Evidence map›Paper›PMID 32298800›Full record

ArticlePhotodiagnosis and photodynamic therapy2020

In vivo detection of circulating tumour cell clusters by photodiagnostic spectroscopy.

Detlef Schikora

Open access · greenAbstract read
In one paragraph

Article in Photodiagnosis and photodynamic therapy, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
0.2field-weighted citation impact, top 49% 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, 2 citations in OpenAlex.

  1. 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

1 author at 1 institution in 1 country.

Detlef SchikoraUniversity of Paderborn, Faculty of Science, Institute of Biophysics, Biophysics Group, Bruchweg 14. 37688, Wehrden, Paderborn, Germany. Electronic address: detlef.schikora@uni-paderborn.de.
Paderborn University · DE

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundWe demonstrate a new diagnostic method, Photodiagnostic Infrared Spectroscoppy (PDIS), which is able to detect circulating tumor clusters and circulating tumor cells in the circulatory system.

methodsThe PDIS method is based on photodiagnostic physics and high resolution spectroscopy and is using calibrated spectroscopic data for the diagnostic analysis of the blood screening spectra. Using Confocal Laser Scanning Mikcroscopy the Indocyangreen-uptake of different cell lines of breast cancer cells is studied.

resultsThe PDIS supplies calibrated diagnostic data about the presence or absence of CTCs and CTC clusters in the bloodstream with a sensitivity of 98 %. Therefore, the PDIS is suited to control the blood of cancer patients with respect of CTC and CTC clusters with an resolution of one CTC and one CTC cluster per blood volume. PDIS distinguishes the different phenotypes of CTC clusters.

conclusionCirculating tumor cell slusters play a key role in the metastatic process and are formed only in solid tumors, they are appropriate objects to validate cancer treatments and to recognice cancer formation. The PDIS is a calibrated diagnostic method which allows to evaluate the results of solid tumor treatments and of chemotherapy treatments and to optimize the individual cancer treatment strategies.

Indexed as

Biomarkers, TumorCell Line, TumorHematologic TestsHumansIndocyanine GreenLiposomesNeoplastic Cells, CirculatingSpectrophotometry, InfraredBiomarkers, TumorIndocyanine GreenLiposomesCirculating tumor cell clustersFluorescence spectroscopyHigh resolution blood screeningPhotodiagnostic diagnosisPhotodiagnostic infrared spectroscopy

Identifiers

PMID32298800
PMCPMC7153531
OpenAlexW3017338452

What OpenQuestion holds

Textmetadata
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.