Evidence map›Paper›PMID 42806126›Full record

ArticleAesthetic plastic surgery2026

Diagnostic Accuracy of Multimodal Large Language Models (LLMs) for Detecting Tuberous Breast Deformity from Standardized Photographs: A Descriptive in Silico Study.

Edoardo Caimi, Stefano Vaccari, Alessandro Marco Lupacchini, Mattia Federico Cavallero, Simone Furlan, Riccardo Di Giuli, Valeria Bandi, Barbara Catania, Alessandra Veronesi, Marco Klinger and 3 more

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Article in Aesthetic plastic surgery, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0citing papers in PubMed
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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

13 authors.

Edoardo CaimiDepartment of Medical Biotechnology and Translational Medicine BIOMETRA, Reconstructive and Aesthetic Plastic Surgery School, University of Milan, Via Festa Del Perdono 7, Milan, Italy.ORCID http://orcid.org/0000-0002-8591-3903
Stefano VaccariIRCCS Humanitas Research Hospital, via Manzoni 56, 20089, Rozzano, Milan, Italy.ORCID http://orcid.org/0000-0002-2327-1810
Alessandro Marco LupacchiniDepartment of Medical Biotechnology and Translational Medicine BIOMETRA, Reconstructive and Aesthetic Plastic Surgery School, University of Milan, Via Festa Del Perdono 7, Milan, Italy.ORCID http://orcid.org/0009-0005-3659-1951
Mattia Federico CavalleroDepartment of Medical Biotechnology and Translational Medicine BIOMETRA, Reconstructive and Aesthetic Plastic Surgery School, University of Milan, Via Festa Del Perdono 7, Milan, Italy.ORCID http://orcid.org/0009-0008-0486-5120
Simone FurlanDepartment of Medical Biotechnology and Translational Medicine BIOMETRA, Reconstructive and Aesthetic Plastic Surgery School, University of Milan, Via Festa Del Perdono 7, Milan, Italy.
Riccardo Di GiuliIRCCS Humanitas Research Hospital, via Manzoni 56, 20089, Rozzano, Milan, Italy.ORCID http://orcid.org/0000-0001-8435-8672
Valeria BandiIRCCS Humanitas Research Hospital, via Manzoni 56, 20089, Rozzano, Milan, Italy.ORCID http://orcid.org/0000-0002-9121-9803
Barbara CataniaIRCCS Humanitas Research Hospital, via Manzoni 56, 20089, Rozzano, Milan, Italy.ORCID http://orcid.org/0009-0000-7658-6392
Alessandra VeronesiIRCCS Humanitas Research Hospital, via Manzoni 56, 20089, Rozzano, Milan, Italy.ORCID http://orcid.org/0000-0003-1303-371X
Marco KlingerIRCCS Humanitas Research Hospital, via Manzoni 56, 20089, Rozzano, Milan, Italy.ORCID http://orcid.org/0000-0001-8417-0186
Francesco KlingerDepartment of Health Sciences, Ospedale San Paolo, University of Milan, Via Antonio di Rudinì, 8, 20142, Milan, Italy.
Valeriano VinciIRCCS Humanitas Research Hospital, via Manzoni 56, 20089, Rozzano, Milan, Italy. valeriano.vinci@humanitas.it.ORCID http://orcid.org/0000-0001-5234-6044
Alberto PadernoDepartment of Biomedical Sciences, Humanitas University, Via Rita Levi Montalcini 4, Pieve Emanuele, 20090, Rozzano, Milan, Italy.ORCID http://orcid.org/0000-0002-1621-2142

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundTuberous breast deformity (TBD) is frequently missed outside specialist units, delaying treatment and compounding psychosocial harm. Vision-enabled large language models (LLMs) could facilitate earlier recognition, but their diagnostic accuracy for TBD has not been quantified. The aim of this study was to benchmark four state-of-the-art multimodal LLMs in [1] detecting TBD from standardized photographs and [2] proposing evidence-based surgical strategies.

methodsIn this single-center, retrospective in-silico study we analyzed 400 photographs (frontal and lateral views) from 200 women aged 16-40 years (100 TBD, 100 controls). GPT-4o, Claude 3 Opus, Gemini 2.5 Pro and DeepSeek V3 were interrogated with a two-tier prompting protocol. Diagnostic accuracy, sensitivity, specificity, PPV, NPV and AUROC were calculated against a surgeon-established reference standard, and 95% CIs were computed by Wilson method. Treatment outputs were independently scored [1-5] by two blinded plastic surgeons; reliability was assessed with the intraclass correlation coefficient (ICC).

resultsGPT-4o achieved the highest overall accuracy (0.94), sensitivity (0.92) and specificity (0.93); AUROC = 0.88. Claude 3 Opus, Gemini 2.5 Pro and DeepSeek V3 followed with accuracies of 0.90, 0.82 and 0.85, respectively. Mean treatment-quality scores paralleled diagnostic performance: GPT-4o = 4.0 ± 0.4, Claude 3 Opus = 2.8 ± 0.5, Gemini 2.5 Pro = 2.6 ± 0.5, DeepSeek V3 = 2.3 ± 0.5; rater agreement was excellent (ICC = 0.94).

conclusionsAmong contemporary LLMs, GPT-4o most accurately identifies TBD and delivers the most comprehensive operative plans. With expert oversight, such models could streamline aesthetic breast consultations and resident education. LEVEL OF EVIDENCE III: Breast Surgery. This journal requires that authors assign a level of evidence to each submission to which Evidence-Based Medicine rankings are applicable. This excludes Review Articles, Book Reviews, and manuscripts that concern Basic Science, Animal Studies, Cadaver Studies, and Experimental Studies. For a full description of these Evidence-Based Medicine ratings, please refer to the Table of Contents or the online Instructions to Authors www.springer.com/00266.

Indexed as

Artificial intelligenceDiagnostic accuracyLarge language modelsTuberous breastTuberous breast deformity

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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.