Evidence mapPaperPMID 41008817Full record

ArticleCancers2025

Wavelia Microwave Breast Imaging Phase#2 Clinical Investigation: Methodological Evolutions and Multidimensional Radiomics Analysis Towards Controlled Specificity.

Angie Fasoula, Giannis Papatrechas, Petros Arvanitis, Luc Duchesne, Julio Daniel Gil Cano, John O'Donnell, Sami Abd Elwahab, Michael Kerin

Abstract read
In one paragraph

Article in Cancers, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. 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

8 authors.

Angie FasoulaWavelia Healthcare, MVG Industries, 10563, Athens, Greece.ORCID 0000-0002-2495-5835
Giannis PapatrechasWavelia Healthcare, MVG Industries, 10563, Athens, Greece.
Petros ArvanitisWavelia Healthcare, MVG Industries, 10563, Athens, Greece.ORCID 0000-0002-1450-4475
Luc DuchesneWavelia Healthcare, MVG Industries, 91140 Villejust, France.
Julio Daniel Gil CanoWavelia Healthcare, MVG Industries, 91140 Villejust, France.
John O'DonnellDiscipline of Surgery, Lambe Institute for Translational Research, School of Medicine, University of Galway, H91TK33 Galway, Ireland.
Sami Abd ElwahabDiscipline of Surgery, Lambe Institute for Translational Research, School of Medicine, University of Galway, H91TK33 Galway, Ireland.ORCID 0000-0002-6839-4339
Michael KerinDiscipline of Surgery, Lambe Institute for Translational Research, School of Medicine, University of Galway, H91TK33 Galway, Ireland.ORCID 0000-0003-4164-5561

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

BACKGROUND/

objectivesThe Wavelia Microwave Breast Imaging (MWBI) technology aims to increase sensitivity in dense breasts, where X-ray mammography is of limited value. Its potential contribution to the reduction in the false positives in breast cancer diagnosis, by developing MWBI image descriptors supporting malignant-to-benign lesion discrimination, is also being investigated. After a First-In-Human (FiH) study with interesting findings on a small dataset of 24 symptomatic breast lesions, an upgraded 2nd prototype of Wavelia was manufactured and tested on a larger and more diverse dataset, including 62 patients and a balanced distribution of malignant and benign symptomatic breast lesions.

methodsA set of technological and methodological evolutions, outlined in this article, was implemented in Wavelia#2 to handle the diversity in larger patient datasets. Multi-modal MWBI imaging is employed to parameterize the interaction mechanisms between the microwaves and the imaged breast at varying geometrical and tissue consistency conditions. MWBI Region-Of-Interest (ROI) extraction and characterization based on multidimensional radiomic feature vectors is implemented to expand the malignant-to-benign lesion diagnostics potential of MWBI compared to the limited scope of the FiH study with Wavelia#1, which employed three specific preselected features.

resultsThis study demonstrates significant diagnostic accuracy of multiple texture-based and intensity-based features to discriminate between malignant and benign breast lesions with Wavelia#2 MWBI. A phenomenological qualitative assessment of the false positive rate on healthy breasts is also presented for the MWBI technology for the first time.

conclusionsThe analysis contributes to the rationalization of the MWBI imaging and image analysis outputs towards standardization, objective interpretability, and ultimate clinical acceptance.

Indexed as

breast cancer diagnosisbreast imagingcomputer-aided diagnosis (CAD)image analysismedical radarmicrowave imagingradiomic features

Identifiers

PMID41008817
PMCPMC12468332

What Socratic holds

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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 Socratic graph.