Evidence map›Paper›PMID 38396457›Full record

ArticleDiagnostics (Basel, Switzerland)2024

Artificial Intelligence-Enhanced Quantitative Ultrasound for Breast Cancer: Pilot Study on Quantitative Parameters and Biopsy Outcomes.

Hyuksool Kwon, Seokhwan Oh, Myeong-Gee Kim, Youngmin Kim, Guil Jung, Hyeon-Jik Lee, Sang-Yun Kim, Hyeon-Min Bae

Abstract read
In one paragraph

Article in Diagnostics (Basel, Switzerland), 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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.

Hyuksool KwonLaboratory of Quantitative Ultrasound Imaging, Seoul National University Bundang Hospital, Seong-nam 13620, Republic of Korea.ORCID 0000-0002-0960-0198
Seokhwan OhLaboratory of Quantitative Ultrasound Imaging, Seoul National University Bundang Hospital, Seong-nam 13620, Republic of Korea.
Myeong-Gee KimElectrical Engineering Department, Korea Advanced Institute of Science and Technology, Daejeon 34141, Republic of Korea.ORCID 0000-0001-7269-3959
Youngmin KimElectrical Engineering Department, Korea Advanced Institute of Science and Technology, Daejeon 34141, Republic of Korea.
Guil JungElectrical Engineering Department, Korea Advanced Institute of Science and Technology, Daejeon 34141, Republic of Korea.ORCID 0009-0008-0117-1393
Hyeon-Jik LeeElectrical Engineering Department, Korea Advanced Institute of Science and Technology, Daejeon 34141, Republic of Korea.
Sang-Yun KimElectrical Engineering Department, Korea Advanced Institute of Science and Technology, Daejeon 34141, Republic of Korea.
Hyeon-Min BaeElectrical Engineering Department, Korea Advanced Institute of Science and Technology, Daejeon 34141, Republic of Korea.

Funding

Korea Medical Device Development RS-2020-KD000007SNUBH Research Fund 16-2020-0001
6 · The paper itself

Abstract

Traditional B-mode ultrasound has difficulties distinguishing benign from malignant breast lesions. It appears that Quantitative Ultrasound (QUS) may offer advantages. We examined the QUS imaging system's potential, utilizing parameters like Attenuation Coefficient (AC), Speed of Sound (SoS), Effective Scatterer Diameter (ESD), and Effective Scatterer Concentration (ESC) to enhance diagnostic accuracy. B-mode images and radiofrequency signals were gathered from breast lesions. These parameters were processed and analyzed by a QUS system trained on a simulated acoustic dataset and equipped with an encoder-decoder structure. Fifty-seven patients were enrolled over six months. Biopsies served as the diagnostic ground truth. AC, SoS, and ESD showed significant differences between benign and malignant lesions (

Indexed as

artificial intelligencebreast cancerquantitative ultrasound

Identifiers

PMID38396457
PMCPMC10888332

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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.