Evidence map›Paper›PMID 36140137›Full record

ArticleBiosensors2022

Non-Invasive Microwave-Based Imaging System for Early Detection of Breast Tumours.

Carolina Blanco-Angulo, Andrea Martínez-Lozano, Roberto Gutiérrez-Mazón, Carlos G Juan, Héctor García-Martínez, Julia Arias-Rodríguez, José M Sabater-Navarro, Ernesto Ávila-Navarro

Open access · goldAbstract read
In one paragraph

Article in Biosensors, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed
2.0field-weighted citation impact, top 15% 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

9 citing papers in PubMed, 27 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

8 authors at 1 institution in 1 country.

Carolina Blanco-AnguloDepartment of Materials Science, Optics and Electronic Technology, Miguel Hernández University of Elche, 03202 Elche, Spain.ORCID 0000-0002-4923-4604
Andrea Martínez-LozanoDepartment of Materials Science, Optics and Electronic Technology, Miguel Hernández University of Elche, 03202 Elche, Spain.ORCID 0000-0002-1320-3312
Roberto Gutiérrez-MazónDepartment of Communications Engineering, Miguel Hernández University of Elche, 03202 Elche, Spain.ORCID 0000-0002-6391-2168
Carlos G JuanNeuroengineering Biomedical Research Group, Institute of Bioengineering, Miguel Hernández University of Elche, 03202 Elche, Spain.ORCID 0000-0003-0793-7958
Héctor García-MartínezDepartment of Materials Science, Optics and Electronic Technology, Miguel Hernández University of Elche, 03202 Elche, Spain.ORCID 0000-0001-6679-9378
Julia Arias-RodríguezDepartment of Materials Science, Optics and Electronic Technology, Miguel Hernández University of Elche, 03202 Elche, Spain.ORCID 0000-0001-7608-8879
José M Sabater-NavarroNeuroengineering Biomedical Research Group, Institute of Bioengineering, Miguel Hernández University of Elche, 03202 Elche, Spain.ORCID 0000-0002-3890-6225
Ernesto Ávila-NavarroDepartment of Materials Science, Optics and Electronic Technology, Miguel Hernández University of Elche, 03202 Elche, Spain.ORCID 0000-0002-2856-5367
Universitat de Miguel Hernández d'Elx · ES

Funding

AEI (Spanish Research State Agency) Race project (ref. PID2019-111023RB-C32)Conselleria de Innovación, Universidades, Ciencia y Sociedad Digital and European Social Fund ACIF/2020/147Ministry of Universities in the Government of Spain, the European Union-NextGenerationEU and Miguel Hernández University of Elche Margarita Salas
6 · The paper itself

Abstract

This work introduces a microwave-based system able to detect tumours in breast phantoms in a non-invasive way. The data acquisition system is composed of a hardware system which involves high-frequency components (antennas, switches and cables), a microcontroller, a vector network analyser used as measurement instrument and a computer devoted to the control and automation of the operation of the system. Concerning the software system, the computer runs a Python script which is in charge of mastering and automatising all the required stages for the data acquisition, from initialisation of the hardware system to performing and saving the measurements. We also report on the design of the high-performance broadband antenna used to carry out the measurements, as well as on the algorithm employed to build the final medical images, based on an adapted version of the so-called Improved Delay-and-Sum (IDAS) algorithm improved by a Hamming window filter and averaging preprocessing. The calibration and start-up of the system are also described. The experimental validation includes the use of different tumour models with different dielectric properties inside the breast phantom. The results show promising tumour detection capabilities, even when there is low dielectric contrast between the tumoural and healthy tissues, as is the usual case for dense breasts in young women.

Indexed as

Breast NeoplasmsMicrowavesAlgorithmsCalibrationFemaleHumansPhantoms, Imagingbreast phantommedical imagingmicrowave-based measurementnon-invasive measurementRadio-Frequency antenna systemTRITON X-100tumour detection

Identifiers

PMID36140137
PMCPMC9496561
OpenAlexW4295560422

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.