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

BACKGROUND

Tuberous 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.

METHODS

In 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).

RESULTS

GPT-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).

CONCLUSIONS

Among 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.