Evidence map›Paper›PMID 30141697›Full record

ArticleArchives of pathology & laboratory medicine2019

Resolving Interobserver Discrepancies in Lung Cancer Diagnoses by Spectral Histopathology.

Ali Akalin, Ayşegül Ergin, Stanley Remiszewski, Xinying Mu, Dan Raz, Max Diem

Open access · diamondAbstract read
In one paragraph

Article in Archives of pathology & laboratory medicine, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
2.3field-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

3 citing papers in PubMed, 11 citations in OpenAlex.

  1. Roadmap on optical sensors.Journal of optics (2010) · 2024
    Review
  2. Review
  3. Review
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

6 authors at 3 institutions in 1 country.

Ali AkalinFrom the Department of Pathology, University of Massachusetts Medical School, Worcester (Dr Akalin); CIRECA, LLC, Cambridge, Massachusetts (Drs Ergin and Diem, Mr Remiszewski, and Ms Mu); the Department of Mathematics and Statistics and Program in Bioinformatics, Boston University, Boston, Massachusetts (Ms Mu); the Division of Thoracic Surgery, City of Hope Medical Center, Duarte, California (Dr Raz); and the Department of Chemistry & Chemical Biology, Northeastern University, Boston, Massachusetts (Dr Diem).
Ayşegül ErginFrom the Department of Pathology, University of Massachusetts Medical School, Worcester (Dr Akalin); CIRECA, LLC, Cambridge, Massachusetts (Drs Ergin and Diem, Mr Remiszewski, and Ms Mu); the Department of Mathematics and Statistics and Program in Bioinformatics, Boston University, Boston, Massachusetts (Ms Mu); the Division of Thoracic Surgery, City of Hope Medical Center, Duarte, California (Dr Raz); and the Department of Chemistry & Chemical Biology, Northeastern University, Boston, Massachusetts (Dr Diem).
Stanley RemiszewskiFrom the Department of Pathology, University of Massachusetts Medical School, Worcester (Dr Akalin); CIRECA, LLC, Cambridge, Massachusetts (Drs Ergin and Diem, Mr Remiszewski, and Ms Mu); the Department of Mathematics and Statistics and Program in Bioinformatics, Boston University, Boston, Massachusetts (Ms Mu); the Division of Thoracic Surgery, City of Hope Medical Center, Duarte, California (Dr Raz); and the Department of Chemistry & Chemical Biology, Northeastern University, Boston, Massachusetts (Dr Diem).
Xinying MuFrom the Department of Pathology, University of Massachusetts Medical School, Worcester (Dr Akalin); CIRECA, LLC, Cambridge, Massachusetts (Drs Ergin and Diem, Mr Remiszewski, and Ms Mu); the Department of Mathematics and Statistics and Program in Bioinformatics, Boston University, Boston, Massachusetts (Ms Mu); the Division of Thoracic Surgery, City of Hope Medical Center, Duarte, California (Dr Raz); and the Department of Chemistry & Chemical Biology, Northeastern University, Boston, Massachusetts (Dr Diem).
Dan RazFrom the Department of Pathology, University of Massachusetts Medical School, Worcester (Dr Akalin); CIRECA, LLC, Cambridge, Massachusetts (Drs Ergin and Diem, Mr Remiszewski, and Ms Mu); the Department of Mathematics and Statistics and Program in Bioinformatics, Boston University, Boston, Massachusetts (Ms Mu); the Division of Thoracic Surgery, City of Hope Medical Center, Duarte, California (Dr Raz); and the Department of Chemistry & Chemical Biology, Northeastern University, Boston, Massachusetts (Dr Diem).
Max DiemFrom the Department of Pathology, University of Massachusetts Medical School, Worcester (Dr Akalin); CIRECA, LLC, Cambridge, Massachusetts (Drs Ergin and Diem, Mr Remiszewski, and Ms Mu); the Department of Mathematics and Statistics and Program in Bioinformatics, Boston University, Boston, Massachusetts (Ms Mu); the Division of Thoracic Surgery, City of Hope Medical Center, Duarte, California (Dr Raz); and the Department of Chemistry & Chemical Biology, Northeastern University, Boston, Massachusetts (Dr Diem).
City of Hope · USBoston University · USUniversity of Massachusetts Chan Medical School · US

Funding

Transgenic Mouse FacilityP30CA033572 · NCI · CITY OF HOPE/BECKMAN RESEARCH INSTITUTE · PI XIWEI WU · 1985 to 2026
$86.3M
NCI NIH HHS P30 CA033572
6 · The paper itself

Abstract

This paper reports the results of a collaborative lung cancer study between City of Hope Cancer Center (Duarte, California) and CIRECA, LLC (Cambridge, Massachusetts), comprising 328 samples from 249 patients, that used an optical technique known as spectral histopathology (SHP) for tissue classification. Because SHP is based on a physical measurement, it renders diagnoses on a more objective and reproducible basis than methods based on assessing cell morphology and tissue architecture. This report demonstrates that SHP provides distinction of adenocarcinomas from squamous cell carcinomas of the lung with an accuracy comparable to that of immunohistochemistry and highly reliable classification of adenosquamous carcinoma. Furthermore, this report shows that SHP can be used to resolve interobserver differences in lung pathology. Spectral histopathology is based on the detection of changes in biochemical composition, rather than morphologic features, and is therefore more akin to methods such as matrix-assisted laser desorption ionization time-of-flight mass spectrometry imaging. Both matrix-assisted laser desorption ionization time-of-flight mass spectrometry and SHP imaging modalities demonstrate that changes in tissue morphologic features observed in classical pathology are accompanied by, and may be correlated to, changes in the biochemical composition at the cellular level. Thus, these imaging methods provide novel insight into biochemical changes due to disease.

Indexed as

HumansImage Interpretation, Computer-AssistedLung NeoplasmsObserver VariationSpectroscopy, Fourier Transform Infrared

Identifiers

PMID30141697
PMCPMC8817896
OpenAlexW2888695548

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.