Evidence map›Paper›PMID 37064527›Full record

ArticleArXiv2023

Quantitative perfusion and water transport time model from multi b-value diffusion magnetic resonance imaging validated against neutron capture microspheres.

M Liu, N Saadat, Y Jeong, S Roth, M Niekrasz, M Giurcanu, T Carroll, G Christoforidis

Open access · hybridAbstract readPreprint
In one paragraph

Article in ArXiv, 2023. 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
0.7field-weighted citation impact, top 30% of its field
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, 3 citations in OpenAlex.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

8 authors at 3 institutions in 1 country.

M Liu
N Saadat
Y Jeong
S Roth
M Niekrasz
M Giurcanu
T Carroll
G Christoforidis
University of Chicago Medical Center · USUniversity of Chicago · USUniversity of Illinois Chicago · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Intravoxel Incoherent Motion (IVIM) is a non-contrast magnetic resonance imaging diffusion-based scan that uses a multitude of b-values to measure various speeds of molecular perfusion and diffusion, sidestepping inaccuracy of arterial input functions or bolus kinetics in quantitative imaging. We test a new method of IVIM quantification and compare our values to reference standard neutron capture microspheres across normocapnia, CO2 induced hypercapnia, and middle cerebral artery occlusion in a controlled animal model. Perfusion quantification in ml/100g/min compared to microsphere perfusion uses the 3D gaussian probability distribution and defined water transport time as when 50% of the molecules remain in the tissue of interest. Perfusion, water transport time, and infarct volume was compared to reference standards. Simulations were studied to suppress non-specific cerebrospinal fluid (CSF). Linear regression analysis of quantitative perfusion returned correlation (slope = .55, intercept = 52.5, $R^2$= .64). Linear regression for water transport time asymmetry in infarcted tissue was excellent (slope = .59, intercept = .3, $R^2$ = .93). Strong linear agreement also was found for infarct volume (slope = 1.01, $R^2$= .79). Simulation of CSF suppression via inversion recovery returned blood signal reduced by 82% from combined T1 and T2 effects. Intra-physiologic state comparison of perfusion shows potential partial volume effects which require further study especially in disease states. The accuracy and sensitivity of IVIM provides evidence that observed signal changes reflect cytotoxic edema and tissue perfusion. Partial volume contamination of CSF may be better removed during post-processing rather than with inversion recovery to avoid artificial loss of blood signal.

Identifiers

PMID37064527
PMCPMC10104192
OpenAlexW4362656059

What OpenQuestion holds

Textmetadata
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.