Recently, intravoxel incoherent motion (IVIM) diffusion-weighted imaging (DWI) has also been demonstrated as an imaging tool for applications in neurological and neurovascular diseases. However, the use of single-shot diffusion-weighted echo-planar imaging for IVIM DWI acquisition leads to suboptimal data quality: for instance, geometric distortion and deteriorated image quality at high spatial resolution. Although the recently commercialized multi-shot acquisition methods, such as multiplexed sensitivity encoding (MUSE), can attain high-resolution and high-quality DWI with signal-to-noise ratio (SNR) performance superior to that of the conventional parallel imaging method, the prolonged scan time associated with multi-shot acquisition is impractical for routine IVIM DWI. This study proposes an acquisition and reconstruction framework based on parametric-POCSMUSE to accelerate the four-shot IVIM DWI with 70% reduction of total scan time (13 min 8 s versus 4 min 8 s). First, the four-shot IVIM DWI scan with 17 b values was accelerated by acquiring only one segment per b value except for b values of 0 and 600 s/mm . Second, an IVIM-estimation scheme was integrated into the parametric-POCSMUSE to enable joint reconstruction of multi-b images from under-sampled four-shot IVIM DWI data. In vivo experiments on both healthy subjects and patients show that the proposed framework successfully produced multi-b DW images with significantly higher SNRs and lower reconstruction errors than did the conventional acceleration method based on parallel imaging. In addition, the IVIM quantitative maps estimated from the data produced by the proposed framework showed quality comparable to that of fully sampled MUSE-reconstructed images, suggesting that the proposed framework can enable highly accelerated multi-shot IVIM DWI without sacrificing data quality. In summary, the proposed framework can make multi-shot IVIM DWI feasible in a routine MRI examination, with reasonable scan time and improved geometric fidelity.
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http://dx.doi.org/10.1002/nbm.5063 | DOI Listing |
Rofo
January 2025
Department of Diagnostic and Interventional Radiology, University Hospital Tübingen, Tübingen, Germany.
Multiparametric MRI is a promising technique for noninvasive structural and functional imaging of the kidneys that is gaining increasing importance in clinical research. Still, there are no standardized recommendations for analyzing the acquired images and there is a need to further evaluate the accuracy and repeatability of currently recommended MRI parameters. The aim of the study was to evaluate the test-retest repeatability of functional renal MRI parameters using different image analysis strategies.
View Article and Find Full Text PDFMed Image Anal
December 2024
Faculty of Biomedical Engineering, Technion, Haifa, Israel. Electronic address:
Quantitative analysis of pseudo-diffusion in diffusion-weighted magnetic resonance imaging (DWI) data shows potential for assessing fetal lung maturation and generating valuable imaging biomarkers. Yet, the clinical utility of DWI data is hindered by unavoidable fetal motion during acquisition. We present IVIM-morph, a self-supervised deep neural network model for motion-corrected quantitative analysis of DWI data using the Intra-voxel Incoherent Motion (IVIM) model.
View Article and Find Full Text PDFMed Image Anal
November 2024
Department of Radiology and Nuclear Medicine, St. Olav's University Hospital, Trondheim, Norway; Department of Circulation and Medical Imaging, NTNU - Norwegian University of Science and Technology, Trondheim, Norway.
In medical image analysis, the utilization of biophysical models for signal analysis offers valuable insights into the underlying tissue types and microstructural processes. In diffusion-weighted magnetic resonance imaging (DWI), a major challenge lies in accurately estimating model parameters from the acquired data due to the inherently low signal-to-noise ratio (SNR) of the signal measurements and the complexity of solving the ill-posed inverse problem. Conventional model fitting approaches treat individual voxels as independent.
View Article and Find Full Text PDFAJNR Am J Neuroradiol
December 2024
From the Department of Diagnostic Medicine, Dell Medical School at The University of Texas at Austin, Austin, TX, USA (C.Y.H.), Department of Radiology and Imaging Sciences, Indiana University School of Medicine, Indianapolis, IN, USA (N.S., G.A., Q.W., P.C., M.A., J.G.P., B.R.G., P.R.T., G.D.H.), Department of Medicine, Indiana University School of Medicine, Indianapolis, IN, USA (E.C., P.R.T., S.A.P.), Stark Neuroscience Research Institute, Indiana University School of Medicine, Indianapolis, IN, USA (P.R.T., S.A.P.), and the Department of Radiology at Texas Children's Hospital, Houston, TX, USA (S.F.K.).
Background And Purpose: There are multiple MRI perfusion techniques, with limited available literature comparing these techniques in the grading of pediatric brain tumors. For efficiency and limiting scan time, ideally only one MRI perfusion technique can be used in initial imaging. We compared DSC, DCE, and IVIM along with ADC from DWI for differentiating high versus low grade pediatric brain tumors.
View Article and Find Full Text PDFEur Radiol
December 2024
Department of Radiology, Qilu Hospital, Shandong University, Jinan, China.
Objectives: To analyze the performance of multiparametric magnetic resonance imaging (MRI) in quantification of pancreatic ductal adenocarcinoma (PDAC) fibrosis grading.
Method: This prospective study enrolled 79 patients with PDAC confirmed by pathology. Multiparametric MRI including native T1 mapping, intravoxel incoherent motion diffusion-weighted imaging (IVIM-DWI), diffusion kurtosis imaging diffusion-weighted imaging (DKI-DWI), and enhanced T1 mapping were performed before surgery.
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