Evidence map›Paper›PMID 31435620›Full record

ArticleMedical devices & sensors2018

High-speed Intraoperative Assessment of Breast Tumor Margins by Multimodal Ultrasound and Photoacoustic Tomography.

Rui Li, Lu Lan, Yan Xia, Pu Wang, Linda K Han, Gary L Dunnington, Samilia Obeng-Gyasi, George E Sandusky, Jennifer A Medley, Susan T Crook and 1 more

Open access · diamondAbstract read
In one paragraph

Article in Medical devices & sensors, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
12citing papers in PubMed, 1 pooled it
0.9field-weighted citation impact, top 27% 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

12 citing papers in PubMed, 1 synthesis or guideline pooled it, 21 citations in OpenAlex.

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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

11 authors at 5 institutions in 2 countries.

Rui Li *Weldon School of Biomedical Engineering, Purdue University, 206 S Martin Jischke Dr., West Lafayette, Indiana, 47907, USA.
Lu Lan *Weldon School of Biomedical Engineering, Purdue University, 206 S Martin Jischke Dr., West Lafayette, Indiana, 47907, USA.
Yan XiaVibronix, Inc., 1281 Win Hentschel Blvd., West Lafayette, Indiana, 47906, USA.
Pu WangVibronix, Inc., 1281 Win Hentschel Blvd., West Lafayette, Indiana, 47906, USA.
Linda K HanIndiana University Health Melvin and Bren Simon Cancer Center, 1030 W. Michigan St., Breast Center, Indianapolis, Indiana 46202, USA.
Gary L DunningtonIndiana University Health Melvin and Bren Simon Cancer Center, 1030 W. Michigan St., Breast Center, Indianapolis, Indiana 46202, USA.
Samilia Obeng-GyasiIndiana University Health Melvin and Bren Simon Cancer Center, 1030 W. Michigan St., Breast Center, Indianapolis, Indiana 46202, USA.
George E SanduskyDepartment of Pathology & Laboratory Medicine, Indiana University School of Medicine, 350 West 11th Street, Indianapolis, Indiana, 46202, USA.
Jennifer A MedleyDepartment of Radiology and Imaging Sciences, Indiana University School of Medicine, 550 N. University Blvd, Indianapolis, Indiana 46202, USA.
Susan T CrookDepartment of Radiology and Imaging Sciences, Indiana University School of Medicine, 550 N. University Blvd, Indianapolis, Indiana 46202, USA.
Ji-Xin ChengWeldon School of Biomedical Engineering, Purdue University, 206 S Martin Jischke Dr., West Lafayette, Indiana, 47907, USA.
Indiana Cancer Consortium · USPurdue University West Lafayette · USIndiana University School of MedicineVizSeek (United States) · USIndiana University – Purdue University Indianapolis · US

Funding

High-speed Intraoperative Assessment of Breast Tumor Margin using MarginPATR41CA200006 · NCI · VIBRONIX, INC. · PI CHENG, JI-XIN · 2016 to 2017
$276k
NCI NIH HHS R41 CA200006
6 · The paper itself

Abstract

Conventional methods for breast tumor margins assessment need a long turnaround time, which may lead to re-operation for patients undergoing lumpectomy surgeries. Photoacoustic tomography (PAT) has been shown to visualize adipose tissue in small animals and human breast. Here, we demonstrate a customized multimodal ultrasound and PAT system for intraoperative breast tumor margins assessment using fresh lumpectomy specimens from 66 patients. The system provides the margin status of the entire excised tissue within 10 minutes. By subjective reading of three researchers, the results show 85.7% [95% confidence interval (CI), 42.0% - 99.2%] sensitivity and 84.6% (95% CI, 53.7% - 97.3%) specificity, 71.4% (95% CI, 30.3% - 94.9%) sensitivity and 92.3% (95% CI, 62.1% - 99.6%) specificity, and 100% (95% CI, 56.1% - 100%) sensitivity and 53.9% (95% CI, 26.1% - 79.6%) specificity respectively when cross-correlated with post-operational histology. Furthermore, a machine learning-based algorithm is deployed for margin assessment in the challenging ductal carcinoma

Indexed as

breast cancerimaginglipidmargin statusphotoacoustic tomography

Identifiers

PMID31435620
PMCPMC6703831
OpenAlexW2902091218

What OpenQuestion holds

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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.