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Evaluating the Performance of Algorithms in Axillary Microwave Imaging towards Improved Breast Cancer Staging

2023-01-29Artigo científico Acesso aberto
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dc.contributor.authorPato, Matilde
dc.contributor.authorEleutério, Ricardo
dc.contributor.authorConceição, Raquel C.
dc.contributor.authorGodinho, Daniela M.
dc.contributor.institutionDF – Departamento de Física
dc.contributor.pblMDPI - Multidisciplinary Digital Publishing Institute
dc.date.accessioned2023-09-28T22:20:21Z
dc.date.available2023-09-28T22:20:21Z
dc.date.issued2023-01-29
dc.descriptionPublisher Copyright: © 2023 by the authors.
dc.description.abstractBreast cancer is the most common and the fifth deadliest cancer worldwide. In more advanced stages of cancer, cancer cells metastasize through lymphatic and blood vessels. Currently there is no satisfactory neoadjuvant (i.e., preoperative) diagnosis to assess whether cancer has spread to neighboring Axillary Lymph Nodes (ALN). This paper addresses the use of radar Microwave Imaging (MWI) to detect and determine whether ALNs have been metastasized, presenting an analysis of the performance of different artifact removal and beamformer algorithms in distinct anatomical scenarios. We assess distinct axillary region models and the effect of varying the shape of the skin, muscle and subcutaneous adipose tissue layers on single ALN detection. We also study multiple ALN detection and contrast between healthy and metastasized ALNs. We propose a new beamformer algorithm denominated Channel-Ranked Delay-Multiply-And-Sum (CR-DMAS), which allows the successful detection of ALNs in order to achieve better Signal-to-Clutter Ratio, e.g., with the muscle layer up to (Formula presented.) dB, a Signal-to-Mean Ratio of up to (Formula presented.) dB and a Location Error of (Formula presented.) mm. In multiple target detection, CR-DMAS outperformed other well established beamformers used in the context of breast MWI. Overall, this work provides new insights into the performance of algorithms in axillary MWI.en
dc.description.versionpublishersversion
dc.description.versionpublished
dc.format.extent15
dc.format.extent6527955
dc.identifier.doi10.3390/s23031496
dc.identifier.issn1424-8220
dc.identifier.otherPURE: 72174695
dc.identifier.otherPURE UUID: 10715095-af48-4a47-b807-b4c4c371e74c
dc.identifier.otherScopus: 85147892841
dc.identifier.otherWOS: 000932966800001
dc.identifier.otherPubMed: 36772536
dc.identifier.otherPubMedCentral: PMC9920014
dc.identifier.urihttp://hdl.handle.net/10362/158429
dc.identifier.urlhttps://www.scopus.com/pages/publications/85147892841
dc.language.isoeng
dc.peerreviewedyes
dc.relationFunding Information: info:eu-repo/grantAgreement/FCT/6817 - DCRRNI ID/UIDB%2F00645%2F2020/PT
dc.subjectaxillary lymph nodes
dc.subjectbeamformer algorithms
dc.subjectbreast cancer staging
dc.subjectmicrowave imaging
dc.subjectAnalytical Chemistry
dc.subjectInformation Systems
dc.subjectAtomic and Molecular Physics, and Optics
dc.subjectBiochemistry
dc.subjectInstrumentation
dc.subjectElectrical and Electronic Engineering
dc.subjectSDG 3 - Good Health and Well-being
dc.titleEvaluating the Performance of Algorithms in Axillary Microwave Imaging towards Improved Breast Cancer Stagingen
dc.typejournal article
degois.publication.issue3
degois.publication.titleSensors
degois.publication.volume23
dspace.entity.typePublication
rcaap.rightsopenAccess

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