Evidence map›Paper›PMID 23613927›Full record

ArticlePloS one2013

Wavelength optimization for quantitative spectral imaging of breast tumor margins.

Justin Y Lo, J Quincy Brown, Sulochana Dhar, Bing Yu, Gregory M Palmer, Nan M Jokerst, Nirmala Ramanujam

Abstract read
In one paragraph

Article in PloS one, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing 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

9 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

7 authors.

Justin Y LoDepartment of Biomedical Engineering, Duke University, Durham, North Carolina, United States of America. justin.lo@duke.edu
J Quincy Brown
Sulochana Dhar
Bing Yu
Gregory M Palmer
Nan M Jokerst
Nirmala Ramanujam

Funding

A Novel Optical Spectral Imaging System for Rapid Imaging of Breast Tumor MarginsR01EB011574 · NIBIB · DUKE UNIVERSITY · PI RAMANUJAM, NIRMALA · 2011 to 2015
$4.9M
NIBIB NIH HHS 1R01EB011574-01NIBIB NIH HHS R01 EB011574
6 · The paper itself

Abstract

A wavelength selection method that combines an inverse Monte Carlo model of reflectance and a genetic algorithm for global optimization was developed for the application of spectral imaging of breast tumor margins. The selection of wavelengths impacts system design in cost, size, and accuracy of tissue quantitation. The minimum number of wavelengths required for the accurate quantitation of tissue optical properties is 8, with diminishing gains for additional wavelengths. The resulting wavelength choices for the specific probe geometry used for the breast tumor margin spectral imaging application were tested in an independent pathology-confirmed ex vivo breast tissue data set and in tissue-mimicking phantoms. In breast tissue, the optical endpoints (hemoglobin, β-carotene, and scattering) that provide the contrast between normal and malignant tissue specimens are extracted with the optimized 8-wavelength set with <9% error compared to the full spectrum (450-600 nm). A multi-absorber liquid phantom study was also performed to show the improved extraction accuracy with optimization and without optimization. This technique for selecting wavelengths can be used for designing spectral imaging systems for other clinical applications.

Indexed as

AlgorithmsBreast NeoplasmsHumansMonte Carlo Method

Identifiers

PMID23613927
PMCPMC3629043

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.