ArticleKorean journal of radiology2024
Differentiating Uterine Sarcoma From Atypical Leiomyoma on Preoperative Magnetic Resonance Imaging Using Logistic Regression Classifier: Added Value of Diffusion-Weighted Imaging-Based Quantitative Parameters.
Article in Korean journal of radiology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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Who cites it
4 citing papers in PubMed, 9 citations in OpenAlex.
- Development and External Testing of an Interpretable MRI-Based Machine Learning Model for Differentiating Endometrial Stromal Sarcoma from Cellular Leiomyoma.Journal of imaging informatics in medicine · 2026Article
- Multicenter Study of MRI Features in Uterine Myxoid Leiomyosarcoma: Revealing and Overcoming a Critical Pitfall in Current Consensus Criteria.Korean journal of radiology · 2026Article
- Review
- Tailoring the Diagnostic Pathway for Medical and Surgical Treatment of Uterine Fibroids: A Narrative Review.Diagnostics (Basel, Switzerland) · 2024Review
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8 authors at 4 institutions in 1 country.
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Abstract
objectiveTo evaluate the added value of diffusion-weighted imaging (DWI)-based quantitative parameters to distinguish uterine sarcomas from atypical leiomyomas on preoperative magnetic resonance imaging (MRI). MATERIALS AND
methodsA total of 138 patients (age, 43.7 ± 10.3 years) with uterine sarcoma (n = 44) and atypical leiomyoma (n = 94) were retrospectively collected from four institutions. The cohort was randomly divided into training (84/138, 60.0%) and validation (54/138, 40.0%) sets. Two independent readers evaluated six qualitative MRI features and two DWI-based quantitative parameters for each index tumor. Multivariable logistic regression was used to identify the relevant qualitative MRI features. Diagnostic classifiers based on qualitative MRI features alone and in combination with DWI-based quantitative parameters were developed using a logistic regression algorithm. The diagnostic performance of the classifiers was evaluated using a cross-table analysis and calculation of the area under the receiver operating characteristic curve (AUC).
resultsMean apparent diffusion coefficient value of uterine sarcoma was lower than that of atypical leiomyoma (mean ± standard deviation, 0.94 ± 0.30 10
conclusionThe addition of DWI-based quantitative parameters to qualitative MRI features improved the diagnostic performance of the logistic regression classifier in differentiating uterine sarcomas from atypical leiomyomas on preoperative MRI.
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