Evidence map›Paper›PMID 28091596›Full record

ArticleScientific reports2017

Non-invasive optical estimate of tissue composition to differentiate malignant from benign breast lesions: A pilot study.

Paola Taroni, Anna Maria Paganoni, Francesca Ieva, Antonio Pifferi, Giovanna Quarto, Francesca Abbate, Enrico Cassano, Rinaldo Cubeddu

Registry-linked trialOpen access · goldAbstract read
In one paragraph

Article in Scientific reports, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT04767659 (Optical Monitoring of Neoadjuvant Chemotherapy and Prediction of Pathological Complete Response in Breast Cancer Patients), which is not on this map. Cited by 30 papers.

0numbers the graph read from it
0cells of the map it votes in
30citing papers in PubMed
6.2field-weighted citation impact, top 3% 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.

NCT04767659 narecruitingnot on this mapstarted 2020, after this paper: background citation

Optical Monitoring of Neoadjuvant Chemotherapy and Prediction of Pathological Complete Response in Breast Cancer Patients

TypeinterventionalSponsorIRCCS San RaffaeleRan2020 to 2025Enrolled20ConditionsBreast Cancer Female, Chemotherapy EffectArmsMAMMOT2
3 · Its place in the literature

Who cites it

30 citing papers in PubMed, 88 citations in OpenAlex.

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  6. Experience using 675 nm laser on three cases of Fitzpatrick skin type IV-V with melasma.Skin research and technology : official journal of International Society for Bioengineering and the Skin (ISBS) [and] International Society for Digital Imaging of Skin (ISDIS) [and] International Society for Skin Imaging (ISSI) · 2024
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  9. The 675-nm wavelength for treating facial melasma.Skin research and technology : official journal of International Society for Bioengineering and the Skin (ISBS) [and] International Society for Digital Imaging of Skin (ISDIS) [and] International Society for Skin Imaging (ISSI) · 2023
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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 3 institutions in 1 country.

Paola TaroniDipartimento di Fisica, Politecnico di Milano, Piazza Leonardo da Vinci 32, 20133 Milano, Italy.
Anna Maria PaganoniDipartimento di Matematica, Politecnico di Milano, Piazza Leonardo da Vinci 32, 20133 Milano, Italy.
Francesca IevaDipartimento di Matematica, Università degli Studi, Via Saldini 50, 20133 Milano, Italy.
Antonio PifferiDipartimento di Fisica, Politecnico di Milano, Piazza Leonardo da Vinci 32, 20133 Milano, Italy.
Giovanna QuartoDipartimento di Fisica, Politecnico di Milano, Piazza Leonardo da Vinci 32, 20133 Milano, Italy.
Francesca AbbateEuropean Institute of Oncology, Breast Imaging Unit, Via G. Ripamonti, 435, 20141 Milano, Italy.
Enrico CassanoEuropean Institute of Oncology, Breast Imaging Unit, Via G. Ripamonti, 435, 20141 Milano, Italy.
Rinaldo CubedduDipartimento di Fisica, Politecnico di Milano, Piazza Leonardo da Vinci 32, 20133 Milano, Italy.
Politecnico di Milano · ITRipamonti · ITUniversity of Milan · IT

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Several techniques are being investigated as a complement to screening mammography, to reduce its false-positive rate, but results are still insufficient to draw conclusions. This initial study explores time domain diffuse optical imaging as an adjunct method to classify non-invasively malignant vs benign breast lesions. We estimated differences in tissue composition (oxy- and deoxyhemoglobin, lipid, water, collagen) and absorption properties between lesion and average healthy tissue in the same breast applying a perturbative approach to optical images collected at 7 red-near infrared wavelengths (635-1060 nm) from subjects bearing breast lesions. The Discrete AdaBoost procedure, a machine-learning algorithm, was then exploited to classify lesions based on optically derived information (either tissue composition or absorption) and risk factors obtained from patient's anamnesis (age, body mass index, familiarity, parity, use of oral contraceptives, and use of Tamoxifen). Collagen content, in particular, turned out to be the most important parameter for discrimination. Based on the initial results of this study the proposed method deserves further investigation.

Indexed as

Area Under CurveBody CompositionBreastBreast NeoplasmsDiagnosis, DifferentialFemaleHumansImage Processing, Computer-AssistedMammographySpectrum Analysis

Identifiers

PMID28091596
PMCPMC5238417
OpenAlexW2574744404

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

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.