Simulation of time-intensity curve based on k-space filling in breast dynamic contrast-enhanced three-dimensional magnetic resonance imaging.

Radiol Phys Technol

Division of Health Sciences, Graduate School of Medical Sciences, Kanazawa University, 5-11-80 Kodatsuno, Kanazawa, 920-0942, Japan.

Published: June 2024

This study elucidated the effects of a three-dimensional k-space trajectory incorporating the partial Fourier (PF) technique on a time-intensity curve (TIC) in a dynamic contrast-enhanced magnetic resonance imaging of a typical malignant breast tumor using a digital phantom. Images were obtained from the Cancer Imaging Archive Open Data for Breast Cancer, and 1-min scans with high temporal resolution were analyzed. The order of the k-space trajectory was set as Linear (sequential), Low-High (centric), PF (62.5%; Z-, Y-, and both directions), and Low-High Radial. k0 (center of the k-space) timing and TIC shape were affected by the chosen k-space trajectory and implementation of the PF technique. A small TIC gradient was obtained using a Low-High Radial order. If the k-space filling method (particularly the radial method) produces a gentle TIC gradient, misinterpretation could arise during the assessment of tumor malignancy status.

Download full-text PDF

Source
http://dx.doi.org/10.1007/s12194-024-00793-yDOI Listing

Publication Analysis

Top Keywords

k-space trajectory
12
time-intensity curve
8
k-space filling
8
dynamic contrast-enhanced
8
magnetic resonance
8
resonance imaging
8
order k-space
8
low-high radial
8
tic gradient
8
k-space
6

Similar Publications

Purpose: To provide a fast quantitative imaging approach for a 0.55T scanner, where signal-to-noise ratio is limited by the field strength and k-space sampling speed is limited by a lower specification gradient system.

Methods: We adapted the three-dimensional spiral projection imaging MR fingerprinting approach to 0.

View Article and Find Full Text PDF

Exploring in vivo human brain metabolism at 10.5 T: Initial insights from MR spectroscopic imaging.

Neuroimage

January 2025

Center for Magnetic Resonance Research, Department of Radiology, University of Minnesota, Minneapolis, USA. Electronic address:

Introduction: Ultra-high-field magnetic resonance (MR) systems (7 T and 9.4 T) offer the ability to probe human brain metabolism with enhanced precision. Here, we present the preliminary findings from 3D MR spectroscopic imaging (MRSI) of the human brain conducted with the world's first 10.

View Article and Find Full Text PDF

Combination of deep learning reconstruction and quantification for dynamic contrast-enhanced (DCE) MRI.

Magn Reson Imaging

December 2024

Weill Cornell Graduate School of Medical Sciences, New York, NY, United States; Department of Medical Physics, Memorial Sloan Kettering Cancer Center, New York, NY, United States; Department of Radiology, Memorial Sloan Kettering Cancer Center, NY, New York, USA. Electronic address:

Dynamic contrast-enhanced (DCE) MRI is an important imaging tool for evaluating tumor vascularity that can lead to improved characterization of tumor extent and heterogeneity, and for early assessment of treatment response. However, clinical adoption of quantitative DCE-MRI remains limited due to challenges in acquisition and quantification performance, and lack of automated tools. This study presents an end-to-end deep learning pipeline that exploits a novel deep reconstruction network called DCE-Movienet with a previously developed deep quantification network called DCE-Qnet for fast and quantitative DCE-MRI.

View Article and Find Full Text PDF

Deuterium metabolic imaging (DMI) is an emerging Magnetic Resonance technique providing valuable insight into the dynamics of cellular glucose (Glc) metabolism of the human brain in vivo using deuterium-labeled (H) glucose as non-invasive tracer. Reliable concentration estimation of H-Glc and downstream synthesized neurotransmitters glutamate + glutamine (Glx) requires accurate knowledge of relaxation times, but so far tissue-specific T and T relaxation times (e.g.

View Article and Find Full Text PDF

Purpose: Proton (H)-MRSI via spatial-spectral encoding poses high demands on gradient hardware at ultra-high fields and high-resolutions. Rosette trajectories help alleviate these problems, but at reduced SNR-efficiency because of their k-space densities not matching any desired k-space filter. We propose modified rosette trajectories, which more closely match a Hamming filter, and thereby improve SNR performance while still staying within gradient hardware limitations and without prolonging scan time.

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!