A pilot study reveals a radiomics model effectively distinguishes sarcomas from leiomyomas, suggesting improved diagnostic tools.
A model including eight radiomics features and patient age demonstrated reasonably good discriminative and classification performance for distinguishing uterine sarcomas from leiomyomas. Its classification ability was similar to that of subjective assessment by the original ultrasound examiner, being more sensitive but less specific. To confirm the role of radiomics for discriminating between uterine sarcomas and leiomyomas, large prospective studies including benign leiomyoma variants are needed. If good performance of radiomics models can be confirmed, integrating automated radiomics analysis into ultrasound machine software may help ultrasound examiners to discriminate between sarcomas and benign leiomyomas.
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Ciccarone et al. (2026) studied this question.
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