Evidence map›Paper›PMID 42004273›Full record

ReviewACS nanoscience Au2026

Breaking Through the Barrier: Nanoparticle-Driven MRI Strategies for Diagnosis and Therapy of Pancreatic Cancer.

Alessandro Amaolo, Angelo Scarciglia, Marianna Sorrentino, Enza Di Gregorio, Giuseppe Ferrauto

Abstract readReview
In one paragraph

Review in ACS nanoscience Au, 2026. 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
–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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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.

Alessandro AmaoloMolecular Imaging Center, Department of Molecular Biotechnology and Health Sciences, University of Turin, Via Nizza 52, Turin 10126, Italy.
Angelo ScarcigliaMolecular Imaging Center, Department of Molecular Biotechnology and Health Sciences, University of Turin, Via Nizza 52, Turin 10126, Italy.
Marianna SorrentinoMolecular Imaging Center, Department of Molecular Biotechnology and Health Sciences, University of Turin, Via Nizza 52, Turin 10126, Italy.
Enza Di GregorioMolecular Imaging Center, Department of Molecular Biotechnology and Health Sciences, University of Turin, Via Nizza 52, Turin 10126, Italy.
Giuseppe FerrautoMolecular Imaging Center, Department of Molecular Biotechnology and Health Sciences, University of Turin, Via Nizza 52, Turin 10126, Italy.ORCID https://orcid.org/0000-0003-4937-6140

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Pancreatic ductal adenocarcinoma (PDAC) remains a highly lethal cancer due to late diagnosis, limited biomarkers, and a dense stromal microenvironment that hinder imaging and therapy. Magnetic resonance imaging (MRI) offers high soft-tissue resolution but lacks molecular sensitivity and specificity when applied to PDAC. Advanced MRI methods such as diffusion-weighted imaging (DWI), hyperpolarized MRI, MR elastography (MRE), and dynamic contrast-enhanced MRI (DCE-MRI) have expanded the ability to characterize tumor microstructure, metabolism, stiffness, and perfusion, offering valuable functional insights. Nanoparticle-based contrast agents are emerging as promising tools to overcome these limitations by improving sensitivity, targeting tumor biomarkers, and enabling theranostic applications. This review explores the frontiers of nanoparticle-enhanced MRI in the context of PDAC. Recent studies show that superparamagnetic iron oxide nanoparticles (SPIONs) enhance T2-weighted MRI contrast and detect small PDAC lesions

Indexed as

contrast agentsmagnetic resonance imaging (MRI)nanoparticles (NP)pancreatic ductal adenocarcinoma (PDAC)stromal barrierstheranosticstumor microenvironment (TME)tumor targeting

Identifiers

PMID42004273
PMCPMC13087952

What OpenQuestion holds

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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.