Evidence map›Paper›PMID 30934999›Full record

ArticleBiosensors2019

Danielle Bury, Camilo L M Morais, Katherine M Ashton, Timothy P Dawson, Francis L Martin

Open access · goldAbstract read
In one paragraph

Article in Biosensors, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
11citing papers in PubMed, 1 pooled it
3.7field-weighted citation impact, top 7% 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

11 citing papers in PubMed, 1 synthesis or guideline pooled it, 31 citations in OpenAlex.

  1. Pooled it
  2. Article
  3. Article
  4. Article
  5. Current Trends of Raman Spectroscopy in Clinic Settings: Opportunities and Challenges.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2024
    Review
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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

5 authors at 2 institutions in 1 country.

Danielle BurySchool of Pharmacy and Biomedical Sciences, University of Central Lancashire, Preston PR1 2HE, UK. deb11@doctors.org.uk.
Camilo L M MoraisSchool of Pharmacy and Biomedical Sciences, University of Central Lancashire, Preston PR1 2HE, UK. CDLMedeiros-de-morai@uclan.ac.uk.
Katherine M AshtonNeuropathology, Royal Preston Hospital, Lancashire Teaching Hospitals NHS Trust, Sharoe Green Lane, Preston PR2 9HT, UK. Katherine.ashton@lthtr.nhs.uk.
Timothy P DawsonNeuropathology, Royal Preston Hospital, Lancashire Teaching Hospitals NHS Trust, Sharoe Green Lane, Preston PR2 9HT, UK. timothy.dawson@lthtr.nhs.uk.
Francis L MartinSchool of Pharmacy and Biomedical Sciences, University of Central Lancashire, Preston PR1 2HE, UK. flmartin@uclan.ac.uk.
University of Central Lancashire · GBRoyal Preston Hospital · GB

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

With brain tumour incidence increasing, there is an urgent need for better diagnostic tools. Intraoperatively, brain tumours are diagnosed using a smear preparation reported by a neuropathologist. These have many limitations, including the time taken for the specimen to reach the pathology department and for results to be communicated to the surgeon. There is also a need to assist with resection rates and identifying infiltrative tumour edges intraoperatively to improve clearance. We present a novel study using a handheld Raman probe in conjunction with gold nanoparticles, to detect primary and metastatic brain tumours from fresh brain tissue sent for intraoperative smear diagnosis. Fresh brain tissue samples sent for intraoperative smear diagnosis were tested using the handheld Raman probe after application of gold nanoparticles. Derived Raman spectra were inputted into forward feature extraction algorithms to build a predictive model for sensitivity and specificity of outcome. These results demonstrate an ability to detect primary from metastatic tumours (especially for normal and low grade lesions), in which accuracy, sensitivity and specificity were respectively equal to 98.6%, 94.4% and 99.5% for normal brain tissue; 96.1%, 92.2% and 97.0% for low grade glial tumours; 90.3%, 89.7% and 90.6% for high grade glial tumours; 94.8%, 63.9% and 97.1% for meningiomas; 95.4%, 79.2% and 98.8% for metastases; and 99.6%, 88.9% and 100% for lymphoma, based on smear samples (κ = 0.87). Similar results were observed when compared to the final formalin-fixed paraffin embedded tissue diagnosis (κ = 0.85). Overall, our results have demonstrated the ability of Raman spectroscopy to match results provided by intraoperative smear diagnosis and raise the possibility of use intraoperatively to aid surgeons by providing faster diagnosis. Moving this technology into theatre will allow it to develop further and thus reach its potential in the clinical arena.

Indexed as

Biosensing TechniquesBrain NeoplasmsGoldHumansMetal NanoparticlesSpectrum Analysis, RamanGoldbrain tumour diagnosisclassificationforward feature extraction algorithmintraoperative useRaman probeRaman spectroscopy

Identifiers

PMID30934999
PMCPMC6627213
OpenAlexW2929812714

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.