ArticleJournal of magnetic resonance imaging : JMRI2022
Magnetic Resonance Imaging-Based Radiomics Features Associated with Depth of Invasion Predicted Lymph Node Metastasis and Prognosis in Tongue Cancer.
Article in Journal of magnetic resonance imaging : JMRI, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 29 papers, 5 of them syntheses that pooled it.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
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
29 citing papers in PubMed, 5 syntheses or guidelines pooled it, 45 citations in OpenAlex.
- Artificial Intelligence-Driven MRI for Cervical Nodal Metastasis Detection in Oral Squamous Cell Carcinoma: A Hierarchical Meta-Analysis of Diagnostic Accuracy.Head & neck · 2026Pooled it
- MRI-Based Radiomics and Artificial Intelligence for Prediction of Recurrence and Prognostic Outcomes in Oral Tongue Squamous Cell Carcinoma: A Systematic Review with Functional Meta-Synthesis.Medical sciences (Basel, Switzerland) · 2026Pooled it
- Application of artificial intelligence and radiomics in the prediction of lymph node metastasis and tumour grading of oral cancer - a systematic review and meta analysis.BMC oral health · 2026Pooled it
- Diagnostic accuracy of radiomics and artificial intelligence models in diagnosing lymph node metastasis in head and neck cancers: a systematic review and meta-analysis.Neuroradiology · 2025Pooled it
- Application of CT and MRI images based on artificial intelligence to predict lymph node metastases in patients with oral squamous cell carcinoma: a subgroup meta-analysis.Frontiers in oncology · 2024Pooled it
- Deep learning radiomics based on multimodal MRI for preoperative prediction of N stage in tongue squamous cell carcinoma: a multicenter study.BMC oral health · 2026Article
- Artificial Intelligence for Preoperative Prediction of Lymph Node Metastasis and Depth of Invasion in Oral Tongue Squamous Cell Carcinoma: A Systematic Review and Meta-Analysis.Diagnostics (Basel, Switzerland) · 2026Review
- Optimal peritumoral regions and fusion strategies for prediction of the double-expressor subtype in diffuse large B-cell lymphoma: a multi-region radiomics study.Frontiers in oncology · 2026Article
- Article
- Artificial Intelligence in the Diagnosis of Tongue Cancer: A Systematic Review with Meta-Analysis.Biomedicines · 2025Review
- Can MRI radiomics predict neck metastasis at initial diagnosis in patients with squamous cell carcinoma of the tongue?Oral radiology · 2025Article
- Novel Nomogram for Prediction of Lymph Node Metastases from Buccal Mucosa Squamous Carcinoma Using Histological Parameters.South Asian journal of cancer · 2025Article
- Application value of dual-sequence MRI based nomogram of radiomics and morphologic features in predicting tumor differentiation degree and lymph node metastasis of Oral squamous cell carcinoma.Frontiers in oncology · 2025Article
- Intratumoral and peritumoral radiomics of MRIs predicts pathologic complete response to neoadjuvant chemoimmunotherapy in patients with head and neck squamous cell carcinoma.Journal for immunotherapy of cancer · 2024Article
- The prognostic role of MRI-based radiomics in tongue carcinoma: a multicentric validation study.La Radiologia medica · 2024Article
- Value of radiological depth of invasion in non-pT4 Oral tongue squamous cell carcinoma: implication for preoperative MR T-staging.European radiology · 2024Article
- Prognostic Analysis Combining Histopathological Features and Clinical Information to Predict Colorectal Cancer Survival from Whole-Slide Images.Digestive diseases and sciences · 2024Article
- Prediction of Histological Grade of Oral Squamous Cell Carcinoma Using Machine Learning Models Applied toBiomedicines · 2024Article
- The Effectiveness of an Adaptive Method to Analyse the Transition between Tumour and Peritumour for Answering Two Clinical Questions in Cancer Imaging.Sensors (Basel, Switzerland) · 2024Article
- Article
Corrections and comments
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Authors and funding
8 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundAdequate safe margin in tongue cancer radical surgery is one of the most important prognostic factors. However, the role of peritumoral tissues in predicting lymph node metastasis (LNM) and prognosis using radiomics analysis remains unclear. PURPOSE: To investigate whether magnetic resonance imaging (MRI)-based radiomics analysis with peritumoral extensions contributes toward the prediction of LNM and prognosis in tongue cancer. STUDY TYPE: Retrospective. POPULATION: Two hundred and thirty-six patients (38.56% female) with tongue cancer (training set, N = 157; testing set, N = 79; 37.58% and 40.51% female for each). FIELD STRENGTH/SEQUENCE: 1.5 T; T2-weighted turbo spin-echo images. ASSESSMENT: Radiomics models (R STATISTICAL TESTS: Chi-square test, regression analysis, receiver operating characteristic curve (ROC) analysis, decision analysis, spearman correlation analysis. The Delong test was used to compare area under the ROC (AUC). P < 0.05 was considered statistically significant.
resultsOf all the models, the CR DATA
conclusionRadiomics analysis with a 10-mm peritumoral extension had excellent power to predict LNM and prognosis in tongue cancer.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.