Trial reportJournal of healthcare engineering2022
Noninvasive Method for Predicting the Expression of Ki67 and Prognosis in Non-Small-Cell Lung Cancer Patients: Radiomics.
Trial report in Journal of healthcare engineering, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers, 1 of them a synthesis that pooled it.
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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
14 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Mastering CT-based radiomic research in lung cancer: a practical guide from study design to critical appraisal.The British journal of radiology · 2025Guideline
- Radiomics in Lung Cancer Imaging: A Narrative Review of Current Evidence.Journal of imaging · 2026Review
- Chebulagic acid targets FBXO38 to enhance natural killer cell-mediated anti-tumor immunity in lung adenocarcinoma.Human cell · 2026Article
- Caveolin-1 inhibits the proliferation and invasion of lung adenocarcinoma via EGFR degradation.Scientific reports · 2025Article
- Prediction of Ki-67 Expression in HIV-Associated Lung Adenocarcinoma Patients Using Multiple Machine Learning Models Based on CT Imaging Radiomics.Cancer management and research · 2025Article
- Combining clinical characteristics with CT radiomics to predict Ki67 expression level of small renal mass based on artificial intelligence algorithms.Frontiers in oncology · 2025Article
- Effects of different KRAS mutants and Ki67 expression on diagnosis and prognosis in lung adenocarcinoma.Scientific reports · 2024Article
- A radiomics-clinical combined nomogram-based on non-enhanced CT for discriminating the risk stratification in GISTs.Journal of cancer research and clinical oncology · 2023Article
- Deep Learning to Predict the Cell Proliferation and Prognosis of Non-Small Cell Lung Cancer Based on FDG-PET/CT Images.Diagnostics (Basel, Switzerland) · 2023Article
- Radiomics nomogram for the prediction of Ki-67 index in advanced non-small cell lung cancer based on dual-phase enhanced computed tomography.Journal of cancer research and clinical oncology · 2023Article
- Deep learning-based radiomic nomograms for predicting Ki67 expression in prostate cancer.BMC cancer · 2023Article
- CT radiomics model for predicting the Ki-67 proliferation index of pure-solid non-small cell lung cancer: a multicenter study.Frontiers in oncology · 2023Article
- Prediction of CD3 T cells and CD8 T cells expression levels in non-small cell lung cancer based on radiomic features of CT images.Frontiers in oncology · 2023Article
- Manual Delineation of the Region of Interest Combined With Clinical Image Analysis to Predict the Ki-67 Expression Level in Non-small Cell Lung Cancer.Sage open pathologyArticle
Corrections and comments
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Authors and funding
9 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Purpose: In this study, we aimed to develop and validate a noninvasive method based on radiomics to evaluate the expression of Ki67 and prognosis of patients with non-small-cell lung cancer (NSCLC). Results: A total of 62 Ki67 positive patients and 58 Ki67 negative patients formed the training set and test training dataset and test dataset. Radiomics signatures showed good performance in predicting the expression of Ki67 with AUCs of 0.86 (training dataset) and 0.85 (test dataset). Validation and calibration showed that the radiomics had a strong predictive power in patients with NSCLC survival, which was significantly close to the effect of Ki67 expression on the survival of patients with NSCLC. Conclusion: Radiomics signatures based on preoperative F-FDG PET/CT could distinguish the expression of Ki67, which also had a strong predictive performance for the survival outcome.
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