Evidence map›Paper›PMID 30278830›Full record

ArticleTechnology in cancer research & treatment2018

An Automated Preprocessing Method for Diffuse Optical Tomography to Improve Breast Cancer Diagnosis.

Murad Althobaiti, Hamed Vavadi, Quing Zhu

Abstract read
In one paragraph

Article in Technology in cancer research & treatment, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing 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

5 citing papers in PubMed.

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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

3 authors.

Murad Althobaiti1 Biomedical Engineering Department, Imam Abdulrahman Bin Faisal University, Dammam, Saudi Arabia.
Hamed Vavadi2 Biomedical Engineering Department, University of Connecticut, Mansfield, CT, USA.ORCID 0000-0002-3054-0169
Quing Zhu3 Biomedical Engineering Department, Washington University in St Louis, St Louis, MO, USA.ORCID 0000-0002-1837-2588

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

The ultrasound-guided diffuse optical tomography is a noninvasive imaging technique for breast cancer diagnosis and treatment monitoring. The technique uses a handheld probe capable of providing measurements of multiple wavelengths in a few seconds. These measurements are used to estimate optical absorptions of lesions and calculate the total hemoglobin concentration. Any measurement errors caused by low signal to noise ratio data and/or movements during data acquisition would reduce the accuracy of reconstructed total hemoglobin concentration. In this article, we introduce an automated preprocessing method that combines data collected from multiple sets of lesion measurements of 4 optical wavelengths to detect and correct outliers in the perturbation. Two new measures of correlation between each pair of wavelength measurements and a wavelength consistency index of all reconstructed absorption maps are introduced. For phantom and patients' data without evidence of measurement errors, the correlation coefficient between each pair of wavelength measurements was above 0.6. However, for patients with measurement errors, the correlation coefficient was much lower. After applying the correction method to 18 patients' data with measurement errors, the correlation has improved and the wavelength consistency index is in the same range as the cases without wavelength-dependent measurement errors. The results show an improvement in classification of malignant and benign lesions.

Indexed as

AlgorithmsAutomationBreast NeoplasmsFemaleHumansImage Processing, Computer-AssistedPhantoms, ImagingTomography, OpticalUltrasonographybreast cancerdiffuse optical tomographyoptical imaging reconstructionultrasound

Identifiers

PMID30278830
PMCPMC6170968

What OpenQuestion holds

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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.