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Purpose: To accelerate the acquisition of free-breathing 3D saturation-recovery-based (SASHA) myocardial T1 mapping by acquiring fewer saturation points in combination with a post-processing 3D denoising technique to maintain high accuracy and precision.
Methods: 3D SASHA T1 mapping acquires nine T1-weighted images along the saturation recovery curve, resulting in long acquisition times. In this work, we propose to accelerate conventional cardiac T1 mapping by reducing the number of saturation points. High T1 accuracy and low standard deviation (as a surrogate for precision) is maintained by applying a 3D denoising technique to the T1-weighted images prior to pixel-wise T1 fitting. The proposed approach was evaluated on a T1 phantom and 20 healthy subjects, by varying the number of T1-weighted images acquired between three and nine, both prospectively and retrospectively. Following the results from the healthy subjects, three patients with suspected cardiovascular disease were acquired using five T1-weighted images. T1 accuracy and precision was determined for all the acquisitions before and after denoising.
Results: In the T1 phantom, no statistical difference was found in terms of accuracy and precision for the different number of T1-weighted images before or after denoising (P = 0.99 and P = 0.99 for accuracy, P = 0.64 and P = 0.42 for precision, respectively). In vivo, both prospectively and retrospectively, the precision improved considerably with the number of T1-weighted images employed before denoising (P<0.05) but was independent on the number of T1-weighted images after denoising.
Conclusion: We demonstrate the feasibility of accelerating 3D SASHA T1 mapping by reducing the number of acquired T1-weighted images in combination with an efficient 3D denoising, without affecting accuracy and precision of T1 values.
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http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0221071 | PLOS |
Magn Reson Med
September 2025
Department of Biomedical Engineering, University of Wisconsin-Madison, Madison, Wisconsin, USA.
Purpose: Gadoxetic acid-enhanced hepatobiliary phase T-weighted (Tw) MRI is effective for the detection of focal liver lesions but lacks sufficient T contrast to distinguish benign from malignant lesions. Although the addition of T, diffusion, and dynamic contrast-enhanced Tw imaging improves lesion characterization, these methods often do not provide adequate spatial resolution to identify subcentimeter lesions. This work proposes a high-resolution, volumetric, free-breathing liver MRI method that produces colocalized fat-suppressed, variable Tw images from a single acquisition, thereby improving both lesion detection and characterization.
View Article and Find Full Text PDFIEEE J Biomed Health Inform
September 2025
Positron Emission Tomography (PET) is a critical imaging modality in nuclear medicine but requires radioactive tracer administration, which increases radiation exposure risks. While recent studies have investigated MR-guided low-dose PET denoising, they neglect two critical factors: the synergistic roles of multicontrast MR images and disease-specific denoising requirements. In this work, we propose a diffusion model that integrates T1-weighted, T2 fluid attenuated inversion recovery (T2 FLAIR), and hippocampal-optimized (T2 HIPPO) MR sequences to achieve ultra-low-dose PET denoising tailored for temporal lobe epilepsy (TLE).
View Article and Find Full Text PDFNeuroradiology
September 2025
Department of Radiology, The First Affiliated Hospital of Soochow University, Suzhou, China.
Purpose: To develop and validate an integrated model based on MR high-resolution vessel wall imaging (HR-VWI) radiomics and clinical features to preoperatively assess periprocedural complications (PC) risk in patients with intracranial atherosclerotic disease (ICAD) undergoing percutaneous transluminal angioplasty and stenting (PTAS).
Methods: This multicenter retrospective study enrolled 601 PTAS patients (PC+, n = 84; PC -, n = 517) from three centers. Patients were divided into training (n = 336), validation (n = 144), and test (n = 121) cohorts.
Front Oncol
August 2025
Department of Radiology, Jinshan Hospital, Fudan University, Shanghai, China.
Purpose: To develop a magnetic resonance imaging (MRI)-based radiomics nomogram to predict lymphovascular space invasion (LVSI) status in patients with early-stage cervical adenocarcinoma (CAC).
Methods: Clinicopathological and MRI data from 310 patients with histopathologically confirmed early-stage CAC were retrospectively analyzed. Patients were divided into training (n = 186) and validation (n = 124) cohorts.
Phys Imaging Radiat Oncol
July 2025
Department of Diagnostic, Molecular and Interventional Radiology, Icahn School of Medicine at Mount Sinai, New York, NY, United States.
Background And Purpose: Predicting hepatocellular carcinoma (HCC) response to Stereotactic Body Radiation Therapy (SBRT) can be challenging. Here, we assessed the value of a radiomics-based machine learning (ML) approach for predicting HCC response to SBRT, using pre-treatment and early post-treatment magnetic resonance imaging (MRI).
Materials And Methods: This retrospective single-center study included 87 patients (M 67, mean age 65.