ArticleScientific reports2019
An Exploratory Radiomics Approach to Quantifying Pulmonary Function in CT Images.
Article in Scientific reports, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 26 papers.
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Who cites it
26 citing papers in PubMed, 60 citations in OpenAlex.
- CT radiomics-based long-term survival prediction for locally advanced non-small cell lung cancer patients treated with concurrent chemoradiotherapy using features from tumor and tumor organismal environment.Radiation oncology (London, England) · 2022Trial
- Radiomics and anaesthetic planning: Quantitative imaging as a new frontier in preoperative risk assessment.World journal of radiology · 2026Review
- Lobar-level radiomic clustering reveals background lung changes associated with lung cancer risk: a new perspective for early screening.Insights into imaging · 2026Article
- Construction of a severity prediction model for hospitalized patients with acute exacerbation of chronic obstructive pulmonary disease based on machine learning.European journal of medical research · 2025Article
- Integrating intramuscular fat radiomics with hamstrings-to-quadriceps structure and function ratios to predict future hamstring strain injury.PLOS digital health · 2025Article
- CT-Based Radiomics Enhance Respiratory Function Analysis for Lung SBRT.Bioengineering (Basel, Switzerland) · 2025Article
- Radiomics and dosiomics approaches to estimate lung function after stereotactic body radiation therapy in patients with lung tumors.Radiological physics and technology · 2025Article
- Spatial encoding and growth-related change of sheep lung radiomic features.Frontiers in veterinary science · 2025Article
- Motion and anatomy dual aware lung ventilation imaging by integrating Jacobian map and average CT image using dual path fusion network.Medical physics · 2025Article
- Radiomics in radiology: What the radiologist needs to know about technical aspects and clinical impact.La Radiologia medica · 2024Review
- Radiomics approach for identifying radiation-induced normal tissue toxicity in the lung.Scientific reports · 2024Article
- Prognostic value of different discretization parameters inJournal of medical imaging (Bellingham, Wash.) · 2024Article
- A CT-Based Lung Radiomics Nomogram for Classifying the Severity of Chronic Obstructive Pulmonary Disease.International journal of chronic obstructive pulmonary disease · 2024Article
- Study on Predicting Clinical Stage of Patients with Bronchial Asthma Based on CT Radiomics.Journal of asthma and allergy · 2024Article
- A super-voxel-based method for generating surrogate lung ventilation images from CT.Frontiers in physiology · 2023Article
- Radiomics: a primer on high-throughput image phenotyping.Abdominal radiology (New York) · 2022Review
- A radiomics-boosted deep-learning model for COVID-19 and non-COVID-19 pneumonia classification using chest x-ray images.Medical physics · 2022Article
- A novel computed tomography radiomic nomogram for early evaluation of small airway dysfunction development.Frontiers in medicine · 2022Article
- Intrinsic radiomic expression patterns after 20 Gy demonstrate early metabolic response of oropharyngeal cancers.Medical physics · 2021Article
- Radiomics in Lung Diseases Imaging: State-of-the-Art for Clinicians.Journal of personalized medicine · 2021Review
Corrections and comments
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Authors and funding
6 authors at 3 institutions in 2 countries.
Funding
Abstract
Contemporary medical imaging is becoming increasingly more quantitative. The emerging field of radiomics is a leading example. By translating unstructured data (i.e., images) into structured data (i.e., imaging features), radiomics can potentially characterize clinically useful imaging phenotypes. In this paper, an exploratory radiomics approach is used to investigate the potential association between quantitative imaging features and pulmonary function in CT images. Thirty-nine radiomic features were extracted from the lungs of 64 patients as potential imaging biomarkers for pulmonary function. Collectively, these features capture the morphology of the lungs, as well as intensity variations, fine-texture, and coarse-texture of the pulmonary tissue. The extracted lung radiomics data was compared to conventional pulmonary function tests. In general, patients with larger lungs of homogeneous, low attenuating pulmonary tissue (as measured via radiomics) were found to be associated with poor spirometry performance and a lower diffusing capacity for carbon monoxide. Unsupervised dynamic data clustering revealed subsets of patients with similar lung radiomic patterns that were found to be associated with similar forced expiratory volume in one second (FEV
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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.