine (CC: 0.030 ± 0.014 mL min–1 mL–1; SO: 0.031 ± 0.014 mL min–1 mL–1; P = .75) or any other site after short-term treatment with SO or CC. However, HU was significantly higher after CC treatment. CONCLUSION 18F-NaF PET/CT is a practical tool with which to evaluate bone metabolism in CKD. Short-term SO treatment did not affect Ki (turnover) differently than CC treatment, but BV/TV (volume) was significantly lower after SO treatment than after CC treatment.

First results on kinetic modelling and parametric imaging of dynamic 18F-FDG datasets from a longaxial FOV PET scanner in oncological patients.

To investigate the kinetics of 18F-fluorodeoxyglucose (18F-FDG) by positron emission tomography (PET) in multiple organs and test the feasibility of total-body parametric imaging using an image-derived input function (IDIF). Twenty-four oncological patients underwent dynamic 18F-FDG scans lasting 65min using a longaxial FOV (LAFOV) PET/CT system. Time activity curves (TAC) were extracted from semi-automated segmentations of multiple organs, cerebral grey and white matter, and from vascular structures. The tissue and tumor lesion TACs were fitted using an irreversible two-tissue compartment (2TC) and a Patlak model. Parametric images were also generated using direct and indirect Patlak methods and their performances were evaluated. We report estimates of kinetic parameters and metabolic rate of glucose consumption (MRFDG) for different organs and tumor lesions. In some organs, there were significant differences between MRFDG values estimated using 2TC and Patlak models. No statistically significant difference was seen between MRFDG values estimated using 2TC and Patlak methods in tumor lesions (paired t-test, P = 0.65). Parametric imaging showed that net influx (Ki) images generated using direct and indirect Patlak methods had superior tumor-to-background ratio (TBR) to standard uptake value (SUV) images (3.1- and 3.0-fold mean increases in TBRmean, respectively). Influx images generated using the direct Patlak method had twofold higher contrast-to-noise ratio in tumor lesions compared to images generated using the indirect Patlak method. We performed pharmacokinetic modelling of multiple organs using linear and non-linear models using dynamic total-body 18F-FDG images. Although parametric images did not reveal more tumors than SUV images, the results confirmed that parametric imaging furnishes improved tumor contrast. We thus demonstrate the feasibility of total-body kinetic modelling and parametric imaging in basic research and oncological studies. LAFOV PET can enhance dynamic imaging capabilities by providing high sensitivity parametric images and allowing total-body pharmacokinetic analysis.

Comparison of [18F] NaF PET/CT dynamic analysis methods and a static analysis method including derivation of a semi-population input function for site-specific measurements of bone formation in a population with chronic kidney disease-mineral and bone disorder

PurposeThe purpose of this study is to compare dynamic and static whole-body (WB) [18F]NaF PET/CT scan methods used for analysis of bone plasma clearance in patients with chronic kidney disease-mineral and bone disorder (CKD-MBD).MethodsSeventeen patients with CKD-MBD underwent a 60-min dynamic scan followed by a 30-min static WB scan. Tracer kinetics in four thoracic vertebrae were analysed using nonlinear regression and Patlak analysis using image-derived arterial input functions. The static WB scan was analysed using a simplified Patlak method requiring only a single data point in combination with a fixed y-intercept value (V0), both obtained using a semi-population function. The semi-population function was constructed by combining a previously derived population input function in combination with data from venous blood samples. Static WB scan analysis data, obtained from the semi-population input functions, was compared with paired data obtained using dynamic input functions.ResultsBone plasma clearance (Ki) from Patlak analyses correlated well with nonlinear regression analysis, but Ki results using Patlak analysis were lower than Ki results using nonlinear regression analysis. However, no significant difference was found between Ki obtained by static WB scans and Ki obtained by dynamic scans using nonlinear regression analysis (p = 0.29).ConclusionBone plasma clearance measured from static WB scans correlates with clearance data measured by dynamic analysis. Static [18F]NaF PET/CT scans can be applied in future studies to measure Ki in patients with CKD-MBD, but the results should not be compared uncritically with results obtained by dynamic scan analysis.

Short-time total-body dynamic PET imaging performance in quantifying the kinetic metrics of 18F-FDG in healthy volunteers.

To investigate the performance of short-time dynamic imaging in quantifying kinetic metrics of 2-[18F]-fluoro-2-deoxy-D-glucose (18F-FDG). Dynamic total-body positron emission tomography (PET) imaging was performed in 11 healthy volunteers for 75min. The data were divided into 30-, 45- and 75-min groups. Nonlinear regression (NLR) generated constant rates (k1 to k3) and NLR-based Ki in various organs. The Patlak method calculated parametric Ki images to generate Patlak-based Ki values. Paired samples t-test or the Wilcoxon signed-rank test compared the kinetic metrics between the groups, depending on data normality. Deming regression and Bland-Altman analysis assessed the correlation and agreement between NLR- and Patlak-based Ki. A two-sided P < 0.05 was considered statistically significant. The 45- and 75-min groups were similar in NLR-based kinetic metrics. The relative difference ranges were as follows: k1, from 3.4% (P = 0.627) in the spleen to 57.9% (P = 0.130) in the white matter; k2, from 6.0% (P = 0.904) in the spleen to 60.7% (P = 0.235) in the left ventricle (LV) myocardium; k3, from 45.6% (P = 0.302) in the LV myocardium to 96.3% (P = 0.478) in the liver; Ki, from 14.0% (P = 0.488) in the liver to 77.8% (P = 0.067) in the kidney. Patlak-based Ki values were also similar between these groups in all organs, except the grey matter (9.6%, P = 0.029) and cerebellum (14.4%, P = 0.002). However, significant differences in kinetic metrics were found between the 30-min and 75-min groups in most organs both in NLR- and Patlak-based analyses. The NLR- and Patlak-based Ki values significantly correlated, with no bias in any of the organs. Dynamic imaging using a high-sensitivity total-body PET scanner for a shorter time of 45min could achieve relevant kinetic metrics of 18F-FDG as done by long-time imaging.

Computed Tomography Perfusion Analysis of Pancreatic Adenocarcinoma using Deconvolution, Maximum Slope, andPatlakMethods - Evaluation of Diagnostic Accuracy andInterchangeability of Cut-Off Values.

The goal of this study was to evaluate the diagnostic accuracy of perfusion computed tomography (CT) parameters obtained by different mathematical-kinetic methods for distinguishing pancreatic adenocarcinoma from normal tissue. To determine cut-off values and to assess the interchangeability of cut-off values, which were determined by different methods. Perfusion CT imaging of the pancreas was prospectively performed in 23 patients. 19 patients with histopathologically confirmed pancreatic adenocarcinoma were included in the study. Blood flow (BF), blood volume (BV) and permeability-surface area product (PS) were measured in pancreatic adenocarcinoma and normal tissue with the deconvolution (BF, BV, PS), maximum slope (BF), and Patlak methods (BV, PS). The interchangeability of cut-off values was examined by assessing agreement between BF, BV, and PS measured with different mathematical-kinetic methods. Bland-Altman analysis demonstrated poor agreement between perfusion parameters, measured with different mathematical-kinetic methods. According to receiver operating characteristic (ROC) analysis, PS measured with the Patlak method had the significantly lowest diagnostic accuracy (area under ROC curve = 0.748). All other parameters were of high diagnostic accuracy (area under ROC curve = 0.940-0.997), although differences in diagnostic accuracy were not statistically different. Cut-off values for BF of ≤ 91.83 ml/100 ml/min and for BV of ≤ 5.36 ml/100 ml, both measured with the deconvolution method, appear to be the most appropriate cut-off values to distinguish pancreatic adenocarcinoma from normal tissue. Perfusion parameters obtained by different methods are not interchangeable. Therefore, cut-off values, which were determined using different methods, are not interchangeable either. Perfusion parameters can help to distinguish pancreatic adenocarcinoma from normal tissue with high diagnostic accuracy, except for PS measured with the Patlak method. · Perfusion CT parameters showed high diagnostic accuracy in differentiating between pancreatic adenocarcinoma and normal tissue.. · Only PS measured with the Patlak method showed a significantly lower diagnostic accuracy.. · Perfusion parameters measured with different mathematical-kinetic methods are not interchangeable.. · A specific cut-off value must be determined for each method and each perfusion parameter.. · Koell M, Klauss M, Skornitzke S et al. Computed Tomography Perfusion Analysis of Pancreatic Adenocarcinoma with the Deconvolution, Maximum Slope, and Patlak Methods - Evaluation of Diagnostic Accuracy and Interchangeability of Cut-Off Values. Fortschr Röntgenstr 2021; 193: 1062 - 1073.

Renogram image characteristics and the reproducibility of differential renal function measurement.

PurposePatient factors such as age and glomerular filtration rate (GFR), have been implicated as causes for poor reproducibility of differential renal function (DRF) estimates on 99mTc-mercaptoacetyltriglycine (99mTc-MAG3) renography. This study aims to investigate factors associated with the reproducibility of DRF measurements.MethodsThe association between age, GFR and imaged derived image characteristics and reproducibility of repeated DRF estimates calculated using the area under the curve method and the Rutland Patlak method was analysed for cohort 1 (n = 127). The association between these variables and reproducibility of DRF was tested with univariate linear regression. The univariate linear regression results were used to plan the multiple linear regression combinations.The associations between variables identified and reproducibility of DRF values were then tested in a second cohort (n = 227).ResultsThe R2 values for goodness-to-fit for the multiple regression models ranged from 0.33 to 0.49 for cohort 1 and from 0.17 to 0.22 for cohort 2. Left kidney to background ratio (LKTBR) was significant in all the multiple linear regression combinations (P < 0.05). Right kidney to background ratio (RKTBR), right renal margins well defined, right renal margins poorly visualised, time visualisation right calyces and age were significant in most combinations. The reproducibility of DRF measurement was decreased when the kidney to background ratio (KTBR) was ≤2.ConclusionOnly LKTBR, RKTBR, right renal margins well defined, time visualisation right calyces and age predicted reproducibility for the measurement of DRF on 99mTc-MAG3 renograms. The KTBR should be incorporated into the renal processing software as a quality control step. The DRF values should be interpreted with caution if the KTBR is ≤2.0.

Diagnostic performance of a whole-body dynamic 68GA-DOTATOC PET/CT acquisition to differentiate physiological uptake of pancreatic uncinate process from pancreatic neuroendocrine tumor.

To evaluate the diagnostic performance of net influx rate (Ki) values from a whole-body dynamic (WBD) Ga-DOTATOC-PET/CT acquisition to differentiate pancreatic neuroendocrine tumors (pNETs) from physiological uptake of pancreatic uncinate process (UP).Patients who were benefited from a WBD acquisition for the assessment of a known well-differentiated neuroendocrine tumor (NET)/suspicion of disease in the prospective GAPET-NET cohort were screened. Only patients with a confirmed pNET/UP as our gold standard were included. The positron emission tomography (PET) procedure consisted in a single-bed dynamic acquisition centered on the heart, followed by a whole-body dynamic acquisition and then a static acquisition. Dynamic (Ki calculated according to Patlak method), static (SUVmax, SUVmean, SUVpeak) parameters, and tumor-to-liver and tumor-to-spleen ratio (TLRKi and TSRKi (according to hepatic/splenic Ki)), tumor SUVmax to liver SUVmax (TM/LM), tumor SUVmax to liver SUVmean (TM/Lm), tumor SUVmax to spleen SUVmax (TM/SM), and tumor SUVmax to spleen SUVmean (TM/Sm) (according to hepatic/splenic SUVmax and SUVmean respectively) were calculated. A Receiver Operating Characteristic (ROC) analysis was performed to evaluate their diagnostic performance to distinguish UP from pNET.One hundred five patients benefited from a WBD between July 2018 and July 2019. Eighteen (17.1%) had an UP and 26 (24.8%) a pNET. For parameters alone, the Ki and SUVpeak had the best sensitivity (88.5%) while the Ki, SUVmax, and SUVmean had the best specificity (94.4%). The best diagnostic accuracy was obtained with Ki (90.9%). For ratios, the TLRKi and the TSRKi had the best sensitivity (95.7%) while the TM/SM and TM/Sm the best specificity (100%). TLRKi had the best diagnostic accuracy (95.1%) and the best area under the curve (AUC) (0.990).Our study is the first one to evaluate the interest of a WBD acquisition to differentiate UP from pNETs and shows excellent diagnostic performances of the Ki approach.

Kinetic analysis of HER2-binding ABY-025 Affibody molecule using dynamic PET in patients with metastatic breast cancer

BackgroundHigh expression of human epidermal growth factor receptor type 2 (HER2) represents an aggressive subtype of breast cancer. Anti-HER2 treatment requires a theragnostic approach wherein sufficiently high receptor expression in biopsy material is mandatory. Heterogeneity and discordance of HER2 expression between primary tumour and metastases, as well as within a lesion, present a complication for the treatment and require multiple biopsies. Molecular imaging using the HER2-targeting Affibody peptide ABY-025 radiolabelled with 68Ga-gallium for PET/CT is currently under investigation as a non-invasive tool for whole-body evaluation of metastatic HER2 expression. Initial studies demonstrated a high correlation between 68Ga-ABY-025 standardized uptake values (SUVs) and histopathology. However, detecting small liver lesions might be compromised by high background uptake. This study aimed to explore the applicability of kinetic modelling and parametric image analysis for absolute quantification of 68Ga-ABY-025 uptake and HER2-receptor expression and how that relates to static SUVs.MethodsDynamic 68Ga-ABY-025 PET of the upper abdomen was performed 0-45 min post-injection in 16 patients with metastatic breast cancer. Five patients underwent two examinations to test reproducibility. Parametric images of tracer delivery (K1) and irreversible binding (Ki) were created with an irreversible two-tissue compartment model and Patlak graphical analysis using an image-derived input function from the descending aorta. A volume of interest (VOI)-based analysis was performed to validate parametric images. SUVs were calculated from 2 h and 4 h post-injection static whole-body images and compared to Ki.ResultsCharacterization of HER2 expression in smaller liver metastases was improved using parametric images. Ki values from parametric images agreed very well with VOI-based gold standard (R2 > 0.99, p < 0.001). SUVs of metastases at 2 h and 4 h post-injection were highly correlated with Ki values from both the two-tissue compartment model and Patlak method (R2 = 0.87 and 0.95, both p < 0.001). 68Ga-ABY-025 PET yielded high test-retest reliability (relative repeatability coefficient for Patlak 30% and for the two-tissue compartment model 47%).Conclusion68Ga-ABY-025 binding in HER2-positive metastases was well characterized by irreversible two-tissue compartment model wherein Ki highly correlated with SUVs at 2 and 4 h. Dynamic scanning with parametric image formation can be used to evaluate metastatic HER2 expression accurately.

Tumor-to-Blood Ratio for Assessment of Somatostatin Receptor Density in Neuroendocrine Tumors Using 68Ga-DOTATOC and 68Ga-DOTATATE.

PET/CT with 68Ga-DOTA-somatostatin analogs has been tested for therapy monitoring in patients with neuroendocrine tumors (NETs). However, SUVs in tumors do not correlate with the net influx rate (Ki), as a representation of the somatostatin receptor expression. In this study, tumor-to-blood ratio (TBR) was evaluated as an alternative tool for semiquantitative assessment of 68Ga-DOTATOC and 68Ga-DOTATATE tumor uptake and as a therapy monitoring tool for patients with NETs. Methods: Twenty-two NET patients underwent a 45-min dynamic PET/CT scan after injection of 68Ga-DOTATOC or 68Ga-DOTATATE. Ki was determined using the Patlak method, and TBR was calculated for the 40- to 45-min interval. Results: A linear relation was found between Ki and TBR, with a square of Pearson correlation of 0.98 and 0.93 for 68Ga-DOTATOC and 68Ga-DOTATATE, respectively. Conclusion: A high correlation was found between Ki and TBR. Hence, TBR reflects somatostatin receptor density more accurately than SUV and is suggested as the preferred metric for semiquantitative assessment of 68Ga-DOTATOC and 68Ga-DOTATATE tumor uptake.

Total-Body Dynamic Reconstruction and Parametric Imaging on the uEXPLORER.

The world's first 194-cm-long total-body PET/CT scanner (uEXPLORER) has been built by the EXPLORER Consortium to offer a transformative platform for human molecular imaging in clinical research and health care. Its total-body coverage and ultra-high sensitivity provide opportunities for more accurate tracer kinetic analysis in studies of physiology, biochemistry, and pharmacology. The objective of this study was to demonstrate the capability of total-body parametric imaging and to quantify the improvement in image quality and kinetic parameter estimation by direct and kernel reconstruction of the uEXPLORER data. Methods: We developed quantitative parametric image reconstruction methods for kinetic analysis and used them to analyze the first human dynamic total-body PET study. A healthy female subject was recruited, and a 1-h dynamic scan was acquired during and after an intravenous injection of 256 MBq of 18F-FDG. Dynamic data were reconstructed using a 3-dimensional time-of-flight list-mode ordered-subsets expectation maximization (OSEM) algorithm and a kernel-based algorithm with all quantitative corrections implemented in the forward model. The Patlak graphical model was used to analyze the 18F-FDG kinetics in the whole body. The input function was extracted from a region over the descending aorta. For comparison, indirect Patlak analysis from reconstructed frames and direct reconstruction of parametric images from the list-mode data were obtained for the last 30 min of data. Results: Images reconstructed by OSEM showed good quality with low noise, even for the 1-s frames. The image quality was further improved using the kernel method. Total-body Patlak parametric images were obtained using either indirect estimation or direct reconstruction. The direct reconstruction method improved the parametric image quality, having a better contrast-versus-noise tradeoff than the indirect method, with a 2- to 3-fold variance reduction. The kernel-based indirect Patlak method offered image quality similar to the direct Patlak method, with less computation time and faster convergence. Conclusion: This study demonstrated the capability of total-body parametric imaging using the uEXPLORER. Furthermore, the results showed the benefits of kernel-regularized reconstruction and direct parametric reconstruction. Both can achieve superior image quality for tracer kinetic studies compared with the conventional indirect OSEM for total-body imaging.

Using Dynamic Contrast-enhanced MRI as an Imaging Biomarker for Migraine: Proceed with Caution

Using Dynamic Contrast-enhanced MRI as an Imaging Biomarker for Migraine: Proceed with Caution

Comparative assessment of linear least-squares, nonlinear least-squares, and Patlak graphical method for regional and local quantitative tracer kinetic modeling in cerebral dynamic 18 F-FDG PET.

Dynamic 18 F-FDG PET allows quantitative estimation of cerebral glucose metabolism both at the regional and local (voxel) level. Although sensitive to noise and highly computationally expensive, nonlinear least-squares (NLS) optimization stands as the reference approach for the estimation of the kinetic model parameters. Nevertheless, faster techniques, including linear least-squares (LLS) and Patlak graphical method, have been proposed to deal with high resolution noisy data, representing a more adaptable solution for routine clinical implementation. Former research investigating the relative performance of the available algorithms lack precise evaluation of kinetic parameter estimates under realistic acquisition conditions. The present study aims at the systematic comparison of the feasibility and pertinence of kinetic modeling of dynamic cerebral 18 F-FDG PET using NLS, LLS, and Patlak method, based on numerical simulations and patient data. Numerical simulations were used to study the bias and variance of K1 and Ki parameters estimation under representative noise levels. Patient data allowed to assess the concordance between the three methods at the regional and voxel scale, and to evaluate the robustness of the estimations with respect to patient head motion. Our findings indicate that at the regional level NLS and LLS provide kinetic parameter estimates (K1 and Ki ) with similar bias and variance characteristics (K1 bias±relative standard deviation [RSD] 0.0±5.1% and 0.1%±4.9% for NLS and LLS respectively, Ki bias±RSD 0.1%±4.5% and -0.7%±4.4% for NLS and LLS respectively). NLS estimates appear, however, to be slightly less sensitive to patient motion. At the voxel level, provided that patient motion is negligible or corrected, LLS offers an appealing alternative solution for local K1 mapping. It yields K1 estimates that are highly correlated, with high correlation with NLS values (Pearson's r=0.95 on actual data) within computations times less than two orders of magnitude lower. Last, Patlak method appears as the most robust and accurate technique for the estimation of Ki values at the regional and voxel scale, with or without head motion. It provides low bias/low variance Ki quantification (bias±RSD -1.5±9.5% and -4.1±19.7% for Patlak and NLS respectively) as well as smooth parametric images suitable for visual assessment.

WED 168 Blood-brain barrier imaging with dynamic contrast-enhanced mri

BackgroundDynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) can detect subtle blood-brain barrier (BBB) permeability. We developed a protocol and conducted experiments to validate the technique.Methods12 subjects with relapsing-remitting multiple sclerosis (RRMS) and 13 controls were recruited. Whole-brain 3D DCE-MRI at 3 Tesla was used to calculate the influx constant Ki (Patlak method). Values were derived for manual regions of interest (ROI) as well as segmented tissue masks. In controls, cerebral blood volume (CBV) was measured in grey and white matter.ResultsIn RRMS, Ki in visibly-enhancing lesions was significantly higher than in normal-appearing white matter (NAWM) (p=0.002). Ki in NAWM was significantly higher in RRMS than controls, by both ROI (p=0.014) and segmentation (p=0.019) methods. In controls, Ki was significantly higher in grey than white matter (p=0.001). CBV (and therefore vascular surface area) was also significantly higher in grey matter (p=0.005), with a mean ratio of 1.9.ConclusionsOur method produces results in line with the expected behaviour of a BBB permeability marker, and the grey/white matter CBV ratio is in agreement with the histologically-established value.

Variations of quantitative perfusion measurement on dynamic contrast enhanced CT for colorectal cancer: implication of standardized image protocol

Tumor angiogenesis is considered an important prognostic factor. With an increasing emphasis on imaging evaluation of the tumor microenvironment, dynamic contrast enhanced-computed tomography (DCE-CT) has evolved as an important functional technique in this setting. Yet many questions remain as to how and when these functional measurements should be performed for each agent and tumor type, and what quantitative models should be used in the fitting process. In this study, we evaluated the variations of perfusion measurement on DCE-CT for rectal cancer patients from (1) different tracer kinetic models, (2) different scan acquisition lengths, and (3) different scan intervals. A total of seven commonly used models were studied: the adiabatic approximation to the tissue homogeneity (AATH) model, adiabatic approximation to the homogeneity tissue with fixed transit time (AATHFT) model, the Tofts model (TM), the extended Tofts model (ETM), Patlak model, Logan model, and the model-free deconvolution method. Akaike’s information criterion was used to identify the best fitting model. The interchangeability of different models was further evaluated using Bland–Altman analysis. All models gave comparable blood volume (BV) measurements except the Patlak method. While for the volume transfer constant (Ktrans) estimation, AATHFT, AATH, and ETM generated reasonable agreement among each other but not for the other models. Regarding the blood flow (BF) measurement, no two models were interchangeable. In addition, the perfusion parameters were compared with four acquisition times (45, 65, 85, and 105 s) and four temporal intervals (1, 2, 3, and 4 s). No significant difference was observed in the volume transfer constant (Ktrans), BV, and BF measurements when comparing data acquired over 65 s with data acquired over 105 s using any of the DCE models in this study. Yet increasing the temporal interval led to a significant overestimation of BF in the deconvolution method. In conclusion, the perfusion measurement is indeed model dependent and the image acquisition/processing technique is dependent. The radiation dose of DCE-CT was an average of 1.5–2 times an abdomen/pelvic CT, which is not insubstantial. To take the DCE-CT forward as a biomarker in oncology, prospective studies should be carefully designed with the optimal image acquisition and analysis technique.