Evidence map›Paper›PMID 29127043›Full record

ReviewMethods (San Diego, Calif.)2018

Fourier phase based depth-resolved nanoscale nuclear architecture mapping for cancer detection.

Shikhar Uttam, Yang Liu

Open access · greenAbstract readReview
In one paragraph

Review in Methods (San Diego, Calif.), 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
1.1field-weighted citation impact, top 21% 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

5 citing papers in PubMed, 11 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

2 authors at 2 institutions in 1 country.

Shikhar UttamDepartment of Computational and Systems Biology, University of Pittsburgh, Pittsburgh, PA, United States. Electronic address: shf28@pitt.edu.
Yang LiuBiomedical Optical Imaging Laboratory, Departments of Medicine and Bioengineering, University of Pittsburgh, Pittsburgh, PA, United States; University of Pittsburgh Cancer Institute, Pittsburgh, PA, United States. Electronic address: liuy@pitt.edu.
University of Pittsburgh · USUPMC Hillman Cancer Center · US

Funding

Novel Nanoscale Single-Cell Analysis of Exfoliative CytologyR01EB016657 · NIBIB · UNIVERSITY OF PITTSBURGH AT PITTSBURGH · PI LIU, YANG · 2013 to 2016
$1.3M
(PQC2)Nanoscale changes in 3D nuclear architecture during breast tumorigenesisR01CA185363 · NCI · UNIVERSITY OF PITTSBURGH AT PITTSBURGH · PI LIU, YANG · 2014 to 2017
$1.3M
NCI NIH HHS R01 CA185363NIBIB NIH HHS R01 EB016657
6 · The paper itself

Abstract

Quantitative phase imaging (QPI) modality has been widely adopted in a variety of applications ranging from identifying photomask defects in lithography to characterizing cell structure and tissue morphology in cancer. Traditional QPI utilizes the electromagnetic phase of transmitted light to measure, with nanometer scale sensitivity, alterations in the optical thickness of a sample of interest. In our work, the QPI paradigm is generalized to study depth-resolved properties of phase objects with slowly varying refractive index without a strong interface by utilizing the Fourier phase associated with Fourier-domain optical coherence tomography (FD-OCT). Specifically, based on computing the Fourier phase of light back-scattered by cell nuclei, we have developed nanoscale nuclear architecture mapping (nanoNAM) method that quantifies, with nanoscale sensitivity, (a) the depth-resolved alterations in mean nuclear optical density, and (b) depth-resolved localized heterogeneity in optical density of the cell nuclei. We have used nanoNAM to detect malignant transformation in colon carcinogenesis, even in tissue that appears histologically normal according to pathologists, thereby showing its potential as a pathology aid in cases where pathology examination remains inconclusive, and for screening patient populations at risk of developing cancer. In this paper, we integrate all aspects of nanoNAM, from principle through instrumentation and analysis, to show that nanoNAM is a promising, low-cost, and label-free method for identifying pathologically indeterminate pre-cancerous and cancerous cells. Importantly, it can seamlessly integrate into the clinical pipeline by utilizing clinically prepared formalin-fixed, paraffin-embedded tissue sections.

Indexed as

Cell NucleusFourier AnalysisHumansImage Interpretation, Computer-AssistedNeoplasmsTomography, Optical Coherence

Identifiers

PMID29127043
PMCPMC5857421
OpenAlexW2768067069

What OpenQuestion holds

Textmetadata
LicenceTDM
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.