Trial reportPloS one2018
18F-fluorodeoxyglucose positron-emission tomography (FDG-PET)-Radiomics of metastatic lymph nodes and primary tumor in non-small cell lung cancer (NSCLC) - A prospective externally validated study.
Trial report in PloS one, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 37 papers, 1 of them a synthesis that pooled it.
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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.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
37 citing papers in PubMed, 1 synthesis or guideline pooled it, 75 citations in OpenAlex.
- Towards clinical application of image mining: a systematic review on artificial intelligence and radiomics.European journal of nuclear medicine and molecular imaging · 2019Pooled it
- Combined CT radiomics of primary tumor and metastatic lymph nodes improves prediction of loco-regional control in head and neck cancer.Scientific reports · 2019Trial
- Quantitative CT analysis in lung cancer research: a bibliometric analysis based on Web of Science [2005-2025].Journal of thoracic disease · 2026Article
- An explainable imaging-clinical biomarker for non-small cell lung cancer prognostication based on normalised hotspot to centroid distance and [European journal of nuclear medicine and molecular imaging · 2026Article
- Prediction of pathological complete response to neoadjuvant chemoimmunotherapy in non-small cell lung cancer usingBMC cancer · 2025Article
- Predicting the immune therapy response of advanced non-small cell lung cancer based on primary tumor and lymph node radiomics features.Frontiers in medicine · 2025Article
- Does FDG PET-Based Radiomics Have an Added Value for Prediction of Overall Survival in Non-Small Cell Lung Cancer?Journal of clinical medicine · 2024Article
- The effect of data resampling methods in radiomics.Scientific reports · 2024Article
- Article
- Radiomics in the evaluation of ovarian masses - a systematic review.Insights into imaging · 2023Article
- Article
- Developing a primary tumor and lymph node 18F-FDG PET/CT-clinical (TLPC) model to predict lymph node metastasis of resectable T2-4 NSCLC.Journal of cancer research and clinical oncology · 2023Article
- The effect of preprocessing filters on predictive performance in radiomics.European radiology experimental · 2022Article
- Gross tumour volume radiomics for prognostication of recurrence & death following radical radiotherapy for NSCLC.NPJ precision oncology · 2022Article
- Multi-lesion radiomics of PET/CT for non-invasive survival stratification and histologic tumor risk profiling in patients with lung adenocarcinoma.European radiology · 2022Article
- Radiomics in Oncological PET Imaging: A Systematic Review-Part 1, Supradiaphragmatic Cancers.Diagnostics (Basel, Switzerland) · 2022Review
- Evaluation of the dependence of radiomic features on the machine learning model.Insights into imaging · 2022Article
- Radiomics and machine learning for the diagnosis of pediatric cervical non-tuberculous mycobacterial lymphadenitis.Scientific reports · 2022Article
- Modulators of radiation-induced cardiopulmonary toxicities for non-small cell lung cancer: Integrated cytokines, single nucleotide variants, and HBP systems imaging.Frontiers in oncology · 2022Review
- Mitigation of noise-induced bias of PET radiomic features.PloS one · 2022Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
9 authors at 3 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundLymph node stage prior to treatment is strongly related to disease progression and poor prognosis in non-small cell lung cancer (NSCLC). However, few studies have investigated metabolic imaging features derived from pre-radiotherapy 18F-fluorodeoxyglucose (FDG) positron-emission tomography (PET) of metastatic hilar/mediastinal lymph nodes (LNs). We hypothesized that these would provide complementary prognostic information to FDG-PET descriptors to only the primary tumor (tumor).
methodsTwo independent cohorts of 262 and 50 node-positive NSCLC patients were used for model development and validation. Image features (i.e. Radiomics) including shape and size, first order statistics, texture, and intensity-volume histograms (IVH) (http://www.radiomics.io/) were evaluated by univariable Cox regression on the development cohort. Prognostic modeling was conducted with a 10-fold cross-validated least absolute shrinkage and selection operator (LASSO), automatically selecting amongst FDG-PET-Radiomics descriptors from (1) tumor, (2) LNs or (3) both structures. Performance was assessed with the concordance-index. Development data are publicly available at www.cancerdata.org and Dryad (doi:10.5061/dryad.752153b).
resultsCommon SUV descriptors (maximum, peak, and mean) were significantly related to overall survival when extracted from LNs, as were LN volume and tumor load (summed tumor and LNs' volumes), though this was not true for either SUV metrics or tumor's volume. Feature selection exclusively from imaging information based on FDG-PET-Radiomics, exhibited performances of (1) 0.53 -external 0.54, when derived from the tumor, (2) 0.62 -external 0.56 from LNs, and (3) 0.62 -external 0.59 from both structures, including at least one feature from each sub-category, except IVH.
conclusionCombining imaging information based on FDG-PET-Radiomics features from tumors and LNs is desirable to achieve a higher prognostic discriminative power for NSCLC.
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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.