Evidence map›Paper›PMID 28684456›Full record

ArticleAJNR. American journal of neuroradiology2017

Optimization of DSC MRI Echo Times for CBV Measurements Using Error Analysis in a Pilot Study of High-Grade Gliomas.

L C Bell, M D Does, A M Stokes, L C Baxter, K M Schmainda, A C Dueck, C C Quarles

Abstract read
In one paragraph

Article in AJNR. American journal of neuroradiology, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed, 1 pooled it
–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

6 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Review
  3. Article
  4. Article
  5. Evaluation of single bolus, dual-echo dynamic susceptibility contrast MRI protocols in brain tumor patients.Journal of cerebral blood flow and metabolism : official journal of the International Society of Cerebral Blood Flow and Metabolism · 2021
    Article
  6. Article
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

7 authors.

L C BellFrom the Division of Imaging Research (L.C. Bell, A.M.S., L.C. Baxter, C.C.Q.), Barrow Neurological Institute, Phoenix, Arizona.ORCID http://orcid.org/0000-0001-8164-8324
M D DoesDepartment of Biomedical Engineering (M.D.D.), Vanderbilt University Institute of Imaging Science, Nashville, Tennessee.ORCID http://orcid.org/0000-0003-2701-6208
A M StokesFrom the Division of Imaging Research (L.C. Bell, A.M.S., L.C. Baxter, C.C.Q.), Barrow Neurological Institute, Phoenix, Arizona.ORCID http://orcid.org/0000-0003-1137-5003
L C BaxterFrom the Division of Imaging Research (L.C. Bell, A.M.S., L.C. Baxter, C.C.Q.), Barrow Neurological Institute, Phoenix, Arizona.ORCID http://orcid.org/0000-0002-3971-863X
K M SchmaindaDepartments of Biophysics and Radiology (K.M.S.), Medical College of Wisconsin, Milwaukee, Wisconsin.ORCID http://orcid.org/0000-0001-6402-2602
A C DueckDivision of Health Sciences Research (A.C.D.), Section of Biostatistics, Mayo Clinic, Scottsdale, Arizona.ORCID http://orcid.org/0000-0002-9912-1085
C C QuarlesFrom the Division of Imaging Research (L.C. Bell, A.M.S., L.C. Baxter, C.C.Q.), Barrow Neurological Institute, Phoenix, Arizona chad.quarles@barrowneuro.org.ORCID http://orcid.org/0000-0002-1731-0940

Funding

MRI CONTRAST AGENT METHODS TO ASSESS TUMOR ANGIOGENESISR01CA082500 · NCI · MEDICAL COLLEGE OF WISCONSIN · PI SCHMAINDA, KATHLEEN MARIE · 2000 to 2016
$5.0M
Quantitative (Perfusion and Diffusion) MRI Biomarkers to Measure Glioma ResponseU01CA176110 · NCI · MEDICAL COLLEGE OF WISCONSIN · PI SCHMAINDA, KATHLEEN MARIE · 2014 to 2023
$4.9M
MRI Assessment of Tumor Perfusion, Permeability and CellularityR01CA158079 · NCI · VANDERBILT UNIVERSITY · PI QUARLES, CHRISTOPHER CHAD · 2011 to 2021
$3.5M
Establishing the Validity of Brain Tumor Perfusion ImagingR01CA213158 · NCI · UNIVERSITY OF TX MD ANDERSON CAN CTR · PI Christopher Chad Quarles · 2017 to 2026
$2.9M
MRI Toolbox for Rodent Brain Microstructure ImagingR01EB019980 · NIBIB · VANDERBILT UNIVERSITY · PI DOES, MARK D · 2016 to 2019
$1.8M
NCI NIH HHS R01 CA082500NCI NIH HHS R01 CA158079NCI NIH HHS R01 CA213158NCI NIH HHS U01 CA176110NIBIB NIH HHS R01 EB019980
6 · The paper itself

Abstract

background and purposeThe optimal TE must be calculated to minimize the variance in CBV measurements made with DSC MR imaging. Simulations can be used to determine the influence of the TE on CBV, but they may not adequately recapitulate the in vivo heterogeneity of precontrast T2*, contrast agent kinetics, and the biophysical basis of contrast agent-induced T2* changes. The purpose of this study was to combine quantitative multiecho DSC MRI T2* time curves with error analysis in order to compute the optimal TE for a traditional single-echo acquisition. MATERIALS AND

methodsEleven subjects with high-grade gliomas were scanned at 3T with a dual-echo DSC MR imaging sequence to quantify contrast agent-induced T2* changes in this retrospective study. Optimized TEs were calculated with propagation of error analysis for high-grade glial tumors, normal-appearing white matter, and arterial input function estimation.

resultsThe optimal TE is a weighted average of the T2* values that occur as a contrast agent bolus transverses a voxel. The mean optimal TEs were 30.0 ± 7.4 ms for high-grade glial tumors, 36.3 ± 4.6 ms for normal-appearing white matter, and 11.8 ± 1.4 ms for arterial input function estimation (repeated-measures ANOVA,

conclusionsGreater heterogeneity was observed in the optimal TE values for high-grade gliomas, and mean values of all 3 ROIs were statistically significant. The optimal TE for the arterial input function estimation is much shorter; this finding implies that quantitative DSC MR imaging acquisitions would benefit from multiecho acquisitions. In the case of a single-echo acquisition, the optimal TE prescribed should be 30-35 ms (without a preload) and 20-30 ms (with a standard full-dose preload).

Indexed as

AdultAgedAlgorithmsBrain NeoplasmsCerebral ArteriesCohort StudiesContrast MediaEcho-Planar ImagingFemaleGliomaHumansImage Processing, Computer-AssistedMaleMiddle AgedPilot ProjectsRetrospective StudiesContrast Media

Identifiers

PMID28684456
PMCPMC5591773

What OpenQuestion holds

Textmetadata
LicenceTDM
Read underepoch 390

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.