Evidence map›Paper›PMID 42351489›Full record

ReviewDiagnostics (Basel, Switzerland)2026

Understanding CT Perfusion in Acute Ischemic Stroke: How Algorithms Shape Perfusion Maps.

Nicola Morelli, Marco Spallazzi, Marina Biondi, Eugenia Rota, Davide Colombi

Abstract readReview
In one paragraph

Review in Diagnostics (Basel, Switzerland), 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. Review
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

5 authors.

Nicola MorelliNeuroradiology Unit, Guglielmo da Saliceto Hospital, 29121 Piacenza, Italy.ORCID 0000-0003-3787-2243
Marco SpallazziNeurology Unit, University of Parma, 43121 Parma, Italy.
Marina BiondiNeuroradiology Unit, Guglielmo da Saliceto Hospital, 29121 Piacenza, Italy.
Eugenia RotaNeurology Unit, San Giacomo Hospital, 15067 Novi Ligure, Italy.ORCID 0000-0003-3154-7634
Davide ColombiDepartment of Diagnostic Imaging, Centro Diagnostico Rocca, 29121 Piacenza, Italy.ORCID 0000-0002-2794-5237

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

CT perfusion (CTP) is widely used in acute ischemic stroke imaging, particularly for treatment selection beyond conventional time windows. However, automated perfusion maps are not direct measurements of irreversible tissue injury, but estimates shaped by deconvolution strategy, temporal correction, dispersion handling, and software-specific thresholds. This review provides a clinically oriented explanation of how CTP algorithms influence the estimation of ischemic core and hypoperfused tissue. Particular attention is given to singular value decomposition (SVD) methods, Bayesian approaches, and timing parameters, including time to maximum (Tmax), Delay, time to peak (TTP), and mean transit time (MTT). Differences in residue function estimation and threshold definition may generate variable outputs across software platforms, even from the same source dataset. Perfusion thresholds should therefore not be treated as universally interchangeable. CTP findings should be integrated with clinical status, non-contrast CT, CT angiography (CTA), collateral status, occlusion site, and imaging-to-treatment context, serving as decision-support tools rather than isolated measures of tissue viability.

Indexed as

acute ischemic strokeBayesian algorithmCT perfusiondeconvolutionischemic coreperfusion imagingstroke imagingTmax

Identifiers

PMID42351489
PMCPMC13297754

What OpenQuestion holds

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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.