Evidence map›Paper›PMID 37957665›Full record

ArticleJournal of biological engineering2023

Label-free multimodal electro-thermo-mechanical (ETM) phenotyping as a novel biomarker to differentiate between normal, benign, and cancerous breast biopsy tissues.

Anil Vishnu G K, Gayatri Gogoi, Midhun C Kachappilly, Annapoorni Rangarajan, Hardik J Pandya

Open access · goldAbstract read
In one paragraph

Article in Journal of biological engineering, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
0.4field-weighted citation impact, top 26% 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

1 citing paper in PubMed, 1 citations in OpenAlex.

  1. 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

5 authors at 2 institutions in 1 country.

Anil Vishnu G KCenter for BioSystems Science and Engineering, Indian Institute of Science, Bangalore, Karnataka, 560012, India.
Gayatri GogoiDepartment of Pathology, Assam Medical College, Dibrugarh, Assam, 786002, India.
Midhun C KachappillyDepartment of Electronic Systems Engineering, Indian Institute of Science, Bangalore, Karnataka, 560012, India.
Annapoorni RangarajanDepartment of Developmental Biology and Genetics, Indian Institute of Science, Bangalore, Karnataka, 560012, India.
Hardik J PandyaDepartment of Electronic Systems Engineering, Indian Institute of Science, Bangalore, Karnataka, 560012, India. hjpandya@iisc.ac.in.
Indian Institute of Science Bangalore · INAssam Medical College · IN

Funding

Biotechnology Industry Research Assistance Council BIRAC SRISTI PMU-2020/001Department of Science and Technology, Ministry of Science and Technology, India SP-DSTO-0019Indian Council of Medical Research 17X(3)/Ad-hoc/81/2022-ITRScience and Engineering Research Board CRG/2019/004963
6 · The paper itself

Abstract

backgroundTechnologies for quick and label-free diagnosis of malignancies from breast tissues have the potential to be a significant adjunct to routine diagnostics. The biophysical phenotypes of breast tissues, such as its electrical, thermal, and mechanical properties (ETM), have the potential to serve as novel markers to differentiate between normal, benign, and malignant tissue.

resultsWe report a system-of-biochips (SoB) integrated into a semi-automated mechatronic system that can characterize breast biopsy tissues using electro-thermo-mechanical sensing. The SoB, fabricated on silicon using microfabrication techniques, can measure the electrical impedance (Z), thermal conductivity (K), mechanical stiffness (k), and viscoelastic stress relaxation (%R) of the samples. The key sensing elements of the biochips include interdigitated electrodes, resistance temperature detectors, microheaters, and a micromachined diaphragm with piezoresistive bridges. Multi-modal ETM measurements performed on formalin-fixed tumour and adjacent normal breast biopsy samples from N = 14 subjects were able to differentiate between invasive ductal carcinoma (malignant), fibroadenoma (benign), and adjacent normal (healthy) tissues with a root mean square error of 0.2419 using a Gaussian process classifier. Carcinoma tissues were observed to have the highest mean impedance (110018.8 ± 20293.8 Ω) and stiffness (0.076 ± 0.009 kNm

conclusionsThe work presents a novel strategy to characterize the multi-modal biophysical phenotype of breast biopsy tissues to aid in cancer diagnosis from small-sized tumour samples. The methodology envisions to supplement the existing technology gap in the analysis of breast tissue samples in the pathology laboratories to aid the diagnostic workflow.

Indexed as

Biophysical phenotypingBreast cancerDiagnosticsGaussian processMicrosensors

Identifiers

PMID37957665
PMCPMC10644568
OpenAlexW4388627398

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LicenceCC BY
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Registered trials

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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 OpenQuestion graph.