Evidence map›Paper›PMID 37495921›Full record

ArticleAdvances in experimental medicine and biology2023

Clinical Importance of 3D Volography in Breast Imaging.

John Klock

Abstract read
PubMed Publisher
In one paragraph

Article in Advances in experimental medicine and biology, 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
–field-weighted citation impact, top 58% 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, 0 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

1 author at 1 institution in 1 country.

John KlockQT Imaging, Novato, CA, USA. john.klock@qtimaging.com.
QT Ultrasound (United States) · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The clinical applications of the volography algorithm and concomitant refraction-corrected reflection algorithm as described in Chap. 10 are discussed here. Comparisons with an H&E stained image, discussion of glandular tissue visibility, related biomarkers, segmentation accuracy and capabilities, microcalcification and cyst detection and analysis, and various VGA and clinical studies show the unique capabilities of the method. The accuracy of the fibroglandular segmentation and its relevance to breast density in imaging is mentioned. The compatibility with artificial intelligence (AI) is shown and clinical results discussed, concluding that low-frequency 3D ultrasound volography is a powerful 3D ultrasound imaging technique for microanatomic and quantitative features of the breast with good potential for AI utilization to provide an imaging technique that will quantitatively improve clinical performance.

Indexed as

Artificial IntelligenceClinical RelevanceAlgorithmsImaging, Three-DimensionalBreast cancerMicrocalcificationSpeed-of-sound imagingUltrasound tomography

Identifiers

PMID37495921
OpenAlexW4385267620

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

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.