Non-stationary convolution subtraction scatter correction with a dual-exponential scatter kernel for the Hamamatsu SHR-7700 animal PET scanner

Fully 3D implementation of the end-to-end deep image prior-based PET image reconstruction using block iterative algorithm

Objective. Deep image prior (DIP) has recently attracted attention owing to its unsupervised positron emission tomography (PET) image reconstruction method, which does not require any prior training dataset. In this paper, we present the first attempt to implement an end-to-end DIP-based fully 3D PET image reconstruction method that incorporates a forward-projection model into a loss function.Approach. A practical implementation of a fully 3D PET image reconstruction could not be performed at present because of a graphics processing unit memory limitation. Consequently, we modify the DIP optimization to a block iteration and sequential learning of an ordered sequence of block sinograms. Furthermore, the relative difference penalty (RDP) term is added to the loss function to enhance the quantitative accuracy of the PET image.Main results. We evaluated our proposed method using Monte Carlo simulation with [18F]FDG PET data of a human brain and a preclinical study on monkey-brain [18F]FDG PET data. The proposed method was compared with the maximum-likelihood expectation maximization (EM), maximuma posterioriEM with RDP, and hybrid DIP-based PET reconstruction methods. The simulation results showed that, compared with other algorithms, the proposed method improved the PET image quality by reducing statistical noise and better preserved the contrast of brain structures and inserted tumors. In the preclinical experiment, finer structures and better contrast recovery were obtained with the proposed method.Significance.The results indicated that the proposed method could produce high-quality images without a prior training dataset. Thus, the proposed method could be a key enabling technology for the straightforward and practical implementation of end-to-end DIP-based fully 3D PET image reconstruction.

Advances in multimodal data fusion in neuroimaging: Overview, challenges, and novel orientation

Multimodal fusion in neuroimaging combines data from multiple imaging modalities to overcome the fundamental limitations of individual modalities. Neuroimaging fusion can achieve higher temporal and spatial resolution, enhance contrast, correct imaging distortions, and bridge physiological and cognitive information. In this study, we analyzed over 450 references from PubMed, Google Scholar, IEEE, ScienceDirect, Web of Science, and various sources published from 1978 to 2020. We provide a review that encompasses (1) an overview of current challenges in multimodal fusion (2) the current medical applications of fusion for specific neurological diseases, (3) strengths and limitations of available imaging modalities, (4) fundamental fusion rules, (5) fusion quality assessment methods, and (6) the applications of fusion for atlas-based segmentation and quantification. Overall, multimodal fusion shows significant benefits in clinical diagnosis and neuroscience research. Widespread education and further research amongst engineers, researchers and clinicians will benefit the field of multimodal neuroimaging.

Validation of a simplified scatter correction method for 3D brain PET with 15O

Objective

Positron emission tomography (PET) enables quantitative measurements of various biological functions. Accuracy in data acquisition and processing schemes is a prerequisite for this. The correction of scatter is especially important when a 3D PET scanner is used. The aim of this study was to validate the use of a simplified calculation-based scatter correction method for ¹⁵O studies in the brain.

Methods

We applied two scatter correction methods to the same ¹⁵O PET data acquired from patients with cerebrovascular disease (n = 10): a hybrid dual-energy-window scatter correction (reference method), and a deconvolution scatter correction (simplified method). The PET study included three sequential scans for ¹⁵O-CO, ¹⁵O-O₂, and ¹⁵O-H₂O, from which the following quantitative parameters were calculated, cerebral blood flow, cerebral blood volume, cerebral metabolic rate of oxygen, and oxygen extraction fraction.

Results

Both scatter correction methods provided similar reconstruction images with almost identical image noise, although there were slightly greater differences in white-matter regions compared with gray matter regions. These differences were also greater for ¹⁵O-CO than for ¹⁵O-H₂O and ¹⁵O-O₂. Region of interest analysis of the quantitative parameters demonstrated that the differences were less than 10 % (except for cerebral blood volume in white-matter regions), and the agreement between the methods was excellent, with intraclass correlation coefficients above 0.95 for all the parameters.

Conclusions

The deconvolution scatter correction despite its simplified implementation provided similar results to the hybrid dual-energy-window scatter correction. We consider it suitable for application in a clinical ¹⁵O brain study using a 3D PET scanner.

[(11)C]UCB-A, a novel PET tracer for synaptic vesicle protein 2A

INTRODUCTION

Development of a selective and specific high affinity PET tracer, [(11)C]UCB-A, for the in vivo study of SV2A expression in humans. Radiochemistry and preclinical studies in rats and pigs including development of a tracer kinetic model to determine VT. A method for the measurement of percent intact tracer in plasma was developed and the radiation dosimetry was determined in rats.

RESULTS

3-5GBq of [(11)C]UCB-A could be produced with radiochemical purity exceeding 98% with a specific radioactivity of around 65GBq/μmol. In vitro binding showed high selective binding towards SV2A. [(11)C]UCB-A displayed a dose-dependent and reversible binding to SV2A as measured with PET in rats and pigs and the VT could be determined by Logan analysis. The dosimetry was favorable and low enough to allow multiple administrations of [(11)C]UCB-A to healthy volunteers, and the metabolite analysis showed no sign of labeled metabolites in brain.

CONCLUSIONS

We have developed the novel PET tracer, [(11)C]UCB-A, that can be used to measure SV2A expression in vivo. The dosimetry allows up to 5 administrations of 400MBq of [(11)C]UCB-A in humans. Apart from measuring drug occupancy, as we have shown, the tracer can potentially be used to compare SV2A expression between individuals because of the rather narrow range of baseline VT values. This will have to be further validated in human studies.

Simultaneous attenuation and scatter corrections from the projections in small animal PET imaging

Attenuation and scatter corrections are important in quantitative positron emission tomography (PET) imaging even in small animals such as mice and rats. In this work we describe a simple and efficient model to correct for both scatter and attenuation in a single operation. The model aims to solve the equation M=(A+F) P for the primaries P, corrected for attenuation and scatter, based on the measured coincidences M, the matrix of compensation for attenuation A and on the scatter fractions F issued from all emitting sources and contributing to M. The scatter functions are analytically calculated using Klein-Nishina formula, the scanner geometry and the detection efficiencies. This method was applied in measured data of line sources and hot spots phantoms as well as in rat heart and tumors and compared to Monte Carlo based simulations and to the single scatter simulation model developed by Watson et al. The corrected data showed a quantitative contrast and signal to noise ratio enhancement with respect to the uncorrected data. In terms of results, our method is comparable to that of Watson et al. The Monte Carlo simulations, where the primaries and the scattered events were separately registered, confirmed the accuracy of the new approach.

Simultaneous attenuation and scatter corrections in small animal PET imaging

The aim of this work is to simultaneously correct for attenuation and scatter in PET by analytically assessing the distribution of the scattered photons using the emission and the transmission images, the probability of scatter interactions and the detection efficiency. Above the usual lower energy threshold of 350 keV, the attenuated photons are dominantly those which have undergone a Compton scattering. By considering that each pixel in the image is the measurement of the transmitted photons through the subject, added to the contribution from the other sources by means of their scatter at this position, a simple equation is established accounting for the primaries by simultaneously correcting the data for attenuation and scatter for all emitting sources. This new method was applied in Monte Carlo simulated and measured data with the Sherbrooke small animal PET scanner in line sources, hot spot phantoms, and in rat hearts and tumors, and was compared to the approach developed by Watson et al.