Evidence map›Paper›PMID 30954651›Full record

ArticleMagnetic resonance imaging2019

Clinical feasibility of brain quantitative susceptibility mapping.

Shun Zhang, Zhe Liu, Thanh D Nguyen, Yihao Yao, Kelly M Gillen, Pascal Spincemaille, Ilhami Kovanlikaya, Ajay Gupta, Yi Wang

Abstract read
In one paragraph

Article in Magnetic resonance imaging, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing 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

7 citing papers in PubMed.

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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

9 authors.

Shun ZhangDepartment of Radiology, Weill Cornell Medicine, New York, NY, USA; Department of Radiology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.
Zhe LiuDepartment of Radiology, Weill Cornell Medicine, New York, NY, USA; Department of Biomedical Engineering, Cornell University, Ithaca, NY, USA.
Thanh D NguyenDepartment of Radiology, Weill Cornell Medicine, New York, NY, USA.
Yihao YaoDepartment of Radiology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.
Kelly M GillenDepartment of Radiology, Weill Cornell Medicine, New York, NY, USA.
Pascal SpincemailleDepartment of Radiology, Weill Cornell Medicine, New York, NY, USA.
Ilhami KovanlikayaDepartment of Radiology, Weill Cornell Medicine, New York, NY, USA.
Ajay GuptaDepartment of Radiology, Weill Cornell Medicine, New York, NY, USA.
Yi WangDepartment of Radiology, Weill Cornell Medicine, New York, NY, USA; Department of Biomedical Engineering, Cornell University, Ithaca, NY, USA. Electronic address: yiwang@med.cornell.edu.

Funding

Quantitative Mapping of Substantia Nigra Iron in Parkinson's DiseaseR01NS095562 · NINDS · WEILL MEDICAL COLL OF CORNELL UNIV · PI SHTILBANS, ALEXANDER, WANG, YI · 2016 to 2022
$3.1M
Multiple Sclerosis Lesion Magnetic Susceptibility ActivityR01NS090464 · NINDS · WEILL MEDICAL COLL OF CORNELL UNIV · PI WANG, YI · 2015 to 2020
$2.3M
3.0T Magnetic Resonance Imaging System for Preclinical, Translational and Clinical ResearchS10OD021782 · OD · WEILL MEDICAL COLL OF CORNELL UNIV · PI WANG, YI · 2016 to 2016
$2.0M
Compact Representations of Dynamic Liver MRIR01CA181566 · NCI · WEILL MEDICAL COLL OF CORNELL UNIV · PI SPINCEMAILLE, PASCAL · 2015 to 2019
$1.9M
Feasibility of challenge-free QSM based quantitative mapping of cerebral metabolic rate of oxygenR21EB024366 · NIBIB · WEILL MEDICAL COLL OF CORNELL UNIV · PI GOYAL, MANU S, SU, YI · 2017 to 2018
$474k
NCI NIH HHS R01 CA181566NIBIB NIH HHS R21 EB024366NIH HHS S10 OD021782NINDS NIH HHS R01 NS090464NINDS NIH HHS R01 NS095562
6 · The paper itself

Abstract

purposeTo evaluate the quality of brain quantitative susceptibility mapping (QSM) that is fully automatically reconstructed in clinical MRI of various neurological diseases.

methods393 consecutive patients in one month were recruited for this evaluation study. QSM was reconstructed using Morphology Enabled Dipole Inversion without zero reference regularization (MEDI) and using MEDI with cerebrospinal fluid automatic zero-reference regularization to generate susceptibility values (MEDI+0). Two neuroradiologists independently assessed the image quality of MEDI+0 and MEDI and image concordance between them. Lesion susceptibility values were measured in 20 cases of glioma, 21 cases of ischemic stroke and 43 multiple sclerosis (MS) cases on both MEDI+0 and MEDI images.

resultsThe two neuroradiologists rated the MEDI+0 image qualities of the 393 cases as 351 (89.3%) and 362 (92.1%) excellent, 29 (7.4%) and 24 (6.1%) diagnostic, and 13 (3.3%) and 7 (1.8%) poor, and scored the concordances between MEDI+0 and MEDI as 364 (92.6%) and 351 (89.3%) excellent, 13 (3.3%) and 31 (7.9%) good, 14 (3.6%) and 9 (2.3%) intermediate, 2 (0.5%) and 2 (0.5%) poor, and 0 (0%) and 0 (0%) none. There was good correlation between MEDI+0 and MEDI in lesion susceptibility contrast of glioma, ischemic stroke, and MS cases (all p < 0.05). The MS lesion susceptibility time course from this patient cohort was found to be similar to the reported pattern: isointense initially for acute enhancing lesions, and hyperintense over the following years for active chronic lesions.

conclusionBrain QSM images of various neurological diseases have reliable diagnostic quality in clinical MRI, with MEDI+0 providing susceptibility values automatically referenced to CSF in longitudinal and cross-center studies.

Indexed as

AdolescentAdultAgedAged, 80 and overAlgorithmsBrainBrain IschemiaBrain MappingChildChild, PreschoolFeasibility StudiesFemaleGliomaHumansImage Processing, Computer-AssistedImaging, Three-DimensionalCerebrospinal fluidMorphology enabled dipole inversionMultiple sclerosisQuantitative susceptibility mappingZero reference

Identifiers

PMID30954651
PMCPMC6535129

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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.