Evidence map›Paper›PMID 42625963›Full record

ReviewWorld journal of methodology2026

Microwave breast imaging: A review of clinical potential and technological advances.

Isabella Akesson, Richard Kovac, Hyuna Son, Ana Claudia Teixeira de Castro Gonçalves Ortega, Daniil Fedorov, Arosh S Perera Molligoda Arachchige

Abstract readReview
In one paragraph

Review in World journal of methodology, 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

6 authors.

Isabella AkessonFaculty of Medicine, Humanitas University, Pieve Emanuele 20072, Italy.
Richard KovacFaculty of Medicine, Humanitas University, Pieve Emanuele 20072, Italy.
Hyuna SonFaculty of Medicine, Humanitas University, Pieve Emanuele 20072, Italy.
Ana Claudia Teixeira de Castro Gonçalves OrtegaFaculty of Medicine, Humanitas University, Pieve Emanuele 20072, Italy.
Daniil FedorovFaculty of Medicine, Humanitas University, Pieve Emanuele 20072, Italy.
Arosh S Perera Molligoda ArachchigeGHOL-Hopital de Nyon, Nyon 1260, Vaud, Switzerland. aroshperera@outlook.it.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Breast cancer is a leading cause of morbidity and mortality among women worldwide, and the limitations of conventional imaging, especially in women with dense breast tissue have sparked interest in safer, more accessible diagnostic alternatives. Microwave breast imaging (MBI) is a promising, non-ionizing, and potentially cost-effective modality that leverages dielectric contrasts between malignant and healthy tissues. This review presents MBI technologies, focusing on microwave tomography and radar-based techniques such as confocal microwave imaging and tissue-sensing adaptive radar. We evaluate system designs, antenna configurations, image reconstruction algorithms, and clinical performance from leading research groups. Additionally, we highlight the growing role of machine learning in enhancing image resolution, segmentation, and lesion classification. Despite encouraging results from early-phase clinical trials, challenges such as limited spatial resolution, anatomical variability, and high computational demands continue to hinder broader adoption. We outline future directions, including real-time motion correction, improved antenna sensitivity, and stronger clinical validation. With continued innovation and regulatory support, MBI has strong potential as an adjunct or alternative to current breast imaging modalities, especially for dense breast tissue and in resource-limited settings.

Indexed as

Antenna designBreast cancer detectionConfocal microwave imagingDeep learningDielectric propertiesImage reconstructionMicrowave breast imagingMicrowave tomographyNon-ionizing imagingRadar-based imaging

Identifiers

PMID42625963
PMCPMC13491166

What OpenQuestion holds

Textmetadata
Read underepoch 390

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.