ArticleMedicine2015
Decoding Tumor Phenotypes for ALK, ROS1, and RET Fusions in Lung Adenocarcinoma Using a Radiomics Approach.
Article in Medicine, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 72 papers, 1 of them a synthesis that pooled it.
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Who cites it
72 citing papers in PubMed, 1 synthesis or guideline pooled it, 120 citations in OpenAlex.
- Clinical applications of textural analysis in non-small cell lung cancer.The British journal of radiology · 2018Pooled it
- Individualized nomogram for predicting ALK rearrangement status in lung adenocarcinoma patients.European radiology · 2021Trial
- A predictive model for fusion gene positivity in treatment-naive advanced non-small cell lung cancer.Translational lung cancer research · 2026Article
- Prognostic analysis and development of a prognostic model for EML4-ALK-positive lung cancer patients treated with ALK-TKIs.Frontiers in medicine · 2026Article
- Texture analysis can predict response to etoposide-doxorubicin-cisplatin in patients with adrenocortical carcinoma.Journal of endocrinological investigation · 2025Article
- An Enhanced CT-based Radiomics Model for Predicting the Anaplastic Lymphoma Kinase Mutation Status in Lung Adenocarcinoma.Current medical imaging · 2025Article
- Annotated test-retest dataset of lung cancer CT scan images reconstructed at multiple imaging parameters.Scientific data · 2024Article
- Artificial intelligence applications in personalizing lung cancer management: state of the art and future perspectives.Journal of thoracic disease · 2024Review
- The prognostic value of radiogenomics using CT in patients with lung cancer: a systematic review.Insights into imaging · 2024Review
- The clinical, radiological, postoperative pathological, and genetic features of nodular lung adenocarcinoma: a real-world single-center data.Journal of thoracic disease · 2024Article
- Implementation of Artificial Intelligence in Personalized Prognostic Assessment of Lung Cancer: A Narrative Review.Cancers · 2024Review
- Lung cancer in patients who have never smoked - an emerging disease.Nature reviews. Clinical oncology · 2024Review
- Surgery for Non-Small Cell Lung Cancer in the Personalized Therapy Era.Current oncology (Toronto, Ont.) · 2023Article
- Estimation of an Image Biomarker for Distant Recurrence Prediction in NSCLC Using Proliferation-Related Genes.International journal of molecular sciences · 2023Article
- Application of radiomics in diagnosis and treatment of lung cancer.Frontiers in pharmacology · 2023Review
- Deep Neural Networks and Machine Learning Radiomics Modelling for Prediction of Relapse in Mantle Cell Lymphoma.Cancers · 2022Article
- Prediction of programmed cell death protein 1 in hepatocellular carcinoma patients using radiomics analysis with radiofrequency-based ultrasound multifeature maps.Biomedical engineering online · 2022Article
- Prediction of BRCA gene mutation status in epithelial ovarian cancer by radiomics models based on 2D and 3D CT images.BMC medical imaging · 2021Article
- CT-Based Hand-crafted Radiomic Signatures Can Predict PD-L1 Expression Levels in Non-small Cell Lung Cancer: a Two-Center Study.Journal of digital imaging · 2021Article
- NSCLC Biomarkers to Predict Response to Immunotherapy with Checkpoint Inhibitors (ICI): From the Cells to In Vivo Images.Cancers · 2021Review
12 more citing papers are in PubMed but not listed here.
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Authors and funding
10 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Quantitative imaging using radiomics can capture distinct phenotypic differences between tumors and may have predictive power for certain phenotypes according to specific genetic mutations. We aimed to identify the clinicoradiologic predictors of tumors with ALK (anaplastic lymphoma kinase), ROS1 (c-ros oncogene 1), or RET (rearranged during transfection) fusions in patients with lung adenocarcinoma.A total of 539 pathologically confirmed lung adenocarcinomas were included in this retrospective study. The baseline clinicopathologic characteristics were retrieved from the patients' medical records and the ALK/ROS1/RET fusion status was reviewed. Quantitative computed tomography (CT) and positron emission tomography imaging characteristics were evaluated using a radiomics approach. Significant features for the fusion-positive tumor prediction model were extracted from all of the clinicoradiologic features, and were used to calculate diagnostic performance for predicting 3 fusions' positivity. The clinicoradiologic features were compared between ALK versus ROS1/RET fusion-positive tumors to identify the clinicoradiologic similarity between the 2 groups.The fusion-positive tumor prediction model was a combination of younger age, advanced tumor stage, solid tumor on CT, higher values for SUV(max) and tumor mass, lower values for kurtosis and inverse variance on 3-voxel distance than those of fusion-negative tumors (sensitivity and specificity, 0.73 and 0.70, respectively). ALK fusion-positive tumors were significantly different in tumor stage, central location, SUV(max), homogeneity on 1-, 2-, and 3-voxel distances, and sum mean on 2-voxel distance compared with ROS1/RET fusion-positive tumors.ALK/ROS1/RET fusion-positive lung adenocarcinomas possess certain clinical and imaging features that enable good discrimination of fusion-positive from fusion-negative lung adenocarcinomas.
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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.