Purpose
Our goal was to use a generative adversarial network (GAN) with feature matching and task‐specific perceptual loss to synthesize standard‐dose amyloid Positron emission tomography (PET) ...images of high quality and including accurate pathological features from ultra‐low‐dose PET images only.
Methods
Forty PET datasets from 39 participants were acquired with a simultaneous PET/MRI scanner following injection of 330 ± 30 MBq of the amyloid radiotracer 18F‐florbetaben. The raw list‐mode PET data were reconstructed as the standard‐dose ground truth and were randomly undersampled by a factor of 100 to reconstruct 1% low‐dose PET scans. A 2D encoder‐decoder network was implemented as the generator to synthesize a standard‐dose image and a discriminator was used to evaluate them. The two networks contested with each other to achieve high‐visual quality PET from the ultra‐low‐dose PET. Multi‐slice inputs were used to reduce noise by providing the network with 2.5D information. Feature matching was applied to reduce hallucinated structures. Task‐specific perceptual loss was designed to maintain the correct pathological features. The image quality was evaluated by peak signal‐to‐noise ratio (PSNR), structural similarity (SSIM), and root mean square error (RMSE) metrics with and without each of these modules. Two expert radiologists were asked to score image quality on a 5‐point scale and identified the amyloid status (positive or negative).
Results
With only low‐dose PET as input, the proposed method significantly outperformed Chen et al.'s method (Chen et al. Radiology. 2018;290:649–656) (which shows the best performance in this task) with the same input (PET‐only model) by 1.87 dB in PSNR, 2.04% in SSIM, and 24.75% in RMSE. It also achieved comparable results to Chen et al.'s method which used additional magnetic resonance imaging (MRI) inputs (PET‐MR model). Experts' reading results showed that the proposed method could achieve better overall image quality and maintain better pathological features indicating amyloid status than both PET‐only and PET‐MR models proposed by Chen et al.
Conclusion
Standard‐dose amyloid PET images can be synthesized from ultra‐low‐dose images using GAN. Applying adversarial learning, feature matching, and task‐specific perceptual loss are essential to ensure image quality and the preservation of pathological features.
siRNA therapeutics have promise for the treatment of a wide range of genetic disorders. Motivated by lipoproteins, we report lipopeptide nanoparticles as potent and selective siRNA carriers with a ...wide therapeutic index. Lead material cKK-E12 showed potent silencing effects in mice (ED50 ∼ 0.002 mg/kg), rats (ED50 < 0.01 mg/kg), and nonhuman primates (over 95% silencing at 0.3 mg/kg). Apolipoprotein E plays a significant role in the potency of cKK-E12 both in vitro and in vivo. cKK-E12 was highly selective toward liver parenchymal cell in vivo, with orders of magnitude lower doses needed to silence in hepatocytes compared with endothelial cells and immune cells in different organs. Toxicity studies showed that cKK-E12 was well tolerated in rats at a dose of 1 mg/kg (over 100-fold higher than the ED50). To our knowledge, this is the most efficacious and selective nonviral siRNA delivery system for gene silencing in hepatocytes reported to date.
The discovery of potent new materials for in vivo delivery of nucleic acids depends upon successful formulation of the active molecules into a dosage form suitable for the physiological environment. ...Because of the inefficiencies of current formulation methods, materials are usually first evaluated for in vitro delivery efficacy as simple ionic complexes with the nucleic acids (lipoplexes). The predictive value of such assays, however, has never been systematically studied. Here, for the first time, by developing a microfluidic method that allowed the rapid preparation of high-quality siRNA-containing lipid nanoparticles (LNPs) for a large number of materials, we have shown that gene silencing assays employing lipoplexes result in a high rate of false negatives (∼90%) that can largely be avoided through formulation. Seven novel materials with in vivo gene silencing potencies of >90% at a dose of 1.0 mg/kg in mice were discovered. This method will facilitate the discovery of next-generation reagents for LNP-mediated nucleic acid delivery.
This paper extends the kernel method that was proposed previously for dynamic PET reconstruction, to incorporate anatomical side information into the PET reconstruction model. In contrast to existing ...methods that incorporate anatomical information using a penalized likelihood framework, the proposed method incorporates this information in the simpler maximum likelihood (ML) formulation and is amenable to ordered subsets. The new method also does not require any segmentation of the anatomical image to obtain edge information. We compare the kernel method with the Bowsher method for anatomically-aided PET image reconstruction through a simulated data set. Computer simulations demonstrate that the kernel method offers advantages over the Bowsher method in region of interest quantification. Additionally the kernel method is applied to a 3D patient data set. The kernel method results in reduced noise at a matched contrast level compared with the conventional ML expectation maximization algorithm.
The repair of white matter damage is of paramount importance for functional recovery after brain injuries. Here, we report that interleukin-4 (IL-4) promotes oligodendrocyte regeneration and ...remyelination. IL-4 receptor expression was detected in a variety of glial cells after ischemic brain injury, including oligodendrocyte lineage cells. IL-4 deficiency in knockout mice resulted in greater deterioration of white matter over 14 d after stroke. Consistent with these findings, intranasal delivery of IL-4 nanoparticles after stroke improved white matter integrity and attenuated long-term sensorimotor and cognitive deficits in wild-type mice, as revealed by histological immunostaining, electron microscopy, diffusion tensor imaging, and electrophysiology. The selective effect of IL-4 on remyelination was verified in an ex vivo organotypic model of demyelination. By leveraging primary oligodendrocyte progenitor cells (OPCs), microglia-depleted mice, and conditional OPC-specific peroxisome proliferator-activated receptor gamma (PPARγ) knockout mice, we discovered a direct salutary effect of IL-4 on oligodendrocyte differentiation that was mediated by the PPARγ axis. Our findings reveal a new regenerative role of IL-4 in the central nervous system (CNS), which lies beyond its known immunoregulatory functions on microglia/macrophages or peripheral lymphocytes. Therefore, intranasal IL-4 delivery may represent a novel therapeutic strategy to improve white matter integrity in stroke and other brain injuries.
Celotno besedilo
Dostopno za:
DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
Positron emission tomography (PET) is a functional imaging modality widely used in oncology, cardiology, and neuroscience. It is highly sensitive, but suffers from relatively poor spatial resolution, ...as compared with anatomical imaging modalities, such as magnetic resonance imaging (MRI). With the recent development of combined PET/MR systems, we can improve the PET image quality by incorporating MR information into image reconstruction. Previously, kernel learning has been successfully embedded into static and dynamic PET image reconstruction using either PET temporal or MRI information. Here, we combine both PET temporal and MRI information adaptively to improve the quality of direct Patlak reconstruction. We examined different approaches to combine the PET and MRI information in kernel learning to address the issue of potential mismatches between MRI and PET signals. Computer simulations and hybrid real-patient data acquired on a simultaneous PET/MR scanner were used to evaluate the proposed methods. Results show that the method that combines PET temporal information and MRI spatial information adaptively based on the structure similarity index has the best performance in terms of noise reduction and resolution improvement.
We present an approach for head MR-based attenuation correction (AC) based on the Statistical Parametric Mapping 8 (SPM8) software, which combines segmentation- and atlas-based features to provide a ...robust technique to generate attenuation maps (μ maps) from MR data in integrated PET/MR scanners.
Coregistered anatomic MR and CT images of 15 glioblastoma subjects were used to generate the templates. The MR images from these subjects were first segmented into 6 tissue classes (gray matter, white matter, cerebrospinal fluid, bone, soft tissue, and air), which were then nonrigidly coregistered using a diffeomorphic approach. A similar procedure was used to coregister the anatomic MR data for a new subject to the template. Finally, the CT-like images obtained by applying the inverse transformations were converted to linear attenuation coefficients to be used for AC of PET data. The method was validated on 16 new subjects with brain tumors (n = 12) or mild cognitive impairment (n = 4) who underwent CT and PET/MR scans. The μ maps and corresponding reconstructed PET images were compared with those obtained using the gold standard CT-based approach and the Dixon-based method available on the Biograph mMR scanner. Relative change (RC) images were generated in each case, and voxel- and region-of-interest-based analyses were performed.
The leave-one-out cross-validation analysis of the data from the 15 atlas-generation subjects showed small errors in brain linear attenuation coefficients (RC, 1.38% ± 4.52%) compared with the gold standard. Similar results (RC, 1.86% ± 4.06%) were obtained from the analysis of the atlas-validation datasets. The voxel- and region-of-interest-based analysis of the corresponding reconstructed PET images revealed quantification errors of 3.87% ± 5.0% and 2.74% ± 2.28%, respectively. The Dixon-based method performed substantially worse (the mean RC values were 13.0% ± 10.25% and 9.38% ± 4.97%, respectively). Areas closer to the skull showed the largest improvement.
We have presented an SPM8-based approach for deriving the head μ map from MR data to be used for PET AC in integrated PET/MR scanners. Its implementation is straightforward and requires only the morphologic data acquired with a single MR sequence. The method is accurate and robust, combining the strengths of both segmentation- and atlas-based approaches while minimizing their drawbacks.
Immunomodulation holds therapeutic promise against brain injuries, but leveraging this approach requires a precise understanding of mechanisms. We report that CD8.sup.+CD122.sup.+CD49d.sup.lo T ...regulatory-like cells (CD8.sup.+ TRLs) are among the earliest lymphocytes to infiltrate mouse brains after ischemic stroke and temper inflammation; they also confer neuroprotection. TRL depletion worsened stroke outcomes, an effect reversed by CD8.sup.+ TRL reconstitution. The CXCR3/CXCL10 axis served as the brain-homing mechanism for CD8.sup.+ TRLs. Upon brain entry, CD8.sup.+ TRLs were reprogrammed to upregulate leukemia inhibitory factor (LIF) receptor, epidermal growth factor-like transforming growth factor (ETGF), and interleukin 10 (IL-10). LIF/LIF receptor interactions induced ETGF and IL-10 production in CD8.sup.+ TRLs. While IL-10 induction was important for the Anti-inflammatory effects of CD8.sup.+ TRLs, ETGF provided direct neuroprotection. Poststroke intravenous transfer of CD8.sup.+ TRLs reduced infarction, promoting long-term neurological recovery in young males or aged mice of both sexes. Thus, these unique CD8.sup.+ TRLs serve as early responders to rally defenses against stroke, offering fresh perspectives for clinical translation.
Background
18F‐fluorodeoxyglucose (FDG) positron emission tomography (PET) is valuable for determining presence of viable tumor, but is limited by geographical restrictions, radiation exposure, and ...high cost.
Purpose
To generate diagnostic‐quality PET equivalent imaging for patients with brain neoplasms by deep learning with multi‐contrast MRI.
Study Type
Retrospective.
Subjects
Patients (59 studies from 51 subjects; age 56 ± 13 years; 29 males) who underwent 18F‐FDG PET and MRI for determining recurrent brain tumor.
Field Strength/Sequence
3T; 3D GRE T1, 3D GRE T1c, 3D FSE T2‐FLAIR, and 3D FSE ASL, 18F‐FDG PET imaging.
Assessment
Convolutional neural networks were trained using four MRIs as inputs and acquired FDG PET images as output. The agreement between the acquired and synthesized PET was evaluated by quality metrics and Bland–Altman plots for standardized uptake value ratio. Three physicians scored image quality on a 5‐point scale, with score ≥3 as high‐quality. They assessed the lesions on a 5‐point scale, which was binarized to analyze diagnostic consistency of the synthesized PET compared to the acquired PET.
Statistical Tests
The agreement in ratings between the acquired and synthesized PET were tested with Gwet's AC and exact Bowker test of symmetry. Agreement of the readers was assessed by Gwet's AC. P = 0.05 was used as the cutoff for statistical significance.
Results
The synthesized PET visually resembled the acquired PET and showed significant improvement in quality metrics (+21.7% on PSNR, +22.2% on SSIM, −31.8% on RSME) compared with ASL. A total of 49.7% of the synthesized PET were considered as high‐quality compared to 73.4% of the acquired PET which was statistically significant, but with distinct variability between readers. For the positive/negative lesion assessment, the synthesized PET had an accuracy of 87% but had a tendency to overcall.
Conclusion
The proposed deep learning model has the potential of synthesizing diagnostic quality FDG PET images without the use of radiotracers.
Evidence Level
3
Technical Efficacy
Stage 2
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