Evidence map›Paper›PMID 40647493›Full record

ReviewCancers2025

Why Do Radiologists Disown Breast Thermography? A Critical Review of Recent Studies and Recommendations.

Ane Goñi-Arana, Jorge Pérez-Martín, Francisco Javier Díez

Abstract readReview
In one paragraph

Review in Cancers, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing 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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

3 authors.

Ane Goñi-AranaDepartment of Artificial Intelligence, Universidad Nacional de Educación a Distancia (UNED), 28040 Madrid, Spain.ORCID 0000-0003-3360-0427
Jorge Pérez-MartínDepartment of Artificial Intelligence, Universidad Nacional de Educación a Distancia (UNED), 28040 Madrid, Spain.ORCID 0000-0002-3588-7233
Francisco Javier DíezDepartment of Artificial Intelligence, Universidad Nacional de Educación a Distancia (UNED), 28040 Madrid, Spain.ORCID 0000-0001-9855-9248

Funding

Comunidad de Madrid PEJ-2019-AI/TIC-15533Ministerio de Ciencia, Innovación y Universidades PID2019-110686RB-I00Ministerio de Ciencia, Innovación y Universidades PID2023-150515OB-I00National University of Distance Education FPI/UNED/2021
6 · The paper itself

Abstract

Thermography was first applied to breast cancer detection in the 1950s but fell out of favor among radiologists due to inconsistent and inconclusive findings in the following decades. Studies conducted in the 21st century using new-generation thermal cameras and computer vision techniques, particularly artificial intelligence, have reported sensitivity and specificity values comparable to those of mammography. However, most radiologists, being unaware of these results, still believe this technique is ineffective, and medical societies advise against using it, even as an adjunct to mammography. In this paper we review recent studies and discuss whether the recommendations of scientific societies are still valid in the light of new evidence. We also propose some ideas for standardizing breast thermography studies that could help make this technique acceptable to the radiology community.

Indexed as

breast cancerinfrared imagingscreeningthermography

Identifiers

PMID40647493
PMCPMC12249184

What OpenQuestion holds

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LicenceCC BY
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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.