We analyzed modified Look-Locker inversion recovery (MOLLI) T1 measurements by applying a dictionary matching strategy and aimed to acquire T1 measurements more accurately than those acquired by the conventional three-parameter matching analysis. We particularly clarified the robustness of this method for measuring heart rate (HR) variability. A phantom experiment using a 3T MRI system was performed for various HRs. The ideal MOLLI signal corresponding to the scan parameter in the MRI experiment was simulated over a wide range of T1 values according to the dictionary. The unknown T1 values were determined by finding the simulated signals in the dictionary corresponding to the measured signals using pattern matching. The measured T1 values showed that the proposed analysis improved the accuracy of T1 measurements compared to those acquired by traditional analysis by up to 10%. In addition, the variability of measurements at several HRs was reduced by up to 100 ms.

Download full-text PDF

Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC10449558PMC
http://dx.doi.org/10.2463/mrms.tn.2022-0013DOI Listing

Publication Analysis

Top Keywords

dictionary matching
8
heart rate
8
rate variability
8
measurements
5
dictionary
4
matching improve
4
improve accuracy
4
accuracy molli
4
molli myocardial
4
analysis
4

Similar Publications

Background: Photon-counting computed tomography (CT) is an advanced imaging technique that enables multi-energy imaging from a single scan. However, the limited photon count assigned to narrow energy bins leads to increased quantum noise in the reconstructed spectral images. To address this issue, leveraging the prior information in the spectral images is essential.

View Article and Find Full Text PDF

Purpose: This study proposes a novel, contrast-free Magnetic Resonance Fingerprinting (MRF) method using balanced Steady-State Free Precession (bSSFP) sequences for the quantification of cerebral blood volume (CBV), vessel radius (R), and relaxometry parameters (T , T , T *) in the brain.

Methods: The technique leverages the sensitivity of bSSFP sequences to intra-voxel frequency distributions in both transient and steady-state regimes. A dictionary-matching process is employed, using simulations of realistic mouse microvascular networks to generate the MRF dictionary.

View Article and Find Full Text PDF

We present PepFuNN, a new open-source version of the PepFun package with functions to study the chemical space of peptide libraries and perform structure-activity relationship analyses. PepFuNN is a Python package comprising five modules to study peptides with natural amino acids and, in some cases, sequences with non-natural amino acids based on the availability of a public monomer dictionary. The modules allow calculating physicochemical properties, performing similarity analysis using different peptide representations, clustering peptides using molecular fingerprints or calculated descriptors, designing peptide libraries based on specific requirements, and a module dedicated to extracting matched pairs from experimental campaigns to guide the selection of the most relevant mutations in design new rounds.

View Article and Find Full Text PDF
Article Synopsis
  • MR fingerprinting (MRF) is an innovative technique for measuring MR relaxometry with high precision, but its complex data requirements hinder its widespread use.
  • A deep learning (DL) network, specifically a U-Net, was created to synthesize MRF signals from regular magnitude-only MRI data collected from 37 volunteers, comparing the results with actual acquired MRF signals.
  • The study found strong concordance between synthesized and actual MRF data, indicating that DL can enable quantitative relaxometry without the need for specialized MRF pulse sequences.
View Article and Find Full Text PDF

Paediatric critical care units are designed for children at a vulnerable stage of development, yet the evidence base for practice and policy in paediatric critical care remains scarce. In this Health Policy, we present a roadmap providing strategic guidance for international paediatric critical care trials. We convened a multidisciplinary group of 32 paediatric critical care experts from six continents representing paediatric critical care research networks and groups.

View Article and Find Full Text PDF

Want AI Summaries of new PubMed Abstracts delivered to your In-box?

Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!