ArticleFrontiers in oncology2022
Differentiating cellular leiomyoma from uterine sarcoma and atypical leiomyoma using multi-parametric MRI.
Article in Frontiers in oncology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers, 1 of them a synthesis that pooled it.
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Who cites it
7 citing papers in PubMed, 1 synthesis or guideline pooled it, 14 citations in OpenAlex.
- MRI for diagnosing uterine sarcoma: a systematic review and meta-analysis.Japanese journal of radiology · 2026Pooled it
- 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
- Gynecologic imaging errors and pitfalls: how to avoid misdiagnosis on pelvic MRI.Insights into imaging · 2026Review
- Biparametric MRI-based nomogram for differentiating malignant from atypical benign uterine smooth muscle tumors.Abdominal radiology (New York) · 2026Article
- Article
- The utility of MRI for the preoperative differential diagnosis of uterine sarcoma and leiomyoma: a single-center study.Fukushima journal of medical science · 2024Article
- Abnormal Uterine Bleeding: A Pictorial Review on Differential Diagnosis and Not-So-Common Cases of Interventional Radiology Management.Diagnostics (Basel, Switzerland) · 2024Review
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Authors and funding
6 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Objectives: To evaluate the diagnostic performance of conventional magnetic resonance imaging (cMRI) combined with diffusion-weighted MRI (DWI) in discrimination of cellular leiomyoma, uterine sarcoma, and atypical leiomyoma. Methods: This retrospective study enrolled 106 patients with uterine masses, including 51 cellular leiomyomas (CLs), 32 uterine sarcomas (USs) and 23 degenerated leiomyomas (LMs) confirmed by histopathologic examination. Clinical data and imaging findings were assessed. Chi-squared test for qualitative variables and one way ANOVA analysis for quantitative variables were performed. Logistic regression analysis and the receiver operating characteristic (ROC) analysis were performed to determine the cut-off point and diagnostic performances for significant numeric values or multiple models. Results: Morphology (Odds ratio [OR] = 6.36) and margin (OR = 13.84) derived from cMRI were independent indicators for differentiating CLs from USs, and T2WI signal (OR = 0.23) were an independent indicator for differentiating CLs from degenerated LMs (all Conclusions: cMRI is a reliable tool for differentiating CLs from USs and atypical leiomyoma, especially degenerated LMs. The combined use of cMRI and DWI can improve the differential diagnostic performance.
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