Evidence map›Paper›PMID 36428726›Full record

ArticleCancers2022

Correlation between PD-L1 Expression of Non-Small Cell Lung Cancer and Data from IVIM-DWI Acquired during Magnetic Resonance of the Thorax: Preliminary Results.

Chandra Bortolotto, Giulia Maria Stella, Gaia Messana, Antonio Lo Tito, Chiara Podrecca, Giovanna Nicora, Riccardo Bellazzi, Alessia Gerbasi, Francesco Agustoni, Robert Grimm and 4 more

Open access · goldAbstract read
In one paragraph

Article in Cancers, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed
1.2field-weighted citation impact, top 23% of its field
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

7 citing papers in PubMed, 10 citations in OpenAlex.

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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

14 authors at 4 institutions in 2 countries.

Chandra BortolottoDiagnostic Imaging and Radiotherapy Unit, Department of Clinical, Surgical, Diagnostic, and Pediatric Sciences, University of Pavia, 27100 Pavia, Italy.ORCID 0000-0002-9193-9309
Giulia Maria StellaUnit of Respiratory Diseases, Department of Medical Sciences and Infective Diseases, Fondazione IRCCS Policlinico San Matteo, 27100 Pavia, Italy.ORCID 0000-0003-0929-4394
Gaia MessanaDiagnostic Imaging and Radiotherapy Unit, Department of Clinical, Surgical, Diagnostic, and Pediatric Sciences, University of Pavia, 27100 Pavia, Italy.ORCID 0000-0002-3212-5305
Antonio Lo TitoDiagnostic Imaging and Radiotherapy Unit, Department of Clinical, Surgical, Diagnostic, and Pediatric Sciences, University of Pavia, 27100 Pavia, Italy.
Chiara PodreccaDepartment of Electrical, Computer and Biomedical Engineering, University of Pavia, 27100 Pavia, Italy.ORCID 0000-0003-4861-7547
Giovanna NicoraDepartment of Electrical, Computer and Biomedical Engineering, University of Pavia, 27100 Pavia, Italy.
Riccardo BellazziDepartment of Electrical, Computer and Biomedical Engineering, University of Pavia, 27100 Pavia, Italy.
Alessia GerbasiDepartment of Electrical, Computer and Biomedical Engineering, University of Pavia, 27100 Pavia, Italy.ORCID 0000-0003-4501-1777
Francesco AgustoniDepartment of Medical Oncology, Fondazione IRCCS Policlinico San Matteo, 27100 Pavia, Italy.
Robert GrimmMR Application Predevelopment, Siemens Healthcare GmbH, 91052 Erlangen, Germany.ORCID 0000-0002-1233-8215
Domenico ZacàSiemens Healthcare, 20128 Milano, Italy.
Andrea Riccardo FilippiDiagnostic Imaging and Radiotherapy Unit, Department of Clinical, Surgical, Diagnostic, and Pediatric Sciences, University of Pavia, 27100 Pavia, Italy.ORCID 0000-0001-7159-7869
Olivia Maria BottinelliDiagnostic Imaging and Radiotherapy Unit, Department of Clinical, Surgical, Diagnostic, and Pediatric Sciences, University of Pavia, 27100 Pavia, Italy.
Lorenzo PredaDiagnostic Imaging and Radiotherapy Unit, Department of Clinical, Surgical, Diagnostic, and Pediatric Sciences, University of Pavia, 27100 Pavia, Italy.ORCID 0000-0002-5479-2766
University of Pavia · ITPoliclinico San Matteo Fondazione · ITSiemens Healthineers (Germany) · DESiemens (Italy) · IT

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

This study aims to investigate the correlation between intravoxel incoherent motion diffusion-weighted imaging (IVIM-DWI) parameters in magnetic resonance imaging (MRI) and programmed death-ligand 1 (PD-L1) expression in non-small cell lung cancer (NSCLC). Twenty-one patients diagnosed with stage III NSCLC from April 2021 to April 2022 were included. The tumors were distinguished into two groups: no PD-L1 expression (<1%), and positive PD-L1 expression (≥1%). Conventional MRI and IVIM-DWI sequences were acquired with a 1.5-T system. Both fixed-size ROIs and freehand segmentations of the tumors were evaluated, and the data were analyzed through a software using four different algorithms. The diffusion (D), pseudodiffusion (D*), and perfusion fraction (pf) were obtained. The correlation between IVIM parameters and PD-L1 expression was studied with Pearson correlation coefficient. The Wilcoxon−Mann−Whitney test was used to study IVIM parameter distributions in the two groups. Twelve patients (57%) had PD-L1 ≥1%, and 9 (43%) <1%. There was a statistically significant correlation between D* values and PD-L1 expression in images analyzed with algorithm 0, for fixed-size ROIs (189.2 ± 65.709 µm²/s × 104 in no PD-L1 expression vs. 122.0 ± 31.306 µm²/s × 104 in positive PD-L1 expression, p = 0.008). The values obtained with algorithms 1, 2, and 3 were not significantly different between the groups. The IVIM-DWI MRI parameter D* can reflect PD-L1 expression in NSCLC.

Indexed as

intravoxel incoherent motion (IVIM)non-small cell lung cancer (NSCLC)programmed death-ligand 1 (PD-L1)

Identifiers

PMID36428726
PMCPMC9688282
OpenAlexW4309710921

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.