Signal separation of simultaneous dual-tracer PET imaging based on global spatial information and channel attention.

BACKGROUND: Simultaneous dual-tracer positron emission tomography (PET) imaging efficiently provides more complete information for disease diagnosis. The signal separation has long been a challenge of dual-tracer PET imaging. To predict the single-tracer images, we proposed a separation network based on global spatial information and channel attention, and connected it to FBP-Net to form the FBPnet-Sep model. RESULTS: Experiments using simulated dynamic PET data were conducted to: (1) compare the proposed FBPnet-Sep model to Sep-FBPnet model and currently existing Multi-task CNN, (2) verify the effectiveness of modules incorporated in FBPnet-Sep model, (3) investigate the generalization of FBPnet-Sep model to low-dose data, and (4) investigate the application of FBPnet-Sep model to multiple tracer combinations with decay corrections. Compared to the Sep-FBPnet model and Multi-task CNN, the FBPnet-Sep model reconstructed single-tracer images with higher structural similarity, peak signal-to-noise ratio and lower mean squared error, and reconstructed time-activity curves with lower bias and variation in most regions. Excluding the Inception or channel attention module resulted in degraded image qualities. The FBPnet-Sep model showed acceptable performance when applied to low-dose data. Additionally, it could deal with multiple tracer combinations. The qualities of predicted images, as well as the accuracy of derived time-activity curves and macro-parameters were slightly improved by incorporating a decay correction module. CONCLUSIONS: The proposed FBPnet-Sep model was considered a potential method for the reconstruction and signal separation of simultaneous dual-tracer PET imaging.

Pyrolysis temperature dependent effects of biochar on shifting fluorescence spectrum characteristics of soil dissolved organic matter under warming.

Biochar generally shift the content and molecular composition of soil dissolved organic matter (DOM) which represent the reactive components and have essential roles in coupling elemental cycling in soil. However, it is not clear how the effects of biochar on soil DOM composition is shifted under warming. This causes a knowledge gap to fully understand the fate of SOM affected by biochar application in a warming climate. To fill this gap, we conducted a simulated climate warming incubation of soil to study the influence of biochar with different pyrolysis temperatures and feedstock types on soil DOM components composition. Three-dimensional fluorescence spectrum analysis combining excitation emission matrix-parallel factor analysis (EEM-PARAFAC), fluorescence region integral (FRI), UV-vis spectrometry, principal component analysis (PCA), clustering analysis, Pearson correlation and multi-factor analysis of variance on fluorescence parameters (including FRI on Region I-V, FI, HIX, BIX, H/P) and soil DOC and DON content were analyzed for this purpose. Results showed that biochar shifted soil DOM composition and enhanced soil humification, which was dominantly pyrolysis-temperature dependent. Biochar shifted the soil DOM components composition probably through mediating soil microbial processing rather than direct input of their pristine DOM, and the influence of biochar on soil microbial processing was pyrolysis-temperature dependent and highly affected by warming. Medium-temperature biochar was more efficient for enhancing soil humification, by accelerating the transformation of protein-like components into humic-like components. Soil DOM composition presented a rapid response to warming, and long-term incubation may eliminate the effects of warming on shifting soil DOM composition. By revealing the heterogeneous effects of biochar with different pyrolysis temperatures on fluorescence characteristics of soil DOM components, our study provides a hint for the essential role of biochar on enhancing soil humification, and also suggests a vulnerability of biochar for soil carbon sequestration under warming.

Direct reconstruction for simultaneous dual-tracer PET imaging based on multi-task learning.

BACKGROUND: Simultaneous dual-tracer positron emission tomography (PET) imaging can observe two molecular targets in a single scan, which is conducive to disease diagnosis and tracking. Since the signals emitted by different tracers are the same, it is crucial to separate each single tracer from the mixed signals. The current study proposed a novel deep learning-based method to reconstruct single-tracer activity distributions from the dual-tracer sinogram. METHODS: We proposed the Multi-task CNN, a three-dimensional convolutional neural network (CNN) based on a framework of multi-task learning. One common encoder extracted features from the dual-tracer dynamic sinogram, followed by two distinct and parallel decoders which reconstructed the single-tracer dynamic images of two tracers separately. The model was evaluated by mean squared error (MSE), multiscale structural similarity (MS-SSIM) index and peak signal-to-noise ratio (PSNR) on simulated data and real animal data, and compared to the filtered back-projection method based on deep learning (FBP-CNN). RESULTS: In the simulation experiments, the Multi-task CNN reconstructed single-tracer images with lower MSE, higher MS-SSIM and PSNR than FBP-CNN, and was more robust to the changes in individual difference, tracer combination and scanning protocol. In the experiment of rats with an orthotopic xenograft glioma model, the Multi-task CNN reconstructions also showed higher qualities than FBP-CNN reconstructions. CONCLUSIONS: The proposed Multi-task CNN could effectively reconstruct the dynamic activity images of two single tracers from the dual-tracer dynamic sinogram, which was potential in the direct reconstruction for real simultaneous dual-tracer PET imaging data in future.

Imaging mitochondrial complex I activation during a vibrotactile stimulation: A PET study using [18F]BCPP-EF in the conscious monkey brain.

In order to evaluate the capability of 2-tert-butyl-4-chloro-5-{6-[2-(2-[18F]fluoroethoxy)-ethoxy]-pyridin-3-ylmethoxy}-2H-pyridazin-3-one ([18F]BCPP-EF), a novel positron emission tomography (PET) probe for mitochondrial complex I (MC-I) activity, to assess neuronal activation, an activation PET study was conducted in the conscious monkey brain with a continuous unilateral vibrotactile stimulation. PET scans with [15O]H2O, [18F]BCPP-EF, or 2-deoxy-2-[18F]fluoroglucose ([18F]FDG) were conducted under: (1) resting conditions; (2) a continuous vibration stimulation; (3) a continuous vibration stimulation after 15-min pre-vibration; and (4) a continuous vibration stimulation after 30-min pre-vibration. The contralateral/ipsilateral ratio (CIR) in the somatosensory cortex showed significant increases in the uptake of [15O]H2O, [18F]BCPP-EF, and [18F]FDG with the vibration stimulation. The longer pre-vibration duration induced significantly lower CIR in regional cerebral blood flow (rCBF) measured using [15O]H2O, whereas it did not affect the CIR in [18F]BCPP-EF or the regional cerebral metabolic rate of glucose (rCMRglc) measured using [18F]FDG 30-60 min after the injection. These results suggest that the [18F]BCPP-EF response in the later phase of scans was not influenced by the increase in rCBF, indicating the capability of [18F]BCPP-EF to detect acute changes in MC-I activity induced by neuronal activation. However, the metabolic shift from glycolysis to oxidation was not observed under the stimulation used here.