Evidence map›Paper›PMID 39318571›Full record

ReviewThe Indian journal of radiology & imaging2024

Ultrasound-Based Noncontrast Microvascular Imaging for Evaluation of Breast Lesions: Imaging Techniques and Review of Diagnostic Criteria.

Namita Mohindra, Neetu Soni

Abstract readReview
In one paragraph

Review in The Indian journal of radiology & imaging, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Review
  2. 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

2 authors.

Namita MohindraDepartment of Radio-diagnosis, Sanjay Gandhi Postgraduate Institute of Medical Sciences, Rae Bareli Road, Lucknow, Uttar Pradesh, India.ORCID 0000-0003-3043-1218
Neetu SoniRadiology, Mayo Clinic, Jacksonville, Florida, United States.ORCID 0000-0003-2082-1634

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Vascularity plays a pivotal role in the progression of breast lesions and may be associated with their aggressiveness and likelihood of being malignant. Contrast-enhanced imaging techniques are necessary to evaluate vascularity due to the limited sensitivity of conventional color Doppler techniques, in which motion artifacts are eliminated using wall filters. However, in this process, low-flow signals from small vessels also get removed unintentionally. Advancements in technology have revolutionized the way ultrasound images are generated, resulting in tremendous improvements in Doppler imaging techniques. The new, ultrasound-based noncontrast microvascular imaging techniques overcome the limitations of conventional Doppler, and are highly sensitive for detecting microvessels and low flow. The resultant high Doppler sensitivity leads to detection of vascularity in more breast lesions. It is important for radiologists to understand the imaging principles and the clinical implications of the new techniques, to optimally utilize them and aid correct diagnosis. Angio-PLUS is one such recent advancement, which uses unfocused or plane waves and three-dimensional wall filtering to analyze tissue motion in time, space, and amplitude domains that effectively distinguish between blood flow and tissue. The information is beneficial for assessing the lesion vascularity without using contrast. This article aims to explain the Doppler imaging techniques, their clinical applications, scanning methods, and review the common Doppler-based diagnostic criteria used in the evaluation of breast lesions.

Indexed as

Angio-PLUSbreast cancerbreast lesionsDoppler imagingultrasound-based microvascular imaging

Identifiers

PMID39318571
PMCPMC11419773

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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.