1,721,060 research outputs found
Novel hierarchical approach for voxel-wise PET quantification: application on multi-compartmental models
No full textA new hierarchical method for PET parametric maps generation: Assessment on multi-compartmental models
No full textMulti-scale hierarchical approach for parametric mapping: assessment on multi-compartmental models
No full textA Bayesian Hierarchical Method For Generation Of PET Parametric Maps: Application On [11C]DPN Test-Retest Study
No full textMultimodal partial-volume correction: Application to 18F-fluoride PET/CT bone metastases studies
No full text18F-fluoride PET/CT offers the opportunity for accurate skeletal metastasis staging, compared with conventional imaging methods. 18F-fluoride is a bone-specific tracer whose uptake depends on osteoblastic activity. Because of the resulting increase in bone mineralization and sclerosis, the osteoblastic process can also be detected morphologically in CT images. Although CT is characterized by high resolution, the potential of PET is limited by its lower spatial resolution and the resulting partial-volume effect. In this context, the synergy between PET and CT presents an opportunity to resolve this limitation using a novel multimodal approach called synergistic functional-structural resolution recovery (SFS-RR). Its performance is benchmarked against current resolution recovery technology using the point-spread function (PSF) of the scanner in the reconstruction procedure. Methods: The SFS-RR technique takes advantage of the multiresolution property of the wavelet transform applied to both functional and structural images to create a high-resolution PET image that exploits the structural information of CT. Although the method was originally conceived for PET/MR imaging of brain data, an ad hoc version for whole-body PET/CT is proposed here. Three phantom experiments and 2 datasets of metastatic bone 18F-fluoride PET/CT images from primary prostate and breast cancer were used to test the algorithm performances. The SFS-RR images were compared with the manufacturer's PSFbased reconstruction using the standardized uptake value (SUV) and the metabolic volume as metrics for quantification. Results: When compared with standard PET images, the phantom experiments showed a bias reduction of 14% in activity and 1.3 cm3 in volume estimates for PSF images and up to 20% and 2.5 cm3 for the SFS-RR images. The SFS-RR images were characterized by a higher recovery coefficient (up to 60%) whereas noise levels remained comparable to those of standard PET. The clinical data showed an increase in the SUV estimates for SFS-RR images up to 34% for peak SUV and 50% for maximum SUV and mean SUV. Images were also characterized by sharper lesion contours and better lesion detectability. Conclusion: The proposed methodology generates PET images with improved quantitative and qualitative properties. Compared with standard methods, SFS-RR provides superior lesion segmentation and quantification, which may result in more accurate tumor characterization
Integration of human whole-brain transcriptome and neuroimaging data: Practical considerations of current available methods
No full textThe Allen Human Brain Atlas (AHBA) is the first example of human brain transcriptomic mappings and detailed anatomical annotations which, for the first time, has allowed the integration of human brain transcriptomics with neuroimaging. This has been made possible because the AHBA offered an original dataset that contains mRNA expression measures for >20,000 genes covering the whole brain and, critically, in a standard stereotaxic space. In recent years many different methods have been used to integrate this data set with brain imaging data, although this endeavour has lacked harmony in terms of the workflow of data processing and subsequent analyses. In this work we discuss five main issues that experience has highlighted as in need of thorough consideration when integrating the AHBA with neuroimaging. These concerns are corroborated by comparing the performance of three different publicly available methods in correlating the same measures of serotonin receptors density with the correspondent AHBA mRNA maps. In this representative case, we were able to show how these methods can lead to discrepant results, suggesting that processing options are not neutral. We believe that the field should take into serious consideration these issues as they could undermine reproducibility and, in the end, the intrinsic value of the AHBA. We also advise on possible strategies to overcome these discrepancies. Finally, we encourage authors towards practices that will improve reproducibility such as transparency in reporting, algorithm and data sharing, collaboration
A new modelling approach for quantification of [11C]PBR28 brain PET data including a vascular component
No full textNormative modelling of molecular-based functional circuits captures clinical heterogeneity transdiagnostically in psychiatric patients
Full text linkAdvanced methods such as REACT have allowed the integration of fMRI with the brain’s receptor landscape, providing novel insights transcending the multiscale organisation of the brain. Similarly, normative modelling has allowed translational neuroscience to move beyond group-average differences and characterise deviations from health at an individual level. Here, we bring these methods together for the first time. We used REACT to create functional networks enriched with the main modulatory, inhibitory, and excitatory neurotransmitter systems and generated normative models of these networks to capture functional connectivity deviations in patients with schizophrenia, bipolar disorder (BPD), and ADHD. Substantial overlap was seen in symptomatology and deviations from normality across groups, but these could be mapped into a common space linking constellations of symptoms through to underlying neurobiology transdiagnostically. This work provides impetus for developing novel biomarkers that characterise molecular- and systems-level dysfunction at the individual level, facilitating the transition towards mechanistically targeted treatments
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