Prediction of Anemia in Adenomyosis Patients Using Transvaginal Ultrasound Radiomics

Chaeheon Lee, Young Jae Kim, Han-Song Song, Soohyun Oh, Kwang Gi Kim
In: Diagnostics · 2026 · vol. 16(17) , pp. 2827 · doi:10.3390/diagnostics16172827 · W7204987185
article OA: gold CC0
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Radiomics features from transvaginal ultrasound provided modest complementary information for predicting anemia in adenomyosis patients, though complete blood count data yielded superior predictive performance.

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Abstract

Background: Abnormal uterine bleeding (AUB) caused by adenomyosis can result in significant iron-deficiency anemia. Given that transvaginal ultrasound (TVUS) is commonly performed during routine examinations, its assessment may facilitate preemptive treatment. Methods: In this study, TVUS images from patients with surgically confirmed adenomyosis were preprocessed to minimize intra- and inter-scan variability. Radiomics features were extracted using PyRadiomics to train automated machine-learning classifiers under k-fold nested cross-validation. Multiple dataset configurations were evaluated, including feature extraction from a custom region-of-interest (ROI) of the uterine corpus, whole-image features adjusted for uterine size, and supplementary variables from complete blood counts (CBC). Results: Radiomics-centered models demonstrated modest discrimination (mean accuracy 0.606–0.618). While incorporating CBC variables with radiomics features substantially improved performance compared to radiomics alone, models trained exclusively on CBC data yielded overall higher results. Conclusions: These findings indicate that quantitative features derived from routine TVUS provide modest complementary information for predicting anemia. While they do not offer clear incremental value when highly discriminatory clinical data (CBC) are available, TVUS radiomics may serve as a supplementary diagnostic tool in settings where blood tests are incomplete or unavailable. Further validation in larger, multi-institutional cohorts with patient-level separation is warranted.

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Papers in the corpus that this work cites (lower rings, blue) and that cite this one (upper rings, green). Dot size scales with the paper's in-corpus citation count — bigger dot = more influential within the endo/adeno field. Click a dot to open that paper. [ expand to 2 hops ] — adds papers reached through this work's immediate citers/citees. Heavier; up to 60 extra dots.

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