Evidence map›Paper›PMID 40931476›Full record

ArticleMagnetic resonance in medicine2026

On the structural and practical identifiability of multi-echo BBB-ASL tracer kinetic models.

Tabitha J Manson, David L Thomas, Matthias Günther, Lynette J Tippett, Michael Dragunow, Catherine A Morgan, Vinod Suresh

Abstract read
In one paragraph

Article in Magnetic resonance in medicine, 2026. 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. 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.

Tabitha J MansonAuckland Bioengineering Institute, The University of Auckland, Auckland, New Zealand.ORCID https://orcid.org/0000-0002-7577-7872
David L ThomasDepartment of Brain Repair and Rehabilitation, UCL Queen Square Institute of Neurology, University College London, London, UK.ORCID https://orcid.org/0000-0003-1491-1641
Matthias GüntherImaging Physics, Fraunhofer Institute for Digital Medicine MEVIS, Bremen, Germany.ORCID https://orcid.org/0000-0002-2650-7956
Lynette J TippettSchool of Psychology and Centre for Brain Research, University of Auckland, Auckland, New Zealand.
Michael DragunowDepartment of Pharmacology and Centre for Brain Research, University of Auckland, Auckland, New Zealand.
Catherine A MorganSchool of Psychology and Centre for Brain Research, University of Auckland, Auckland, New Zealand.
Vinod SureshAuckland Bioengineering Institute, The University of Auckland, Auckland, New Zealand.

Funding

Brain Research New ZealandFreemasons New ZealandHealth Research Council of New ZealandNeurological Foundation of New ZealandNew Zealand Dementia Prevention TrustSir Thomas and Lady Duncan Trust
6 · The paper itself

Abstract

purposeTracer kinetic models are used in arterial spin labeling (ASL); however, deciding which model parameters to fix or fit is not always trivial. The identifiability of the resultant system of equations is useful to consider, since it will likely impact parameter uncertainty. Here, we analyze the identifiability of two-compartment models used in multi-echo (ME) blood-brain-barrier (BBB)-ASL and evaluate the reliability of the fitted water-transfer rate

methodThe identifiability of two variants of a two-compartment model (referred to here as "series" and "parallel") were analyzed using sensitivity matrix and Monte-Carlo simulation methods, the latter including the effects of noise and fixed-parameter error. ME-ASL data were collected at 3T in 25 cognitively normal participants (57-85 y). In one volunteer, additional scans were acquired to estimate noise. Fits for whole-gray-matter

resultsAll models needed one or more fixed parameters to be structurally identifiable, with different combinations required for each. Practical identifiability analysis yielded

conclusionWe used identifiability analysis to determine an appropriate BBB-ASL model for acquired data. Through simulations we showed that parameter estimates depend on model selection and the value of fixed parameters. We demonstrated that fixed-parameter value and errors significantly impact the reliability of

Indexed as

Blood-Brain BarrierMagnetic Resonance ImagingAgedAged, 80 and overAlgorithmsBrainComputer SimulationFemaleHumansImage Processing, Computer-AssistedKineticsMaleMiddle AgedMonte Carlo MethodReproducibility of ResultsSpin LabelsSpin Labelsarterial spin labelingblood–brain barriercerebral blood flowidentifiabilitywater exchangewater permeability

Identifiers

PMID40931476
PMCPMC12681319

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.