Evidence map›Paper›PMID 32728378›Full record

ReviewEcancermedicalscience2020

Automatic breast ultrasound: state of the art and future perspectives.

Luca Nicosia, Federica Ferrari, Anna Carla Bozzini, Antuono Latronico, Chiara Trentin, Lorenza Meneghetti, Filippo Pesapane, Maria Pizzamiglio, Nicola Balesetreri, Enrico Cassano

Abstract readReview
In one paragraph

Review in Ecancermedicalscience, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.

0numbers the graph read from it
0cells of the map it votes in
15citing papers in PubMed
–field-weighted citation impact
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

15 citing papers in PubMed.

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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

10 authors.

Luca NicosiaDepartment of Breast Radiology, European Institute of Oncology, 20141 Milan, Italy.
Federica FerrariPostgraduation School in Radiodiagnostics, Università degli Studi di Milano, 20122 Milan, Italy.
Anna Carla BozziniDepartment of Breast Radiology, European Institute of Oncology, 20141 Milan, Italy.
Antuono LatronicoDepartment of Breast Radiology, European Institute of Oncology, 20141 Milan, Italy.
Chiara TrentinDepartment of Breast Radiology, European Institute of Oncology, 20141 Milan, Italy.
Lorenza MeneghettiDepartment of Breast Radiology, European Institute of Oncology, 20141 Milan, Italy.
Filippo PesapaneDepartment of Breast Radiology, European Institute of Oncology, 20141 Milan, Italy.
Maria PizzamiglioDepartment of Breast Radiology, European Institute of Oncology, 20141 Milan, Italy.
Nicola BalesetreriDepartment of Radiology, European Institute of Oncology, 20141 Milan, Italy.
Enrico CassanoDepartment of Breast Radiology, European Institute of Oncology, 20141 Milan, Italy.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The three-dimensional automated breast ultrasound system (3D ABUS) is a new device which represents a huge innovation in the breast ultrasound field, with several application scenarios of great interest. ABUS's aim is to solve some of the main defects of traditional ultrasound, such as lack of standardization, high level of skill non-reproducibility, small field of view and high commitment of physician time. ABUS has proven to be an excellent non-ionising alternative to other supplemental screening options for women with dense breast tissue; also, it has appeared to be very promising in daily clinical practice. The purpose of this paper is to present a summary of current applications of ABUS, focusing on clinical applications and future perspectives as ABUS is particularly promising for studies involving artificial intelligence, radiomics and evaluation of breast molecular subtypes.

Indexed as

automatic breast ultrasoundclinical practiceretraction phenomenonscreening

Identifiers

PMID32728378
PMCPMC7373644

What OpenQuestion holds

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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.