Evidence map›Paper›PMID 40146425›Full record

ArticleEuropean radiology2025

Non-invasive PD-L1 stratification in non-small cell lung cancer using dynamic contrast-enhanced MRI.

Gaia Messana, Chandra Bortolotto, Sithin Thulasi Seetha, Alessandra Marrocco, Carlotta Pairazzi, Francesco Sanvito, Francesca Brero, Agnese Robustelli Test, Raffaella Fiamma Cabini, Alessandro Lascialfari and 6 more

Abstract read
In one paragraph

Article in European radiology, 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. 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

16 authors.

Gaia Messana *Diagnostic Imaging and Radiotherapy Unit, Department of Clinical, Surgical, Diagnostic, and Pediatric Sciences, University of Pavia, Pavia, Italy.
Chandra BortolottoDiagnostic Imaging and Radiotherapy Unit, Department of Clinical, Surgical, Diagnostic, and Pediatric Sciences, University of Pavia, Pavia, Italy.
Sithin Thulasi Seetha *Diagnostic Imaging and Radiotherapy Unit, Department of Clinical, Surgical, Diagnostic, and Pediatric Sciences, University of Pavia, Pavia, Italy. sithin.thulasiseetha@unipv.it.ORCID http://orcid.org/0000-0002-9079-9949
Alessandra MarroccoDiagnostic Imaging and Radiotherapy Unit, Department of Clinical, Surgical, Diagnostic, and Pediatric Sciences, University of Pavia, Pavia, Italy.
Carlotta PairazziDiagnostic Imaging and Radiotherapy Unit, Department of Clinical, Surgical, Diagnostic, and Pediatric Sciences, University of Pavia, Pavia, Italy.
Francesco SanvitoUCLA Brain Tumor Imaging Laboratory (BTIL), Center for Computer Vision and Imaging Biomarkers, University of California Los Angeles, Los Angeles, CA, USA.
Francesca BreroDepartment of Physics, University of Pavia, Pavia, Italy.
Agnese Robustelli TestDepartment of Physics, University of Pavia, Pavia, Italy.
Raffaella Fiamma CabiniEuler Institute, Università della Svizzera Italiana, Lugano, Switzerland.
Alessandro LascialfariDepartment of Physics, University of Pavia, Pavia, Italy.
Domenico ZacàSiemens Healthcare srl, Milano, Italy.
Giulia Maria StellaDepartment of Medical Sciences and Infective Diseases, Unit of Respiratory Diseases, Fondazione IRCCS Policlinico San Matteo, Pavia, Italy.
Francesco AgustoniDepartment of Medical Oncology, Fondazione IRCCS Policlinico San Matteo, Pavia, Italy.
Jessica SaddiRadiation Oncology, Fondazione IRCCS Policlinico San Matteo, Pavia, Italy.
Andrea Riccardo FilippiDiagnostic Imaging and Radiotherapy Unit, Department of Clinical, Surgical, Diagnostic, and Pediatric Sciences, University of Pavia, Pavia, Italy.
Lorenzo PredaDiagnostic Imaging and Radiotherapy Unit, Department of Clinical, Surgical, Diagnostic, and Pediatric Sciences, University of Pavia, Pavia, Italy.

Funding

Fondazione IRCCS Policlinico San Matteo 20190049910
6 · The paper itself

Abstract

objectivesThis study aimed to assess whether pharmacokinetic parameters derived from DCE-MRI can stratify Programmed Death-Ligand 1 (PD-L1) expression in NSCLC. The secondary aim was to identify a suitable pharmacokinetic model configuration for anisotropic temporally-spaced DCE-MRI sequences, considering Tofts variants, population-averaged arterial input functions (AIF), and bolus arrival time (BAT) estimation methods. MATERIALS AND

methodsFrom April 2021 to May 2023, patients with locally advanced non-small cell lung cancer (NSCLC) were prospectively enrolled. Tumors were categorized based on: PD-L1 absence/presence (threshold 1%) and hyperexpression/hypoexpression (threshold 50%). Pharmacokinetic parameters were extracted using several candidate configurations; fit quality was evaluated using coefficient of determination (R²). Mann-Whitney U-test and ROC-AUC were used to assess correlation with PD-L1 for the best-fit configuration.

resultsThirty-eight patients (mean age 68 ± 9 years, 28 men) were included. PD-L1 expression was present in 25 patients (66%) and absent in 13 (34%). PD-L1 was hyperexpressed in 13 (34%) patients and hypoexpressed in 25 (66%). Voxel-wise pharmacokinetic parameters were extracted using the best-fit configuration-extended Tofts model (ETM) with Georgiou AIF and Peak-Gradient (PG) BAT estimation (R

conclusionDCE-MRI pharmacokinetic parameters could stratify PD-L1 hypo/hyperexpression in NSCLC. The ETM with PG BAT estimation method and Georgiou AIF was the best-performing pharmacokinetic configuration. KEY POINTS: Question Could Dynamic Contrast-Enhanced (DCE) MRI offer a safe and non-invasive way to assess Programmed Death-Ligand 1 (PD-L1) expression? Findings Quantitative DCE-MRI parameters K

Indexed as

B7-H1 AntigenCarcinoma, Non-Small-Cell LungContrast MediaLung NeoplasmsMagnetic Resonance ImagingAgedFemaleHumansMaleMiddle AgedProspective StudiesB7-H1 AntigenCD274 protein, humanContrast MediaImmunotherapyNon-small cell lung carcinomaPD-L1 inhibitorsPerfusion magnetic resonance imagingPharmacokinetics

Identifiers

PMID40146425
PMCPMC12350491

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.