Evidence map›Paper›PMID 30350491›Full record

ArticleJournal of biomedical optics2018

Compact ultrasound-guided diffuse optical tomography system for breast cancer imaging.

Hamed Vavadi, Atahar Mostafa, Feifei Zhou, K M Shihab Uddin, Murad Althobaiti, Chen Xu, Rajeev Bansal, Foluso Ademuyiwa, Steven Poplack, Quing Zhu

Abstract read
In one paragraph

Article in Journal of biomedical optics, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 33 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
33citing papers in PubMed, 1 pooled it
–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

33 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Convolutional-transformer fusion of ultrasound and diffuse optical tomography for breast lesion classification.Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society · 2026
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  19. Deep learning in macroscopic diffuse optical imaging.Journal of biomedical optics · 2022
    Review
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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.

Hamed VavadiUniversity of Connecticut, BME and ECE Departments, Connecticut, United States.
Atahar MostafaWashington University in St. Louis, Department of Biomedical Engineering, St. Louis, Missouri, United States.
Feifei ZhouUniversity of Connecticut, BME and ECE Departments, Connecticut, United States.
K M Shihab UddinWashington University in St. Louis, Department of Biomedical Engineering, St. Louis, Missouri, United States.
Murad AlthobaitiUniversity of Connecticut, BME and ECE Departments, Connecticut, United States.
Chen XuNew York City College of Technology, Brooklyn, New York, United States.
Rajeev BansalUniversity of Connecticut, BME and ECE Departments, Connecticut, United States.
Foluso AdemuyiwaWashington University School of Medicine, Department of Medical Oncology, St. Louis, Missouri, United States.
Steven PoplackWashington University School of Medicine, Department of Radiology, St. Louis, Missouri, United States.
Quing ZhuWashington University in St. Louis, Department of Biomedical Engineering, St. Louis, Missouri, United States.

Funding

Near Infrared Diffused Light Imaging with Ultrasound Guidance: Predicting Neoadjuvant Chemotherapy ResponseR01EB002136 · NIBIB · WASHINGTON UNIVERSITY · PI ZHU, QUING · 2003 to 2016
$3.4M
NIBIB NIH HHS R01 EB002136
6 · The paper itself

Abstract

Near-infrared diffuse optical tomography (DOT) has demonstrated a great potential as an adjunct modality for differentiation of malignant and benign breast lesions and for monitoring treatment response in patients with locally advanced breast cancers. The path toward commercialization of DOT techniques depends upon the improvement of robustness and user-friendliness of this technique in hardware and software. In this study, we introduce our recently developed ultrasound-guided DOT system, which has been improved in system compactness, robustness, and user-friendliness by custom-designed electronics, automated data preprocessing, and implementation of a new two-step reconstruction algorithm. The system performance has been tested with several sets of solid and blood phantoms and the results show accuracy in reconstructed absorption coefficients as well as blood oxygen saturation. A clinical example of a breast cancer patient, who was undergoing neoadjuvant chemotherapy, is given to demonstrate the system performance.

Indexed as

Breast NeoplasmsFemaleHumansSpectroscopy, Near-InfraredTomography, OpticalUltrasonography, Mammarydiffuse optical tomographyimaging reconstructionnear-infrared instrumentultrasound

Identifiers

PMID30350491
PMCPMC6197842

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.