Evidence map›Paper›PMID 33427349›Full record

ArticleMagnetic resonance in medicine2021

Optimization of adiabatic pulses for pulsed arterial spin labeling at 7 tesla: Comparison with pseudo-continuous arterial spin labeling.

Kai Wang, Xingfeng Shao, Lirong Yan, Samantha J Ma, Jin Jin, Danny J J Wang

Abstract read
In one paragraph

Article in Magnetic resonance in medicine, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing 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

8 citing papers in PubMed.

  1. Dynamic BMagnetic resonance in medicine · 2025
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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

6 authors.

Kai WangLaboratory of FMRI Technology (LOFT), USC Mark & Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, Los Angeles, California, USA.ORCID 0000-0003-2752-6953
Xingfeng ShaoLaboratory of FMRI Technology (LOFT), USC Mark & Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, Los Angeles, California, USA.ORCID 0000-0002-4130-6204
Lirong YanLaboratory of FMRI Technology (LOFT), USC Mark & Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, Los Angeles, California, USA.
Samantha J MaLaboratory of FMRI Technology (LOFT), USC Mark & Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, Los Angeles, California, USA.
Jin JinLaboratory of FMRI Technology (LOFT), USC Mark & Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, Los Angeles, California, USA.
Danny J J WangLaboratory of FMRI Technology (LOFT), USC Mark & Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, Los Angeles, California, USA.ORCID 0000-0002-0840-7062

Funding

Imaging Cerebral and Retinal Microvasculature in Cerebral Small Vessel DiseaseUH3NS100614 · NINDS · UNIVERSITY OF SOUTHERN CALIFORNIA · PI KASHANI, AMIR H, RINGMAN, JOHN M · 2018 to 2020
$4.3M
Validation of Imaging and Blood-based Small Vessel VCID Biomarkers in Multiethnic PopulationUF1NS100614 · NINDS · UNIVERSITY OF SOUTHERN CALIFORNIA · PI KASHANI, AMIR H, RINGMAN, JOHN M · 2021 to 2021
$2.6M
Laminar Perfusion ImagingR01EB032169 · NIBIB · UNIVERSITY OF SOUTHERN CALIFORNIA · PI Danny JJ WANG · 2021 to 2026
$2.5M
Multiband ASL for Neurodevelopment StudyR01EB028297 · NIBIB · UNIVERSITY OF SOUTHERN CALIFORNIA · PI WANG, DANNY JJ · 2019 to 2023
$2.2M
BBB Permeability Imaging in CADASILR01NS114382 · NINDS · UNIVERSITY OF SOUTHERN CALIFORNIA · PI WANG, DANNY JJ · 2020 to 2024
$1.2M
NOVA PTX Coil for Ultrahigh Field ImagingS10OD025312 · OD · UNIVERSITY OF SOUTHERN CALIFORNIA · PI WANG, DANNY JJ · 2018 to 2018
$330k
NIBIB NIH HHS R01 EB028297NIBIB NIH HHS R01 EB032169NIH HHS S10 OD025312NINDS NIH HHS R01 NS114382NINDS NIH HHS UF1 NS100614NINDS NIH HHS UH3 NS100614
6 · The paper itself

Abstract

purposeTo optimize and evaluate adiabatic pulses for pulsed arterial spin labeling at ultrahigh field 7 tesla.

methodsFour common adiabatic inversion pulses, including hyperbolic secant, wideband uniform rate smooth truncation, frequency offset corrected inversion, and time-resampled frequency offset corrected inversion pulses, were optimized based on a custom-defined loss function that included labeling efficiency and inversion band uniformity. The optimized pulses were implemented in flow-sensitive alternating inversion recovery sequences and tested on phantom and 11 healthy volunteers with 2 constraints: 1) specific absorption rate normalized; and 2) equal peak RF amplitude, respectively. A pseudo-continuous arterial spin labeling sequence was implemented for comparison. Quantitative metrics such as perfusion and relative labeling efficiency versus residual tissue signal were calculated.

resultsAmong the 4 pulses, the wideband uniform rate smooth truncation pulse yielded the lowest loss in simulation and achieved a good balance between labeling efficiency and residual tissue signal from both phantom and in vivo experiments. Wideband uniform rate smooth truncation-pulsed arterial spin labeling showed significantly higher relative labeling efficiency compared to the other sequences (P < .01), whereas the perfusion signal was increased by 40% when the highest

conclusionOptimized wideband uniform rate smooth truncation pulse with the highest

Indexed as

ArteriesMagnetic Resonance ImagingCerebrovascular CirculationHumansPerfusionPhantoms, ImagingSpin LabelsSpin Labelsadiabatic inversion pulsearterial spin labeling (ASL)flow-sensitive alternating inversion recovery (FAIR)parameter optimizationperfusionultrahigh field (UHF)

Identifiers

PMID33427349
PMCPMC8351166

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Registered trials

None linked

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.