ArticleCancers2021
Predicting Tumor Budding Status in Cervical Cancer Using MRI Radiomics: Linking Imaging Biomarkers to Histologic Characteristics.
Article in Cancers, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
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Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
9 citing papers in PubMed.
- Functional drug screening of tumor organoids on an active-matrix digital microfluidic chip for cancer precision medicine.Microsystems & nanoengineering · 2026Article
- Predicting esophageal cancer response to neoadjuvant therapy with magnetic resonance imaging radiomics.World journal of gastrointestinal oncology · 2025Article
- Associations between MRI radiomics analysis and tumor-micro milieu in uterine cervical cancer.Journal of cancer research and clinical oncology · 2025Article
- Artificial intelligence radiomics in the diagnosis, treatment, and prognosis of gynecological cancer: a literature review.Translational cancer research · 2025Review
- A multivariate model of IVIM-DWI in the preoperative diagnosis of tumor budding grade in rectal cancer.Frontiers in oncology · 2025Article
- Exploring Radiomics Features Based on H&E Images as Potential Biomarkers for Evaluating Muscle Atrophy: A Preliminary Study.Journal of imaging informatics in medicine · 2024Article
- The radiomorphological appearance of the invasive margin in pancreatic cancer is associated with tumor budding.Langenbeck's archives of surgery · 2024Article
- Delta radiomics analysis for prediction of intermediary- and high-risk factors for patients with locally advanced cervical cancer receiving neoadjuvant therapy.Scientific reports · 2023Article
- Preoperative prediction of tumor budding in rectal cancer using multiple machine learning algorithms based on MRI T2WI radiomics.Frontiers in oncology · 2023Article
Corrections and comments
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Authors and funding
10 authors.
Funding
Abstract
backgroundOur previous study demonstrated that tumor budding (TB) status was associated with inferior overall survival in cervical cancer. The purpose of this study is to evaluate whether radiomic features can predict TB status in cervical cancer patients.
methodsSeventy-four patients with cervical cancer who underwent preoperative MRI and radical hysterectomy from 2011 to 2015 at our institution were enrolled. The patients were randomly allocated to the training dataset (
resultsTwenty radiomic features were selected; all were features from filtered-images and 85% were texture-related features. The area under the curve values and accuracy of the models by LR, RF, SVM and NN were 0.742 and 0.769, 0.782 and 0.731, 0.849 and 0.885, and 0.891 and 0.731, respectively, in the test dataset.
conclusionMRI-based radiomic features could predict TB status in patients with cervical cancer.
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