Evidence map›Paper›PMID 37316579›Full record

ArticleScientific reports2023

Dynamic contrast enhanced (DCE) MRI estimation of vascular parameters using knowledge-based adaptive models.

Hassan Bagher-Ebadian, Stephen L Brown, Mohammad M Ghassemi, Tavarekere N Nagaraja, Olivia Grahm Valadie, Prabhu C Acharya, Glauber Cabral, George Divine, Robert A Knight, Ian Y Lee and 4 more

Abstract read
In one paragraph

Article in Scientific reports, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing 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

5 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Article
  5. 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

14 authors.

Hassan Bagher-EbadianDepartment of Radiation Oncology, Henry Ford Health, Detroit, MI, 48202, USA. hbagher1@hfhs.org.
Stephen L BrownDepartment of Radiation Oncology, Henry Ford Health, Detroit, MI, 48202, USA.
Mohammad M GhassemiDepartment of Computer Science and Engineering, Michigan State University, East Lansing, MI, 48824, USA.
Tavarekere N NagarajaDepartment of Radiology, Michigan State University, East Lansing, MI, 48824, USA.
Olivia Grahm ValadieDepartment of Radiation Oncology, Wayne State University, Detroit, MI, 48202, USA.
Prabhu C AcharyaDepartment of Physics, Oakland University, Rochester, MI, 48309, USA.
Glauber CabralDepartment of Neurology, Henry Ford Health, Detroit, MI, 48202, USA.
George DivineDepartment of Public Health Sciences, Henry Ford Health, Detroit, MI, 48202, USA.
Robert A KnightDepartment of Neurology, Henry Ford Health, Detroit, MI, 48202, USA.
Ian Y LeeDepartment of Neurosurgery, Henry Ford Health, Detroit, MI, 48202, USA.
Jun H XuDepartment of Neurosurgery, Henry Ford Health, Detroit, MI, 48202, USA.
Benjamin MovsasDepartment of Radiation Oncology, Henry Ford Health, Detroit, MI, 48202, USA.
Indrin J ChettyDepartment of Radiation Oncology, Henry Ford Health, Detroit, MI, 48202, USA.
James R EwingDepartment of Radiology, Michigan State University, East Lansing, MI, 48824, USA.

Funding

MRI Signatures of Response to High-Dose Radiotherapy in Rat Models of Cerebral TumorR01CA218596 · NCI · HENRY FORD HEALTH SYSTEM · PI BROWN, STEPHEN L, EWING, JAMES R · 2018 to 2022
$2.4M
NCI NIH HHS R01 CA218596NCI NIH HHS R01-CA218596
6 · The paper itself

Abstract

We introduce and validate four adaptive models (AMs) to perform a physiologically based Nested-Model-Selection (NMS) estimation of such microvascular parameters as forward volumetric transfer constant, K

Indexed as

ArteriesMagnetic Resonance ImagingAlgorithmsAnimalsExtracellular SpaceHumansMicrovesselsRats

Identifiers

PMID37316579
PMCPMC10267191

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.