Trial reportMedical physics2015
Can radiomics features be reproducibly measured from CBCT images for patients with non-small cell lung cancer?
Trial report in Medical physics, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 92 papers, 5 of them syntheses that pooled it.
What it found
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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
92 citing papers in PubMed, 5 syntheses or guidelines pooled it, 174 citations in OpenAlex.
- Patient outcome prognosis for external beam radiation therapy using CBCT-based radiomics: a systematic review.Biomedical physics & engineering express · 2026Pooled it
- Artificial intelligence applied to image-guided radiation therapy (IGRT): a systematic review by the Young Group of the Italian Association of Radiotherapy and Clinical Oncology (yAIRO).La Radiologia medica · 2024Pooled it
- Integrated imaging and molecular analysis to decipher tumor microenvironment in the era of immunotherapy.Seminars in cancer biology · 2022Pooled it
- Repeatability and Reproducibility of Radiomic Features: A Systematic Review.International journal of radiation oncology, biology, physics · 2018Pooled it
- Clinical applications of textural analysis in non-small cell lung cancer.The British journal of radiology · 2018Pooled it
- Improving the robustness of radiomic features to patient size variations in CBCT imaging for radiotherapy.Journal of X-ray science and technology · 2026Article
- Multimodal Radiogenomic Imaging in Oropharyngeal Squamous Cell Carcinoma: Implications for Dentomaxillofacial Radiology.Medical sciences (Basel, Switzerland) · 2026Review
- Early toxicity prediction using longitudinal cone-beam CT delta-radiomics in HPV-positive oropharyngeal cancer.Frontiers in oncology · 2026Article
- Radiomics in Action: Multimodal Synergies for Imaging Biomarkers.Bioengineering (Basel, Switzerland) · 2025Review
- Reducing radiomics errors in nasopharyngeal cancer via deep learning-based synthetic CT generation from CBCT.BMC medical imaging · 2025Article
- CT-based delta-radiomics signature of visceral adipose tissue for prediction of disease progression in ileal stricturing Crohn's disease.Japanese journal of radiology · 2025Article
- Texture Analysis in Volumetric Imaging for Dentomaxillofacial Radiology: Transforming Diagnostic Approaches and Future Directions.Journal of imaging · 2024Review
- Cone beam computed tomography (CBCT) and megavoltage computed tomography (MVCT)-based radiomics in head and neck cancers: a systematic review and radiomics quality score assessment.Quantitative imaging in medicine and surgery · 2024Review
- Prediction of prognosis in glioblastoma with radiomics features extracted by synthetic MRI images using cycle-consistent GAN.Physical and engineering sciences in medicine · 2024Article
- A comparative analysis of preclinical computed tomography radiomics using cone-beam and micro-computed tomography scanners.Physics and imaging in radiation oncology · 2024Article
- Differential diagnosis of cemento-osseous dysplasia and periapical cyst using texture analysis of CBCT.BMC oral health · 2024Article
- Prediction of SBRT response in liver cancer by combining original and delta cone-beam CT radiomics: a pilot study.Physical and engineering sciences in medicine · 2024Article
- Reproducibility in Radiomics: A Comparison of Feature Extraction Methods and Two Independent Datasets.Applied sciences (Basel, Switzerland) · 2024Article
- Repeatability, reproducibility, and the effects of radiotherapy on radiomic features of lowfield MR-LINAC images of the prostate.Frontiers in oncology · 2024Article
- A quantitative CBCT pipeline based on 2D antiscatter grid and grid-based scatter sampling for image-guided radiation therapy.Medical physics · 2023Article
32 more citing papers are in PubMed but not listed here.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
12 authors at 2 institutions in 1 country.
Funding
Abstract
purposeIncreasing evidence suggests radiomics features extracted from computed tomography (CT) images may be useful in prognostic models for patients with nonsmall cell lung cancer (NSCLC). This study was designed to determine whether such features can be reproducibly obtained from cone-beam CT (CBCT) images taken using medical Linac onboard-imaging systems in order to track them through treatment.
methodsTest-retest CBCT images of ten patients previously enrolled in a clinical trial were retrospectively obtained and used to determine the concordance correlation coefficient (CCC) for 68 different texture features. The volume dependence of each feature was also measured using the Spearman rank correlation coefficient. Features with a high reproducibility (CCC > 0.9) that were not due to volume dependence in the patient test-retest set were further examined for their sensitivity to differences in imaging protocol, level of scatter, and amount of motion by using two phantoms. The first phantom was a texture phantom composed of rectangular cartridges to represent different textures. Features were measured from two cartridges, shredded rubber and dense cork, in this study. The texture phantom was scanned with 19 different CBCT imagers to establish the features' interscanner variability. The effect of scatter on these features was studied by surrounding the same texture phantom with scattering material (rice and solid water). The effect of respiratory motion on these features was studied using a dynamic-motion thoracic phantom and a specially designed tumor texture insert of the shredded rubber material. The differences between scans acquired with different Linacs and protocols, varying amounts of scatter, and with different levels of motion were compared to the mean intrapatient difference from the test-retest image set.
resultsOf the original 68 features, 37 had a CCC >0.9 that was not due to volume dependence. When the Linac manufacturer and imaging protocol were kept consistent, 4-13 of these 37 features passed our criteria for reproducibility more than 50% of the time, depending on the manufacturer-protocol combination. Almost all of the features changed substantially when scatter material was added around the phantom. For the dense cork, 23 features passed in the thoracic scans and 11 features passed in the head scans when the differences between one and two layers of scatter were compared. Using the same test for the shredded rubber, five features passed the thoracic scans and eight features passed the head scans. Motion substantially impacted the reproducibility of the features. With 4 mm of motion, 12 features from the entire volume and 14 features from the center slice measurements were reproducible. With 6-8 mm of motion, three features (Laplacian of Gaussian filtered kurtosis, gray-level nonuniformity, and entropy), from the entire volume and seven features (coarseness, high gray-level run emphasis, gray-level nonuniformity, sum-average, information measure correlation, scaled mean, and entropy) from the center-slice measurements were considered reproducible.
conclusionsSome radiomics features are robust to the noise and poor image quality of CBCT images when the imaging protocol is consistent, relative changes in the features are used, and patients are limited to those with less than 1 cm of motion.
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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.