PET Parametric Imaging Improved by Global-Two-Stage Method

PET Imaging of Dopamine Neurotransmission During EEG Neurofeedback

Neurofeedback (NFB) is a brain-based training method that enables users to control their own cortical oscillations using real-time feedback from the electroencephalogram (EEG). Importantly, no investigations to date have directly explored the potential impact of NFB on the brain's key neuromodulatory systems. Our study's objective was to assess the capacity of NFB to induce dopamine release as revealed by positron emission tomography (PET). Thirty-two healthy volunteers were randomized to either EEG-neurofeedback (NFB) or EEG-electromyography (EMG), and scanned while performing self-regulation during a single session of dynamic PET brain imaging using the high affinity D2/3 receptor radiotracer, [18F]Fallypride. NFB and EMG groups down-regulated cortical alpha power and facial muscle tone, respectively. Task-induced effects on endogenous dopamine release were estimated in the frontal cortex, anterior cingulate cortex, and thalamus, using the linearized simplified reference region model (LSRRM), which accounts for time-dependent changes in radiotracer binding following task initiation. Contrary to our hypothesis of a differential effect for NFB vs. EMG training, significant dopamine release was observed in both training groups in the frontal and anterior cingulate cortex, but not in thalamus. Interestingly, a significant negative correlation was observed between dopamine release in frontal cortex and pre-to-post NFB change in spontaneous alpha power, suggesting that intra-individual changes in brain state (i.e., alpha power) could partly result from changes in neuromodulatory tone. Overall, our findings constitute the first direct investigation of neurofeedback's effect on the endogenous release of a key neuromodulator, demonstrating its feasibility and paving the way for future studies using this methodology.

Dynamic image denoising for voxel-wise quantification with Statistical Parametric Mapping in molecular neuroimaging

Purpose

PET and SPECT voxel kinetics are highly noised. To our knowledge, no study has determined the effect of denoising on the ability to detect differences in binding at the voxel level using Statistical Parametric Mapping (SPM).

Methods

In the present study, groups of subject-images with a 10%- and 20%- difference in binding of [¹²³I]iomazenil (IMZ) were simulated. They were denoised with Factor Analysis (FA). Parametric images of binding potential (BP_ND) were produced with the simplified reference tissue model (SRTM) and the Logan non-invasive graphical analysis (LNIGA) and analyzed using SPM to detect group differences. FA was also applied to [¹²³I]IMZ and [¹¹C]flumazenil (FMZ) clinical images (n = 4) and the variance of BP_ND was evaluated.

Results

Estimations from FA-denoised simulated images provided a more favorable bias-precision profile in SRTM and LNIGA quantification. Simulated differences were detected in a higher number of voxels when denoised simulated images were used for voxel-wise estimations, compared to quantification on raw simulated images. Variability of voxel-wise binding estimations on denoised clinical SPECT and PET images was also significantly diminished.

Conclusion

In conclusion, noise removal from dynamic brain SPECT and PET images may optimize voxel-wise BP_ND estimations and detection of biological differences using SPM.

Multi-Scale hierarchical generation of PET parametric maps: application and testing on a [11C]DPN study

We propose a general approach to generate parametric maps. It consists in a multi-stage hierarchical scheme where, starting from the kinetic analysis of the whole brain, we then cascade the kinetic information to anatomical systems that are akin in terms of receptor densities, and then down to the voxel level. A-priori classes of voxels are generated either by anatomical atlas segmentation or by functional segmentation using unsupervised clustering. Kinetic properties are transmitted to the voxels in each class using maximum a posteriori (MAP) estimation method. We validate the novel method on a [11C]diprenorphine (DPN) test-retest data-set that represents a challenge to estimation given [11C]DPN's slow equilibration in tissue. The estimated parametric maps of volume of distribution (VT) reflect the opioid receptor distributions known from previous [11C]DPN studies. When priors are derived from the anatomical atlas, there is an excellent agreement and strong correlation among voxel MAP and ROI results and excellent test-retest reliability for all subjects but one. Voxel level results did not change when priors were defined through unsupervised clustering. This new method is fast (i.e. 15 min per subject) and applied to [11C]DPN data achieves accurate quantification of VT as well as high quality VT images. Moreover, the way the priors are defined (i.e. using an anatomical atlas or unsupervised clustering) does not affect the estimates.

Contrast-enhanced ultrasonic parametric perfusion imaging in the evaluation of antiangiogenic tumor treatment

PURPOSE

To assess the validity of contrast-enhanced ultrasonic parametric perfusion imaging in the evaluation of antiangiogenic tumor treatment by using histology as the reference standard.

MATERIALS AND METHODS

H22 hepatoma-bearing mice were treated with thalidomide or placebo by intraperitoneal injection. Contrast-enhanced ultrasound was performed on day 8 after bolus injection of SonoVue. Three different parametric perfusion images were calculated based on the following parameters: area under the curve (AUC), maximum intensity (IMAX) and perfusion index (PI). A score from 1 to 5 (1 = low, 5 = excellent) was used for analysis of parametric perfusion images by two independent readers. Immunohistochemical analysis was performed for evaluation of microvascular density (MVD).

RESULTS

Treatment with thalidomide resulted in a significant decrease in perfusion scores assigned to AUC, IMAX and PI parametric images as compared with control tumors (P < 0.001). Immunohistochemistry showed significant decreases of MVD in treated tumors as compared with control tumors (P = 0.002). MVD was positively correlated with the perfusion scores assigned to AUC parametric images (r = 0.568, P = 0.009), IMAX parametric images (r = 0.614, P = 0.004) and PI parametric images (r = 0.636, P = 0.003).

CONCLUSION

Contrast-enhanced ultrasonic parametric perfusion imaging provides a noninvasive tool to directly visualize tumor perfusion changes after antiangiogenic tumor treatment.

Global-two-stage filtering of clinical PET parametric maps: application to [(11)C]-(R)-PK11195

INTRODUCTION

In Positron Emission Tomography (PET) quantification of physiological parameters at the voxel level may result in unreliable estimates due to the high noise of voxel time activity curves. Global-Two-Stage (GTS), an estimation technique belonging to the group of "population approaches", can be used to tackle this problem. GTS was previously tested on simulated PET data and yielded substantial improvements when compared to standard estimation approaches such as Weighted NonLinear Least Squares (WNLLS) and Basis Function Method (BFM). In this work GTS performance is assessed in a clinical context using the neuroinflammation marker [(11)C]-(R)-PK11195 applied to a cohort of Huntington's disease (HD) patients with and without symptoms.

MATERIALS AND METHODS

Parametric maps of binding potential (BP(ND)) of 12 normal controls (NC), 9 symptomatic and 9 presymptomatic HD patients were generated by applying a modified reference tissue model that accounts for tracer vascular activity in both reference and target tissues (SRTMV). GTS was then applied to SRTMV maps and its performance compared with that of SRTMV. Three smoothed versions of SRTMV, obtained by filtering the original SRTMV maps with Gaussian filters of 3 mm, 5 mm and 7 mm Full Width Half Maximum (FWHM), were also included in the comparison. Since striatal degeneration is the hallmark of HD, sensitivity was assessed for all methods by computing the mean of z-scores in caudate, putamen and globus pallidus in the voxel-by-voxel statistical comparison of BP(ND) between HD and NC.

RESULTS

Application of GTS to parametric maps brought a substantial qualitative improvement to SRTMV maps to the extent that anatomical structures often became visible. In addition, most parameter estimates that were outside the physiological range with SRTMV were corrected by GTS. GTS yielded a 2.3-fold increase in sensitivity with respect to SRTMV for the symptomatic cohort (mean of striatal z-scores of 0.76 for SRTMV and 1.79 for GTS) and an even more substantial increase for the presymptomatic cohort (mean of striatal z-scores of 0.34 for SRTMV and 0.96 for GTS). The sensitivity of GTS was similar to the one obtained with a filter of 7 mm FWHM applied to the initial SRTMV maps but GTS images were not characterized by the notable loss of resolution typical of smoothed maps. GTS, additionally, does not require to change/define settings according to the tracer and level of noise, whereas the choice of the FWHM value of the Gaussian filter normally employed in the smoothing procedure is typically arbitrary.

CONCLUSIONS

GTS is a powerful and robust tool for improving the quality of parametric maps in PET. The method is particularly appealing in that it can be applied to any tracer and estimation method, provided that initial estimates of the parameter vector and of its covariance are available. Although the benefits of GTS are far from being exhaustively assessed, the significant improvements obtained both on real and simulated data suggest that it could become an important tool for dynamic PET in the future.