Evidence map›Paper›PMID 27861201›Full record

ArticlePancreas2017

Tissue Classification Using Optical Spectroscopy Accurately Differentiates Cancer and Chronic Pancreatitis.

Robert H Wilson, Malavika Chandra, James M Scheiman, Seung Yup Lee, Oliver E Lee, Barbara J McKenna, Diane M Simeone, Jeremy M G Taylor, Mary-Ann Mycek

Abstract read
In one paragraph

Article in Pancreas, 2017. 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
2.0field-weighted citation impact, top 10% 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, 12 citations in OpenAlex.

  1. Article
  2. Article
  3. Observational
  4. Article
  5. Article
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

9 authors at 1 institution in 1 country.

Robert H WilsonFrom the *Department of Biomedical Engineering, †Department of Internal Medicine, ‡Comprehensive Cancer Center §Department of Biostatistics, ∥Department of Pathology, and ¶Department of Surgery, University of Michigan, Ann Arbor, MI.
Malavika Chandra
James M Scheiman
Seung Yup Lee
Oliver E Lee
Barbara J McKenna
Diane M Simeone
Jeremy M G Taylor
Mary-Ann Mycek
U.S. National Science Foundation · US

Funding

Biostatistics Training Program in Cancer ResearchT32CA083654 · NCI · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI Veerabhadran Baladandayuthapani, Kelley McLain Kidwell · 2002 to 2026
$4.3M
Photon Migration Codes for Tissue Spectroscopy &ImagingR01CA114542 · NCI · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI MYCEK, MARY-ANN · 2005 to 2008
$840k
NCI NIH HHS R01 CA114542NCI NIH HHS T32 CA083654
6 · The paper itself

Abstract

objectivesCurrent pancreatic cancer diagnostics cannot reliably detect early disease or distinguish it from chronic pancreatitis. We test the hypothesis that optical spectroscopy can accurately differentiate cancer from chronic pancreatitis and normal pancreas. We developed and tested clinically compatible multimodal optical spectroscopy technology to measure reflectance and endogenous fluorescence from human pancreatic tissues.

methodsFreshly excised pancreatic tissue specimens (39 normal, 34 chronic pancreatitis, 32 adenocarcinoma) from 18 patients were optically interrogated, with site-specific histopathology representing the criterion standard. A multinomial logistic model using principal component analysis and generalized estimating equations provided statistically rigorous tissue classification.

resultsOptical spectroscopy distinguished pancreatic cancer from normal pancreas and chronic pancreatitis (sensitivity, 91%; specificity, 82%; positive predictive value, 69%; negative predictive value, 95%; area under receiver operating characteristic curve, 0.89). Reflectance alone provided essentially the same classification accuracy as reflectance and fluorescence combined, suggesting that a rapid, low-cost, reduced-footprint, reflectance-based device could be deployed without notable loss of diagnostic power.

conclusionsOur novel, clinically compatible, label-free optical diagnostic technology accurately characterizes pancreatic tissues. These data provide the scientific foundation demonstrating that optical spectroscopy can potentially improve diagnosis of pancreatic cancer and chronic pancreatitis.

Indexed as

AdenocarcinomaDiagnosis, DifferentialHumansPancreasPancreatic NeoplasmsPancreatitis, ChronicPrincipal Component AnalysisReproducibility of ResultsROC CurveSpectrum Analysis

Identifiers

PMID27861201
PMCPMC5235923
OpenAlexW2553168900

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.