Evidence map›Paper›PMID 39805838›Full record

ArticleScientific reports2025

Probabilistic nested model selection in pharmacokinetic analysis of DCE-MRI data in animal model of cerebral tumor.

Hassan Bagher-Ebadian, Stephen L Brown, Mohammad M Ghassemi, Prabhu C Acharya, Indrin J Chetty, Benjamin Movsas, James R Ewing, Kundan Thind

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Scientific reports, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Review
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

8 authors.

Hassan Bagher-EbadianDepartment of Radiation Oncology, Henry Ford Hospital, Detroit, USA. hbagher1@hfhs.org.
Stephen L BrownDepartment of Radiation Oncology, Henry Ford Hospital, Detroit, USA.
Mohammad M GhassemiDepartment of Computer Science and Engineering, Michigan State University, East Lansing, USA.
Prabhu C AcharyaDepartment of Physics, Oakland University, Rochester, USA.
Indrin J ChettyDepartment of Physics, Oakland University, Rochester, USA.
Benjamin MovsasDepartment of Radiation Oncology, Henry Ford Hospital, Detroit, USA.
James R EwingDepartment of Radiology, Michigan State University, East Lansing, USA.
Kundan ThindDepartment of Radiation Oncology, Henry Ford Hospital, Detroit, 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
Dykstra Steel Family (Philanthropic ) F5670HSC Pilot Grant -HFH-MSU F80005NCI NIH HHS R01 CA218596NIH HHS R01-CA218596Siemens Healthineers MRA1 & MRA2Varian Medical Systems MRA1 &MRA2
6 · The paper itself

Abstract

Best current practice in the analysis of dynamic contrast enhanced (DCE)-MRI is to employ a voxel-by-voxel model selection from a hierarchy of nested models. This nested model selection (NMS) assumes that the observed time-trace of contrast-agent (CA) concentration within a voxel, corresponds to a singular physiologically nested model. However, admixtures of different models may exist within a voxel's CA time-trace. This study introduces an unsupervised feature engineering technique (Kohonen-Self-Organizing-Map (K-SOM)) to estimate the voxel-wise probability of each nested model. Sixty-six immune-compromised-RNU rats were implanted with human U-251 N cancer cells, and DCE-MRI data were acquired from all the rat brains. The time-trace of change in the longitudinal-relaxivity (ΔR

Indexed as

Brain NeoplasmsContrast MediaDynamic Contrast Enhanced Magnetic Resonance ImagingModels, StatisticalAnimalsCell Line, TumorDisease Models, AnimalHumansRatsContrast MediaDynamic Contrast Enhanced MRIModel AveragingNested Model SelectionPhysiological Tissue CharacterizationUnsupervised Kohonen Self Organizing Map

Identifiers

PMID39805838
PMCPMC11729890

What OpenQuestion holds

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LicenceCC BY
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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.