Evidence map›Paper›PMID 34806755›Full record

ArticleActa dermato-venereologica2022

Differentiation Between Benign and Malignant Pigmented Skin Tumours Using Bedside Diagnostic Imaging Technologies: A Pilot Study.

Terese Von Knorring, Niels Møller Israelsen, Vilde Ung, Julie L Formann, Mikkel Jensen, Merete Hædersdal, Ole Bang, Gabriella Fredman, Mette Mogensen

Abstract read
In one paragraph

Article in Acta dermato-venereologica, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed
–field-weighted citation impact
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

8 citing papers in PubMed.

  1. Trial
  2. Article
  3. Article
  4. Review
  5. Article
  6. Article
  7. Review
  8. Cutaneous Oncology: Strategies for Melanoma Prevention, Diagnosis, and Therapy.Cancer control : journal of the Moffitt Cancer Center
    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

9 authors.

Terese Von KnorringDepartment of Dermatology, Copenhagen University Hospital, Bispebjerg and Frederiksberg, Nielsine Nielsens Vej 17, DK-2400 Copenhagen, Denmark. teresevonknorring@gmail.com.
Niels Møller Israelsen
Vilde Ung
Julie L Formann
Mikkel Jensen
Merete Hædersdal
Ole Bang
Gabriella Fredman
Mette Mogensen

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Rapid diagnosis of suspicious pigmented skin lesions is imperative; however, current bedside skin imaging technologies are either limited in penetration depth or resolution. Combining imaging methods is therefore highly relevant for skin cancer diagnostics. This pilot study evaluated the ability of optical coherence tomography, reflectance confocal microscopy, photo-acoustic imaging and high-frequency ultrasound to differentiate malignant from benign pigmented skin lesions. A total of 41 pigmented skin tumours were scanned prior to excision. Morphological features and blood vessel characteristics were analysed with reflectance confocal microscopy, optical coherence tomography, high-frequency ultrasound and photoacoustic imaging images, and the diagnostic accuracy was assessed. Three novel photoacoustic imaging features, 7 reflectance confocal microscopy features, and 2 optical coherence tomography features were detected that had a high correlation with malignancy; diagnostic accuracy > 71%. No significant features were found in high-frequency ultrasound. In conclusion, optical coherence tomography, reflectance confocal microscopy and photoacoustic imaging in combination enable image-guided bedside evaluation of suspicious pigmented skin tumours. Combining these advanced techniques may enable more efficient diagnosis of skin cancer.

Indexed as

Skin NeoplasmsHumansMicroscopy, ConfocalPilot ProjectsSkinTomography, Optical Coherence

Identifiers

PMID34806755
PMCPMC9631264

What OpenQuestion holds

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Registered trials

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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.