Evidence map›Paper›PMID 41277993›Full record

ArticleMethodsX2025

Implementation of bidirectional crusher gradient method for measuring labelling efficiency of pseudocontinuous arterial spin labeling MRI in mice.

Xiuli Yang, Yuguo Li, Zhiliang Wei

Abstract read
In one paragraph

Article in MethodsX, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors.

Xiuli YangDepartment of Radiology and Radiological Science, The Johns Hopkins University School of Medicine, Baltimore, Maryland, USA.
Yuguo LiDepartment of Radiology and Radiological Science, The Johns Hopkins University School of Medicine, Baltimore, Maryland, USA.
Zhiliang WeiDepartment of Radiology and Radiological Science, The Johns Hopkins University School of Medicine, Baltimore, Maryland, USA.

Funding

TRD 4: Platforms for multi-modal and multi-scale imaging dataP41EB031771 · NIBIB · HUGO W. MOSER RES INST KENNEDY KRIEGER · PI Hanzhang Lu, Peter CM Van Zijl · 2021 to 2026
$9.9M
Pathophysiological mechanisms of hypoperfusion in mouse models of Alzheimer?s disease and small vessel diseaseR01AG081932 · NIA · JOHNS HOPKINS UNIVERSITY · PI Zhiliang Wei · 2023 to 2026
$2.1M
NIA NIH HHS R01 AG081932NIBIB NIH HHS P41 EB031771
6 · The paper itself

Abstract

The pseudocontinuous arterial spin labeling (pCASL) MRI technique provides a powerful tool for in vivo evaluation of microvascular functions, including cerebral blood flow, blood-brain barrier permeability, and blood-cerebrospinal fluid exchange. These microvascular parameters have emerged as promising biomarkers for tracking pathological progression and therapeutic efficacy in both preclinical and clinical settings. Accurate quantification of pCASL signals requires consideration of labeling efficiency, a critical parameter that can vary substantially in mice due to their small vessel size and intersubject vascular heterogeneity. Determination of labeling efficiency on an individual basis is therefore desirable. Recently, the bidirectional crusher gradient (BIC) method was proposed to measure labeling efficiency in mouse pCASL MRI. The present study aims to outline step-by-step procedures for implementing the BIC method and associated validation studies. (1) Measurement of mouse pCASL MRI labeling efficiency in approximately 3 min (2) Improved accuracy in pCASL-based cerebral perfusion imaging of mice.

Indexed as

Arterial spin labelingASLCerebral blood flowCrusher gradientLabeling efficiencyPerfusion

Identifiers

PMID41277993
PMCPMC12637394

What OpenQuestion holds

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.