Multi-graphical analysis of dynamic PET

Exploring the nigrostriatal and digestive interplays in Parkinson's disease using dynamic total-body [11C]CFT PET/CT

PURPOSE

Dynamic total-body imaging enables new perspectives to investigate the potential relationship between the central and peripheral regions. Employing uEXPLORER dynamic [11C]CFT PET/CT imaging with voxel-wise simplified reference tissue model (SRTM) kinetic modeling and semi-quantitative measures, we explored how the correlation pattern between nigrostriatal and digestive regions differed between the healthy participants as controls (HC) and patients with Parkinson's disease (PD).

METHODS

Eleven participants (six HCs and five PDs) underwent 75-min dynamic [11C]CFT scans on a total-body PET/CT scanner (uEXPLORER, United Imaging Healthcare) were retrospectively enrolled. Time activity curves for four nigrostriatal nuclei (caudate, putamen, pallidum, and substantia nigra) and three digestive organs (pancreas, stomach, and duodenum) were obtained. Total-body parametric images of relative transporter rate constant (R1) and distribution volume ratio (DVR) were generated using the SRTM with occipital lobe as the reference tissue and a linear regression with spatial-constraint algorithm. Standardized uptake value ratio (SUVR) at early (1-3 min, SUVREP) and late (60-75 min, SUVRLP) phases were calculated as the semi-quantitative substitutes for R1 and DVR, respectively.

RESULTS

Significant differences in estimates between the HC and PD groups were identified in DVR and SUVRLP of putamen (DVR: 4.82 ± 1.58 vs. 2.58 ± 0.53; SUVRLP: 4.65 ± 1.36 vs. 2.84 ± 0.67; for HC and PD, respectively, both p < 0.05) and SUVREP of stomach (1.12 ± 0.27 vs. 2.27 ± 0.65 for HC and PD, respectively; p < 0.01). In the HC group, negative correlations were observed between stomach and substantia nigra in both the R1 and SUVREP values (r=-0.83, p < 0.05 for R1; r=-0.94, p < 0.01 for SUVREP). Positive correlations were identified between pancreas and putamen in both DVR and SUVRLP values (r = 0.94, p < 0.01 for DVR; r = 1.00, p < 0.001 for SUVRLP). By contrast, in the PD group, no correlations were found between the aforementioned target nigrostriatal and digestive areas.

CONCLUSIONS

The parametric images of R1 and DVR generated from the SRTM model, along with SUVREP and SUVRLP, were proposed to quantify dynamic total-body [11C]CFT PET/CT in HC and PD groups. The distinction in correlation patterns of nigrostriatal and digestive regions between HC and PD groups identified by R1 and DVR, or SUVRs, may provide new insights into the disease mechanism.

Quantitation of dynamic total-body PET imaging: recent developments and future perspectives

BACKGROUND

Positron emission tomography (PET) scanning is an important diagnostic imaging technique used in disease diagnosis, therapy planning, treatment monitoring, and medical research. The standardized uptake value (SUV) obtained at a single time frame has been widely employed in clinical practice. Well beyond this simple static measure, more detailed metabolic information can be recovered from dynamic PET scans, followed by the recovery of arterial input function and application of appropriate tracer kinetic models. Many efforts have been devoted to the development of quantitative techniques over the last couple of decades.

CHALLENGES

The advent of new-generation total-body PET scanners characterized by ultra-high sensitivity and long axial field of view, i.e., uEXPLORER (United Imaging Healthcare), PennPET Explorer (University of Pennsylvania), and Biograph Vision Quadra (Siemens Healthineers), further stimulates valuable inspiration to derive kinetics for multiple organs simultaneously. But some emerging issues also need to be addressed, e.g., the large-scale data size and organ-specific physiology. The direct implementation of classical methods for total-body PET imaging without proper validation may lead to less accurate results.

CONCLUSIONS

In this contribution, the published dynamic total-body PET datasets are outlined, and several challenges/opportunities for quantitation of such types of studies are presented. An overview of the basic equation, calculation of input function (based on blood sampling, image, population or mathematical model), and kinetic analysis encompassing parametric (compartmental model, graphical plot and spectral analysis) and non-parametric (B-spline and piece-wise basis elements) approaches is provided. The discussion mainly focuses on the feasibilities, recent developments, and future perspectives of these methodologies for a diverse-tissue environment.

Tumor-to-blood ratio for assessment of fibroblast activation protein receptor density in pancreatic cancer using [68Ga]Ga-FAPI-04

PURPOSE

[⁶⁸Ga]Ga-FAPI PET/CT has been widely used in clinical diagnosis and radiopharmaceutical therapy. In this study, tumor-to-blood ratio (TBR) was evaluated as a powerful tool for semiquantitative assessment of [⁶⁸Ga]Ga-FAPI-04 tumor uptake and as an effective index for tumors with high FAP expression in theranostics.

METHODS

Nine patients with pancreatic cancer underwent a 60-min dynamic PET/CT scan by total-body PET/CT (with a long AFOV of 194 cm) after injection of [⁶⁸Ga]Ga-FAPI-04. After dynamic PET/CT scan, three patients received chemotherapy and underwent the second dynamic scan to evaluate treatment response. Time-activity curves (TACs) were obtained by drawing regions of interest for primary pancreatic lesions and metastatic lesions. The lesion TACs were fitted using four compartment models by the software PMOD PKIN kinetic modeling. The preferred pharmacokinetic model for [⁶⁸Ga]Ga-FAPI-04 was evaluated based on the Akaike information criterion. The correlations between simplified methods for quantification of [⁶⁸Ga]Ga-FAPI-04 (SUVs; tumor-to-blood ratios [TBRs]) and the total distribution volume (V_t) estimates obtained from pharmacokinetic analysis were calculated.

RESULTS

In total, 9 primary lesions and 25 metastatic lesions were evaluated. The reversible two-tissue compartment model (2TCM) was the most appropriate model among the four compartment models. The total distribution volume V_t values derived from 2TCM varied significantly in pathological lesions and background regions. A strong positive correlation was observed between TBR_mean and V_t from the 2TCM model in pathological lesions (R²=0.92, P<0.001). The relative difference range for TBR_mean was 2.1% compared to the reduction rate of V_t in the patients who were treated with chemotherapy.

CONCLUSIONS

A strong positive correlation was observed between TBR_mean and V_t for [⁶⁸Ga]Ga-FAPI-04. TBR_mean reflects FAP receptor density better than SUV_mean and SUV_max, and would be the preferred measurement tool for semiquantitative assessment of [⁶⁸Ga]Ga-FAPI-04 tumor uptake and as a means for evaluating treatment response.

Human Cortical Serotonin 2A Receptor Occupancy by Psilocybin Measured Using [11C]MDL 100,907 Dynamic PET and a Resting-State fMRI-Based Brain Parcellation

Psilocybin (a serotonin 2A, or 5-HT2A, receptor agonist) has shown preliminary efficacy as a treatment for mood and substance use disorders. The current report utilized positron emission tomography (PET) with the selective 5-HT2A receptor inverse agonist radioligand [11C]MDL 100,907 (a.k.a. M100,907) and cortical regions of interest (ROIs) derived from resting-state functional connectivity-based brain parcellations in 4 healthy volunteers (2 females) to determine regional occupancy/target engagement of 5-HT2A receptors after oral administration of a psychoactive dose of psilocybin (10 mg/70 kg). Average 5-HT2A receptor occupancy across all ROIs was 39.5% (± 10.9% SD). Three of the ROIs with greatest occupancy (between 63.12 and 74.72% occupancy) were within the default mode network (subgenual anterior cingulate and bilateral angular gyri). However, marked individual variability in regional occupancy was observed across individuals. These data support further investigation of the relationship between individual differences in the acute and enduring effects of psilocybin and the degree of regional 5-HT2A receptor occupancy.

Astrocyte activation imaging with 11C-acetate and amyloid PET in mild cognitive impairment due to Alzheimer pathology

BACKGROUND

Neuroinflammation is a well-known feature of early Alzheimer disease (AD) yet astrocyte activation has not been extensively evaluated with in vivo imaging in mild cognitive impairment (MCI) due to amyloid plaque pathology. Unlike neurons, astrocytes metabolize acetate, which has potential as a glial biomarker in neurodegeneration in response to AD pathologic features. Since the medial temporal lobe (MTL) is a hotspot for AD neurodegeneration and inflammation, we assessed astrocyte activity in the MTL and compared it to amyloid and cognition.

METHODS

We evaluate spatial patterns of in vivo astrocyte activation and their relationships to amyloid deposition and cognition in a cross-sectional pilot study of six participants with MCI and five cognitively normal participants. We measure 11C-acetate and 18F-florbetaben amyloid standardized uptake values ratios (SUVRs) and kinetic flux compared to the cerebellum on PET, with MRI and neurocognitive testing.

RESULTS

MTL 11C-acetate SUVR was significantly elevated in MCI compared to cognitively normal participants (P = 0.03; Cohen d = 1.76). Moreover, MTL 11C-acetate SUVR displayed significant associations with global and regional amyloid burden in MCI. Greater MTL 11C-acetate retention was significantly related with worse neurocognitive measures including the Montreal Cognitive Assessment (P = 0.001), word list recall memory (P = 0.03), Boston naming test (P = 0.04) and trails B test (P = 0.04).

CONCLUSIONS

While further validation is required, this exploratory pilot study suggests a potential role for 11C-acetate PET as a neuroinflammatory biomarker in MCI and early AD to provide clinical and translational insights into astrocyte activation as a pathological response to amyloid.

Spatially constrained kinetic modeling with dual reference tissues improves 18F-flortaucipir PET in studies of Alzheimer disease

PURPOSE

Recent studies have shown that standard compartmental models using plasma input or the cerebellum reference tissue input are generally not reliable for quantifying tau burden in dynamic 18F-flortaucipir PET studies of Alzheimer disease. So far, the optimal reference region for estimating 18F-flortaucipir delivery and specific tau binding has yet to be determined. The objective of the study is to improve 18F-flortaucipir brain tau PET quantification using a spatially constrained kinetic model with dual reference tissues.

METHODS

Participants were classified as either cognitively normal (CN) or cognitively impaired (CI) based on clinical assessment. T1-weighted structural MRI and 105-min dynamic 18F-flortaucipir PET scans were acquired for each participant. Using both a simplified reference tissue model (SRTM2) and Logan plot with either cerebellum gray matter or centrum semiovale (CS) white matter as the reference tissue, we estimated distribution volume ratios (DVRs) and the relative transport rate constant R1 for region of interest-based (ROI) and voxelwise-based analyses. Conventional linear regression (LR) and LR with spatially constrained (LRSC) parametric imaging algorithms were then evaluated. Noise-induced bias in the parametric images was compared to estimates from ROI time activity curve-based kinetic modeling. We finally evaluated standardized uptake value ratios at early phase (SUVREP, 0.7-2.9 min) and late phase (SUVRLP, 80-105 min) to approximate R1 and DVR, respectively.

RESULTS

The percent coefficients of variation of R1 and DVR estimates from SRTM2 with spatially constrained modeling were comparable to those from the Logan plot and SUVRs. The SRTM2 using CS reference tissue with LRSC reduced noise-induced underestimation in the LR generated DVR images to negligible levels (< 1%). Inconsistent overestimation of DVR in the SUVRLP only occurred using the cerebellum reference tissue-based measurements. The CS reference tissue-based DVR and SUVRLP, and cerebellum-based SUVREP and R1 provided higher Cohen's effect size d to detect increased tau deposition and reduced relative tracer transport rate in CI individuals.

CONCLUSION

Using a spatially constrained kinetic model with dual reference tissues significantly improved quantification of relative perfusion and tau binding. Cerebellum and CS are the suggested reference tissues to estimate R1 and DVR, respectively, for dynamic 18F-flortaucipir PET studies. Cerebellum-based SUVREP and CS-based SUVRLP may be used to simplify 18F-flortaucipir PET study.

Noninvasive quantification of nonhuman primate dynamic 18F-FDG PET imaging

¹⁸F-FDG uptake rate constant K_i is the main physiology parameter measured in dynamic PET studies. A model-independent graphical analysis using Patlak plot with plasma input function (PIF) is a standard approach used to estimate K_i . The PIF is the ¹⁸F-FDG time activity curve (TAC) in plasma that is obtained by serial arterial blood sampling. The purpose of the study is to evaluate a Patlak plot-based optimization approach with reduced blood samples for noninvasive quantification of dynamic ¹⁸F-FDG PET imaging. Eight 60 min rhesus monkey brain dynamic ¹⁸F-FDG PET scans with arterial blood samples were collected. The measured PIF (mPIF) was determined by arterial blood samples. TACs of seven cerebral regions of interest were generated from each study. With a given number of blood samples, the population-based PIF (pPIF) was determined by either interpolation or extrapolation method using scale calibrated population mean of normalized PIF. The optimal sampling scheme with given blood sample size was determined by maximizing the correlations between the K_i estimated from pPIF and those obtained by mPIF. A leave-two-out cross-validation method was used for evaluation. The linear correlations between the K_i estimates from pPIF with optimal sampling schemes and those from mPIF were: K_i (pPIF 1 sample at 40 min) = 1.015 K_i (mPIF) - 0.000, R ² = 0.974; K_i (pPIF 2 samples at 35 and 50 min) = 1.052 K_i (mPIF) - 0.001, R ² = 0.976; K_i (pPIF 3 samples at 12, 40, and 50 min) = 1.030 K_i (mPIF) - 0.000, R ² = 0.985; and K_i (pPIF 4 samples at 10, 20, 40, and 50 min) = 1.016 K_i (mPIF)- 0.000, R ² = 0.993. As the sample size became greater or equal to 4, the K_i estimates from pPIF with the optimal protocol were almost identical to those from mPIF. The Patlak plot-based optimization approach is a reliable method to estimate PIF for noninvasive quantification of non-human primate dynamic ¹⁸F-FDG PET imaging and is potentially extendable to further translational human studies.

Imaging Biotin Trafficking In Vivo with Positron Emission Tomography

The water-soluble vitamin biotin is essential for cellular growth, development, and well-being, but its absorption, distribution, metabolism, and excretion are poorly understood. This paper describes the radiolabeling of biotin with the positron emission tomography (PET) radionuclide carbon-11 ([¹¹C]biotin) to enable the quantitative study of biotin trafficking in vivo. We show that intravenously administered [¹¹C]biotin is quickly distributed to the liver, kidneys, retina, heart, and brain in rodents-consistent with the known expression of the biotin transporter-and there is a surprising accumulation in the brown adipose tissue (BAT). Orally administered [¹¹C]biotin was rapidly absorbed in the small intestine and swiftly distributed to the same organs. Preadministration of nonradioactive biotin inhibited organ uptake and increased excretion. [¹¹C]Biotin PET imaging therefore provides a dynamic in vivo map of transporter-mediated biotin trafficking in healthy rodents. This technique will enable the exploration of biotin trafficking in humans and its use as a research tool for diagnostic imaging of obesity/diabetes, bacterial infection, and cancer.

A cholecystokinin B receptor antagonist and cocaine interaction, phase I study

AIMS

RPR 102681, a cholecystokinin-B antagonist, increased dopamine (DA) release and reduced cocaine self-administration in animals. This pilot study sought to assess the safety and pharmacokinetics (PK) of co-administration of RPR 102681 and cocaine, and to confirm the DA release mechanism of RPR 102681.

METHODS

Sixteen cocaine-dependent participants were randomized to either placebo or RPR102681 at 3 ascending doses; cocaine was co-administered at steady state of RPR 102681. [¹¹ C]raclopride positron emission tomography scans were conducted at baseline and at each RPR102681 dose.

RESULTS

RPR 102681 was well tolerated, and safe to co-administer with cocaine. RPR 102681 did not alter the PK of either cocaine or its metabolite benzoylecgonine and showed no intrinsic abuse liability. There was a trend toward reduction of cocaine craving scores. In contrast to animal studies, RPR 102681 significantly increased the binding potential of [¹¹ C]raclopride in the ventral striatum (t test, P < .001) and caudate nucleus (t test, P < .0001) in a small subset of patients, suggesting that it may reduce intrasynaptic striatal DA.

CONCLUSION

Overall, this pilot study suggests that RPR 102681 would be unlikely candidate, as an agonist medication for the treatment for cocaine addiction but worth investigating further for possible role in reducing craving.

Simplified estimation of binding parameters based on image-derived reference tissue models for dopamine transporter bindings in non-human primates using [18F]FE-PE2I and PET

The aim of this study on dopamine transporter binding by [¹⁸F]FE-PE2I and PET was to describe an image-derived approach using reference tissue models: the Logan DVR approach and simplified reference tissue model (SRTM), the features of which were simple to operate and precise in the measurements. Using the approach, the authors sought to obtain binding images and parameters. [¹⁸F]FE-PE2I and dynamic PET as well as an MRI was performed on three rhesus monkeys, and metabolite corrected arterial plasma inputs were obtained. After co-registering of PET to MR images, both image sets were resliced. The time-activity curve of the cerebellum was used as indirect input, and binding parametric images were computed voxel-by-voxel. Voxel-wise linear calculations were used for the Logan DVR approach, and nonlinear least squares fittings for the SRTM. To determine the best linear regression in the Logan DVR approach, the distribution volume ratio was obtained using the optimal starting frame analysis. The obtained binding parameters were compared with those obtained by the other independent ROI-based numerical approaches: two-tissue compartment model (2TCM), Logan DVR approach and SRTM using PMOD software. Binding potentials (BP) obtained by the present approach agreed well with those obtained by ROI-based numerical approaches, although reference tissue models tended to underestimate the BP value than 2TCM. Image-derived Logan approach provided a low-noise image, the computation time was short, and the error in the optimal starting frame analysis was small. The present approach provides a high-quality binding parametric image and reliable parameter value easily.

Noninvasive bi-graphical analysis for the quantification of slowly reversible radioligand binding

In this paper, we presented a novel reference-region-based (noninvasive) bi-graphical analysis for the quantification of a reversible radiotracer binding that may be too slow to reach relative equilibrium (RE) state during positron emission tomography (PET) scans. The proposed method indirectly implements the noninvasive Logan plot, through arithmetic combination of the parameters of two other noninvasive methods and the apparent tissue-to-plasma efflux rate constant for the reference region ([Formula: see text]). We investigated its validity and statistical properties, by performing a simulation study with various noise levels and [Formula: see text] values, and also evaluated its feasibility for [¹⁸F]FP-CIT PET in human brain. The results revealed that the proposed approach provides distribution volume ratio estimation comparable to the Logan plot at low noise levels while improving underestimation caused by non-RE state differently depending on [Formula: see text]. Furthermore, the proposed method was able to avoid noise-induced bias of the Logan plot, and the variability of its results was less dependent on [Formula: see text] than the Logan plot. Therefore, this approach, without issues related to arterial blood sampling given a pre-estimate of [Formula: see text] (e.g. population-based), could be useful in parametric image generation for slow kinetic tracers staying in a non-RE state within a PET scan.

Federated optimisation of kinetic analysis problems

Positron Emission Tomography (PET) data is intrinsically dynamic, and kinetic analysis of dynamic PET data can substantially augment the information provided by static PET reconstructions. Yet despite the insights into disease that kinetic analysis offers, it is not used clinically and seldom used in research beyond the preclinical stage. The utility of PET kinetic analysis is hampered by several factors including spatial inconsistency within regions of homogeneous tissue and relative computational expense when fitting complex models to individual voxels. Even with sophisticated algorithms inconsistencies can arise because local optima frequently have narrow basins of convergence, are surrounded by relatively flat (uninformative) regions, have relatively low-gradient valley floors, or combinations thereof. Based on the observation that cost functions for individual voxels frequently bear some resemblance to each-other, this paper proposes the federated optimisation of the individual kinetic analysis problems within a given image. This approach shares parameters proposed during optimisation with other, similar voxels. Federated optimisation exploits the redundancy typical of large medical images to improve the optimisation residuals, computational efficiency and, to a limited extent, image consistency. This is achieved without restricting the formulation of the kinetic model, resorting to an explicit regularisation parameter, or limiting the resolution at which parameters are computed.

Comparative assessment of parametric neuroreceptor mapping approaches based on the simplified reference tissue model using [¹¹C]ABP688 PET

In recent years, several linearized model approaches for fast and reliable parametric neuroreceptor mapping based on dynamic nuclear imaging have been developed from the simplified reference tissue model (SRTM) equation. All the methods share the basic SRTM assumptions, but use different schemes to alleviate the effect of noise in dynamic-image voxels. Thus, this study aimed to compare those approaches in terms of their performance in parametric image generation. We used the basis function method and MRTM2 (multilinear reference tissue model with two parameters), which require a division process to obtain the distribution volume ratio (DVR). In addition, a linear model with the DVR as a model parameter (multilinear SRTM) was used in two forms: one based on linear least squares and the other based on extension of total least squares (TLS). Assessment using simulated and actual dynamic [(11)C]ABP688 positron emission tomography data revealed their equivalence with the SRTM, except for different noise susceptibilities. In the DVR image production, the two multilinear SRTM approaches achieved better image quality and regional compatibility with the SRTM than the others, with slightly better performance in the TLS-based method.

The PET Radioligand 18F-FIMX Images and Quantifies Metabotropic Glutamate Receptor 1 in Proportion to the Regional Density of Its Gene Transcript in Human Brain

A recent study from our laboratory found that (18)F-FIMX is an excellent PET radioligand for quantifying metabotropic glutamate receptor 1 (mGluR1) in monkey brain. This study evaluated the ability of (18)F-FIMX to quantify mGluR1 in humans. A second goal was to use the relative density of mGluR1 gene transcripts in brain regions to estimate specific uptake and nondisplaceable uptake (VND) in each brain region.

METHODS

After injection of 189 ± 3 MBq of (18)F-FIMX, 12 healthy volunteers underwent a dynamic PET scan over 120 min. For 6 volunteers, images were acquired until 210 min. A metabolite-corrected arterial input function was measured from the radial artery. Four other subjects underwent whole-body scanning to estimate radiation exposure.

RESULTS

(18)F-FIMX uptake into the human brain was high (SUV = 4-6 in the cerebellum), peaked at about 10 min, and washed out rapidly. An unconstrained 2-tissue-compartment model fitted the data well, and distribution volume (VT) (mL⋅cm(-3)) values ranged from 1.5 in the caudate to 11 in the cerebellum. A 120-min scan provided stable VT values in all regions except the cerebellum, for which an acquisition time of at least 170 min was necessary. VT values in brain regions correlated well with mGluR1 transcript density, and the correlation suggested that VND of (18)F-FIMX was quite low (0.5 mL⋅cm(-3)). This measure of VND in humans was similar to that from a receptor blocking study in monkeys, after correcting for differences in plasma protein binding. Similar to other (18)F-labeled ligands, the effective dose was about 23 μSv/MBq.

CONCLUSION

(18)F-FIMX can quantify mGluR1 in the human brain with a 120- to 170-min scan. Correlation of brain uptake with the relative density of mGluR1 transcript allows specific receptor binding of a radioligand to be quantified without injecting pharmacologic doses of a blocking agent.

Generalized whole-body Patlak parametric imaging for enhanced quantification in clinical PET

We recently developed a dynamic multi-bed PET data acquisition framework to translate the quantitative benefits of Patlak voxel-wise analysis to the domain of routine clinical whole-body (WB) imaging. The standard Patlak (sPatlak) linear graphical analysis assumes irreversible PET tracer uptake, ignoring the effect of FDG dephosphorylation, which has been suggested by a number of PET studies. In this work: (i) a non-linear generalized Patlak (gPatlak) model is utilized, including a net efflux rate constant kloss, and (ii) a hybrid (s/g)Patlak (hPatlak) imaging technique is introduced to enhance contrast to noise ratios (CNRs) of uptake rate Ki images. Representative set of kinetic parameter values and the XCAT phantom were employed to generate realistic 4D simulation PET data, and the proposed methods were additionally evaluated on 11 WB dynamic PET patient studies. Quantitative analysis on the simulated Ki images over 2 groups of regions-of-interest (ROIs), with low (ROI A) or high (ROI B) true kloss relative to Ki, suggested superior accuracy for gPatlak. Bias of sPatlak was found to be 16-18% and 20-40% poorer than gPatlak for ROIs A and B, respectively. By contrast, gPatlak exhibited, on average, 10% higher noise than sPatlak. Meanwhile, the bias and noise levels for hPatlak always ranged between the other two methods. In general, hPatlak was seen to outperform all methods in terms of target-to-background ratio (TBR) and CNR for all ROIs. Validation on patient datasets demonstrated clinical feasibility for all Patlak methods, while TBR and CNR evaluations confirmed our simulation findings, and suggested presence of non-negligible kloss reversibility in clinical data. As such, we recommend gPatlak for highly quantitative imaging tasks, while, for tasks emphasizing lesion detectability (e.g. TBR, CNR) over quantification, or for high levels of noise, hPatlak is instead preferred. Finally, gPatlak and hPatlak CNR was systematically higher compared to routine SUV values.

ITI-007 demonstrates brain occupancy at serotonin 5-HT₂A and dopamine D₂ receptors and serotonin transporters using positron emission tomography in healthy volunteers

RATIONALE

Central modulation of serotonin and dopamine underlies efficacy for a variety of psychiatric therapeutics. ITI-007 is an investigational new drug in development for treatment of schizophrenia, mood disorders, and other neuropsychiatric disorders.

OBJECTIVES

The purpose of this study was to determine brain occupancy of ITI-007 at serotonin 5-HT2A receptors, dopamine D2 receptors, and serotonin transporters using positron emission tomography (PET) in 16 healthy volunteers.

METHODS

Carbon-11-MDL100907, carbon-11-raclopride, and carbon-11-3-amino-4-(2-dimethylaminomethyl-phenylsulfanyl)-benzonitrile) (carbon-11-DASB) were used as the radiotracers for imaging 5-HT2A receptors, D2 receptors, and serotonin transporters, respectively. Brain regions of interest were outlined using magnetic resonance tomography (MRT) with cerebellum as the reference region. Binding potentials were estimated by fitting a simplified reference tissue model to the measured tissue-time activity curves. Target occupancy was expressed as percent change in the binding potentials before and after ITI-007 administration.

RESULTS

Oral ITI-007 (10-40 mg) was safe and well tolerated. ITI-007 rapidly entered the brain with long-lasting and dose-related occupancy. ITI-007 (10 mg) demonstrated high occupancy (>80 %) of cortical 5-HT2A receptors and low occupancy of striatal D2 receptors (~12 %). D2 receptor occupancy increased with dose and significantly correlated with plasma concentrations (r (2) = 0.68, p = 0.002). ITI-007 (40 mg) resulted in peak occupancy up to 39 % of striatal D2 receptors and 33 % of striatal serotonin transporters.

CONCLUSIONS

The results provide evidence for a central mechanism of action via dopaminergic and serotonergic pathways for ITI-007 in living human brain and valuable information to aid dose selection for future clinical trials.

Clustering-initiated factor analysis application for tissue classification in dynamic brain positron emission tomography

The goal is to quantify the fraction of tissues that exhibit specific tracer binding in dynamic brain positron emission tomography (PET). It is achieved using a new method of dynamic image processing: clustering-initiated factor analysis (CIFA). Standard processing of such data relies on region of interest analysis and approximate models of the tracer kinetics and of tissue properties, which can degrade accuracy and reproducibility of the analysis. Clustering-initiated factor analysis allows accurate determination of the time-activity curves and spatial distributions for tissues that exhibit significant radiotracer concentration at any stage of the emission scan, including the arterial input function. We used this approach in the analysis of PET images obtained using (11)C-Pittsburgh Compound B in which specific binding reflects the presence of β-amyloid. The fraction of the specific binding tissues determined using our approach correlated with that computed using the Logan graphical analysis. We believe that CIFA can be an accurate and convenient tool for measuring specific binding tissue concentration and for analyzing tracer kinetics from dynamic images for a variety of PET tracers. As an illustration, we show that four-factor CIFA allows extraction of two blood curves and the corresponding distributions of arterial and venous blood from PET images even with a coarse temporal resolution.

Quantification of [(11)C]yohimbine binding to α2 adrenoceptors in rat brain in vivo

We quantified the binding potentials (BPND) of [(11)C]yohimbine binding in rat brain to alpha-2 adrenoceptors to evaluate [(11)C]yohimbine as an in vivo marker of noradrenergic neurotransmission and to examine its sensitivity to the level of noradrenaline. Dual [(11)C]yohimbine dynamic positron emission tomography (PET) recordings were applied to five Sprague Dawley rats at baseline, followed by acute amphetamine administration (2 mg/kg) to induce elevation of the endogenous level of noradrenaline. The volume of distribution (VT) of [(11)C]yohimbine was obtained using Logan plot with arterial plasma input. Because alpha-2 adrenoceptors are distributed throughout the brain, the estimation of the BPND is complicated by the absence of an anatomic region of no displaceable binding. We used the Inhibition plot to acquire the reference volume, VND, from which we calculated the BPND. Acute pharmacological challenge with amphetamine induced a significant decline of [(11)C]yohimbine BPND of ~38% in all volumes of interest. The BPND was greatest in the thalamus and striatum, followed in descending order by, frontal cortex, pons, and cerebellum. The experimental data demonstrate that [(11)C]yohimbine binding is sensitive to a challenge known to increase the extracellular level of noradrenaline, which can benefit future PET investigations of pathologic conditions related to disrupted noradrenergic neurotransmission.

An update on novel quantitative techniques in the context of evolving whole-body PET imaging

Since its foundation PET has established itself as one of the standard imaging modalities enabling the quantitative assessment of molecular targets in vivo. In the past two decades, quantitative PET has become a necessity in clinical oncology. Despite introduction of various measures for quantification and correction of PET parameters, there is debate on the selection of the appropriate methodology in specific diseases and conditions. In this review, we have focused on these techniques with special attention to topics such as static and dynamic whole body PET imaging, tracer kinetic modeling, global disease burden, texture analysis and radiomics, dual time point imaging and partial volume correction.

Recent advances in parametric neuroreceptor mapping with dynamic PET: basic concepts and graphical analyses

Tracer kinetic modeling in dynamic positron emission tomography (PET) has been widely used to investigate the characteristic distribution patterns or dysfunctions of neuroreceptors in brain diseases. Its practical goal has progressed from regional data quantification to parametric mapping that produces images of kinetic-model parameters by fully exploiting the spatiotemporal information in dynamic PET data. Graphical analysis (GA) is a major parametric mapping technique that is independent on any compartmental model configuration, robust to noise, and computationally efficient. In this paper, we provide an overview of recent advances in the parametric mapping of neuroreceptor binding based on GA methods. The associated basic concepts in tracer kinetic modeling are presented, including commonly-used compartment models and major parameters of interest. Technical details of GA approaches for reversible and irreversible radioligands are described, considering both plasma input and reference tissue input models. Their statistical properties are discussed in view of parametric imaging.

Dynamic whole-body PET parametric imaging: I. Concept, acquisition protocol optimization and clinical application

Static whole-body PET/CT, employing the standardized uptake value (SUV), is considered the standard clinical approach to diagnosis and treatment response monitoring for a wide range of oncologic malignancies. Alternative PET protocols involving dynamic acquisition of temporal images have been implemented in the research setting, allowing quantification of tracer dynamics, an important capability for tumor characterization and treatment response monitoring. Nonetheless, dynamic protocols have been confined to single-bed-coverage limiting the axial field-of-view to ~15-20 cm, and have not been translated to the routine clinical context of whole-body PET imaging for the inspection of disseminated disease. Here, we pursue a transition to dynamic whole-body PET parametric imaging, by presenting, within a unified framework, clinically feasible multi-bed dynamic PET acquisition protocols and parametric imaging methods. We investigate solutions to address the challenges of: (i) long acquisitions, (ii) small number of dynamic frames per bed, and (iii) non-invasive quantification of kinetics in the plasma. In the present study, a novel dynamic (4D) whole-body PET acquisition protocol of ~45 min total length is presented, composed of (i) an initial 6 min dynamic PET scan (24 frames) over the heart, followed by (ii) a sequence of multi-pass multi-bed PET scans (six passes × seven bed positions, each scanned for 45 s). Standard Patlak linear graphical analysis modeling was employed, coupled with image-derived plasma input function measurements. Ordinary least squares Patlak estimation was used as the baseline regression method to quantify the physiological parameters of tracer uptake rate Ki and total blood distribution volume V on an individual voxel basis. Extensive Monte Carlo simulation studies, using a wide set of published kinetic FDG parameters and GATE and XCAT platforms, were conducted to optimize the acquisition protocol from a range of ten different clinically acceptable sampling schedules examined. The framework was also applied to six FDG PET patient studies, demonstrating clinical feasibility. Both simulated and clinical results indicated enhanced contrast-to-noise ratios (CNRs) for Ki images in tumor regions with notable background FDG concentration, such as the liver, where SUV performed relatively poorly. Overall, the proposed framework enables enhanced quantification of physiological parameters across the whole body. In addition, the total acquisition length can be reduced from 45 to ~35 min and still achieve improved or equivalent CNR compared to SUV, provided the true Ki contrast is sufficiently high. In the follow-up companion paper, a set of advanced linear regression schemes is presented to particularly address the presence of noise, and attempt to achieve a better trade-off between the mean-squared error and the CNR metrics, resulting in enhanced task-based imaging.

Dynamic whole-body PET parametric imaging: II. Task-oriented statistical estimation

In the context of oncology, dynamic PET imaging coupled with standard graphical linear analysis has been previously employed to enable quantitative estimation of tracer kinetic parameters of physiological interest at the voxel level, thus, enabling quantitative PET parametric imaging. However, dynamic PET acquisition protocols have been confined to the limited axial field-of-view (~15-20 cm) of a single-bed position and have not been translated to the whole-body clinical imaging domain. On the contrary, standardized uptake value (SUV) PET imaging, considered as the routine approach in clinical oncology, commonly involves multi-bed acquisitions, but is performed statically, thus not allowing for dynamic tracking of the tracer distribution. Here, we pursue a transition to dynamic whole-body PET parametric imaging, by presenting, within a unified framework, clinically feasible multi-bed dynamic PET acquisition protocols and parametric imaging methods. In a companion study, we presented a novel clinically feasible dynamic (4D) multi-bed PET acquisition protocol as well as the concept of whole-body PET parametric imaging employing Patlak ordinary least squares (OLS) regression to estimate the quantitative parameters of tracer uptake rate Ki and total blood distribution volume V. In the present study, we propose an advanced hybrid linear regression framework, driven by Patlak kinetic voxel correlations, to achieve superior trade-off between contrast-to-noise ratio (CNR) and mean squared error (MSE) than provided by OLS for the final Ki parametric images, enabling task-based performance optimization. Overall, whether the observer's task is to detect a tumor or quantitatively assess treatment response, the proposed statistical estimation framework can be adapted to satisfy the specific task performance criteria, by adjusting the Patlak correlation-coefficient (WR) reference value. The multi-bed dynamic acquisition protocol, as optimized in the preceding companion study, was employed along with extensive Monte Carlo simulations and an initial clinical (18)F-deoxyglucose patient dataset to validate and demonstrate the potential of the proposed statistical estimation methods. Both simulated and clinical results suggest that hybrid regression in the context of whole-body Patlak Ki imaging considerably reduces MSE without compromising high CNR. Alternatively, for a given CNR, hybrid regression enables larger reductions than OLS in the number of dynamic frames per bed, allowing for even shorter acquisitions of ~30 min, thus further contributing to the clinical adoption of the proposed framework. Compared to the SUV approach, whole-body parametric imaging can provide better tumor quantification, and can act as a complement to SUV, for the task of tumor detection.

PET imaging for receptor occupancy: meditations on calculation and simplification

This invited mini-review briefly summarizes procedures and challenges of measuring receptor occupancy with positron emission tomography. Instead of describing the detailed analytic procedures of in vivo ligand-receptor imaging, the authors provide a pragmatic approach, along with personal perspectives, for conducting positron emission tomography imaging for receptor occupancy, and systematically elucidate the mathematics of receptor occupancy calculations in practical ways that can be understood with elementary algebra. The authors also share insights regarding positron emission tomography imaging for receptor occupancy to facilitate applications for the development of drugs targeting receptors in the central nervous system.

Voxel-based imaging of translocator protein 18 kDa (TSPO) in high-resolution PET

In vivo imaging of translocator protein 18 kDa (TSPO) has received significant attention as potential biomarker of microglia activation. Several radioligands have been designed with improved properties. Our group recently developed an (18)F-labeled TSPO ligand, [(18)F]-FEPPA, and confirmed its reliability with a 2-tissue compartment model. Here, we extended, in a group of healthy subjects, its suitability for use in voxel-based analysis with the newly proposed graphical analysis approach, Relative-Equilibrium-Gjedde-Patlak (REGP) plot. The REGP plot successfully replicated the total distribution volumes estimated by the 2-tissue compartment model. We also showed its proof-of-concept in a patient with possible meningioma showing increased [(18)F]-FEPPA total distribution volume.

Glycine transporter type 1 occupancy by bitopertin: a positron emission tomography study in healthy volunteers

Deficient N-methyl-D-aspartate (NMDA) receptor transmission is thought to underlie schizophrenia. An approach for normalizing glutamate neurotransmission by enhancing NMDA receptor transmission is to increase glycine availability by inhibiting the glycine transporter type 1 (GlyT1). This study investigated the relationship between the plasma concentration of the glycine reuptake inhibitor bitopertin (RG1678) and brain GlyT1 occupancy. Healthy male volunteers received up to 175 mg bitopertin once daily, for 10-12 days. Three positron emission tomography scans, preceded by a single intravenous infusion of ∼30 mCi [(11)C]RO5013853, were performed: at baseline, on the last day of bitopertin treatment, and 2 days after drug discontinuation. Eighteen subjects were enrolled. At baseline, regional volume of distribution (V(T)) values were highest in the pons, thalamus, and cerebellum (1.7-2.7 ml/cm(3)) and lowest in cortical areas (∼0.8 ml/cm(3)). V(T) values were reduced to a homogeneous level following administration of 175 mg bitopertin. Occupancy values derived by a two-tissue five-parameter (2T5P) model, a simplified reference tissue model (SRTM), and a pseudoreference tissue model (PRTM) were overall comparable. At steady state, the relationship between bitopertin plasma concentration and GlyT1 occupancy derived by the 2T5P model, SRTM, and PRTM exhibited an EC(50) of ∼190, ∼200, and ∼130 ng/ml, respectively. E(max) was ∼92% independently of the model used. Bitopertin plasma concentration was a reliable predictor of occupancy because the concentration-occupancy relationship was superimposable at steady state and 2 days after drug discontinuation. These data allow understanding of the concentration-occupancy-efficacy relationship of bitopertin and support dose selection of future molecules.

(18)F-Deoxyglucose (FDG) kinetics evaluated by a non-compartment model based on a linear regression function using a computer based simulation: correlation with the parameters of the two-tissue compartment model

Parametric imaging with a linear regression function of the tracer activity curve fit is a non-compartmental method, which can be used for the evaluation of dynamic PET (dPET) studies. However, the dependency of the slope of the regression function fit on the (18)F-Deoxyglucose (FDG) 2-tissue compartment parameters (vb, k1-k4) is not known yet. This study is focused on the impact of the 2-tissue compartment parameters on the slope of the curve. A data base of 1760 dynamic PET FDG studies with the corresponding 2-tissue compartment model parameter solutions were available and used to calculate synthetic time-activity data based on the 2-tissue compartment model. The input curve was calculated from the median values of the input curves of the 1760 dynamic data sets. Then, sequentially each of the five parameters (vb, k1-k4) of the 2-tissue compartment model was varied from 0.1 to 0.9 and tracer activity curves were calculated (60000 curves/parameter). A linear regression function was fitted to these curves. The comparison of the slope values of the regression function with the corresponding compartment data revealed a primary dependency on k3, which is associated with the intracellular phosphorylation of FDG. The squared correlation coefficient was high with r(2)=0.9716, which refers to 97 % explained variance of the data. k2 and vb had only a minor impact, while k1 and k4 had no impact on the slope values. The results demonstrate, that k3 has a major impact on the slope values calculated by the linear regression function.

Kinetic parameter estimation using a closed-form expression via integration by parts

Dynamic emission computed tomographic imaging with compartment modeling can quantify in vivo physiologic processes, eliciting more information regarding underlying molecular disease processes than is obtained from static imaging. However, estimation of kinetic rate parameters for multi-compartment models can be computationally demanding and problematic due to local minima. A number of techniques for kinetic parameter estimation have been studied and are in use today, generally offering a tradeoff between computation time, robustness of fit and flexibility with differing sets of assumptions. This paper presents a means to eliminate all differential operations by using the integration-by-parts method to provide closed-form formulas, so that the mathematical model is less sensitive to data sampling and noise. A family of closed-form formulas are obtained. Computer simulations show that the proposed method is robust without having to specify the initial condition.

Quantitative analysis and comparison study of [18F]AlF-NOTA-PRGD2, [18F]FPPRGD2 and [68Ga]Ga-NOTA-PRGD2 using a reference tissue model

With favorable pharmacokinetics and binding affinity for α_vβ₃ integrin, ¹⁸F-labeled dimeric cyclic RGD peptide ([¹⁸F]FPPRGD2) has been intensively used as a PET imaging probe for lesion detection and therapy response monitoring. A recently introduced kit formulation method, which uses an ¹⁸F-fluoride-aluminum complex labeled RGD tracer ([¹⁸F]AlF-NOTA-PRGD2), provides a strategy for simplifying the labeling procedure to facilitate clinical translation. Meanwhile, an easy-to-prepare ⁶⁸Ga-labeled NOTA-PRGD2 has also been reported to have promising properties for imaging integrin α_vβ₃. The purpose of this study is to quantitatively compare the pharmacokinetic parameters of [¹⁸F]FPPRGD2, [¹⁸F]AlF-NOTA-PRGD2, and [⁶⁸Ga]Ga-NOTA-PRGD2. U87MG tumor-bearing mice underwent 60-min dynamic PET scans following the injection of three tracers. Kinetic parameters were calculated using Logan graphical analysis with reference tissue. Parametric maps were generated using voxel-level modeling. All three compounds showed high binding potential (Bp_ND = k₃/k₄) in tumor voxels. [¹⁸F]AlF-NOTA-PRGD2 showed comparable Bp_ND value (3.75±0.65) with those of [¹⁸F]FPPRGD2 (3.39±0.84) and [⁶⁸Ga]Ga-NOTA-PRGD2 (3.09±0.21) (p>0.05). Little difference was found in volume of distribution (V_T) among these three RGD tracers in tumor, liver and muscle. Parametric maps showed similar kinetic parameters for all three tracers. We also demonstrated that the impact of non-specific binding could be eliminated in the kinetic analysis. Consequently, kinetic parameter estimation showed more comparable results among groups than static image analysis. In conclusion, [¹⁸F]AlF-NOTA-PRGD2 and [⁶⁸Ga]Ga-NOTA-PRGD2 have comparable pharmacokinetics and quantitative parameters compared to those of [¹⁸F]FPPRGD2. Despite the apparent difference in tumor uptake (%ID/g determined from static images) and clearance pattern, the actual specific binding component extrapolated from kinetic modeling appears to be comparable for all three dimeric RGD tracers.

Direct 4D parametric imaging for linearized models of reversibly binding PET tracers using generalized AB-EM reconstruction

Due to high noise levels in the voxel kinetics, development of reliable parametric imaging algorithms remains one of most active areas in dynamic brain PET imaging, which in the vast majority of cases involves receptor/transporter studies with reversibly binding tracers. As such, the focus of this work has been to develop a novel direct 4D parametric image reconstruction scheme for such tracers. Based on a relative equilibrium (RE) graphical analysis formulation (Zhou et al 2009b Neuroimage 44 661-70), we developed a closed-form 4D EM algorithm to directly reconstruct distribution volume (DV) parametric images within a plasma input model, as well as DV ratio (DVR) images within a reference tissue model scheme (wherein an initial reconstruction was used to estimate the reference tissue time-activity curves). A particular challenge with the direct 4D EM formulation is that the intercept parameters in graphical (linearized) analysis of reversible tracers (e.g. Logan or RE analysis) are commonly negative (unlike for irreversible tracers, e.g. using Patlak analysis). Subsequently, we focused our attention on the AB-EM algorithm, derived by Byrne (1998, Inverse Problems 14 1455-67) to allow inclusion of prior information about the lower (A) and upper (B) bounds for image values. We then generalized this algorithm to the 4D EM framework, thus allowing negative intercept parameters. Furthermore, our 4D AB-EM algorithm incorporated and emphasized the use of spatially varying lower bounds to achieve enhanced performance. As validation, the means of parameters estimated from 55 human (11)C-raclopride dynamic PET studies were used for extensive simulations using a mathematical brain phantom. Images were reconstructed using conventional indirect as well as proposed direct parametric imaging methods. Noise versus bias quantitative measurements were performed in various regions of the brain. Direct 4D EM reconstruction resulted in notable qualitative and quantitative accuracy improvements (over 35% noise reduction, with matched bias, in both plasma and reference-tissue input models). Similar improvements were also observed in the coefficient of variation of the estimated DV and DVR values even for relatively low uptake cortical regions, suggesting the enhanced ability for robust parameter estimation. The method was also tested on a 90 min (11)C-raclopride patient study performed on the high-resolution research tomograph wherein the proposed method was shown across a variety of regions to outperform the conventional method in the sense that for a given DVR value, improved noise levels were observed.

Comparative evaluation of Logan and relative-equilibrium graphical methods for parametric imaging of dynamic [18F]FDDNP PET determinations

Logan graphical analysis with cerebellum as reference region has been widely used for the estimation of the distribution volume ratio (DVR) of [(18)F]FDDNP as a measure of amyloid burden and tau deposition in human brain because of its simplicity and computational ease. However, spurious parametric DVR images may be produced with shorter scanning times and when the noise level is high. In this work, we have characterized a relative-equilibrium-based (RE) graphical method against the Logan analysis for parametric imaging and region-of-interest (ROI) analysis.

METHODS

Dynamic [(18)F]FDDNP PET scans were performed on 9 control subjects and 12 patients diagnosed with Alzheimer's disease. Using the cerebellum as reference input, regional DVR estimates were derived using both the Logan analysis and the RE plot approach. Effects on DVR estimates obtained at voxel and ROI levels by both graphical approaches using data in different time windows were investigated and compared with the standard values derived using the Logan analysis on a voxel-by-voxel basis for the time window of 35-125 min used in previous studies.

RESULTS

Larger bias and variability were observed for DVR estimates obtained by the Logan graphical analysis at the voxel level when short time windows (85-125 and 45-65 min) were used, because of high noise levels in voxel-wise parametric imaging. However, when the Logan graphical analysis was applied at the ROI level over those short time windows, the DVR estimates did not differ significantly from the standard values derived using the Logan analysis on the voxel level for the time window of 35-125 min, and their bias and variability were remarkably lower. Conversely, the RE plot approach was more robust in providing DVR estimates with less bias and variability even when short time windows were used. The DVR estimates obtained at voxel and ROI levels were consistent. No significant differences were observed in DVR estimates obtained by the RE plot approach for all paired comparisons with the standard values.

CONCLUSIONS

The RE plot approach provides less noisy parametric images and gives consistent and reliable regional DVR estimates at both voxel and ROI levels, indicating that it is preferred over the Logan graphical analysis for analyzing [(18)F]FDDNP PET data.

Characterization of [11C]RO5013853, a novel PET tracer for the glycine transporter type 1 (GlyT1) in humans

We characterize a novel radioligand for the glycine transporter type 1 (GlyT1), [(11)C]RO5013853, in humans. Ten healthy male volunteers, 23-60 years of age, were enrolled in this PET study; seven subjects participated in the evaluation of test-retest reliability and three subjects in whole body dosimetry. Subjects were administered intravenous bolus injections of approximately 1100 MBq (30 mCi) [(11)C]RO5013853 with a high specific activity of about 481 GBq (13 Ci)/μmol. Standard compartmental model analysis with arterial plasma input function, and an alternative noninvasive analysis method which was evaluated and validated by occupancy studies in both baboons and humans, were performed. Mean parameter estimates of the volumes of distribution (VT) obtained by a 2-tissue 5-parameter model were higher in the cerebellum, pons, and thalamus (1.99 to 2.59 mL/mL), and lower in the putamen, caudate, and cortical areas (0.86 to 1.13 mL/mL), with estimates showing less than 10% difference between test and retest scans. Tracer retention was effectively blocked by the specific glycine reuptake inhibitor (GRI), bitopertin (RG1678). [(11)C]RO5013853 was safe and well tolerated. Human dosimetry studies showed that the effective dose was approximately 0.0033 mSv/MBq, with the liver receiving the highest absorbed dose. In conclusion, quantitative dynamic PET of the human brain after intravenous injection of [(11)C]RO5013853 attains reliable measurements of GlyT1 binding in accordance with the expected transporter distribution in the human brain. [(11)C]RO5013853 is a radioligand suitable for further clinical PET studies. Full characterization of a novel radiotracer for GlyT1 in humans is provided. The tracer has subsequently been used to assess receptor occupancy in healthy volunteers and to estimate occupancy at doses associated with best efficacy in a clinical trial with schizophrenic patients with predominantly negative symptoms.

Reference tissue modeling with parameter coupling: application to a study of SERT binding in HIV

When applicable, it is generally preferred to evaluate positron emission tomography (PET) studies using a reference tissue-based approach as that avoids the need for invasive arterial blood sampling. However, most reference tissue methods have been shown to have a bias that is dependent on the level of tracer binding, and the variability of parameter estimates may be substantially affected by noise level. In a study of serotonin transporter (SERT) binding in HIV dementia, it was determined that applying parameter coupling to the simplified reference tissue model (SRTM) reduced the variability of parameter estimates and yielded the strongest between-group significant differences in SERT binding. The use of parameter coupling makes the application of SRTM more consistent with conventional blood input models and reduces the total number of fitted parameters, thus should yield more robust parameter estimates. Here, we provide a detailed evaluation of the application of parameter constraint and parameter coupling to [(11)C]DASB PET studies. Five quantitative methods, including three methods that constrain the reference tissue clearance (k(r)(2)) to a common value across regions were applied to the clinical and simulated data to compare measurement of the tracer binding potential (BP(ND)). Compared with standard SRTM, either coupling of k(r)(2) across regions or constraining k(r)(2) to a first-pass estimate improved the sensitivity of SRTM to measuring a significant difference in BP(ND) between patients and controls. Parameter coupling was particularly effective in reducing the variance of parameter estimates, which was less than 50% of the variance obtained with standard SRTM. A linear approach was also improved when constraining k(r)(2) to a first-pass estimate, although the SRTM-based methods yielded stronger significant differences when applied to the clinical study. This work shows that parameter coupling reduces the variance of parameter estimates and may better discriminate between-group differences in specific binding.

An analysis tool to calculate permeability based on the Patlak method

Strokes are commonly diagnosed by utilizing images obtained from magnetic resonance imaging (MRI) technology. Nowadays, computer software can play a large role in analyzing these images and arriving at diagnoses quickly and accurately. Additionally, this software can reduce workload for medical personnel and lower misdiagnoses. In this paper a flexible permeability calculation tool called PCT based on the Patlak plot method is presented. Using the PCT we can calculate the permeability co-efficient of the Blood-Brain Barrier (BBB) function. The PCT tool offers both manual and automatic options for diagnosing the regions of the brain affected by stroke. Moreover, the PCT tool supports various extensions such as dicom, nifty and analyze.