Evidence map›Paper›PMID 37692564›Full record

ArticleJournal of biomedical optics2023

Compressive hyperspectral microscopy for cancer detection.

Yaniv Oiknine, Marwan Abuleil, Eugene Brozgol, Isaac Y August, Iris Barshack, Ibrahim Abdulhalim, Yuval Garini, Adrian Stern

Open access · goldAbstract read
In one paragraph

Article in Journal of biomedical optics, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed, 1 pooled it
1.3field-weighted citation impact, top 24% 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

1 citing paper in PubMed, 1 synthesis or guideline pooled it, 6 citations in OpenAlex.

  1. Pooled it
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

8 authors at 5 institutions in 1 country.

Yaniv OiknineBen-Gurion University of the Negev, School of Electrical and Computer Engineering, Electro-Optics and Photonics Engineering Department, Beer-Sheva, Israel.ORCID 0000-0003-0074-9516
Marwan AbuleilBen-Gurion University of the Negev, School of Electrical and Computer Engineering, Electro-Optics and Photonics Engineering Department, Beer-Sheva, Israel.ORCID 0000-0003-2355-624X
Eugene BrozgolBar-Ilan University, Physics Department, Faculty of Exact Sciences, Ramat Gan, Israel.
Isaac Y AugustShamoon College of Engineering, Department of Electrical Engineering and Physics, Beer Sheva, Israel.ORCID 0000-0001-7500-8224
Iris BarshackTel-Aviv University, Sackler Faculty of Medicine, Tel-Aviv, Israel.
Ibrahim AbdulhalimBen-Gurion University of the Negev, School of Electrical and Computer Engineering, Electro-Optics and Photonics Engineering Department, Beer-Sheva, Israel.
Yuval GariniTechnion IIT, Biomedical Engineering Faculty, Haifa, Israel.ORCID 0000-0002-8783-2015
Adrian SternBen-Gurion University of the Negev, School of Electrical and Computer Engineering, Electro-Optics and Photonics Engineering Department, Beer-Sheva, Israel.ORCID 0000-0002-3696-7526
Ben-Gurion University of the Negev · ILBar-Ilan University · ILSami Shamoon College of Engineering · ILTechnion – Israel Institute of Technology · ILTel Aviv University · IL

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Significance: Hyperspectral microscopy grants the ability to characterize unique properties of tissues based on their spectral fingerprint. The ability to label and measure multiple molecular probes simultaneously provides pathologists and oncologists with a powerful tool to enhance accurate diagnostic and prognostic decisions. As the pathological workload grows, having an objective tool that provides companion diagnostics is of immense importance. Therefore, fast whole-slide spectral imaging systems are of immense importance for automated cancer prognostics that meet current and future needs. Aim: We aim to develop a fast and accurate hyperspectral microscopy system that can be easily integrated with existing microscopes and provide flexibility for optimizing measurement time versus spectral resolution. Approach: The method employs compressive sensing (CS) and a spectrally encoded illumination device integrated into the illumination path of a standard microscope. The spectral encoding is obtained using a compact liquid crystal cell that is operated in a fast mode. It provides time-efficient measurements of the spectral information, is modular and versatile, and can also be used for other applications that require rapid acquisition of hyperspectral images. Results: We demonstrated the acquisition of breast cancer biopsies hyperspectral data of the whole camera area within Conclusions: CS hyperspectral microscopy was successfully demonstrated on a common lab microscope for measuring biopsies stained with the most common stains, such as hematoxylin and eosin. The high spectral resolution demonstrated here in a rather short time indicates the ability to use it further for coping with the highly demanding needs of pathological diagnostics, both for cancer diagnostics and prognostics.

Indexed as

Data CompressionNeoplasmsBiopsyColoring AgentsMicroscopyPhysical PhenomenaColoring Agentscancer detectioncompressive sensingdigital pathologyhyperspectral imagingliquid crystal modulatorsmicroscopy

Identifiers

PMID37692564
PMCPMC10491981
OpenAlexW4386571198

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.