ArticleClinical radiology2018
Integrative radiomics expression predicts molecular subtypes of primary clear cell renal cell carcinoma.
Article in Clinical radiology, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 27 papers.
What it found
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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
27 citing papers in PubMed, 35 citations in OpenAlex.
- Advances in renal cancer: diagnosis, treatment, and emerging technologies.La Radiologia medica · 2025Review
- Fully automated segmentation and classification of renal tumors on CT scans via machine learning.BMC cancer · 2025Article
- Radiomics and machine learning analysis of liver magnetic resonance imaging for prediction and early detection of tumor response in colorectal liver metastases.Korean journal of clinical oncology · 2024Article
- The value of a dual-energy CT Iodine map radiomics model for the prediction of collagen fiber content in the ccRCC tumor microenvironment.BMC medical imaging · 2023Article
- Radiomics analysis based on CT for the prediction of pulmonary metastases in ewing sarcoma.BMC medical imaging · 2023Article
- Role of AI and Radiomic Markers in Early Diagnosis of Renal Cancer and Clinical Outcome Prediction: A Brief Review.Cancers · 2023Review
- Review
- Radiogenomics in Renal Cancer Management-Current Evidence and Future Prospects.International journal of molecular sciences · 2023Review
- Neuroimaging is the new "spatial omic": multi-omic approaches to neuro-inflammation and immuno-thrombosis in acute ischemic stroke.Seminars in immunopathology · 2023Review
- Maladaptive cognitive regulation moderates the mediating role of emotion dysregulation on the association between psychosocial factors and non-suicidal self-injury in depression.Frontiers in psychiatry · 2023Article
- Deep Learning-Based Prediction of Molecular Tumor Biomarkers from H&E: A Practical Review.Journal of personalized medicine · 2022Review
- Radiomics in medical imaging: pitfalls and challenges in clinical management.Japanese journal of radiology · 2022Review
- Novel Imaging Methods for Renal Mass Characterization: A Collaborative Review.European urology · 2022Review
- Radiogenomics in Clear Cell Renal Cell Carcinoma: A Review of the Current Status and Future Directions.Cancers · 2022Review
- An update on radiomics techniques in primary liver cancers.Infectious agents and cancer · 2022Article
- Review
- A CT-based radiomics model for predicting renal capsule invasion in renal cell carcinoma.BMC medical imaging · 2022Article
- Article
- Radiomics in hepatic metastasis by colorectal cancer.Infectious agents and cancer · 2021Article
- Immunology and Immunotherapeutic Approaches for Advanced Renal Cell Carcinoma: A Comprehensive Review.International journal of molecular sciences · 2021Review
Corrections and comments
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Authors and funding
13 authors at 7 institutions in 4 countries.
Funding
Abstract
aimTo identify combined positron-emission tomography (PET)/magnetic resonance imaging (MRI)-based radiomics as a surrogate biomarker of intratumour disease risk for molecular subtype ccA and ccB in patients with primary clear cell renal cell carcinoma (ccRCC). MATERIALS AND
methodsPET/MRI data were analysed retrospectively from eight patients. One hundred and sixty-eight radiomics features for each tumour sampling based on the regionally sampled tumours with 23 specimens were extracted. Sparse partial least squares discriminant analysis (SPLS-DA) was applied to feature screening on high-throughput radiomics features and project the selected features to low-dimensional intrinsic latent components as radiomics signatures. In addition, multilevel omics datasets were leveraged to explore the complementing information and elevate the discriminative ability.
resultsThe correct classification rate (CCR) for molecular subtype classification by SPLS-DA using only radiomics features was 86.96% with permutation test p=7×10
conclusionFeatured with high accuracy, an integrated multi-omics model of PET/MRI-based radiomics could be the first non-invasive investigation for disease risk stratification and guidance of treatment in patients with primary ccRCC.
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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.