ReviewWorld journal of methodology2026
Microwave breast imaging: A review of clinical potential and technological advances.
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.
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.
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.
Who cites it
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
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Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
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.
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Registered trials
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.