Assessment of population-based input functions for Patlak imaging of whole body dynamic 18F-FDG PET

BACKGROUND

Arterial blood sampling is the gold standard method to obtain the arterial input function (AIF) for quantification of whole body (WB) dynamic 18F-FDG PET imaging. However, this procedure is invasive and not typically available in clinical environments. As an alternative, we compared AIFs to population-based input functions (PBIFs) using two normalization methods: area under the curve (AUC) and extrapolated initial plasma concentration (CP*(0)). To scale the PBIFs, we tested two methods: (1) the AUC of the image-derived input function (IDIF) and (2) the estimated CP*(0). The aim of this study was to validate IDIF and PBIF for FDG oncological WB PET studies by comparing to the gold standard arterial blood sampling.

METHODS

The Feng 18F-FDG plasma concentration model was applied to estimate AIF parameters (n = 23). AIF normalization used either AUC(0-60 min) or CP*(0), estimated from an exponential fit. CP*(0) is also described as the ratio of the injected dose (ID) to initial distribution volume (iDV). iDV was modeled using the subject height and weight, with coefficients that were estimated in 23 subjects. In 12 oncological patients, we computed IDIF (from the aorta) and PBIFs with scaling by the AUC of the IDIF from 4 time windows (15-45, 30-60, 45-75, 60-90 min) (PBIFAUC) and estimated CP*(0) (PBIFiDV). The IDIF and PBIFs were compared with the gold standard AIF, using AUC values and Patlak Ki values.

RESULTS

The IDIF underestimated the AIF at early times and overestimated it at later times. Thus, based on the AUC and Ki comparison, 30-60 min was the most accurate time window for PBIFAUC; later time windows for scaling underestimated Ki (- 6 ± 8 to - 13 ± 9%). Correlations of AUC between AIF and IDIF, PBIFAUC(30-60), and PBIFiDV were 0.91, 0.94, and 0.90, respectively. The bias of Ki was - 9 ± 10%, - 1 ± 8%, and 3 ± 9%, respectively.

CONCLUSIONS

Both PBIF scaling methods provided good mean performance with moderate variation. Improved performance can be obtained by refining IDIF methods and by evaluating PBIFs with test-retest data.

First demonstration of in vivo mapping for regional brain monoacylglycerol lipase using PET with [11C]SAR127303

Monoacylglycerol lipase (MAGL) is a main regulator of the endocannabinoid system within the central nervous system (CNS). Recently, [¹¹C]SAR127303 was developed as a promising radioligand for MAGL imaging. In this study, we aimed to quantify regional MAGL concentrations in the rat brain using positron emission tomography (PET) with [¹¹C]SAR127303. An irreversible two-tissue compartment model (2-TCMi, k₄ = 0) analysis was conducted to estimate quantitative parameters (k₃, K_i^2-TCMi, and λk₃). These parameters were successfully obtained with high identifiability (<10 %COV) for the following regions ranked in order from highest to lowest: cingulate cortex > striatum > hippocampus > thalamus > cerebellum > hypothalamus ≈ pons. In vitro autoradiographs using [¹¹C]SAR127303 showed a heterogeneous distribution of radioactivity, as seen in the PET images. The K_i^2-TCMi and λk₃ values correlated relatively highly with in vitro binding (r > 0.4, P < 0.005). The K_i^2-TCMi values showed high correlation and low underestimation (<10%) compared with the slope of a Patlak plot analysis with linear regression (K_i^Patlak). In conclusion, we successfully estimated regional net uptake value of [¹¹C]SAR127303 reflecting MAGL concentrations in rat brain regions for the first time.

Blood-brain barrier permeability of normal-appearing white matter in patients with vestibular schwannoma: A new hybrid approach for analysis of T1 -W DCE-MRI

PURPOSE

To develop and assess a "hybrid" method that combines a first-pass analytical approach and the Patlak plot (PP) to improve assessment of low blood-brain barrier permeability from dynamic contrast-enhanced (DCE) magnetic resonance imaging (MRI) data.

MATERIALS AND METHODS

Seven patients with vestibular schwannoma were enrolled. T1 -W DCE imaging was acquired on a 1.5T scanner. Normal-appearing white matter (NAWM) was divided into four regions of interest (ROIs) based on the magnitude of changes in longitudinal relaxation rate (ΔR1) after gadolinium administration. Kinetic analysis of ROI-averaged contrast agent concentration curves was performed using both the conventional PP and the hybrid method. Computer simulated uptake curves that resemble those from NAWM were analyzed with both methods. Percent deviations (PD) of the "measured" values from the "true" values were calculated to evaluate accuracy and precision of the two methods.

RESULTS

The simulation showed that, at a noise level of 4% (a noise level similar to the in vivo data) and using a signal intensity (SI) averaging scheme, the new hybrid method achieved a PD of 0.9 ± 2.7% for vp , and a PD of -5.4 ± 5.9% for Ktrans . In comparison, the PP method obtained a PD of 3.6 ± 11.3% for vp , and -8.3 ± 12.8% for Ktrans . One-way analyses of variance (ANOVAs) showed significant variations from the four WM regions (P < 10-15 for ΔR1; P < 10-6 for Ktrans ; P < 10-4 for vp ).

CONCLUSION

Both computer simulation and in vivo studies demonstrate improved reliability in vp and Ktrans estimates with the hybrid method.

LEVEL OF EVIDENCE

3 Technical Efficacy: Stage 1 J. MAGN. RESON. IMAGING 2017;46:79-93.

Feasibility of triphasic CT with a modified two-point Patlak plot to determine spit kidney glomerular filtration rate in clinical practice

PURPOSE

To investigate whether triphasic CT with a simplified Patlak plot can be used in clinical practice for the estimate of split kidney glomerular filtration rate (SKGFR).

MATERIALS AND METHODS

The animal experiment included 15 rabbits that underwent 40 dynamic contrast-enhanced CT scans of the kidneys with 1.5 s time interval. Patlak-derived SKGFR was obtained using standard forty-point, two-point (unenhanced phase, arterial phase t _α, and portovenous phase t _β), and a modified two-point (MTP) (unenhanced, t _α, t _β, and a virtual t _τ [t _τ = (t _α + t _β)/2]) image data, respectively. The MTP-Patlak plot approach was then validated in 13 patients who underwent a triphasic renal contrast-enhanced CT examination. SKGFR measured by 99^mTc-DTPA clearance was as a standard reference.

RESULTS

MTP-Patlak significantly reduced input function errors than two-point Patlak (21.1 ± 16.2 % vs 30.8 ± 15.2 %, p < 0.01) and showed good concordance with standard Patlak for measurement of SKGFR in animal experiment (1.20 ± 0.38 mL/g/min vs 1.51 ± 0.43 mL/g/min; linear correlation coefficient r = 0.87, p < 0.001). Human study showed that mean SKGFR was 45.7 mL/min (range, 26.5-86.2 mL/min) obtained from 99^mTc-DTPA, and 38.2 mL/min (range, 18.6-79.3 mL/min) obtained from triphasic CT using MTP-Patlak plot. Linear correlation between the two methods was r = 0.75 (p < 0.01). The mean difference between SKGFRs as determined with the two methods was 7.4 ± 9.0 mL/min.

CONCLUSION

The MTP-Patlak approach, featured with simplicity, is feasible in a clinically indicated CT examination for the evaluation of split renal function.

Evaluation of glioblastomas and lymphomas with whole-brain CT perfusion: Comparison between a delay-invariant singular-value decomposition algorithm and a Patlak plot

OBJECTIVE

Correction of contrast leakage is recommended when enhancing lesions during perfusion analysis. The purpose of this study was to assess the diagnostic performance of computed tomography perfusion (CTP) with a delay-invariant singular-value decomposition algorithm (SVD+) and a Patlak plot in differentiating glioblastomas from lymphomas.

MATERIALS AND METHODS

This prospective study included 17 adult patients (12 men and 5 women) with pathologically proven glioblastomas (n=10) and lymphomas (n=7). CTP data were analyzed using SVD+ and a Patlak plot. The relative tumor blood volume and flow compared to contralateral normal-appearing gray matter (rCBV and rCBF derived from SVD+, and rBV and rFlow derived from the Patlak plot) were used to differentiate between glioblastomas and lymphomas. The Mann-Whitney U test and receiver operating characteristic (ROC) analyses were used for statistical analysis.

RESULTS

Glioblastomas showed significantly higher rFlow (3.05±0.49, mean±standard deviation) than lymphomas (1.56±0.53; P<0.05). There were no statistically significant differences between glioblastomas and lymphomas in rBV (2.52±1.57 vs. 1.03±0.51; P>0.05), rCBF (1.38±0.41 vs. 1.29±0.47; P>0.05), or rCBV (1.78±0.47 vs. 1.87±0.66; P>0.05). ROC analysis showed the best diagnostic performance with rFlow (Az=0.871), followed by rBV (Az=0.771), rCBF (Az=0.614), and rCBV (Az=0.529).

CONCLUSION

CTP analysis with a Patlak plot was helpful in differentiating between glioblastomas and lymphomas, but CTP analysis with SVD+ was not.

Peritumoral tissue compression is predictive of exudate flux in a rat model of cerebral tumor: an MRI study in an embedded tumor

MRI estimates of extracellular volume and tumor exudate flux in peritumoral tissue are demonstrated in an experimental model of cerebral tumor. Peritumoral extracellular volume predicted the tumor exudate flux. Eighteen RNU athymic rats were inoculated intracerebrally with U251MG tumor cells and studied with dynamic contrast enhanced MRI (DCE-MRI) approximately 18 days post implantation. Using a model selection paradigm and a novel application of Patlak and Logan plots to DCE-MRI data, the distribution volume (i.e. tissue porosity) in the leaky rim of the tumor and that in the tissue external to the rim (the outer rim) were estimated, as was the tumor exudate flow from the inner rim of the tumor through the outer rim. Distribution volume in the outer rim was approximately half that of the inner adjacent region (p < 1 × 10(-4)). The distribution volume of the outer ring was significantly correlated (R(2) = 0.9) with tumor exudate flow from the inner rim. Thus, peritumoral extracellular volume predicted the rate of tumor exudate flux. One explanation for these data is that perfusion, i.e. the delivery of blood to the tumor, was regulated by the compression of the mostly normal tissue of the tumor rim, and that the tumor exudate flow was limited by tumor perfusion.

Theoretical considerations in measurement of time discrepancies between input and myocardial time-signal intensity curves in estimates of regional myocardial perfusion with first-pass contrast-enhanced MRI

The purpose of this study was to develop a method to determine time discrepancies between input and myocardial time-signal intensity (TSI) curves for accurate estimation of myocardial perfusion with first-pass contrast-enhanced MRI. Estimation of myocardial perfusion with contrast-enhanced MRI using kinetic models requires faithful recording of contrast content in the blood and myocardium. Typically, the arterial input function (AIF) is obtained by setting a region of interest in the left ventricular cavity. However, there is a small delay between the AIF and the myocardial curves, and such time discrepancies can lead to errors in flow estimation using Patlak plot analysis. In this study, the time discrepancies between the arterial TSI curve and the myocardial tissue TSI curve were estimated based on the compartment model. In the early phase after the arrival of the contrast agent in the myocardium, the relationship between rate constant K1 and the concentrations of Gd-DTPA contrast agent in the myocardium and arterial blood (LV blood) can be described by the equation K1={dCmyo(tpeak)/dt}/Ca(tpeak), where Cmyo(t) and Ca(t) are the relative concentrations of Gd-DTPA contrast agent in the myocardium and in the LV blood, respectively, and tpeak is the time corresponding to the peak of Ca(t). In the ideal case, the time corresponding to the maximum upslope of Cmyo(t), tmax, is equal to tpeak. In practice, however, there is a small difference in the arrival times of the contrast agent into the LV and into the myocardium. This difference was estimated to correspond to the difference between tpeak and tmax. The magnitudes of such time discrepancies and the effectiveness of the correction for these time discrepancies were measured in 18 subjects who underwent myocardial perfusion MRI under rest and stress conditions. The effects of the time discrepancies could be corrected effectively in the myocardial perfusion estimates.

Usefulness of an Automatic Quantitative Method for Measuring Regional Cerebral Blood Flow Using (99m)Tc Ethyl Cysteinate Dimer Brain Uptake Ratio

OBJECTIVES

Improved brain uptake ratio (IBUR), employing (99m)Tc-ethyl cysteinate dimer ((99m)Tc-ECD), is an automatic non-invasive method for quantitatively measuring regional cerebral blood flow (rCBF). This method was developed by the reconstruction of the theory and linear regression equation, based on rCBF measurement by H2 (15)O positron emission tomography. Clarification of differences in rCBF values obtained by Patlak plot (PP) and IBUR method is important for clinical diagnosis during the transition period between these methods. Our purpose in this study was to demonstrate the relationship between rCBF values obtained by IBUR and PP methods and to evaluate the clinical applicability of IBUR method.

METHODS

The mean CBF (mCBF) and rCBF values in 15 patients were obtained using the IBUR method and compared with PP method values.

RESULTS

Overall, mCBF and rCBF values, obtained using these independent techniques, were found to be correlated (r=0.68). The mCBF values obtained by the IBUR method ranged from 18.9 to 44.9 ml/100g/min, whereas those obtained by the PP method ranged from 34.7 to 48.1 ml/100g/min. The rCBF values obtained by the IBUR method ranged from 16.3 to 60.2 ml/100g/min, whereas those obtained by the PP method were within the range of 26.7-58.8 ml/100g/min.

CONCLUSION

The ranges of mCBF and rCBF values, obtained by the IBUR method, were approximately 60% lower than those obtained by the PP method; therefore, this method can be useful for diagnosing lower flow area. Re-analysis of prior PP data, using the IBUR method, could be potentially useful for the clinical follow-up of rCBF.

Intratumor distribution and test-retest comparisons of physiological parameters quantified by dynamic contrast-enhanced MRI in rat U251 glioma

The distribution of dynamic contrast-enhanced MRI (DCE-MRI) parametric estimates in a rat U251 glioma model was analyzed. Using Magnevist as contrast agent (CA), 17 nude rats implanted with U251 cerebral glioma were studied by DCE-MRI twice in a 24 h interval. A data-driven analysis selected one of three models to estimate either (1) plasma volume (vp), (2) vp and forward volume transfer constant (K(trans)) or (3) vp, K(trans) and interstitial volume fraction (ve), constituting Models 1, 2 and 3, respectively. CA distribution volume (VD) was estimated in Model 3 regions by Logan plots. Regions of interest (ROIs) were selected by model. In the Model 3 ROI, descriptors of parameter distributions--mean, median, variance and skewness--were calculated and compared between the two time points for repeatability. All distributions of parametric estimates in Model 3 ROIs were positively skewed. Test-retest differences between population summaries for any parameter were not significant (p ≥ 0.10; Wilcoxon signed-rank and paired t tests). These and similar measures of parametric distribution and test-retest variance from other tumor models can be used to inform the choice of biomarkers that best summarize tumor status and treatment effects.