Background And Purpose: Arterial spin labeling (ASL) is an MRI technique to measure cerebral blood flow (CBF) without the need of exogenous contrast agents and is thus a promising alternative to the clinical standard dynamic susceptibility-weighted contrast-enhanced (DSC) perfusion imaging. Latest international guidelines encourage its application in the clinical setting. However, susceptibility-induced image distortions impair ASL with fast readout modules (eg Echo Planar Imaging, EPI; gradient and spin echo, GRASE). In the present study, we investigated the benefit of a distortion correction for ASL compared to DSC.

Methods: A pulsed ASL (PASL) sequence combined with a 3D-GRASE readout at multiple inflow times (multi-TI) was used and was corrected for susceptibility distortions using a FMRIB Software Library (FSL) implemented tool TOPUP. We performed qualitative (three expert raters) and quantitative (volume of interest [VOI]-based) comparisons of ASL and DSC imaging in 13 patients with chronic steno-occlusive disease.

Results: In the qualitative analysis, distortion correction of the images led to a strong increase in diagnostic precision of ASL compared to DSC in the anterior cerebral artery (ACA) perfusion territory, where the susceptibility artifact was most pronounced (specificity 8% vs. 75%). In the quantitative analysis, the correlation between ASL and DSC values increased for all perfusion territories with the best improvement for the ACA territory (for anterior, middle and posterior cerebral artery: ACA: rho -0.22 vs. 0.71; MCA: rho 0.58 vs. 0.76; PCA: rho 0.58 vs. 0.63).

Conclusions: We showed that susceptibility distortion correction strongly improves the comparability of multi-TI ASL 3D-GRASE to DSC in steno-occlusive disease. We suggest it to be implemented in ASL postprocessing routines.

Download full-text PDF

Source
http://dx.doi.org/10.1111/jon.12331DOI Listing

Publication Analysis

Top Keywords

distortion correction
12
asl
9
susceptibility distortions
8
arterial spin
8
spin labeling
8
asl compared
8
asl dsc
8
cerebral artery
8
artery aca
8
rho 058
8

Similar Publications

Wide dynamic range compression (WDRC) and noise reduction both play important roles in hearing aids. WDRC provides level-dependent amplification so that the level of sound produced by the hearing aid falls between the hearing threshold and the highest comfortable level of the listener, while noise reduction reduces ambient noise with the goal of improving intelligibility and listening comfort and reducing effort. In most current hearing aids, noise reduction and WDRC are implemented sequentially, but this may lead to distortion of the amplitude modulation patterns of both the speech and the noise.

View Article and Find Full Text PDF

Age-related macular degeneration (AMD) is a progressive, chronic eye disease with no permanent cure currently available. Symptoms of the disease, including distorted and blurred vision and gradual loss of central vision, significantly aggravate patients' daily functioning. The purpose of this study was to assess the acceptance of the disease among patients diagnosed with neovascular age-related macular degeneration before treatment and after receiving seven intravitreal injections and to determine how it was related to the values of visual parameters.

View Article and Find Full Text PDF

Objects project different images when viewed from varying locations, but the visual system can correct perspective distortions and identify objects across viewpoints. This study investigated the conditions under which the visual system allocates computational resources to construct view-invariant, extraretinal representations, focusing on planar symmetry. When a symmetrical pattern lies on a plane, its symmetry in the retinal image is degraded by perspective.

View Article and Find Full Text PDF

Automated Audit and Self-Correction Algorithm for Seg-Hallucination Using MeshCNN-Based On-Demand Generative AI.

Bioengineering (Basel)

January 2025

Department of Applied Bioengineering, Graduate School of Convergence Science and Technology, Seoul National University, Seoul 08826, Republic of Korea.

Recent advancements in deep learning have significantly improved medical image segmentation. However, the generalization performance and potential risks of data-driven models remain insufficiently validated. Specifically, unrealistic segmentation predictions deviating from actual anatomical structures, known as a Seg-Hallucination, often occur in deep learning-based models.

View Article and Find Full Text PDF

Single-cell RNA sequencing (scRNA-seq) offers remarkable insights into cellular development and differentiation by capturing the gene expression profiles of individual cells. The role of dimensionality reduction and visualization in the interpretation of scRNA-seq data has gained widely acceptance. However, current methods face several challenges, including incomplete structure-preserving strategies and high distortion in embeddings, which fail to effectively model complex cell trajectories with multiple branches.

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!