Purpose: To evaluate the impact of different fat spectral models on proton density fat fraction quantification using chemical shift-encoded MRI (CSE-MRI).
Methods: In a simulation study, spectral models of fat were compared pairwise. Comparison of magnitude fitting and mixed fitting was performed over a range of echo times and fat fractions. In vivo acquisitions from 41 patients were reconstructed using seven published spectral models of fat. T2-corrected stimulated echo acquisition mode MR spectroscopy was used as a reference.
Results: The simulations demonstrated that imperfectly calibrated spectral models of fat result in biases that depend on echo times and fat fraction. Mixed fitting was more robust against this bias than magnitude fitting. Multipeak spectral models showed much smaller differences among themselves than from the single-peak spectral model. In vivo studies showed that all multipeak models agreed better (for mixed fitting, the slope ranged from 0.967 to 1.045 using linear regression) with the reference standard than the single-peak model (for mixed fitting, slope = 0.76).
Conclusion: It is essential to use a multipeak fat model for accurate quantification of fat with CSE-MRI. Furthermore, fat quantification techniques using multipeak fat models are comparable, and no specific choice of spectral model has been shown to be superior to the rest.
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http://dx.doi.org/10.1002/mrm.25681 | DOI Listing |
Front Neurorobot
January 2025
School of Computer Science, Northwestern Polytechnical University, Xi'an, China.
Significant strides have been made in emotion recognition from Electroencephalography (EEG) signals. However, effectively modeling the diverse spatial, spectral, and temporal features of multi-channel brain signals remains a challenge. This paper proposes a novel framework, the Directional Spatial and Spectral Attention Network (DSSA Net), which enhances emotion recognition accuracy by capturing critical spatial-spectral-temporal features from EEG signals.
View Article and Find Full Text PDFData Brief
February 2025
Centro Surcolombiano de Investigación en Café (CESURCAFÉ), Departamento de Ingeniería Agrícola, Universidad Surcolombiana, Neiva-Huila 410001, Colombia.
This work presents a comprehensive dataset of adsorption isotherms and infrared spectral data for roasted specialty coffee ( L.). The dataset includes adsorption isotherms for whole roasted beans and ground coffee at medium (850 µm) and fine (600 µm) particle sizes.
View Article and Find Full Text PDFData Brief
February 2025
Centro Surcolombiano de Investigación en Café (CESURCAFÉ), Departamento de Ingeniería Agrícola, Universidad Surcolombiana, Neiva-Huila 410001, Colombia.
This paper presents a comprehensive dataset of mid-infrared spectra for dried and roasted cocoa beans ( L.), along with their corresponding theobromine and caffeine content. Infrared data were acquired using Attenuated Total Reflectance-Fourier Transform Infrared (ATR-FTIR) spectroscopy, while High-Performance Liquid Chromatography (HPLC) was employed to accurately quantify theobromine and caffeine in the dried cocoa beans.
View Article and Find Full Text PDFFront Neurosci
January 2025
School of Electronic Information and Communications, Huazhong University of Science and Technology, Wuhan City, China.
Introduction: Transcranial magnetic stimulation (TMS) is widely used for the noninvasive activation of neurons in the human brain. It utilizes a pulsed magnetic field to induce electric pulses that act on the central nervous system, altering the membrane potential of nerve cells in the cerebral cortex to treat certain mental diseases. However, the effectiveness of TMS can be compromised by significant heat generation and the clicking noise produced by the pulse in the TMS coil.
View Article and Find Full Text PDFACS Earth Space Chem
January 2025
School of Chemistry, Norwich Research Park, University of East Anglia, Norwich NR4 7TJ, U.K.
2-Cyanoindene is one of the few specific aromatic or polycyclic aromatic hydrocarbon (PAH) molecules positively identified in Taurus molecular cloud-1 (TMC-1), a cold, dense molecular cloud that is considered the nearest star-forming region to Earth. We report cryogenic mid-infrared (550-3200 cm) and visible (16,500-20,000 cm, over the ← electronic transition) spectra of 2-cyanoindene radical cations (2CNI), measured using messenger tagging (He and Ne) photodissociation spectroscopy. The infrared spectra reveal the prominence of anharmonic couplings, particularly over the fingerprint region.
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